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123 SEE, INC.
SBIR Phase II: Gaze-independent contactless autorefractor for self-serve eye exam kiosk.
Contact
240 COMMERCIAL STREET
Boston, MA 02109--1385
NSF Award
2322305 – SBIR Phase II
Award amount to date
$1,000,000
Start / end date
10/01/2023 – 09/30/2025 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is to improve access to vision care and eyeglasses for all Americans through a self-serve, rapid vision exam kiosk for retail stores and public spaces. An estimated 175 million Americans suffer from blurry vision, of which 30 million live without eyeglasses. By partnering with retailers, pharmacies, and supermarkets, the company has the potential to reach a large number of Americans via a network of kiosks spread across the US. With 70% of the population benefitting from eyeglasses, the development of the company?s rapid vision exam kiosk aims to democratize vision care and eliminate the gap in easily accessible vision exams.
This project develops a gaze-independent, contactless autorefractor technology (GIPR) for use in a self-serve and autonomous vision exam kiosk. Gaze-camera misalignment is a leading contributor to accuracy drift in autorefractors using the retinal reflex method. Eliminating the gaze alignment requirement marks a significant milestone in the company?s development. The GIPR design refracts the inner visual field in a single capture, thus providing a measurement of refractive error at the subject?s foveal position. Building on the success of the Phase I feasibility project, this Phase II project will continue the development of the GIPR module towards commercial readiness by optimizing hardware layout and improving data processing pipeline throughput.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
2KR SYSTEMS, LLC
SBIR Phase II: Remote IoT Monitoring Network for Early Warning and Measurement of Structural Movements
Contact
217 MCDANIEL SHORE DR
Barrington, NH 03825--5052
NSF Award
2337470 – SBIR Phase II
Award amount to date
$1,000,000
Start / end date
03/15/2024 – 02/28/2026 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project will be in deploying an easy-to-use roof monitoring system. This affordable high-performance geolocated wireless monitoring system detects unsafe loads and movements on buildings, especially flat commercial rooftops found on schools, distribution centers, office buildings, malls, factories, arenas, apartments, condominiums, and warehouses. This project will innovate scientific and technological advancements that realize the promise of the Internet of Things, generating not just useful products demanded by the marketplace but products that can save lives and fundamentally improve life cycle infrastructure management. The affordability of our technology directly benefits disadvantaged communities, especially in rural areas where resources are severely limited, and serious infrastructure and substandard building problems tend to linger for years. In 2015, it was reported on a major national channel that more than 160 roofs collapsed or faced imminent collapse in Massachusetts alone due to snow load throughout 2014-2015. This SBIR project will inform precisely where unsafe rooftop snow and water loads exist to ensure resources are allocated in advance and as required.
The proposed project efficiently pinpoints risks in flat roof structures at an affordable cost. All 5.9 million commercial buildings in the USA are vulnerable to the destructive forces of nature and negligence. Out of building failures that occur for known reasons, accumulated ice, snow, and/or liquid water account for 33% of incidents. Dilapidation caused by a lack of maintenance, which makes up 30.7% of known-cause building failures, often develops slowly and is not apparent immediately. Complete or partial building collapses leave occupants at risk of mortal injury and the valuable property contained in the structure lost or damaged. Avoiding damage to large-scale infrastructure will save society significant resources and reduce lost productivity. Even minor collapses impact business continuity, affecting revenues and often the larger community, in the case of grocery stores and similar institutions. The sensor technology improves greatly upon current structural health monitoring methods, limited to single-dimension measurements, higher system costs, and complex installations. The project will develop sets of battery-powered wireless sensors and deploy them across several building rooftops. An intuitive online application will be developed to display building health data and provide users with alerts when loads exceed safety thresholds.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
4-D AVIONIC SYSTEMS, LLC
SBIR Phase II: 4D Flightpath-Based Autonomous Separation Assurance Systems (ASAS)
Contact
301 S 4TH ST STE 200
Manhattan, KS 66502--6233
NSF Award
2404858 – SBIR Phase II
Award amount to date
$999,919
Start / end date
07/01/2024 – 06/30/2026 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase II project is enabling efficient, safe, and cost effective deconfliction of dense Uncrewed Aerial Vehicle (UAV) operations. Widespread usage of UAVs is expected to bring significant societal benefits. The UAVs that are anticipated to be utilized for package delivery are estimated to have lower carbon impact than their ground transport counterparts. Delivery drones are currently used for life saving delivery of organs and medications. UAVs currently used for inspection provide safer and more economical alternatives to traditional inspection techniques. To safely get to the flight densities that capture the true societal and economic potential of UAVs, robust autonomous air traffic management solutions are needed. The technology that will be commercialized in this project will fill this need for the emerging UAV market by providing reliable and fast aerial conflict detection and suggestion of conflict avoidance maneuvers.
This Small Business Innovation Research (SBIR) Phase II project will focus on improving the autonomous Air Traffic Management (ATM) technology developed in the SBIR Phase I project and extending the system to include a wider range of Uncrewed Aerial Vehicle (UAV) operations. Improvements to the ATM technology will include improved fault tolerance, improved consideration of UAV capabilities when suggesting aerial conflict avoidance maneuvers, adding flight planning tools, and using optimization techniques to avoid compounding aerial conflicts. Common open-source UAV mission descriptions, developing international standards for the sharing of UAV flight intent, and data sources providing updates of UAV positions will be infused into the ATM technology to detect and avoid aerial conflicts with a more diverse set of UAVs. The result of this SBIR Phase II project will be a safe, reliable, and feature rich software product for providing autonomous ATM services to UAV operators.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
ADVISORY AEROSPACE OSC LLC
SBIR Phase II: A robust production scheduling optimizer for aerospace manufacturers
Contact
4460 GAYWOOD DR
Minnetonka, MN 55345--3808
NSF Award
2208742 – SBIR Phase II
Award amount to date
$999,550
Start / end date
12/01/2022 – 11/30/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase II project seeks to increase the competitiveness of the US in manufacturing high value parts for shops with high product variety, low volumes, large lead times, and large set up times. The application addresses a need to find the optimal way of utilizing existing resources in order to maximize production rates. The proposed technology may provide an affordable and easy-to-use solution for target markets in aerospace and medical technologies industries. The technology may also help strengthen the national defense of the United States by facilitating onshoring of defense manufacturing by making domestic producers more cost competitive.
This Small Business Innovation Research (SBIR) Phase II project involves the development of a new technology that enables high value manufacturers in optimizing the flow of materials in their shops. For shops with high product variety, low volume, large lead times, and large set up times, there is a need to find the optimal way to utilize existing resources in order to maximize production rate. Most scheduling optimizers are unable to handle this problem reliably or affordably. The newly proposed methods, algorithms, and software may solve this challenge. The business model for delivering this software solution is designed for small and medium size businesses in terms of both cost and usability perspectives. The solution demonstrates double digit improvements in all Key Performance Indicators (KPIs), such as on-time delivery (OTD), inventory turns, and profitability. Phase II work will mature shop optimization software through demonstration in a real aerospace parts factory.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
AEROMUTABLE CORPORATION
SBIR Phase II: Multi Sub-System Miniaturization and Development for Semi-Truck Fuel Savings Device
Contact
9431 DOWDY DR
San Diego, CA 92126--4480
NSF Award
2213299 – SBIR Phase II
Award amount to date
$1,000,000
Start / end date
04/01/2023 – 03/31/2025 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is reducing fuel consumption, improving safety and stability, and reducing the carbon footprint of the trucking industry while increasing profitability. Over 70% of US freight tonnage is moved by trucks. At highway speeds, aerodynamic drag uses over 65% of the total vehicle energy. The proposed device modifies the aerodynamic behavior of semi-trucks using air injection by allowing continuous optimization of aerodynamic performance. This project will bring the pneumatic, sensor and artificial intelligence (AI) control systems from proof-of-concept to commercialization. Having a commercial product capable of determining and delivering the trailer?s best aerodynamic profile based on real-time operating conditions may be a game-changer for the trucking industry, as fuel is a significant operating cost. Commercializing this system has the potential to create an energy savings for all US fleets, saving more than 3 billion gallons of diesel fuel, reducing the release of more than 33.5 million tons of carbon dioxide into the atmosphere, tripling trucking company profits, and saving an annual $22 billion.
This SBIR Phase II project proposes development of an aerodynamic add-on prototype for semi-trucks to save fuel by dynamically changing the trailer?s aerodynamic profile to accommodate diverse operating conditions. Objectives of this SBIR Project are to evolve the device from prototype to the first commercially viable release through system miniaturization and encapsulation, controller optimization, and improved overall system performance, reliability, and safety. Research conducted to miniaturize the overall system footprint will minimize any additional operational impacts, ensuring widespread adoption and utilization that maximizes fuel savings. Research to optimize the Artificial Intelligence-Controller operation will maximize fuel savings because it will allow the device to operate under a broader set of operational conditions. Further development to improve system performance, reliability, and the addition of a safety assist will improve the profit margins of the trucking industry while simultaneously improving on-road safety for the public. The project seeks to deliver 10% savings in operational costs for the trucking industry while improving the efficiency and safety of their country-wide operations.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
AI POW LLC
SBIR Phase II: A Hardware-Aware AutoML Platform for Resource-Constrained Devices
Contact
2605 SOMERTON CT
College Station, TX 77845--7466
NSF Award
2335642 – SBIR Phase II
Award amount to date
$1,000,000
Start / end date
06/15/2024 – 05/31/2026 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase II project will support industries keen on harnessing the power of artificial intelligence and Internet of Things. By simplifying the deployment of artificial intelligence technologies, this project allows a broader range of businesses in the manufacturing sector to join the data revolution. It empowers businesses to leverage their existing data assets, leading to enhanced efficiency, fostering a culture of innovation, and carving out a competitive edge in the market. On the commercial front, the benefits are multifold, ranging from bolstered business efficiency and substantial cost reductions to potential market expansion for solutions in artificial intelligence of things. From a societal perspective, this technology contributes substantially to the development of a data-literate 21st-century workforce and strengthens human-technology synergies. The project will drive efficiency and standardization across diverse industries and streamline the process of analyzing and acting upon extensive data sets which will result in improved product quality, fuels innovation, and pave the way for more efficient decision-making processes in an increasingly data-driven world.
This Small Business Innovation Research Phase II project addresses the complex challenge of efficiently deploying artificial intelligence models on edge devices for real-time defect detection in industrial manufacturing systems. The problem lies in creating a scalable, efficient, and easy-to-use solution that allows for the wide application of artificial intelligence technologies in Internet of Things devices. The research objectives include developing a modular end-to-end defect detection system, implementing advanced machine learning automation techniques, improving model interpretability, and enhancing model compression for edge devices. The research will leverage machine learning, edge computing, and user feedback to create a practical, robust, and user-friendly solution. The anticipated results include an artificial intelligence of things system that effectively performs real-time defect detection with improved interpretability and reduced resource usage. The expected outcomes comprise an artificial intelligence of things system capable of performing real-time defect detection with elevated interpretability, using minimal computational resources, and revolutionizing defect detection in industrial manufacturing systems.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
AIDAR HEALTH, INC
STTR Phase II: Development of a Smart Remote Health Management System for Patients with Kidney Disease
Contact
3402 BIRCH HOLLOW RD.
Pikesville, MD 21208--1839
NSF Award
2243718 – STTR Phase II
Award amount to date
$1,000,000
Start / end date
10/01/2023 – 09/30/2025 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase II project is to develop a novel technology for the early detection of complications and effective management of kidney disease at home. More than 37 million patients in the US have chronic kidney disease, which is associated with increased mortality and morbidity, including a greater risk of cardiovascular disease, hospitalization, premature death, and progression to end-stage kidney disease. According to the Centers for Disease Control and Prevention, in 2018, treating Medicare beneficiaries with chronic kidney disease cost over $81 billion, and approximately 20% of the Medicare budget was spent on kidney disease. This project leverages a medical device and digital tools with advanced analytics capabilities to provide actionable data and key health insights for timely interventions for at-risk patients. There is a rapid shift towards value-based healthcare from the traditional fee-for-service model accelerated by the significant cost burden and poor outcomes, especially in kidney care management. This solution is designed to facilitate this transition seamlessly, lowering unnecessary emergency room visits and/or hospitalizations, and minimizing exacerbations and associated healthcare costs in a disease condition that contributes over $100 billion in healthcare expenses.
This STTR Phase II project develops a comprehensive disease management solution for chronic kidney disease by offering a personalized clinical-decision support system for providers as well as a companion diagnostic solution for patients to improve therapeutic benefits. There is a dearth of reliable and accurate predictive tools that can non-invasively measure critical biophysical and biochemical markers to inform clinical care and empower self-identification of undesirable effects. The objective of this research is to develop and validate disruptive technologies for the non-invasive assessment of biomarkers critical to chronic kidney disease diagnosis and management such as hemoglobin levels, electrocardiography (ECG)-based arrhythmia, estimated potassium levels, and lung functions, augmenting the existing capability that measure 10+ vital signs. The innovation also includes a novel concept for any medical device, to record and broadcast personalized messages in a trusted voice (physician/family member), to improve treatment adherence and outcomes. The project further incorporates a proprietary cloud-based analytics system that leverages both subjective and objective data to generate a unique ?digital fingerprint? for effective management and triage. Consistent use of the proposed solution will improve symptoms management, care delivery, and diagnosis, and ultimately lead to dramatic reductions in hospitalizations, total medical expenditure related to morbidity and lost productivity, and patient anxiety.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
AIR COMPANY HOLDINGS, INC.
STTR Phase II: Earth-abundant catalyst for power-to-liquids chemical production at the kiloton scale
Contact
407 JOHNSON AVE
Brooklyn, NY 11206--2805
NSF Award
2304275 – STTR Phase II
Award amount to date
$997,743
Start / end date
04/15/2024 – 03/31/2025 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase II project is to help lessen the environmental burden of climate change by reducing greenhouse gas emissions and dependence on fossil fuels. Climate change is an urgent environmental challenge and to address it, it is essential to provide alternatives to the use of fossil fuels that generate greenhouse gases. Nearly all the jet fuel or aviation fuel in use today is made from crude oil, which is a fossil fuel. This project provides an alternative technology that makes sustainable aviation fuel (SAF) using only carbon dioxide (CO2) captured from waste sources, relatively small volumes of water, and renewable (e.g., solar and wind) electricity. Catalysts are one of the key components of the process that is used to produce this SAF, helping the chemical reactions that produce the fuel occur more efficiently. This project will optimize the catalysts for improved production of SAF.
This STTR Phase II project seeks to significantly improve SAF production by developing and characterizing catalysts that convert carbon dioxide (CO2) into the hydrocarbon constituents in sustainable aviation fuels using advanced characterization techniques such as x-ray diffraction, x-ray photoelectron spectroscopy, and electron microscopy. The process will use catalysts as mimics for photosynthesis, taking air (as a CO2 source), water (as a hydrogen source) and sunlight (as an energy source) and converting them into sustainable chemicals and transportation fuels. The only by-products are oxygen and water. Many other related processes often rely on multiple reaction steps to target the same products. This project develops a novel family of proprietary catalysts to convert CO2 to fuels and chemicals in a single step via a direct CO2 hydrogenation process, enabling yields even greater than the theoretical maximum of legacy processes, such as Fischer-Tropsch. This new process eliminates the need for extra intermediate steps that negatively affect process energy demands, emissions, capital and operational cost, and product selling price. The successful outcome of the project will allow significant improvements in production and economics of sustainable aviation fuels.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
AKTTYVA THERAPEUTICS, INC.
SBIR Phase II: AI-assisted identification of small molecules for targeted repair of vascular barrier dysfunctions
Contact
116 STANDISH RD
Watertown, MA 02472--1239
NSF Award
2335290 – SBIR Phase II
Award amount to date
$999,878
Start / end date
08/15/2024 – 07/31/2026 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase II project will lead to an Artificial Intelligence (AI) assisted drug discovery platform that may shed light on unexplored interactions and mechanisms to quickly predict the best small molecules to design new therapies for diseases with unmet clinical needs. Currently, there is no targeted treatment addressing endothelial dysfunctions or vascular leaks. Through the AI-assisted platform the company will generate treatment candidates for disorders associated with vascular leaks and improve the efficiency of the drug discovery workflow. The first condition that the company will address is acute respiratory distress syndrome (ARDS), a life-threatening form of respiratory failure that affects approximately 200,000 patients each year in the US, resulting in nearly 75,000 deaths annually. The company?s therapeutic intervention for ARDS and other diseases with vascular leakage could significantly increase the survival rate, reduce costs associated with hospitalization, and improve the health outcomes of the patients. Leveraging AI-assisted drug discovery approach for ARDS drug development, the company will strive to bring forward effective strategies to screen approved and investigational therapeutic agents as well as novel chemical entities (NCEs) to derisk future clinical development.
The proposed project seeks to develop an AI-assisted drug discovery platform to identify existing drugs as well as NCEs able to repair the vascular permeability barrier in several different conditions. In this project, the R&D efforts will be dedicated towards (1) further development of the Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADME-Tox) Engine to flag toxicophores and predict ADME-Tox endpoints, (2) development of the next level active-learning docking-scoring protocol for superior screening efficiency, (3) performing a Hit-to-lead campaign for protein activators for restoring disrupted endothelial barrier and identifying NCE candidates, and (4) performing advanced proof of concept studies of pre-lead protein activator compounds in ADME-Tox, human lung-on-chip model, and in vivo vascular leak mouse model. The successful completion of the Phase II activities could bring the development of an AI-assisted drug discovery platform with a novel pocket prediction engine, active learning-based docking-scoring workflow, ADME-Tox engine, and an electronic library of AI-generated synthesizable molecules collection. At the end of the SBIR Phase II project, the company will select the lead ARDS drug candidate for IND-enabling studies based on the battery of in vitro and in vivo studies.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
ALERJE, INC.
SBIR Phase II: A digital platform to support food allergy oral immunotherapy treatments
Contact
440 BURROUGHS ST STE 328
Detroit, MI 48202--3471
NSF Award
2233429 – SBIR Phase II
Award amount to date
$1,000,000
Start / end date
09/15/2023 – 08/31/2025 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader/commercial impact potential of this Small Business Innovation Research (SBIR) Phase II project is to provide the food allergy patient community with a digital platform in order to improve care and support the implementation of emerging food allergy oral immunotherapy treatments. Today there are no cures for food allergies. Patients and their families are in constant fear of anaphylaxis reactions. The proposed technology is a comprehensive platform addressing pain points of food allergy oral immunotherapy, meeting the needs of patients, families, and caregivers. The platform enhances patient treatment adherence and allows healthcare professionals to assess the progress of the patient?s condition remotely and efficiently. Furthermore, the solution provides artificial intelligence analytical capabilities for a systematic approach to food allergy oral immunotherapy that is currently not available. There is a promising commercial opportunity in developing and commercializing such a holistic digital platform. While the platform will enable the creation of a clinical database of food allergy immunotherapy experiences not available previously, it will also shed light on yet unknown factors of food allergy conditions and their potential treatments.
This project addresses the challenge of patient adherence to oral immunotherapy treatments. Oral immunotherapy is still an emerging treatment that consists of feeding an allergic individual an increasing amount of an allergen, under clinical supervision, with the goal of desensitizing the immune system against the allergen. However, perfect adherence of patients to the treatment plan is essential to ensure safety and enhance treatment efficacy. This platform is the first-ever solution aimed at providing a systematic and comprehensive approach to food allergy immunotherapy treatment. The platform includes an innovative epinephrine auto-injector (EAI) that integrates into an ad-hoc smartphone case and a smartphone app that supports the daily life of food allergy patients. The team will develop a HIPAA-compliant database, a machine learning engine to analyze relevant clinical data and unveil data patterns that allow predicting relevant events in the treatment, a web-based application for allergists to help patients with data management and analyses, and a digital access point for pharmaceutical companies to receive a raw data feed for research and development purposes.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
ALTYX SURGICAL, INC.
SBIR Phase II: A mesh-free, sling-free, minimally invasive treatment for stress urinary incontinence in women
Contact
2717 LINCOLN ST
Evanston, IL 60201--2042
NSF Award
2233106 – STTR Phase II
Award amount to date
$975,713
Start / end date
01/01/2024 – 12/31/2026 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is a novel, surgically implanted device for treating female stress urinary incontinence (SUI). Nearly 50% of women in the U.S. will suffer from stress urinary incontinence with age resulting in over 40 million suffering women by 2050. No pharmacological solutions currently exist and mesh-based midurethral slings (MUS) are the mainstay surgical option, even though they are associated with various long-term complications, challenges, and risks. Furthermore, all SUI repair products on the market are polypropylene mesh-based with no alternatives available. This project aims to address this gap in options with a mesh-free, sling-free, outpatient transvaginal repair device for female urinary incontinence.
This Small Business Innovation Research (SBIR) Phase II project aims to develop and validate a novel, transvaginal surgical procedural technology for treating stress urinary incontinence. This project progresses findings from the SBIR Phase I project which demonstrated functional proof-of-concept biomechanical feasibility. This Phase II project aims to further the surgical procedure and system in a manner suitable for human use. The scope of technical activities includes design optimization, mechanical testing and validation, surgical procedure validation, biocompatibility testing, and histological characterization in a series of benchtop, cadaveric, and animal studies. The scope of the activities will be conducted in accordance with practices needed to demonstrate chronic implanted safety and efficacy in pre-clinical models in order to gain eventual U.S. regulatory approval.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
ALVA HEALTH, INC.
SBIR Phase II: Defining the Multimodal Signature of Stroke
Contact
3 WASHINGTON CT
Towaco, NJ 07082--0000
NSF Award
2039532 – SBIR Phase II
Award amount to date
$1,000,000
Start / end date
05/15/2021 – 12/31/2025 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project falls within the scope of the grand challenges in health informatics. There are excellent protocols for the management and treatment of acute stroke, however, these protocols are only effective once patients have been admitted into the healthcare system. Ischemic stroke affects 700,000 Americans, costs approximately $33 billion annually, and is the fifth leading cause of death and a leading cause of disability in the US. Health care providers, however, have limited interaction with their patients, and these interactions occur in the highly constrained environment of the clinical setting. Physicians have limited control over patient behavior and limited tools to help patients recognize stroke symptoms outside the clinical setting. For patients with high stroke risk, there is currently no system available to monitor stroke symptoms and initiate a response in real-time. Thus, there is a need to monitor patients remotely, where the current systems for stroke response fail to provide coverage. The proposed solution will expand the provision of stroke symptom monitoring to the daily lives of patients. Tracking patients as they go through their daily lives will considerably enrich our knowledge of stroke and will allow extension to monitoring for other neurological and neuropsychiatric disorders and diseases.
This Small Business Innovation Research (SBIR) Phase II project addresses the real-time detection of stroke. IV tissue plasminogen activator (tPA) has been an FDA approved therapy since 1995, yet only 5-10% of eligible patients receive this therapy. Arrival time in the emergency room after initial stroke symptoms is directly associated with better outcomes after tPA and endovascular therapy, with a time window of 4.5 hours and 24 hours for these treatments, respectively. Despite massive public health campaigns, identifying symptoms of stroke and activating emergency response systems remains a major challenge. The goal of this project is to develop and test a wearable and computational solution to effectively alert ischemic stroke victims and initiate emergency response in a timely manner. The solution consists of a cloud-based analysis system for real-time detection of stroke onset, enabled by body-worn sensors and a mobile app. Once deployed, the device is expected to dramatically improve stroke emergency response and increase the number of patients arriving in the hospital in time for IV tPA treatment and other reperfusion therapies.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
AMPHIX BIO, INC.
SBIR Phase II: Scalable Manufacturing of Supramolecular Polymers for Regenerative Medicine
Contact
57 E DELAWARE PL
Chicago, IL 60611--1624
NSF Award
2422766 – SBIR Phase II
Award amount to date
$1,000,000
Start / end date
09/15/2024 – 08/31/2026 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase II project is to develop a synthetic bone graft that enables safer, simpler, and lower-cost spinal fusion surgery. The success of this technology would reinforce the United States? competitive advantage and leadership position in the $12B global spinal implant market. The bone graft implant consists of a novel nanotechnology which introduces a new approach for regenerative medicine. This technology requires the development of new manufacturing methods, as standard approaches are not sufficient for larger scale production. This project directly addresses the manufacturing challenges in producing this implant, and the knowledge generated can accelerate the clinical development of other similar therapies. This project will serve as a model for other novel forms of matter requiring unique manufacturing and processing methods. Since the technology used in the implant has deep roots in academic research, this project also serves as a model for academia-industry collaboration.
The proposed project will develop methods for manufacturing a new spine implant technology at large scales, which will enable its translation to clinical trials. First, the active ingredient in the implant, which has novel chemical properties, will be manufactured at large scales in conditions appropriate for use in human patients. The active ingredient is a supramolecular polymer held together by non-covalent bonds, which are sensitive to manufacturing and processing steps, akin to protein misfolding. Spectroscopic and microscopy techniques will be used to ensure that the correct structures and function are maintained as manufacturing is scaled up. Second, the active ingredient will be combined with other supporting materials to create a formulation that surgeons can easily handle and place into the spine. Manufacturing methods will be developed to address the challenge of processing and freeze-drying viscous solutions at large scale. Furthermore, the biocompatibility of the spine implants will be established to ensure the manufacturing methods are safe for human use. The final deliverable of this project is a packaged and sterilized implant, manufactured at scale and under conditions appropriate for clinical use in humans.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
APOGEE SEMICONDUCTOR, INC.
SBIR Phase II: Low-Cost Packaging Solution for Space-Grade and High-Reliability Integrated Circuits
Contact
840 CENTRAL PKWY E STE 140
Plano, TX 75074--5673
NSF Award
2304975 – SBIR Phase II
Award amount to date
$999,561
Start / end date
12/01/2023 – 11/30/2025 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
This Small Business Innovation Research (SBIR) Phase II project enables the use of modern packaging technologies for integrated circuits in space applications. While failures in satellites are common and high insurance claims due to such failures are frequent, the space industry continues to use integrated circuits (ICs) that are either unreliable (non-space-grade) and are prone to failure, or space-grade ICs with large and costly packaging and compromised performance. This innovation offers a cost-effective and reduced-size solution for the packaging of ICs that can operate reliably over the extreme temperature cycles experienced in space applications. Wafer Level Chip Scale Packaging (WLCSP) is lighter, smaller, and has superior electrical and thermal performance when compared to traditional leaded packaging solutions. These attributes make it desirable to the space industry by reducing size and weight, while not compromising performance. As this packaging technology is limited due to its performance under temperature cycling, this project seeks to address this reliability problem by using existing manufacturing techniques coupled with a novel design concept.
This Small Business Innovation Research (SBIR) Phase II project aims to redesign specific layers within the existing Wafer Level Chip Scale Packaging (WLCSP) to improve reliability under temperature cycling. The temperature cycle reliability problem in the WLCSP is caused by a thermal expansion rate mismatch of silicon die and the copper circuit board. This project will redesign the redistribution layer within the WLCSP to compensate for this mismatch by effectively moving the interconnects on the silicon die in accordance with the faster moving printed circuit board (PCB). This project will make the benefits of WLCSP accessible for the entire space community.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
APPLIED OCEAN SCIENCES, LLC
SBIR Phase II: Developing the First Flow-Through Sensor for Real Time Microplastics Measurements
Contact
11006 CLARA BARTON DR
Fairfax Station, VA 22039--1409
NSF Award
2335438 – SBIR Phase II
Award amount to date
$998,320
Start / end date
05/01/2024 – 04/30/2026 (Estimated)
NSF Program Director
Errata
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Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase II project is to revolutionize microplastics detection with the development of the first near real-time automated in-situ sensor. Unlike existing sensors that take hours to days for a single sample, this
technology promises quick and cost-effective analysis of microplastics abundance in water samples. This technology can enable communities nationwide to monitor drinking water and characterize undersampled environments and sources of human exposure to microplastics pollution. Given the
alarming environmental and human health implications of microplastic contamination, a rapid and affordable sensor is crucial to the NSF?s broader impact goal of advancing the health and welfare of the American public. The commercial sensor caters to scientists, drinking water providers,
monitoring facilities, conservation organizations, and health professionals, facilitating widespread access to microplastics data.
The goal of this project is to create an ultrasound-based sensor that can detect and characterize microplastics in water or other fluids. Traditional optical-based methods for microplastic detection are time-consuming, labor-intensive, and expensive, and cannot detect the smallest microplastics
that are most harmful to human health and environmental systems. Traditional ultrasonic particle detectors use reflection and scattering to detect particles based on the material's different bulk modulus (compression resistance) compared to that of the fluid. However, the bulk modulus of
plastic is similar to that of water. This project utilizes a novel detection method inspired by tomography and interferometry to measure spectral differences as a function of concentration and composition of microplastics, even for the smallest of microplastics. The method leverages
observables from multiple physical processes including scattering, reflection, absorption, attenuation, and resonance in order to empirically map the received ultrasonic energy to concentration and composition of suspended particulates in a fluid sample.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
AQUAGGA, INC.
SBIR Phase II: Optimized Hydrothermal Reactor for Scalable and Affordable Destruction of Per- and Polyfluorinated Substances (PFAS)
Contact
326 EAST D ST
Tacoma, WA 98421--1804
NSF Award
2232969 – SBIR Phase II
Award amount to date
$979,270
Start / end date
05/01/2023 – 04/30/2025 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is the acceleration of a new technology for the destruction of toxic per- and polyfluoroalkyl (PFAS), otherwise known as ?forever chemicals?. PFAS chemicals are widely used in firefighting foams and consumer goods. However, they are incredibly recalcitrant environmental pollutants, highly toxic to humans, and very hard to destroy. Widespread contamination of soil, groundwater, and drinking water at sites near airports, military bases, and manufacturing sites is driving a global effort to remove and destroy PFAS toxins. PFAS are poorly broken down by incineration and they do not have a natural half-life. The environmental remediation industry needs effective technology for on-site, end-of-life destruction of PFAS. The technology being developed in this SBIR Phase II project is energy efficient, scalable, pairs with existing technologies, and can be deployed at-scale for the destruction of PFAS-rich wastes.
This SBIR Phase II project seeks to reduce technical risks related to system corrosion and chemical consumption in the development and scale-up of the hydrothermal alkaline treatment (HALT) process for the destruction of PFAS. Hydrothermal processing has historically been plagued by challenges with corrosion and low component lifetimes, and/or has requiring the use of expensive alloys, replaceable system components, and/or elegant chemical corrosion prevention strategies. This said, hydrothermal processes are some of the most effective and efficient technologies for destroying hazardous wastes, such as PFAS. This project will focus on measuring and mitigating the material corrosion challenges to enable more widespread adoption of hydrothermal processes for waste disposal. Additionally, HALT processing requires the use of alkaline chemicals as process additives. In this project, by adopting chemical recycling strategies, the use of chemicals may be drastically reduced, improving overall unit economics and reducing the environmental footprint of HALT processing.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
ARACARI BIOSCIENCES, INC.
SBIR Phase II: Vasoreactive Perfused in Vitro Vascular Network
Contact
226 JASMINE AVE
Corona Del Mar, CA 92625--3034
NSF Award
2127102 – SBIR Phase II
Award amount to date
$988,018
Start / end date
09/15/2021 – 05/31/2025 (Estimated)
Errata
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Abstract
This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2).
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is to improve clinical outcomes related to cardiovascular side effects of various treatments. It is currently not possible to test this activity on cells in a petri dish, and mice are not an accurate model for predicting these outcomes in human clinical trials. Rodent lifespans, metabolism and responses to drugs are often very different from those of humans. This project advances a pre-clinical drug screening platform, leading to the development of better and safer drugs.
This Small Business Innovation Research (SBIR) Phase II project improves accurate pre-clinical screening of new pharmaceutical compounds that may trigger unwanted effects on vascular tone and blood pressure. Both hypertension and hypotension can have immediate and long-term life-threatening effects on patients, and are almost always disqualifying for further development of a new drug. As a result, there is a need for improved, human cell-based models to screen vasoactive drugs for human patients. This project advances a platform to accurately mimic physiologically-relevant vasoactivity.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
ASANTE BIO LLC
SBIR Phase II: Additive Manufacturing for Soft Tissue Repair by Three-Dimensional Microfiber Fabrication (3DMF)
Contact
5923 POWHATAN AVE
Norfolk, VA 23508--1012
NSF Award
2404176 – SBIR Phase II
Award amount to date
$979,298
Start / end date
05/01/2024 – 04/30/2026 (Estimated)
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is to improve the outcomes for upwards of 500,000 Americans each year who undergo shoulder soft tissue repair surgeries. Shoulder repair surgeries have an unacceptably high failure rate of around 25% and lack effective, economical, and easy-to-use treatment options in this $7B market. This NSF Phase II SBIR campaign will develop a multi-axial filament winding process (3DMF) for robotically positioning biological materials to medical device implants. 3DMF implants will be made more rapidly and economically than existing technologies, with extraordinary biomechanical performance, and, importantly, designed for facile surgical use without additional tooling or fixation for delivery, based on extensive surgeon-guided inputs. Upon commercialization, this technology will significantly reduce the cost of surgical implant augmentation and minimize surgical touch time, surgical complexity, and overall costs while providing a superior healing implant for challenging rotator cuff repairs.
This Small Business Innovation Research (SBIR) Phase II project will biomanufacture 3DMF orthobiologic implants using human collagen resin and biopolymer yarns to form physiologically high-strength microfibrous implants that mimic native tissue strength and biology. This research advances knowledge in the field, progressing beyond existing limited additive and fiber-based manufacturing technologies (i.e., electrospinning, weaving, braiding, 3D printing, etc.) to provide features critical for the end-user surgeon. The work?s main objectives include: 1.) To biomanufacture quality-controlled 3DMF implants at the clinical scale; 2.) To optimize 3DMF arthroscopic surgical delivery and human factors, 3.) to determine 3DMF biomechanical performance, and 4.) To determine 3DMF device biocompatibility. Completing this work will progress product development of the 3DMF device with proven manufacturability, yielding implants with the required strength and accessible surgical approach for facile implantation within the existing surgical workflow to drive commercial adoption and reimbursement. This work specifically targets research and development of 3DMF implants for the rotator cuff repair niche with a large market with an unmet need for an accessible, economical, and effective solution.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
ASTEK DIAGNOSTICS LLC
SBIR Phase II: Automated One-Hour Testing for Bacterial Detection and Antibiotic Sensitivity in Clinical Samples
Contact
1450 S ROLLING RD STE 3.019
Halethorpe, MD 21227--3863
NSF Award
2423587 – SBIR Phase II
Award amount to date
$991,832
Start / end date
09/15/2024 – 08/31/2026 (Estimated)
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is to deliver a rapid antibiotic susceptibility testing (AST) platform, toward revolutionizing the diagnosis and treatment of infections across a variety of specimen types, including urine, cerebrospinal fluid (CSF), and wound effluent. The AST platform will enable rapid identification of effective antibiotics for treating infections such as urinary tract infections (UTIs), urosepsis, meningitis, and wound infections, and significantly reducing morbidity and mortality. The novel AST platform will enable identification of appropriate antibiotics for a given infection within an hour. This will reduce the need for empirical antibiotic administration and address the urgent public health challenge of increasing antimicrobial resistance, where the potential to reduce the empirical use of broad-spectrum antibiotics could slow the development of antibiotic resistance. Commercialization associated with this project has significant potential to impact nearly all facets of AST and clinical diagnostics toward guiding treatment with quantitative results rather than empirical observation, where adoption is expected in emergency rooms, primary care facilities, and specialty clinics. The AST market is projected to reach US$ 4.05 Billion by 2028 and a novel AST device would be well positioned to address critical market deficits.
This Small Business Innovation Research (SBIR) Phase II project is focused on developing a novel rapid antibiotic susceptibility testing (AST) platform, the first of its kind designed to perform AST across various critical specimen types such as urine, cerebrospinal fluid (CSF), and wound effluent, delivering results in under an hour. Traditional methods, which are based on culture techniques, often take several days, causing delays in administering the correct antibiotics for infections and adversely affecting patient outcomes. To avoid the wait for AST results, clinicians frequently resort to prescribing broad-spectrum antibiotics empirically, which contributes to the growing problem of antibiotic resistance. There is a significant need for rapid AST methods that can quickly determine the most effective antibiotics, especially for critical conditions like urinary tract infections (UTIs), complicated UTIs, urosepsis, bacterial meningitis, and skin and wound infections. The goals of this project are to 1) adapt a previously developed urine cartridge for use in CSF and effluent specimen types; 2) characterize analytical parameters for detection of relevant bacterial strains in urine, CSF, and effluent; and 3) complete clinical verification of the AST platform with urine, CSF, and effluent clinical specimens.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
ASTROLABE ANALYTICS, INC.
SBIR Phase II: Forecasting Battery Health and Maintenance using Data-Driven Predictive Analytics
Contact
4625 UNION BAY PL NE, SUITE 215
Seattle, WA 98105--4026
NSF Award
2243671 – SBIR Phase II
Award amount to date
$991,095
Start / end date
10/01/2023 – 09/30/2025 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase II project includes enhancing US economic competitiveness, improving the health and welfare of the American public, and developing the US technical workforce. The success of this project will have a direct impact on the manufacturers, integrators, and operators of battery-powered assets. Empowering battery engineering teams with predictive analytics across their product life cycle will be a crucial competitive advantage to accelerating the scale-up of domestic battery technology development and deployment. Bringing better battery technology to market faster and ensuring a long, safe operating life will, in turn, catalyze the transition away from fossil fuels and towards electric vehicles, grid-scale energy storage, and other clean technologies. The social and economic implications include clean energy jobs, improved environmental quality, and ubiquitous low-cost energy. The potential commercial impact of this project will help accelerate the development and deployment of new battery-powered vehicles, energy storage systems, and other assets. It will allow the company to serve the wider battery industry by de-risking operation and extending service life of battery assets, thereby increasing customer revenue and avoiding costly warranty events.
This Small Business Innovation Research (SBIR) Phase II project's goal is to de-risk the deployment, operation, and maintenance of battery energy storage systems. It will combine results from the Phase I with data from partners to forecast system maintenance and inform warranty design, thereby lowering the total cost of ownership and minimizing liability. Access to cell testing, outgoing quality control, and field data will allow for a deep dive across the product life cycle to identify how known degradation mechanisms manifest in the real-world battery data. Physics-informed feature engineering will be used to extend models to incorporate these insights and then implement these models at scale in the cloud. Criteria for success include: 1) correlating real-world operating conditions with known Lithium-ion battery degradation pathways, 2) engineering new features that are correlated with physics- and electrochemical-based insights, 3) accurately estimating remaining useful life to within 5% of total cycle life, and 4) implementing data-driven model in a scalable cloud environment.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
ATHEM L.L.C.
SBIR Phase II: A Bioprocessing System to Isolate and Purify Therapeutic Antibodies Directly from Cell Culture.
Contact
2109 JADEWOOD DR
Morrisville, NC 27560--6511
NSF Award
2318892 – SBIR Phase II
Award amount to date
$999,998
Start / end date
08/15/2024 – 07/31/2026 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase II project is to enable the manufacturing of novel lifesaving biologics, reduce the high manufacturing cost of current biologics, and improve their quality by significantly simplifying their purification using a nanoparticle-based technology. Current technologies require time-consuming harvest-clarification steps that are a prerequisite for traditional purification processes and require expensive cleaning and storage validations so that the costly purification resin can be stored for reuse. This technology eliminates the harvest-clarification step completely and its fast purification allows small amounts of resin to be fully utilized within a single batch so that it can be disposed of at the end. In addition, current purification technologies have minimal product recoveries when purifying viral vectors for gene therapy manufacturing. Improved purification of viral vectors with this technology may enable mass commercialization of cell and gene therapies and other novel therapies. This platform technology has applications beyond the manufacturing of biologics, such as a medical device to isolate antibodies from human blood, remove circulating toxins from human blood, and isolate therapeutic antibodies against novel pathogens or biothreats from immunized animals.
The proposed project aims to address key downstream challenges associated with the manufacturing of biologics. While upstream processes have improved product titers to reduce the cost of biologics, there are no efficient solutions to manage harvest clarification that is required prior to the chromatography process. Furthermore, current-industry-standard porous chromatography is unsuitable for the purification of viruses and viral vectors. The goal of this project is to scale up the novel media and develop disposables and an automated prototype system to demonstrate direct purification of monoclonal antibodies from challenging cell cultures that cannot be processed efficiently with current technologies. In addition, the purification cycle time will be reduced such that Protein A media can be recycled 50 times in a day and discarded, removing the need for storage. The media will be further characterized and improved, and a cGMP-compliant single-use manifold will be developed. The prototype system will perform all process steps based on the parameters provided by the user and the information from the sensors. The system may be able to purify about 50 grams of monoclonal antibodies with 10 to 20 times less media than current chromatography systems while providing a better-quality product and not requiring harvest clarification.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
AV-CONNECT, INC.
SBIR Phase II: Improving fleet operational metrics through service optimization with automated learning of vehicle energy performance models for zero-emission public transport
Contact
1054 FONTANA DR
Alameda, CA 94502--6820
NSF Award
2220811 – SBIR Phase II
Award amount to date
$999,339
Start / end date
04/15/2023 – 03/31/2025 (Estimated)
Errata
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Abstract
This Small Business Innovation Research Phase (SBIR) II project will research and validate an internet-of-things (IOT) platform to help commercial fleets transition to zero-emission vehicles (ZEVs). The ZEV transition is the primary solution to the decarbonization of the transportation sector, which is the largest emitter of greenhouse gases in the US. The project focuses on transit agencies, with the ultimate goal of lowering both operating costs and capital costs of their ZEV fleets. Coupled with the current funding support by federal, state and local governments to transit agencies to purchase ZEVs, this project could accelerate the decarbonization of the US transit fleet. A 50% transition of the US transit fleet to ZEVs will reduce nearly 200 million metric tons of carbom dioxide (CO2) equivalent, providing cleaner air quality and reducing urban noise pollution, particularly in low-income communities that rely more heavily on transit services for their transportation needs. The addressable market of Transportation Management Systems will grow from $8.8 billion in 2020 to $27.48 billion in 2028. Demonstrating success in the transit segment will enable the replication of this approach to other fleet segments like school bus fleets, last-mile and mid-mile delivery fleets, and long-haul trucking fleets.
The intellectual merit of this project is the design and implementation of an artificial intelligence software platform to automatically learn predictive vehicle models of transit ZEVs and provide recommendation services to transit agencies. The Phase II project has three integrated goals. The first goal is the development of energy prediction algorithms which are scalable and highly accurate. Transit ZEV fleets have stochastic load changes, high sensitivity to operator driving style and high variation of battery size, weight and driving range, even for similar vehicles. These challenges will be addressed by developing automated learning techniques built on algorithms developed in Phase I, which use contextualized data from ZEV stops and trips. The second goal is to validate the prediction accuracy via pilots with ZEV fleets providing scheduled bus services. The final goal is development of real-time, scalable, fleet optimization algorithms which optimize daily assignment and charge management of ZEV fleets. Chance-constrained optimization will be merged with predictive control theory to address scalability and real-time performance of the resulting optimization algorithms. These recommendations will, if successful, demonstrate highly accurate predictions of charge usage, a substantial increase in ZEV fleet utilization, and a reduction of transit ZEV fleet operating costs.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
Abram Scientific, Inc.
SBIR Phase II: CoagCare-A POC Blood Coagulation Diagnostic Platform That Utilizes A Hand-held Meter and Mechanically Sensitive Test Strips for Broad Spectrum Hemostasis Monitoring
Contact
2337 SHARON RD
Menlo Park, CA 94025--6807
NSF Award
2050272 – SBIR Phase II
Award amount to date
$968,825
Start / end date
03/15/2021 – 08/31/2025 (Estimated)
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project will be to develop and commercialize a new technology for accurate, portable, and inexpensive measurement of multiple blood clotting parameters. Common tests are routinely performed on patients who suffer from conditions like atrial fibrillation, deep vein thrombosis, or have had heart valve replacement. These conditions affect millions of patients in the US alone and represent $2 B of spending annually. However, many current solutions cannot accurately or conveniently perform multiple blood clotting tests on the same system or sample, causing clinically significant problems for end-users and raising the cost and inconvenience of performing these tests routinely. The technology in this project will enable various blood clotting tests to be performed in a single portable system. This will potentially lead to cheaper and more convenient blood coagulation testing for medical professionals and improve medical outcomes by bringing accurate and multiple tests to a single portable devices.
This Small Business Innovation Research (SBIR) Phase II project will develop a technology that will enable the first-of-its-kind implementation of a point of care (POC) direct, mechanical test in a meter and single-use disposable card format, to more closely replicate the mechanical methods that underpin blood clotting tests in the clinical laboratory. As a mechanical measurement, the card will measure physical properties of a clotting whole blood sample and account for confounding factors, such as hematocrit. Specifically, the objective of the project will be to develop a POC, hand-held, battery-operated system that can enable the generation of a viscoelastic curve and associated thromboelastography parameters in less than 10 minutes, a significant improvement over current bulky and labor-intensive solutions with turnaround times of up to 30 minutes or more. Beyond addressing the thromboelastography needs, the proposed broad-spectrum portable hemostasis platform can be extended to other coagulation tests based on fluid mechanical characterization of a blood sample, including prothrombin time, partial thromboplastin time, and activated clotting time. This project will demonstrate the implementation of a blood coagulation test in a portable POC system.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
Accelerate Wind, Inc.
SBIR Phase II: Integrated Solution for Low Cost Distributed Wind Energy Generation
Contact
911 WASHINGTON AVE STE 501
St. Louis, MO 63101--1272
NSF Award
2036552 – SBIR Phase II
Award amount to date
$1,016,000
Start / end date
05/15/2021 – 09/30/2026 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is in its strong potential to disrupt the small wind market, which to date has lagged behind solar counterparts. Through dual installation with solar on commercial buildings, the proposed roof-edge wind turbines will be able to deliver enhanced energy capture systems to buildings, with a shorter payback period, thus improving cost-efficiency and power potential, and attracting a broader body of adopters. By improving product offerings in the renewable energy sector, this technology has the potential to promote sustainable infrastructure, reducing reliance on and consumption of fossil fuels.
This Small Business Innovation Research (SBIR) Phase II project develops a roof-edge wind capture technology with commercial viability. The proposed distributed wind technology reduces costs by harnessing elevated wind speeds at the roof edge, optimizing powertrain architecture, and mitigating soft costs through sale to solar installers, who have already achieved significant market penetration yet would benefit from a diversified portfolio. The project aims to: 1) Prove the feasibility of integrating a Vertical Axis Wind Turbine into the system 2) Design for additional stakeholders, with respect to aesthetics, structural integration, ease of installation, and code compliance, while maintaining cost targets needed for scaleup 3) Design and test full powertrain architecture using components intended for commercial scaleup and 4) Build and test the full turbine for reliability and certification testing. These efforts will inform critical needs to address prior to large-scale commercial rollout, providing a strong foundation for translation as a reliable and cost-efficient distributed wind solution.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
Akanocure Pharmaceuticals, Inc.
SBIR Phase II: A Novel Host-Directed Broad-Spectrum Antiviral and Efficient Immunomodulatory Agent Against Coronaviruses: Lead Optimization Studies
Contact
3495 KENT AVE
West Lafayette, IN 47906--1074
NSF Award
2325532 – SBIR Phase II
Award amount to date
$1,000,000
Start / end date
09/01/2024 – 08/31/2026 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase II project stems from the development of a virus agnostic drug that can control the current coronavirus pandemic and potentially future pandemics caused by yet unknown viruses. Since 2020, research has been chasing COVID-19 and its variants by reformulating vaccines and developing more antibodies and antivirals, but the virus has always been ahead, mutating so fast to make those approaches obsolete. Because COVID-19 is not going away, and because a dysregulated (toxic) immune response is not unique to COVID-19, and because viral threats will not stop at COVID-19, a virus and variant agnostic drug that can stop the virus from multiplying, can fix the toxic immune response, is easy to administer in an outpatient or pandemic setting (oral), and can be given early or late in the infection cycle is imperative to get ahead of viral threats. In addition to the positive effect on pandemic preparedness and decreasing the pressure on healthcare systems, such drug can positively impact the economy by preventing the devastating health effects that COVID-19 has on the cardiovascular (heart) and nervous systems, which have led to disability claims sharply rising among the working age group.
The proposed project focuses on the lead optimization of a candidate molecule for oral administration against coronaviruses. SARS-CoV-2 infections cause hyperinflammation and autoimmunity leading to multi-organ damage even with mild infections. The damage is cumulative and repeat infections increase the risk of long COVID. These clinical manifestations are due to persistent/chronic infections and dysregulated immune responses. An ideal treatment would not only suppress viral replication but would also restore the immune system homeostasis and healthy immune response. In Phase I, a molecule was designed, synthesized, and shown to be an efficient immunomodulatory and broad-spectrum antiviral. This molecule targets the host rather than the virus which decreases the chances of resistance and makes it virus/variant agnostic, unlike vaccines and direct-acting antivirals. In Phase II, the technical objectives focus on design, synthesis, and testing of analogs with improved drug-like properties for oral administration. Those analogs will be evaluated against several SARS-CoV-2 variants in-vitro, subjected to in-vitro ADME studies, and assessed for their effect on the production of immune mediators in virus-infected cells. The analog with the best profile will advance to in-vivo studies to test its pharmacokinetic and toxicological properties in mice, as well as its efficacy and immune modulations activity in virus-infected animal rodents.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
Alchemie Solutions, Inc.
SBIR Phase II: Re-envisioning alt text for education through concurrent authoring and diagram design
Contact
4735 WALNUT LAKE RD
Bloomfield Hills, MI 48301--1328
NSF Award
2404541 – SBIR Phase II
Award amount to date
$1,000,000
Start / end date
05/01/2024 – 04/30/2026 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact of this SBIR Phase II project is to create a pathway to success in STEM for all students, including those who are blind or have low vision (BLV), with a truly usable and effective description system for STEM diagrams. The lack of accessible accommodations creates roadblocks for BLV students in STEM education, leading many students to give up, even though they have equal potential as the general population for academic success. All web-based, non-decorative diagrams are required to include alternative (alt) text descriptions for use with screen readers. Current methods for making STEM visualizations accessible through alt text are not scalable or amenable for use with dynamic digital media. Visualizing STEM concepts through a linear string of text can be difficult for BLV students, because of the high cognitive load. Integrating an interactive method for querying specific information provides screen reader users a more personalized learning experience. This interactive system can be used by all students to make sense of STEM concepts, creating a use case where all users benefit from the inclusion of alt text. Commercialization will be from integration into existing learning platforms to meet accessibility requirements required of federally funded educational institutions.
This Small Business Innovation Research Phase II project will create an expandable system for generating detailed and standardized descriptions of STEM diagrams in interactive media. The goal is to provide real-time alt text generation for screen reader users (SRUs) and to create an inclusive and accessible communication method for all students in STEM courses. The alt text description engine provides a method for integrating visual information from STEM diagrams with large language models and the algorithms of current artificial intelligence (AI) platforms. The AI-driven learning assistant from this project guides SRUs in understanding complex alt text descriptions in a manner that best matches their skillsets and prior knowledge. The AI learning assistant also provides personalized contextual learning support for all users. The technical objectives include 1) Expanding the architecture to scale the alt text generation engine to other STEM subjects and readily integrate with AI platforms, 2) Implementing accessibility features to the suite of learning interactives, and 3) Developing a database of learning activities aligned to learning objectives. Usability studies with SRUs and instructors will guide iterative product development. Research studies in classrooms will demonstrate the promise of outcomes to enhance commercial success for the suite of accessible learning interactives.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
Anaflash Inc.
SBIR Phase II: Logic compatible non-volatile neural network accelerator using analog compute-in-memory architecture
Contact
1290B REAMWOOD AVE OFC E
Sunnyvale, CA 94089--2233
NSF Award
1951113 – SBIR Phase II
Award amount to date
$806,000
Start / end date
05/01/2020 – 08/31/2025 (Estimated)
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is to enable energy efficient smart internet of things (IoT) devices capable of running a neural network locally. The proposed energy-efficient neural network accelerator solution uses circuit architecture that allows for chips with a small area, a key enabler for cost-effective adoption and inclusion in space-constrained systems such as mobile devices. The solution is energy-efficient compared to the existing digital logic-based accelerator solutions, which will enable edge implementation for systems with power constraints. The manufacturing process is fully scalable in advanced standard logic processes at almost all manufacturing foundries, thus allowing for widespread adoption of the architecture. The outcome of this project will be an energy-efficient system on a chip (SoC) solution that offers artificial intelligence integration in smart IoT devices without cloud access, while enabling security and privacy enhancements.
This Small Business Innovation Research (SBIR) Phase II project seeks to further develop an energy efficient analog circuit topology and variation tolerable system solution. To enable analog compute-in-memory architecture based neural network accelerator solution in an advanced semiconductor process technology, significant design challenges need to be solved with reduced supply voltage and noise margin. Along with the newly proposed area efficient and performance efficient analog compute-in-memory architecture solution, the logic compatible non-volatile neural network accelerator intellectual property core will be designed, fabricated, and validated in the advanced process technology through the project. Once verified successfully from the fabricated silicon in this project, the proposed neural network IP will be ready to be integrated as a key building block of future artificial intelligence systems on a chip and enable energy-efficient smart edge IoT devices.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
Aquasys LLC
SBIR Phase II: Machine Learning Driven Synthetic Sensor for Plant Water Stress
Contact
1925 KENYON ST NW
Washington, DC 20010--2620
NSF Award
2026058 – SBIR Phase II
Award amount to date
$1,000,000
Start / end date
12/15/2020 – 12/31/2025 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
This SBIR Phase II project will advance a novel system for sensing, predicting, and addressing plant stress, offering affordable guidance for permanent and specialty crop farmers. This guidance will simultaneously reduce irrigation water and agricultural chemical applications, while also increasing crop yields and farmer profits. The project will develop easy-to-use equipment and software that delivers guidance compatible with installed irrigation systems and processes. The addressable market for this technology is $3 B in the United States and $30 B internationally. The system's ability to reduce the use of irrigation water and chemicals has a profound societal benefit. The system will conserve scarce fresh water resources, allowing for population growth and an increase in irrigated land. The system will reduce water pollution from agricultural activities, addressing a $210 B annual problem in the United States; furthermore, it will improve agricultural yields, ensuring adequate food for growing populations, with reduced use of pesticides and fungicides.
This SBIR Phase II project will demonstrate a software and distributed hardware system for measuring and predicting yield-reducing plant abiotic and biotic stressors, and delivering intervention guidance to farmers to mitigate these stressors. In order to predict plant stresses at a localized level, many data feeds must be fused and analyzed to create a synthetic sensor estimating plant water stress, predicting microclimatic conditions, and performing localized plant disease and pest modeling. The project will advance the fields of ultra-low power sensor arrays, wide-area networking, machine learning, and human interface design for big data interpretation.
This project will expand a test system by adding microclimate and disease and pest model prediction algorithms for precision temporal and location-targeted interventions of irrigation, fertilizer, fungicide, pesticide, and biostimulant applications to mitigate plant stress.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
Arieca Inc.
SBIR Phase II: Ultrasoft Thermal Interface Elastomer for Microelectronics
Contact
201 N BRADDOCK AVE STE 334
Pittsburgh, PA 15208--2598
NSF Award
2233069 – SBIR Phase II
Award amount to date
$858,714
Start / end date
04/15/2023 – 03/31/2025 (Estimated)
NSF Program Director
Errata
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Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase II project is in improving the efficiency and performance of electronic devices. Modern devices, including cell phones, laptops, and electric vehicles contain high-powered semiconductor components which generate unwanted heat that, in turn, reduces their efficiency. If left unchecked, this heat may destroy the devices and even injure users or cause damage to the environment. This project addresses excessing heating in electronic devices by introducing new high-performance thermal interface materials based upon embedding liquid metal droplets inside of stretchable polymers. These so-called liquid metal embedded elastomer (LMEE) materials can be applied to computer processors, graphics cards, advanced artificial intelligence (AI) chips, and even power modules in electric vehicles, to help keep electronic devices operating at peak performance at all times. The growing prevalence of the Internet of Things, 5G network infrastructure, and electric cars all necessitate better thermal solutions so that devices can function properly. This project could contribute to the semiconductor, automotive, and healthcare industries.
This project?s goal is to develop and commercialize a thermal interface material (TIM) for packaged microelectronics, building upon the LMEE composite architecture. The technology will outperform existing TTIMs by combining the superior thermal resistance of metal-based solid TIMs (S-TIMs) with the mechanical reliability of polymer-based TIMs and the high-volume manufacturing compatibility of thermal greases. Specifically, LMEEs possess a unique combination of metal-like thermal resistance, rubber-like elasticity, and liquid emulsion-like rheology prior to curing, thereby solving two main challenges present with existing S-TIMs: (i) poor mechanical reliability over long durations and (ii) incompatibility with syringe-based dispensing for high volume manufacturing. The strategy proposed in this project is to synthesize an LMEE-based TIM that forms a robust bond between the surfaces of the semiconductor chip and surrounding enclosure, maintains a controlled thickness between the chip and enclosure, and ensures the necessary rheology for syringe-based dispensing. Specific project tasks build around a comprehensive technical plan that includes materials synthesis, performance characterization, and in-package evaluation. In parallel, the project will examine methods for storage, shipment, and dispensing to ensure a product that is ready for integrated device manufacturers and semiconductor assembly and testing industry by the end of this project.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
Axalume Inc.
SBIR Phase II: High-performance, tunable silicon laser arrays designed for mass production
Contact
16132 CAYENNE CREEK ROAD
San Diego, CA 92127--3708
NSF Award
1927082 – SBIR Phase II
Award amount to date
$919,519
Start / end date
09/15/2019 – 11/30/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is demonstrate new lasers for advanced communication and sensing applications. The proposed work includes the design, simulation, and testing of new lasers to meet rapidly-growing high-speed data center optical communication and emerging automotive laser range-finding requirements.
The proposed project activities will include the design, simulation, and experimental verification of hybrid, external-cavity silicon-based optical sources to meet rapidly-growing high-speed datacenter optical communication and emerging automotive laser range-finding requirements. The project will demonstrate that a flexible electronic-photonic integration process can be created to enable dense integration of silicon-photonic and silicon-electronic circuits, independent of specific foundry or fabrication production limitations. This process can be used to develop arrays of high-performance, low-noise, and widely-tunable lasers for advanced optical communication and sensing applications. The proposed project will address existing laser mode-control issues and reduce back-reflection issues. The result will be silicon-photonic lasers suitable for commercial production that will demonstrate industry-leading semiconductor laser capabilities including low-noise, narrow-linewidth, and wide tunability in single and multi-laser chipsets.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
Axon Dx LLC
SBIR Phase II: Development of AI Software to Capture and Identify Circulating Rare Cells in Lung Patients
Contact
379 REAS FORD RD STE 1
Earlysville, VA 22936--2407
NSF Award
2230782 – SBIR Phase II
Award amount to date
$999,702
Start / end date
03/15/2023 – 02/28/2025 (Estimated)
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is a new cancer treatment liquid biopsy product using Artificial Intelligence (AI) that can detect and classify cancer derived rare cell (CRC) from a blood draw. There are over 100 different types of cancers and over 1.9 million new cancer cases are expected to be diagnosed in the US in 2022 resulting in over 600,000 deaths (1,670 deaths per day). Cancer is the second most common cause of death in the US, exceeded only by heart disease. New treatment therapies are being developed for a substantial proportion of cancers with many clinical trials for new therapies on-going world-wide. The minimally invasive, high sensitivity blood test will monitor therapeutic response and progression at low-cost, supporting development of these new cancer treatments. Specifically, with a less invasive and more comprehensive diagnostic tool, the test results will give clinical researchers real-time insights into cancer tumor biology, providing better understanding of cancer heterogeneity.
This Small Business Innovation Research (SBIR) Phase II project combines Artificial Intelligence (AI), specifically deep learning neural networks used for computer vision, with CRC immunofluorescent reagents integrated into an immunofluorescent microscope. The main objective of this effort is to identify and classify CRCs with high accuracy. There is increasing evidence that CRCs are correlated with cancer type, staging, treatment response, minimal residual disease, and overall disease progression. However, in a typical blood sample, there are over 7 million blood artifacts with very few CRCs present. Current techniques to analyze CRCs are expensive, lengthy, and are limited in automation. To meet project sensitivity, specificity, and runtime requirements, the AI image analysis will be further optimized to: 1) find CRCs, 2) discriminate against false positives, and 3) classify CRCs into clinically relevant types. The developed AI architectures will be selected through extensive training using thousands of clinical samples compared to expertly characterized cancer blood pathology images. After high sensitivity and specificity are demonstrated, development work will continue to mature the AI-revolutionized CRC liquid biopsy test to meet clinical research use only (RUO) requirements. For the cancer research community, the product offering will be used in the conduct of non-clinical laboratory research.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
BABYLON MICRO-FARMS INC.
SBIR Phase II: Intelligent modular vertical farming system
Contact
700 HARRIS ST STE 107
Charlottesville, VA 22903--4584
NSF Award
2035792 – SBIR Phase II
Award amount to date
$999,056
Start / end date
05/01/2021 – 11/30/2024 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is to improve vertical farms. The global threat to food security and the need to deal with unpredictable climate conditions have opened the doors to advanced precision agriculture and vertical urban farming. Rapidly growing global populations, demand for higher agricultural yields with limited arable farmland drive demand for vertical farming and new technologies to expand access to this method of sustainable crop cultivation. The proposed system will reduce the burden on the environment by decreasing water, fertilizers and pesticides required to grow crops. These micro-farms will boost agricultural profitability by providing a reliable, sustainable food system with fresh, healthy, and eco-friendly produce. This reduces food waste and the environmental impact of the food supply chain while improving yields and nutritional density.
This SBIR Phase II project advances a system with integrated environmental control, consumables management, alerting, and scheduling. Furthermore, the automated controls are continuously improved by using camera vision to estimate yield and machine learning to forecast yield and optimize the environmental variables. To make the system cost-effective, a novel multispectral camera will be developed to collect agricultural data. Using machine learning, the images collected will be correlated to the environmental variables, such as pH and nutrient concentration, so that those variables can be optimized to increase yields. In order to improve scheduling and logistics, the platform will track inputs such as seeds, nutrients, and pH solution, using sensors and QR codes to automate consumable replacement. Sensors and software checks will determine when component or human failure have occurred, before they lead to crop failure, leading to just-in-time component replacement and maintenance.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
BALLYDEL TECHNOLOGIES INC.
SBIR Phase II: Serialized Anti-Counterfeit Labeling Technology for Pharmaceutical and Biological Products
Contact
200 POWDER HILL RD BLDG E500
Wilmington, DE 19803-
NSF Award
2330736 – SBIR Phase II
Award amount to date
$951,394
Start / end date
06/15/2024 – 05/31/2026 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase II project is on the mitigation of the worldwide counterfeit drug market which has a significant impact on public health, brand integrity, and revenue. Specifically, this project aims to develop a state of the art, counterfeit-proof, ID security technology that enables vaccine and biologic manufacturers to tag, track, and authenticate its products throughout the supply chain. The technology involves a scalable manufacturing process that imprints a covert and highly encrypted pattern onto a label that may be placed on individual vaccine vials. The imprinted pattern produces an image that may only be read with a proprietary interrogation process. Additionally, each label incorporates a serialized code. The focus of this serialization is to provide each dose, each vial, with its own unique signature or fingerprint. The serialization aspect of the labels is significant for vaccine/biologic manufacturers, as this enables traceability of dosage form throughout the supply chain, a mandate required by global regulatory agencies.
The proposed project aims to provide both the pharma industry and the global health community with tagging technology that ensures supply chain integrity for drug products throughout the world. Specifically, the focus of the Phase II effort is to: 1) demonstrate the scalable production of computationally designed tags, 2) integrate an automated tagging and reading process directly with a drug product manufacturing line, and 3) demonstrate the production and use of a handheld reader that enables authentication of product at any point in the supply chain. An ID technology that differentiates authentic from counterfeit products is anticipated at the conclusion of the effort. The authentication process will reveal product composition, origin of manufacture, date of manufacture, expiration, and other pertinent information. The labels will withstand temperatures typically encountered during storage and will also incorporate various degrees of tamper evident and tamper proof characteristics.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
BEAMLINK, INC.
SBIR Phase II: Adaptable Ad Hoc Network Architecture for Rapid Infrastructure Development in Disaster Zones
Contact
892 N FAIR OAKS AVE
Pasadena, CA 91103--3046
NSF Award
2322049 – SBIR Phase II
Award amount to date
$999,932
Start / end date
12/01/2023 – 11/30/2025 (Estimated)
NSF Program Director
Errata
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Abstract
This Small Business Innovation Research (SBIR) Phase II project reduces the cost and complexity of building modern cellular networks. In grave emergencies such as natural or manmade disasters, and in rural areas where infrastructure for Internet access is limited, one of the largest barriers to digital access is the cost and complexity of building cellular networks. Cellular networks are relied upon everyday by millions of Americans to communicate with others, conduct business, work together, access healthcare and information resources, and power the economy through Point of Sale (PoS) devices, utility meters and transportation infrastructure. Loss of these cellular networks constitutes a major disruption in life, an example being Hurricane Maria that struck Puerto Rico in 2017 and created a massive island-wide communications blackout that lasted several weeks. Even in normal times, the lack of high-speed Internet sets communities back. According to the U.S. Census in 2020, more than 12% of households across the nation's 50 states do not have internet access. As digital infrastructure is upgraded to 5G and even 6G, cellular base station technology is more expensive, requires expertise to configure, and widening the digital divide. This project will combat these problems.
This Small Business Innovation Research (SBIR) Phase II project will create new cellular base station technology (the equipment that provides cellular signals) to decentralize cellular networks and make them easier to establish. Compared to current solutions, this project will reduce the cost to set up new cellular networks, by at least an order of magnitude compared to existing networks. The technology will reduce the deployment time and enable individuals with no training to easily set up a large network, even if no infrastructure exists. The cellular infrastructure increases the reliability resulting from the use of a mesh network to communicate and transfer data between base stations. The research objectives of this project are to develop integrated digital and radiofrequency (RF) circuitry and the enclosure for a production-ready base station device reducing the cost by 2.5x and the weight by 2x. In addition, the objectives are to develop a high-performance amplifier to allow the base station to operate on any band at higher power up to 1 W peak output, implement telecommunications device for the deaf (TDD) communication ability for the radio and amplifier, implement a spectrum access system, and design a phased array antenna to increase the link budget by up to 18 dBi for the mesh network.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
BEZWADA BIOMEDICAL LLC
SBIR Phase II: Development of a bioabsorbable tissue adhesive
Contact
15-1 ILENE CT
Hillsborough, NJ 08844--1920
NSF Award
2221790 – SBIR Phase II
Award amount to date
$962,735
Start / end date
01/15/2023 – 12/31/2025 (Estimated)
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is advancement in the development of an effective wound closure product for internal gastrointestinal (GI) surgical applications. Anastomotic leaks resulting from ineffective GI surgical wound closures are associated with significant healthcare and economic costs. Effective closure of wounds decreases the likelihood of complications that significantly impact patient outcomes and increases the cost of care. Development of an enhanced tissue adhesive to address the limitations of current products has the potential to offer a reliable wound closure product to support improved patient outcomes. Successful development and commercialization of the enhanced GI wound closure product will provide surgeons with an effective tissue adhesive that is easy to use and can be safe for the closure of internal GI wounds, thus ensuring safe and reliable closure, decreasing anastomotic leaks, and allowing for enhanced patient outcomes. Additionally, this project has the potential to support additional product development to generate improved tissue adhesives/sealants for a wide range of surgical applications that will have the potential to decrease surgical complications related to ineffective wound closure.
This Small Business Innovation Research (SBIR) Phase II project will advance the development of an enhanced tissue adhesive to improve surgical wound care specific to gastrointestinal (GI) tract surgeries. Gastrointestinal tract surgical wounds have a high rate of anastomotic leaks resulting from incomplete and sub-optimal surgical closures. These leaks put the patients at an increased risk of infection and creates an estimated $28.6 million in hospitalization and readmission costs per 1000 patients. Current tissue adhesives for GI applications are biologically derived, which are amenable for internal use but pose a risk of infection. The technology being developed is a polyurethane-based adhesive that is biodegradable, easy to use, and biocompatible. The overall goal of this SBIR Phase II project is to demonstrate in vivo efficacy for the use of the surgical adhesive in GI surgical wound care. To meet this goal, the surgical adhesive formulation developed from Phase I will be refined to identify the ideal formulation for GI use and a lead formulation will be assessed for in vivo performance. The results from this project have the potential to identify a safe, easy-to-use, and effective lead tissue adhesive for implementation in GI surgical applications to prevent anastomotic leaks and improve GI surgical wound closures.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
BIOCHIP LABS, INC.
STTR Phase II: Optimized manufacturing and machine learning based automation of Endothelium-on-a-chip microfluidic devices for drug screening applications.
Contact
10000 CEDAR AVE STE 3-139
Cleveland, OH 44106--2119
NSF Award
2332121 – STTR Phase II
Award amount to date
$904,947
Start / end date
04/01/2024 – 03/31/2026 (Estimated)
Errata
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Abstract
The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase II project is to address the unmet need in the companion diagnostic guided therapy market for Sickle Cell Disease (SCD). SCD is a lifelong disease affecting millions of people worldwide. Emerging therapies are estimated to be $150k-$200k per patient each year. A companion diagnostic cost in SCD anti-adhesive therapies is estimated at least $3,000 per patient. With improved accessibility to patients living in low- and middle-income countries and scalable curative therapies, the global SCD treatment market size is projected to increase to $8.75B by 2029. Additionally, companion diagnostic-guided drugs have an increased regulatory approval probability of 50% in Phase III clinical trials. The proprietary Endothelium-on-a-chip platform with human donor cells provides a physiologically relevant means to study blood-endothelium interaction. This platform can be integrated into preclinical studies to screen the effect of novel drug candidates as well as for assessment of drug toxicity. In Phase I of the STTR project, standards and quality control criteria for experimental conditions on the Endothelium-on-a-chip were established. The continuing projects with pharmaceutical companies have highlighted the need to scale the manufacturing process.
This Small Business Technology Transfer (STTR) Phase II project will focus on optimizing the manufacturing process to enable the scale-up of the assay and develop the machine learning system for automated data analysis. Currently, this assay involves in-house fabrication and is limited to the central laboratory at the company?s location. Manufacturing will be optimized with proper selection of material, fabrication methods, scalable techniques, and systematic integration of different elements of the assay. This will potentially enable the commercialization and implementation of the technology at a larger scale. Current methods of analysis include counting adhesion events manually. This method will be replaced by a machine learning-based system to identify and classify adhesion events and separate those from the endothelial cells in the background. Automated data analysis will enable faster outcomes and remove user bias. Since this approach relies on enhancing the capabilities of the existing platform for scale-up and streamlined analysis, it is anticipated that it will improve its accessibility to the broader research community.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
BIOMESENSE, INC.
SBIR Phase II: Development of a Novel Measurement Technology to Enable Longitudinal Multiomic Investigations of the Gut Microbiome
Contact
1452 E 53RD ST
Chicago, IL 60615--4512
NSF Award
2314685 – SBIR Phase II
Award amount to date
$976,771
Start / end date
03/15/2024 – 02/28/2026 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase II project would be a significant increase the commercial, scientific, and human health potential of the microbiome field by enabling large-scale, dense longitudinal measurement and analysis of microbial RNA. This could enable: (1) a significant reduction in false discoveries caused by a lack of reproducible data; (2) a major cost reduction ? ensuring these advancements are accessible to the entire industry; (3) high-frequency sampling, making time-series explorations routine; and (4) the creation of a large-scale database that contains both DNA and RNA data, which could lead to unprecedented discovery and validation of precision medicine biomarkers. Successful completion of this project could have a high likelihood of advancing the health and welfare of the American public, increasing the economic competitiveness of the United States healthcare and life sciences sector, and enhancing partnerships between academia and industry.
The proposed project describes the development of an RNA feature to an existing microbiome measurement and analysis platform that consists of an automated sample collection system and an analytics engine for sequence data. Currently, the question of which genes are being expressed by gut microbes (which can be studied using RNA transcripts) is an extraordinarily promising research field for advancing the understanding of host-microbial interactions. This is because bacteria that make up a small amount of the gut microbiome can still influence the community dramatically through their gene expression. This can be overlooked by DNA sequence data, which only measures bacterial abundance. Despite this, RNA remains under-utilized, as RNA quickly degrades outside of the cell, and most laboratories lack the capability to measure RNA at any significant scale reliably. The main activities of this project will be (1) refining a process for RNA capture and storage, (2) integrating these into the automated hardware system, and (3) developing the methods and infrastructure for analysis of the resulting RNA datasets. This project will allow studies of gene expression in the gut microbiome to become commonplace, allowing researchers to discover more powerful clinically relevant biomarkers for precision medicine applications.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
BIOMIMICS, LLC
SBIR Phase II: Biobased and Biodegradable Polyester Surfactants
Contact
170 SHUEY DR
Moraga, CA 94556--2556
NSF Award
2343053 – SBIR Phase II
Award amount to date
$1,000,000
Start / end date
09/01/2024 – 08/31/2026 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is to mitigate the environmental impact of personal care products by developing cost-effective and sustainable alternatives to polymeric surfactants widely used in formulations. A typical surfactant contains over 55% carbon content, whereas the developmental surfactants proposed in this Phase II project can have at least 20% lower carbon content than their commercial counterparts, thus significantly reducing carbon dioxide emissions. Given that an average U.S. citizen uses between 2 and 6 personal care products daily, the majority of which contain 3% to 40% surfactants, this Phase II project's potential environmental and, hence, societal benefits are significant. This work will enhance the design understanding of these polymeric surfactants that will be built using farm residue ingredients and programmed to biodegrade after their useful life, creating a closed-loop carbon cycle. The market impact of these polymeric surfactants is not limited to personal care products but extends into household detergents, institutional and industrial cleaners, agriculture, oilfield chemicals, food processing, textiles, etc. This project can revolutionize multiple industries, making it a promising commercialization opportunity.
The proposed project intends to develop and scale up the next-generation polymeric surfactants, which are safe for human use, enhance consumer experience, and are built with environmental sustainability in mind. The development and utilization of a novel chemoselective synthesis will enables a polycondensation reaction for building polyester and polyesteramide surfactants from biobased residues. The research objectives are to 1) demonstrate that the optimized surfactants can be scaled up using green chemistry principles, 2) demonstrate, verify, and validate their surface activity, 3) establish their safety profile, and 4) validate their biodegradability. This research will utilize design-of-experiment studies to generate surface response curves to identify the optimized surface activity attributes by varying the molecular composition of the polymeric surfactants. Furthermore, the safety studies for the optimized surfactants will confirm their suitability for human skin applications, while biodegradability tests will ascertain their ready biodegradability in effluent treatment plant environments. Successful execution of the experimental design will result in the development of sustainable polymeric surfactants.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
BIOSENS8, INC.
SBIR Phase II: Novel progesterone biosensor for monitoring fertility health
Contact
750 MAIN ST
Cambridge, MA 02139--3544
NSF Award
2341568 – SBIR Phase II
Award amount to date
$1,000,000
Start / end date
01/15/2024 – 12/31/2026 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
This Small Business Innovation Research (SBIR) Phase II project provides more 7.7 million women in the U.S. struggling with infertility a quantitative and affordable way to assess their ovulatory health. This progesterone biosensor is the first outcome of a platform technology built to improve at-home blood diagnostics and telehealth implementation. This project will produce a novel class of inexpensive, real-time, and point-of-care biosensors. The commercialization of this product may also increase public engagement and comfort with biosensors and at-home diagnostics. In concert with informational videos, website pages, and workshops the commercialization of this product will improve scientific literacy. Finally, the affordability of this product may help narrow the disparity of access to fertility technology allowing for more socioeconomically disadvantaged and underserved populations equal opportunity to assess their fertility.
This Small Business Innovation Research (SBIR) Phase II project is developing a novel class of biosensors for progesterone. The technical hurdles to be addressed are to first translate optical transduction technology onto low-cost paper strips, then to determine the efficacy of the biosensors as paper test strips. The team will then develop a low-cost and portable measurement device which reads the paper lateral flow strips. The anticipated technical results are a lateral-flow strip device which can measure progesterone from clinical blood samples of women who have never been pregnant, women with Polycystic Ovary Syndrome (PCOS), pre-menopausal women, and post-menopausal women down to levels which indicate successful ovulation.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
BIRCH BIOSCIENCES, LLC
SBIR Phase II: Enzymes for Accelerated Plastic Recycling
Contact
4023 NE HANCOCK ST
Portland, OR 97212--5324
NSF Award
2414859 – SBIR Phase II
Award amount to date
$1,000,000
Start / end date
09/15/2024 – 08/31/2026 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase II project is to improve the economics, sustainability, and circularity of polyethylene terephthalate (PET) plastic recycling. Conventional plastic recycling technologies are typically energy intensive, produce low quality plastic, and do not enable continuous recycling of PET plastics into recycled, high value PET packaging for food contact and similar applications. Today, less than 9% of plastics are recycled in the United States. Enzyme-mediated plastic recycling may enable more types of PET plastics to be recycled. In addition, enzyme-mediated plastic recycling may improve the quality and purity of recycled PET plastic products, enabling efficient, circular recycling of bottles, thermoformed PET, and polyester textiles. Future plastic manufacturing could use enzymatically recycled plastics rather than sourcing chemical building block molecules from fossil fuel-derived sources. Development of this novel recycling technology could serve as an example to improve the recycling rate of other types of plastic, reduce carbon emissions associated with plastic manufacturing, and reduce the plastic pollution in our environment.
The proposed project is focused on developing high performance engineered enzymes for breakdown of PET plastic into circular plastic chemical building blocks. Enzymes act as specific molecular scissors to cut bonds within the PET polymer plastic and release the chemical building blocks terepthalic acid and ethylene glycol that are drop-in replacements for PET plastic manufacturing. These chemical building blocks should be high quality and enable manufacturing of PET plastic products from 100% recycled materials. The goal of this research is to design and engineer enzymes that efficiently break down PET plastic in a sustainable and economical process under industrial, scalable recycling conditions. These enzymes will be designed to operate within a simplified end-to-end recycling process that uses novel, green chemistry to enable efficient recovery and purification of chemical building blocks for remanufacture of high quality plastic products.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
BioAmp Diagnostics, Inc.
SBIR Phase II: Development of a urine dipstick test that can guide immediate and appropriate antibiotic therapy for treatment of complicated urinary tract infections
Contact
845 SUTTER ST APT 103
San Francisco, CA 94109--6109
NSF Award
2213034 – SBIR Phase II
Award amount to date
$1,000,000
Start / end date
01/15/2023 – 12/31/2025 (Estimated)
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is to improve the clinical outcomes and quality of life for patients suffering from complicated urinary tract infections (cUTI). Today, cUTIs account for 400,000 hospitalizations annually in the United States. Unfortunately, multidrug resistant pathogens are a common cause of cUTI. Many are resistant to the first-line antibiotic (Ceftriaxone), which is used as the empiric treatment of this condition. However, the high incidence of multidrug resistant pathogens causing cUTI delays the time until patients receive more appropriate treatment. Delayed time to appropriate therapy in cUTI has been attributed to extended hospital stays and an increased risk of morbidity and mortality. The current standard test for diagnosing a drug-resistant cUTI takes 2-3 days from obtaining a patient sample. Therefore, diagnostic tests that can rapidly inform the initial treatment of UTIs are urgently needed to improve patient care.
This Small Business Innovation Research (SBIR) Phase II project aims to develop a rapid urinary diagnostic test that will enable the detection of ceftriaxone-resistant uropathogens. Early detection of resistance to first-line therapies would enable antibiotic prescribing to be informed, reducing the risk of disease progression in patients. In the case of UTIs, disease progression can lead to severely invasive infections, predominately sepsis. Therefore, diagnostics that can detect resistance to first-line antibiotics enable early treatment interventions, reducing the time to appropriate treatment and reducing the risk of disease progression. Decreased treatment time also lowers the healthcare costs associated with drug-resistant cUTI, as disease progression is associated with increased lengths of hospital stays compared to susceptible infections. The completion of the Phase II project will yield the development of a prototype test that can provide actionable information regarding ceftriaxone susceptibility in less than 5 minutes. This project?s success will provide clinicians with a diagnostic solution for cUTIs that can be acted on immediately to improve patient outcomes and aid antibiotic stewardship by preventing the unnecessary use of inappropriate antibiotics.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
CANOMIKS, INC.
SBIR Phase II: Genomics and AI technology to benchmark biological effects of active ingredients in dietary supplements, food, beverages and skincare to ensure safety and efficacy
Contact
221 FIRST AVE SW
Rochester, MN 55902--3125
NSF Award
2335033 – SBIR Phase II
Award amount to date
$998,064
Start / end date
06/15/2024 – 05/31/2026 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase II project is an innovation to test functional ingredients used in the health and wellness industry, ultimately being a critical first step in the development of efficacious and responsibly sourced consumer products. Using this innovation, companies within the functional food and beverage, dietary supplement, and skincare (FFBDS) industry including, ingredient suppliers, manufacturers, and consumer packaged goods (CPG) can produce safe and effective products backed by scientific rigor. Additionally, this technology enables companies to quickly and cost effectively assure ingredient consistency and quality. The end result is consumers' access to products that are supported by science, bringing clarity, trust, and ease to the purchasing process in a confusing market. Long-term, the data from these studies can help with understanding which ingredients have the most beneficial effect on human health and can be used to develop personalized nutrition products. The data can also be tied to ingredient traceability insights and to optimize sustainable farming, harvesting, extracting, and manufacturing practices to produce ingredients with the most advantageous biological effect. Ultimately, the outcomes from this project could benefit all stakeholders in the functional ingredient supply chain, from farmers to producers to the end consumers.
The proposed project creates a new testing standard for ingredients used in FFBDS products that measures the ingredient?s biological effect quickly and cost-effectively. Functional ingredients have benefits beyond normal nutrition, including ingredients such as curcumin (turmeric), cranberry, and elderberry. However, companies face challenges sourcing ingredients that are consistent in batch-to-batch quality. Currently available batch-to-batch testing methods fall short, measuring only the amount of ingredients but not their biological activity. In the present proposal, using commercially available human cells, and genomics and artificial intelligence technologies, biological effect benchmarks will be developed for the functional ingredients. Processes and protocols established for turmeric benchmark development in Phase I of this project will be used to optimize cranberry and elderberry benchmark development through this Phase II project. The final product will be a lab test that compares the commercial functional ingredients? biological effectiveness to that of the benchmark. Upon test completion, customers will receive a report detailing the biological effect score of the ingredient, a list of key genes affected with a description of their relevance to human health. This high-throughput, cost-effective test will enable companies to develop products that help build consumer trust and confidence as well as mitigate compliance risk.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
CANOPII INC.
SBIR Phase II: Full-Scale Demonstration of Autonomous Robotic Greenhouse for Sustainable Local Food Production
Contact
191 IOWA ST
Silverton, OR 97381--1942
NSF Award
2233520 – SBIR Phase II
Award amount to date
$999,991
Start / end date
05/01/2023 – 04/30/2025 (Estimated)
NSF Program Director
Errata
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Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase II project promotes small and mid-sized farming in the United States through environmentally friendly means. Through cost-effective labor automation, a fully automated, turn-key greenhouse production system can be made more accessible. This project will provide farmers with a tool that can guarantee a baseline annual production of leafy greens and herbs, independent of weather variables and labor accessibility. By removing weather limitations and labor requirements, small and mid-sized farms can be made more profitable and scalable. This project will have a positive impact on the advancement of local and regional food systems. By advancing a market that has been historically ignored from a technological standpoint, an attractive alternative to large-scale industrial agriculture and foreign fresh food imports will be created. Making small and mid-sized farms more economically viable will create a more robust and sustainable food system.
This SBIR Phase II effort will design, build, and demonstrate a full-scale, automated greenhouse farm prototype. This prototype will remain completely autonomous for weeks at a time requiring no humans to enter the farm while all processes from seed to storage of harvested crops are performed robotically. No greenhouse technology, at any price point, has been able to demonstrate an ability to achieve this degree of automation. This technology will advance the implementation of robotics in food production by addressing the capital costs, labor, and energy barriers that controlled environment agriculture systems currently face. Key challenges include the production of approximately 340 plants per day without any human intervention, a low-cost design for setup and ongoing operations, and the ability to adjust product outputs in real-time to meet market demands. Human interaction with the growing process will be limited through a high degree of system automation, including computer vision for plant inspections and self-cleaning processes. Novel plant growth and handling processes will allow for virtually any type of leafy green or herb to be grown. A variety of sensors will be used to monitor conditions and adjust the system, allowing fresh produce in areas without suitable agricultural opportunities.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
CARTESIAN SYSTEMS, INC.
SBIR Phase II: A Handheld Fine-Grained Radio Frequency IDentification (RFID) Localization System for Retail Automation
Contact
169 MONSIGNOR OBRIEN HWY APT 301
Cambridge, MA 02141--1277
NSF Award
2409627 – SBIR Phase II
Award amount to date
$1,000,000
Start / end date
08/15/2024 – 07/31/2026 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase I project is to help US retailers and consumers save billions of dollars, while enhancing the technological competitiveness and sustainability of the United States of America. Specifically, this project will improve labor efficiency for retailers, thus alleviating the $27B labor shortage they face today. By cutting labor costs, the product would not only help retailers but also tame retail inflation to end-consumers. Furthermore, by introducing cost-effective solutions to brick-and-mortar retailers, this project will boost their competitiveness with e-commerce giants, resulting in better quality and prices and higher customer satisfaction. The developed technology will also help supply chain operations become more sustainable by enabling industries to reduce excess inventory, improve end-of-life item returns, and repurpose old goods. Finally, the project will bring a new generation of indoor positioning technologies to the retail and supply chain sectors, elevating the experience for retail workers and shoppers.
This Small Business Innovation Research (SBIR) Phase I project seeks to design, build, and evaluate a system for inventory tracking in retail stores by leveraging mobile radio frequency (RF) identification (RFID) technology. The proposed plan has multiple technical objectives: (1) developing computer vision machine learning models for automatic map creation and updates, (2) designing algorithms for robust self-localization of the handheld mobile device indoors, (3) developing RF-visual sensor fusion algorithms for item-level 3D localization, and (4) developing augmented reality-based user interfaces for scanning and navigating indoor environments. The technical contributions will go beyond designing the algorithms to implementing them on a mobile-to-cloud platform and evaluating them in real retail stores. This project will advance the state-of-the-art in indoor positioning and mapping, impacting the fields of mobile vision, RF localization, split computing, and human computer interaction.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
CELLUDOT LLC
SBIR Phase II: Nanocellulose-based Adjuvant Formulation for the Reduction of Agrochemical Drift and Volatilization
Contact
123 W MOUNTAIN ST
Fayetteville, AR 72701--6069
NSF Award
2304528 – SBIR Phase II
Award amount to date
$959,510
Start / end date
08/15/2023 – 07/31/2025 (Estimated)
NSF Program Director
Errata
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Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase II project is to provide an ecofriendly, efficient, and cost affordable adjuvant product to solve the pressing problem of herbicide drift. For years, farmers growing organic, non-genetically modified (non-GM) and specialty crops have incurred financial losses in the hundreds of millions of dollars due to drift of volatile herbicides such as dicamba, a highly volatile and efficient herbicide that is used to get rid of weeds. The devastation of dicamba on non-GM crops and the natural landscape has been a widespread issue. In 2021, about 4,000 dicamba-related herbicide misuse complaints were reported across 27 states. If successfully commercialized, the new adjuvant will help all key stakeholders, including farmers who grow GM crops and use dicamba, and those who grow non-GM crops and do not want drift of dicamba. The award reflects NSF?s statutory mission of promoting and improving national economy and health, as well as protecting the environment for the well-being of U.S. citizens.
The innovation proposed in this SBIR Phase II project is a bio-based emulsion adjuvant, derived from renewable resources, with the combined functionality of a volatility and drift reducing agent and surfactant that will be used to reduce the volatility and off-target movement of herbicides and improve their spreading. The adjuvant has environmental and financial benefits that give it a competitive edge over commercially available but less efficient petroleum-based and synthetic adjuvants on the market. The patent-pending technology is a platform technology that can be applied to other industries from paints and coatings to pharmaceuticals. The project sets the following technical objectives to evaluate and demonstrate the commercial feasibility of the innovation: 1) assess droplet dynamics of several drift-prone herbicides when used in conjunction with the adjuvant at different use rates, 2) complete the registration of the adjuvant, 3) conduct field trials to evaluate particle drift of dicamba and dicamba-glyphosate tank mixes when used in conjunction with the adjuvant, 4) low tunnel field test to assess volatility of tank mixes on different surfaces, 5) evaluate the effects of the adjuvant on dicamba efficacy that are common in the South and Mid-West, and 6) scale up the production of the minimally viable product.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
CHIBITRONICS INC.
SBIR Phase II: Computer Aided Design Toolkit for Desktop Digital Fabrication of Circuits on Paper
Contact
1652 MOUNTAIN ASH WAY
New Port Richey, FL 34655--4144
NSF Award
2233004 – SBIR Phase II
Award amount to date
$991,408
Start / end date
06/15/2023 – 05/31/2025 (Estimated)
NSF Program Director
Errata
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Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase II project is to bring new and more diverse audiences to circuit design and digital fabrication through an integrated STEAM (science, technology, engineering, art, and math) approach. Research shows that the STEAM approach is especially successful for reaching underrepresented minorities, girls, and women. This project continues the development of the Phase I circuit design software and accompanying physical toolkit for do-it-yourself (DIY) digital fabrication of circuits on paper. Through the design, development, and evaluation of this toolkit, the team will contribute to the scientific understanding of human computer interaction design for STEAM learning, accessibility, and equity. By introducing the novel category of technology-integrated crafts to mainstream education and craft markets, open market opportunities create a new ecosystem of products and accessories, customers, and inventors. This innovation brings the digital manufacturing of electronics out of traditional technical environments and into entirely new, more mainstream, and more diverse audiences.
This Small Business Innovation Research (SBIR) Phase II project will continue the development of the Phase I activities towards commercial deployment. The team is developing a novel electronics design software that greatly reduces the complexity of existing computer-aided design tools and prepares a custom toolkit optimized for the do-it-yourself digital fabrication of circuits. The research objective is to blend engineering activities with arts and crafts in innovative ways to radically reduce the barriers to entry for learning, designing, and producing electronic circuits. The team will develop a production version of their software that includes advanced simulation and design features, as well as a library of projects and resources to scaffold the circuit learning and design process. The team will also refine and manufacture the toolkit for user testing and deployment at scale. In close partnership with K-12 educators and hobby crafters, the technology will be developed to meet the needs of target users.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
CHOSEN DIAGNOSTICS INC
SBIR Phase II: Absolute protein quantitation in in vitro diagnostics for gut inflammation
Contact
1441 CANAL ST
New Orleans, LA 70112--2714
NSF Award
2242174 – SBIR Phase II
Award amount to date
$999,749
Start / end date
03/15/2024 – 02/28/2026 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase II project is to advance clinical methods that address the extensive physiological variation that is age- and race-dependent. Well-publicized over the last few decades is the lack of healthcare solutions for diseases in preemie babies, who are born to mothers with significant socioeconomic inequalities. Case in point, necrotizing enterocolitis (NEC) is a common and often fatal gastrointestinal, or gut, emergency in premature infants that disproportionately affects African American babies. The disease has not only confounded doctors and nurses for 200 years, but also these neonatal emergencies are also frightening to almost all preemie care providers due to its high mortality rate. Its healthcare in the US requires $3 billion annually due to repeated x-ray testing, surgery, longer hospital stays, and long-term complications of its survivors. An early and accurate diagnostic test for NEC would be a disruptive paradigm shift in preemie intensive care: it would enable medical intervention to be more effective, reduce risk of disease progression, decrease medical care expenses by hundreds of millions annually, and lower mortality.
The proposed project will develop requisite reagents for a diagnostic test that will enable detection of infant proteins that play a role in gut health. Absolute quantitation is a prerequisite for data interpretation and validation between experiments, laboratories, and testing platforms. Research objectives are directed toward critical technical hurdles: (1) determination of optimal reference standard to quantitate host biomolecules in clinical settings and (2) understanding the usage limitations of these reference standards in the background of high variation in the human population. Native and recombinant candidates will be compared and analyzed with various methods. Anticipated results are reference standards that are age-specific for diagnostic use in the most fragile and smallest patients and that are acceptable to regulatory stakeholders.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
CL CHEMICAL COMPANY
STTR Phase II: Scalable Thermochemical Conversion of Carbon Dioxide to Commodity Chemical Intermediates
Contact
17815 GREEN WILLOW DR
Tampa, FL 33647--2242
NSF Award
2151560 – STTR Phase II
Award amount to date
$951,530
Start / end date
09/01/2023 – 08/31/2025 (Estimated)
Errata
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Abstract
The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase II project is to advance dynamic chemical reactor systems that repurposes waste gases (primarily carbon dioxide (CO2)) for use as fuels and as chemicals. This effort can have substantial commercial and market impacts as its output is compatible with existing infrastructure. This project leverages significant recent investments into carbon capture, renewable energy generation, and green hydrogen. A particularly interesting application of this technology is the production of chemical feedstocks that are used to make plastics and other commodity chemicals from living organisms. This is inherently a step towards carbon negative manufacturing.
The proposed project aims to re-purpose pollutants to a feedstock for fuels and chemicals. Although renewable energy sources are increasing and becoming cheaper, these technologies are not ready for heavy-duty transportation and chemical sectors. No commercial scale operation is in existence in which CO2 is captured from the air or flue gas and converted to value-added fuels despite much fundamental research effort. The research objectives are to scale up the materials and system from the Phase I results and conduct a design and analysis of a full-scale system. The main advance is to achieve dynamic chemical reactor modules that achieve high reactant conversions. These results will permit analysis of a pilot-scale facility as well as translation of the benefits of this sustainable chemical reaction toward industrial scale production of clean and green hydrocarbon fuels and chemicals.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
CLAUDIUS LEGAL INTELLIGENCE INC
SBIR Phase II: Artificial Intelligence Tool for Analysis of Legal Documents
Contact
6920 SW 44TH ST APT 107
Miami, FL 33155--4772
NSF Award
2335532 – SBIR Phase II
Award amount to date
$947,862
Start / end date
09/01/2024 – 08/31/2026 (Estimated)
Errata
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Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase II project will be to reduce the need for attorney-driven expertise and an extended discovery period, and instead shift reliance to data-driven expertise to enhance and democratize outcomes in civil cases. The proposed AI platform will allow for the computational prediction of case outcomes, helping to better inform case decisions and address existing inefficiencies within the legal industry. Adoption of this technology will allow attorneys to bypass the time-intensive process involved in case value prediction, allowing for more time to focus on discovery and strategy, as well as allow for better informed decision-making. Notably, the platform will have built-in anti-bias algorithms that will actively work to correct discriminatory past outcomes when making data-driven computations moving forward. Therefore, this technology is not only the first to unlock access to the wealth of informative yet disparate data to support personal injury attorneys in quickly making reliable decisions but is also alone in delivering anti-bias tools that improve fairness and access to justice for clients from all backgrounds, most notably among demographics that have not historically received equal or fair compensation.
This Small Business Innovation Research (SBIR) Phase II project aims to improve the likelihood of a positive outcome for attorneys? clients, while also freeing up time for attorneys to take on greater caseloads, resulting in social justice gains. In virtually every business sector, data analysis has become a driving force behind decision-making, yet the legal services sector has largely lagged, with many law firms instead relying on conventional wisdom and time-intensive research. To address this issue, the preceding Phase I project leveraged an innovative learning technique to enable algorithm training across multiple decentralized databases without exchanging data samples, thus keeping information private and confidential. This Phase II project seeks to 1) Build out the artificial intelligence (AI) model to return predictions on value and outcomes over case lifetime and improve accuracy of trial predictions; 2) Expand platform features to support case management and improve usability; and 3) Build a novel dataset compiling demographic information on 50,000 case outcomes to quantify the racial component of case bias and develop bias-correcting models. This project will significantly expand the applicability of the AI-driven platform to deliver reliable, equitable, and interpretable outputs on case value prediction for diverse case types.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
COBIO DIAGNOSTICS INC.
SBIR Phase II: Phage-amplified Identification and Antimicrobial Susceptibility Test
Contact
12635 E MONTVIEW BLVD RM 219
Aurora, CO 80045--7335
NSF Award
2334595 – SBIR Phase II
Award amount to date
$984,381
Start / end date
09/01/2024 – 08/31/2026 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase II project will be the expansion of a new diagnostic tool that was first developed in Phase I that allows rapid, direct-from-specimen bloodstream infection testing in clinical settings. This expansion may increase the method?s applicability from a single organism, E. coli, to a full suite of six highly virulent and antibiotic resistant bacterial pathogens (ESKAPE pathogens), as described below. The new technological innovations proposed here may more quickly identify bacteria responsible for the vast majority of blood infections in patients and simultaneously provide phenotypic data to determine which antibiotics should be effective for treating these infections and at what doses. If successful, this will improve patient outcomes through faster diagnosis and more precise antibiotic selection while also helping to combat the growing incidence of multidrug resistant infections by reducing the indiscriminate prescription of these drugs, thereby preserving the effectiveness of existing antibiotics.
The proposed project will expand on the advancements achieved in Phase I to develop new tests for direct-from-specimen identification, antimicrobial susceptibility testing (AST) and minimum inhibitory drug concentration (MIC) determination against key ESKAPE bloodborne pathogens: Staphylococcus aureus, Klebsiella pneumoniae, Pseudomonas aeruginosa and Acinetobacter baumannii. A significant limitation with existing standards-of-care is time required for actionable results; current approaches require 18-72 hours. Physicians must therefore make empiric treatment decisions that often lead to negative outcomes. Genotypic approaches are limited because of the varied mechanisms utilized by bacteria to evolve resistance, which can lead to false-negatives. Mass spectrometry requires colony isolation and provides ID only. Other time-consuming tests are then required for AST and MIC. To solve these problems, the proposed approach utilizes bacteriophage mixtures that are highly specific and have demonstrated overlapping host ranges, produce a signal quickly, and are well-suited to automatable 96-well plate immunoassays. Project objectives are: 1) Develop regulatory pathway for FDA 510(k) or de novo clearance, 2) Develop/characterize antibodies to expand test and 3) Validate expanded tests against clinical specimens. Side-by-side comparison to current standard-of-care strategies will also be performed. As demonstrated in Phase I feasibility work, results include ID, AST/MIC in less than 5 hours.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
COMON SOLUTIONS LLC
SBIR Phase II: High-Resolution Image Segmentation for Natural Resource Management
Contact
519 CONGRESS AVE
Pacific Grove, CA 93950--4111
NSF Award
2233680 – SBIR Phase II
Award amount to date
$1,000,000
Start / end date
04/15/2023 – 03/31/2025 (Estimated)
NSF Program Director
Errata
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Abstract
The commercial/broader impact of this Small Business Innovation Research (SBIR) Phase II project is to provide economic benefits, health advantages, and improved natural disaster response readiness to the USA. Historically, natural resource and conservation organizations have had difficulties mapping their targeted ecosystems, whether due to high costs of manual surveys or poor resolution of imaging technologies. Annually, organizations spend more than $27 billion on geospatial monitoring and analysis. This Phase II project will decrease the cost of ecosystem mapping while increasing resolution, allowing for the best quality vegetation health tracking available. Additionally, this project will result in a 50-90% reduction in work hours for natural resource mapping. By saving time, stakeholders can allocate effort to other aspects of natural resource management. By mapping land use over time, managers and conservationists can track land changes and determine if currently-implemented programs are having intended impacts on the ecosystem. This project will also improve monitoring and managing of vegetation across watersheds that provide roughly 80% of US drinking water - systems where water quality relies on healthy and biodiverse vegetation to filter pollutants. Lastly, this project will improve the ability of government agencies to rapidly monitor environmental impacts of natural disasters and inform responses.
This Small Business Innovation Research Phase II project will develop a comprehensive software system that can provide unparalleled spectral and spatial detail on diverse landscape scenes. Compared to current labor-intensive field testing, this project?s outputs will offer scene characterization at comparable, or better, levels of detail, while surmounting the time, cost, and accessibility constraints that have historically precluded comprehensive and repetitive monitoring. Accomplishment of these Phase II goals will yield a user-friendly land cover mapping system that will enable high-resolution environmental monitoring. System outputs on population dynamics, climate change-induced vegetation shifts, and disease assessments can facilitate data-driven decision-making for precision ecosystem management and climate action. The framework of the innovation consists of three main components: 1) image pre-processing and alteration, 2) image segmentation, and 3) resolution recovery. This approach provides rapid replicability between ecosystem types and versatile scalability due to processing efficiency, while providing currently unavailable ecosystem health indicators.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
COMPACT MEDICAL SOLUTIONS LLC
SBIR Phase II: A Novel Respiratory Bag-Valve-Mask Resuscitator
Contact
7711 ASHTREE DR
Indianapolis, IN 46259--8603
NSF Award
2242331 – SBIR Phase II
Award amount to date
$999,931
Start / end date
11/01/2023 – 10/31/2025 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is a novel device which reduces injury to patients by emergency personnel when using a bag-valve-mask (BVM) manual resuscitator. BVMs are used in pre-hospital and hospital settings by emergency medical personnel on a daily basis to deliver air to critically ill patients. Their basic design has been in place for over 60 years and are often misused resulting in damage, complications, or occasionally fatal lung injury. This project will complete development of a novel BVM that precisely controls the volumes and pressures delivered, and aims to redefine the stagnant BVM market which is projected to surpass $750M annually by 2025.
This Small Business Innovation Research (SBIR) Phase II project develops a novel, adjustable, universal bag-valve-mask resuscitator enabling emergency providers to deliver air volumes and pressures customized to patient body size. Current devices are commonly misused, even by highly trained medical personnel, resulting in hyperventilation, barotrauma, and occasional death. The project will complete remaining design and testing tasks, and a human factors proof of concept study to demonstrate users are able to quickly and properly utilize the device with minimal instruction will be performed. The second objective will address manufacturability and testing requirements within standards for US approval. Finally, the third objective is to establish the assembly processes and initial quality control testing to ensure consistent manufacturing at scale and in a cost effective and quality consistent manner.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
COMPLETIONAI LLC
SBIR Phase II: Simplifying the use of recycled plastics in film extrusion
Contact
20 HIGH ST
Marblehead, MA 01945--3408
NSF Award
2212917 – SBIR Phase II
Award amount to date
$981,780
Start / end date
02/01/2023 – 01/31/2025 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase II project will be to allow recycled plastics to be used more efficiently and affordably than is currently possible. Regulatory and societal pressures are forcing reconsideration of single use plastics, and manufacturers of plastic film must use recycled plastic at higher quantities. However, it is difficult for the manufacturers to affordably reincorporate single-use plastics due to the low quality and unpredictable content of the material. Increasing yield of usable plastics through use of the proposed technology is expected to reduce waste, offering the potential to annually save 6.5 million metric tons of carbon dioxide emissions in the US and Canada, and 28 million metric tons globally. Also, the greater use of artificial intelligence in manufacturing is of strategic advantage to the US, with the proposed technology also applicable to metals, paper, or advanced materials. Furthermore, skills shortages are impacting manufacturing and are likely to worsen due to a rapidly aging workforce. A great deal of on-the-job expertise will be lost in the coming years as a generation of experienced operators retires. The proposed solution can ease this transition, acting as an expert decision system to carry the intelligence forward and help maintain US manufacturing competitiveness.
This Small Business Innovation Research (SBIR) Phase II project will apply artificial intelligence (AI) capabilities and process control methods to plastic film extrusion, and subsequently to other types of manufacturing. Currently hardware solutions exist for manufacturers, though they can be expensive, difficult to use and maintain, and can require specialized skills to use. By contrast, the proposed technology is a software-based approach to the control of complex plastic film extrusion processes, particularly in the context of widely variable input materials such as recycled plastics. The AI software will be robust to changes in the production environment and will account for process drift over time. These technology capabilities are industrially novel and not known in the academic literature. Phase I outcomes suggest that the technology can automatically control extrusion processes to achieve optimal steady state production faster than is the currently possible via human control. The AI-based expert system effectively recreates the knowledge tacitly held by long-experienced factory operators. This type of industrial automation has the potential to be value-generating for the wider manufacturing sector. The proposed technology may be applicable to a wider range of extrusion manufacturing processes, such as extrusion of metals, paper or advanced materials.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
CONNECT DYNAMICS, INC.
SBIR Phase II: Implementation of Machine Learning Module in Novel Relay Trucking Pilot
Contact
900 SE 5TH ST STE 22F
Bentonville, AR 72712--6090
NSF Award
2404724 – SBIR Phase II
Award amount to date
$998,234
Start / end date
08/15/2024 – 07/31/2026 (Estimated)
NSF Program Director
Errata
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Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase II project will be to enhance traditional U.S. long-haul trucking by eliminating costly downtown in supply chains, while making significant environmental and societal impacts. Currently, traditional long-haul freight trucking is limited to conventional point-to-point trucking models that require excessive idling, resulting in over $3 billion annually in unnecessary fuel and maintenance costs. More importantly, these inefficiencies contribute to mental and physical strains on truck drivers, exacerbating the industry's sustainability issues. With trucking demand projected to increase by 36% by 2031, this project's relay model aims to shift the status quo by enhancing asset utilization, effectively reducing delivery times by 20-50%, while lowering truck driver turnover costs. Transforming trucking into a local day job will significantly improve working conditions, while secondarily solving the driver retention and shortage crisis. Moreover, the relay model promises environmental benefits by cutting emissions from idling and empty backhauls while facilitating the adoption of battery-powered fleets.
This Small Business Innovation Research (SBIR) Phase II project will build upon the machine learning (ML) based module software component developed in Phase I by validating its ability to quantify impacts of disruption events in long-haul relay trucking, resulting in a thorough and timely recommendation of mitigation strategies. Academic researchers have used simulation, mathematical programming, and other modeling techniques to establish the theoretical viability of trucking relay systems to solve equipment and human capacity issues; however, these models have relied on simplifying assumptions and do not account for common disruption events that pose a significant operational challenge. Quantifying the impacts of potential disruptions on travel time reliability while recommending timely and effective mitigation strategies to dynamically adjust driver schedules is essential to real-world deployment. Therefore, Phase II centers on four key objectives: 1) revising and integrating the ML models with real-time data stream APIs; 2) testing the scheduling engine (with integrated ML models) in a simulation environment; 3) piloting the software platform with live trucks and drivers on the road; and 4) analyzing key findings, incorporating changes, and creating a final report and revised product roadmap. Project learnings will translate to a practical relay software platform to propel commercialization.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
CORELESS TECHNOLOGIES, INC.
SBIR Phase II: Large-Scale Synthesis of Hollow Metal Nanospheres: Conversion of Batch Synthesis to Continuous Flow
Contact
2125 DELAWARE AVE STE D
Santa Cruz, CA 95060--4942
NSF Award
2127133 – SBIR Phase II
Award amount to date
$991,478
Start / end date
01/01/2022 – 06/30/2025 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase II project is based upon establishing a consistent, reliable source of high-quality hollow metal nanoparticles, thus enabling their commercial adoption in applications where they markedly outperform their conventional counterparts. One such application is point-of-use testing: by switching to hollow metal nanoparticles, lateral flow assays will reach higher levels of sensitivity and lower limits of detection, improving field testing for environmental contamination; detection of toxins and pathogens in agriculture; and early disease identification in clinical and veterinary care. Integration into rapid antibody and antigen tests for highly contagious diseases such as COVID-19 should prove particularly impactful, as the resulting higher sensitivity would reduce the occurrence of false negative results, thereby improving the performance (and public perception) of rapid testing. Critically, it would also improve baseline testing availability for rural and under-served populations who do not have access to PCR-equipped clinical laboratories. They can be applied to many other industries as well.
This Small Business Innovation Research Phase II project will advance the state of the art of continuous flow synthesis of plasmonic nanomaterials. Nanoparticle synthesis is a highly sensitive process, and obtaining high quality samples of advanced architectures has previously required labor-intensive, small-batch processes incompatible with large-scale production. Simply scaling traditional batch techniques has led to product with poor quality and prohibitive costs. This project advances a prototype reactor that has demonstrated high-throughput production of hollow plasmonic nanoparticles with control over size and color, while maintaining structural uniformity (<15% CV). Importantly, it reduced the cost of labor per liter of product by 950% from that of small batch synthesis. The proposed project will increase fidelity, further scale production volume, post-process and stabilize the final product, and benchmark its optical performance. The resulting production-scale reactor will have the capacity necessary to supply LFA manufacturers with ready-to-use, advanced color labels. It will enable new research and new nano-enabled devices by creating a consistent commercial supply of high performance plasmonic nanostructures with well-controlled physical properties. The manufacture of hollow metal nanoparticles for point-of-use testing applications will also pave the way for their expansion into other industries that would also benefit from their advantageous optical and photothermal plasmonic properties, such as photocatalysis, water purification, and phototherapeutics.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
CREATIVE BIOTHERAPEUTICS LLC
SBIR Phase II: Stress Pathway Inhibition To Prevent COVID-19 Infection (COVID-19)
Contact
4835 KINGS WAY W
Gurnee, IL 60031--3257
NSF Award
2150149 – SBIR Phase II
Award amount to date
$990,000
Start / end date
04/01/2022 – 03/31/2025 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project advance the treatment of COVID-19. A viral infection like that leading to COVID-19 creates stress on cells similar to cancer, obesity, diabetes and aging. This project advances a single non-toxic injection for critical patients to reduce cellular stress, block virus infection, and increase survival. In addition, this biologic therapy is also effective against the SARS-CoV-2 mutations, Ebola, and Influenza A. This has the potential to transform treatment for virus infections and cancer therapy.
This Small Business Innovation Research (SBIR) Phase II project advances a treatment to end COVID-19 by blocking the SARS-CoV-2 receptors on lung cells. The project advances discoveries that a survival protein, GRP78, is essential for virus infectivity and that an associated inhibitor can prevent infection. The project optimizes methods to use a lead GRP78 inhibitor to block spike proteins (SPs) of SARS-CoV-2 and mutations, as well as other virus receptor binding domains (RBDs) from binding to receptors and to lung cells. It is anticipated that the efficacy of the lead GRP78 inhibitor to block whole virus SARS-CoV-2, Ebola, and Influenza A viruses? infection on lung cells will exceed 99%.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
CRYPTYX BIOSCIENCE, INC.
SBIR Phase II: A Natural Product Drug Discovery Platform Based on High-Throughput Elicitor Screening (HiTES)
Contact
WASHINGTON ROAD
Princeton, NJ 08544--0001
NSF Award
2335297 – SBIR Phase II
Award amount to date
$999,109
Start / end date
09/01/2024 – 08/31/2026 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase II project stems from the identification and advancement of novel compounds with therapeutic or commercial potential from natural sources. Microbial natural products have been a traditional source of FDA-approved drugs and drug leads, but discovery efforts are hampered by the fact that 80-90% of natural products that a given microbe can produce are cryptic, meaning they are not produced under standard laboratory conditions. By turning on >90% of biosynthetic pathways and unearthing these cryptic natural products, the technology developed by this project may enable discovery of novel microbial compounds, giving researchers access to urgently needed new therapeutics while making the whole process faster and more affordable than extant methodologies. This approach has the potential to usher in a new era of drug discovery, strengthening the U.S. pharmaceutical industry and economy. New antibiotics will help to combat the alarming rise of multidrug-resistant bacteria. Other pharmaceuticals, like anticancer agents, immunosuppressants and antivirals will contribute to improved health outcomes for those with cancer, autoimmune diseases, and viral infections. Of relevance to national defense and security, this technology could be used to rapidly identify novel therapeutics and bioactive compounds against emerging pandemic diseases and potential agents of bioterrorism.
The proposed project seeks to develop novel antibiotics and anticancer agents using a revolutionary drug discovery platform. While natural products are the most promising source of new drugs, conventional methods of discovery fail to unlock the full metabolomic potential of the organisms that produce them, require challenging culture conditions, and are plagued with high rates of rediscovery. Phase I demonstrated proof-of-concept for a comprehensive drug discovery pipeline focusing on cryptic microbial natural products. The platform challenges bacteria with a library of small molecules, some of which mimic the bacteria?s competitive native environment, thus activating otherwise silent biosynthetic pathways. It is flexible and allows for chemistry-first or built-in bioactivity screening as the first step in the pipeline. The focus of Phase II is to further validate molecules discovered in Phase I and demonstrate the ability of the platform to uncover compounds with suitable drug-like properties. The project will also scale up the technology to establish a large library of ~2,000 novel natural products to be screened against various indications, and expand the utility for the identification of anticancer agents. Successful completion of this project will further validate and expand the utility of the platform for drug and bioactive molecule discovery.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
CRYSTAL SONIC, INC.
SBIR Phase II: Sonic Lift-Off (SLO) for Lower Cost Wide Bandgap Devices
Contact
311 W VIRGINIA AVE
Phoenix, AZ 85003--1020
NSF Award
2423366 – SBIR Phase II
Award amount to date
$1,000,000
Start / end date
09/15/2024 – 08/31/2026 (Estimated)
Errata
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Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase II project will be to accelerate the adoption of next generation semiconductor power devices based on Gallium Nitride. Gallium Nitride (GaN) devices, compared to legacy Silicon devices, offer much increased performance and energy efficiency across a wide range of applications, including those essential for the Nation?s future energy, transportation and communications infrastructure. The project is impacting the adoption of GaN devices by significantly lowering the production costs. It is estimated that replacing power conversion devices based on Silicon with GaN (and SiC, another advanced material) will be able to save 120 TWh/year, corresponding to the energy consumption of a whole country like Switzerland. In addition to energy savings, GaN devices will furthermore allow further miniaturization of power supplies, car chargers, and other everyday consumer and industrial appliances. The ability to re-use GaN wafers during the manufacturing process in addition lowers energy consumption and pollution in the manufacturing process of these devices.
This Small Business Innovation Research (SBIR) Phase II project will develop a process that allows multiple re-use of GaN wafers for advanced power electronics. GaN wafer costs are very high and dominate the cost of power devices manufactured from it. The objective is to develop a process that uses sound energy in combination with stressing the wafer material to precisely cut the semiconductor material and release a thin layer from the surface of a GaN wafer leaving the wafer for subsequent reuse, possibly multiple times. This cuts the material cost per device manufactured significantly. The development of this process involves optimization of the materials used to generate the stress in the wafer, the acoustic energy delivery system, and determination of ideal process parameters. The desired outcome of the project is the demonstration of a reproducible process to lift-off thin (on the order of twenty micrometers) layers of GaN from a thick (500 micrometers) semiconductor wafer leaving a low roughness, damage-free surface for processing the next device layer.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
CULTURALLY RESPONSIVE SOLUTIONS, LLC
SBIR Phase II: Agentic AI Augmenting Qualitative Data Analysis
Contact
1 OAK KNOLL DRIVE
Wallingford, PA 19086--6315
NSF Award
2417969 – SBIR Phase II
Award amount to date
$874,195
Start / end date
09/01/2024 – 08/31/2026 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is a market-ready AI CoPilot for qualitative data collection, analysis, and evaluation in a single Software-as-a-Service (SaaS) platform with use cases as varied as academic research to human resource management. The research and development of this novel AI CoPilot for qualitative data will improve the accuracy and efficiency of qualitative data analytics while identifying potential biases in data and accelerating the process of analysis and discovery. The project aims to shift how qualitative data is leveraged in research and industry to offer more robust, real-time, and contextually relevant insights from qualitative data. An enhanced approach to analyzing qualitative data may result in more informed decision-making and higher quality outcomes across market sectors with clear societal impacts immediately evidence in educational institutions as well as in the delivery of healthcare informatics and market research providing timely data for wide swaths of society.
The proposed project aims to develop a comprehensive Software-as-a-Service (SaaS) platform that integrates a proprietary Artificial Intelligence (AI)-enabled suite of qualitative data analysis tools with nuanced and contextually relevant analysis of qualitative data. The primary objective is optimization of a novel system which collects, structures, and stores unstructured data for subsequent analysis by both human and AI-enabled raters to increase accountability leading to higher quality outcomes and more informed decision-making. The core enabling technology includes dynamic dashboards, advanced analytics, and customer-relationship management (CRM) tools which integrate across the suite of qualitative analytic tools. The research will focus on refining the platform's architecture for scalability and integrating responsive proprietary AI models. The anticipated technical results include a robust, scalable platform capable of delivering accurate and reliable data analysis, significantly improving the workflow of data analysts in various fields. The methodology involves iterative testing, user feedback integration, and continuous enhancement of AI models to ensure the platform meets high standards of performance and usability
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
CYTORECOVERY, INC.
SBIR Phase II: Bioelectrical Cell Enrichment, Sorting, and Recovery with On-Chip Sample Prep and Monitoring
Contact
1872 PRATT DR
Blacksburg, VA 24060--6322
NSF Award
2222933 – SBIR Phase II
Award amount to date
$952,558
Start / end date
02/15/2023 – 01/31/2025 (Estimated)
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is a label-free, biological sample preparation and cell isolation platform for recovery of rare cells from a variety of sample inputs. Specifically, by carrying out sample preparation, manipulation, and monitoring on a single chip platform for selective cell recovery, the sample handling steps will be greatly reduced, thereby ensuring the maintenance of cell viability, improving sample consistency, and sustaining native cell behaviors. This recovered sample is essential for the development of cell-based therapies in regenerative medicine and cancer management. Personalized medicine also requires precision cell recoveries.
This Small Business Technology Transfer (STTR) Phase I project will develop an electrically functional microfluidic sample manipulation platform for phenotype-selective recovery of cells, based on their biophysical attributes. Specifically, microfluidic designs will be integrated to swap cells from complex biological inputs into an optimized buffer to enable cell manipulation. Also, instrumentation will be developed for on-chip monitoring of the sample during various stages of the phenotype-selective cell recovery process. Further, a variety of sample inputs will be validated on the designed devices to ensure performance, consistency, and reliability for translation into commercial product lines.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
Camerad Technologies, LLC
SBIR Phase II: Point-of-Care Patient Photography Integrated with Medical Imaging
Contact
2098 SYLVANIA DRIVE
Decatur, GA 30033--2616
NSF Award
1853142 – SBIR Phase II
Award amount to date
$759,942
Start / end date
05/15/2019 – 04/30/2025 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is the widespread adoption of an efficient and accessible technology to integrate patient photographs with radiology images to improve patient safety, increase healthcare efficiency, and reconnect radiologists with their patients. A successful commercialization outcome is this adoption leading to direct cost-savings in healthcare by improving patient safety and hospital quality; even a 10% improvement in radiologists' efficiency leads to healthcare savings of ~$900 million. The broader impact of this novel technology is that it can provide patient authentication for the digital data being generated by hundreds of new digital medical devices. Any of this digital data could end up in the wrong patient's medical record and authentication is crucial. Rapid advances in smart, telehealth systems present the danger that patients can turn into mere data, but these photographs can return the interpreting physician's focus to the patient, leading to improved outcomes through patient-centered care. The technology achieves this by allowing doctors to connect with the patient as a person before diving deep and exploring data at anatomic, physiologic and molecular levels.
This Small Business Innovation Research Phase II project will seamlessly and securely integrate a radiology patient identification system to improve patient safety, by avoiding preventable errors, and enhance throughput. This transformative approach overcomes the failure of existing patient identification methods while harnessing the power of an embedded camera system to improve patient care. Technology to automatically and simultaneously obtain and embed audio and video data of the patient during X-ray and CT acquisition will be developed under this award. Specifically, the following objectives will be completed: 1) develop a mature software framework for rapid system scalability to a large number of hospitals, 2) expand the system to CT scanners and stationary X-ray machines, 3) improve image quality by adding infrared stereoscopic image capture, to ensure photographs add value even when obtained in low light settings, 4) enhancing the cameras with video and audio capabilities, which will improve patient identification, while simultaneously gathering rich clinical information, and 5) refine the triggering method for photograph acquisition. The long-term objectives are to increase the detection rate of wrong-patient errors by embedding an intrinsic, externally visible biometric identifier with medical imaging studies; and increase interpreting physician throughput by decreasing interpretation time.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
CellDrop Inc
STTR Phase II: Stem Cell Delivery in Microscopic Hydrogel Droplets for Faster and More Complete Healing of Equine Tendon and Ligament Injuries
Contact
1938 HARNEY ST
Laramie, WY 82072--3037
NSF Award
2304324 – STTR Phase II
Award amount to date
$999,999
Start / end date
10/01/2023 – 09/30/2025 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact of this Small Business Technology Transfer (STTR) Phase II project involves continued development of technology to extend the therapeutic window of cell-based tissue regeneration therapies. This technology could significantly enhance the scientific understanding of cellular therapies and enable the healing of injuries more rapidly and less invasively than current techniques. A significant need for this technology has been identified in the competition horse market. A significant fraction (98%) of competitive horses suffers from soft tissue injuries and more than 80% of these horses develop a tendon or ligament injury. These injuries can take years to heal and are the leading cause of missed performances? drastically reducing quality of life for the animal and often necessitating euthanasia. This is a significant emotional and financial pain-point for horse owners and veterinarians. The technology being developed offers a solution by providing veterinarians a means of healing tendon and ligament injuries in a faster and more durable manner than currently possible, resulting in fewer missed performances, reduced need for animal euthanasia, and significantly reducing earning losses. Initial implementation of this technology in the equine market is expected to result in the subsequent commercialization of products to improve the healing of orthopedic injuries in humans.
This project addresses the slow healing and frequent reinjury of superficial digital flexor tendon (SDFT) injuries in elite equine athletes. A significant fraction (98%) of veterinarians uses stem cell injections to aid in recovery of these injuries, however, this strategy has limited efficacy due to poor viability of injected cells and short cell retention times at the site of injury. This problem is addressed by this technology to preserve and localize mesenchymal stem cells (MSCs) at an injury site through delivery in inert, injectable hydrogel microparticles. The research objectives are twofold: 1) examine early healing metrics in an equine model of SDFT injury treated with encapsulated MSCs compared to conventional unencapsulated MSCs, and 2) examine long term healing metrics using the same model. The goal of this research is to provide evidence of two key customer needs: faster tissue healing and more durable tissue regeneration of SDFT injuries. Functional, histological, genetic, and biomechanical metrics will be used to assess experimental outcomes and the results are anticipated to lead directly to a clinical trial in elite equine athletes.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
Charmtech Labs LLC
SBIR Phase II: PeTeS: Personalized Text Simplification For Struggling Readers (COVID-19)
Contact
77 GOODELL ST STE 441
Stony Brook, NY 11794--4600
NSF Award
2036502 – SBIR Phase II
Award amount to date
$1,000,000
Start / end date
06/15/2021 – 11/30/2025 (Estimated)
NSF Program Director
Errata
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This phase II award received additional funding to mitigate the COVID-19 crisis.Abstract
This Small Business Innovation Research Phase II project seeks to develop a Personalized Text Simplification (PeTeS) technology to be used as a Computer Assisted Tool for students with learning difficulties and/or disabilities. Several automatic text simplification tools are available in the market. Unfortunately, the existing tools are one-size-fits-all solutions offering no personalization and not supporting the teacher?s instructional goals. The innovation of PeTeS is in the use of Machine Learning and Natural Language Processing algorithms to perform automatic text simplification customizing texts for each student, enabling him/her to understand the curriculum and improve vocabulary knowledge at the same time. PeTeS will be compatible with both independent use by students and teacher-driven data-driven instruction. PeTeS will be usable both in class and in remote education settings, which is a new critical demand in our schools caused by COVID-19 pandemic. The objective of this Phase II Project is to fully develop the PeTeS product and evaluate its effectiveness in classroom and remote education settings.
The objective of this Phase II Project is to develop PeTeS a Personalized Text Simplification tool. PeTeS will enable teachers of material in courses such as education, reading, language, and literacy coaches to provide personalized reading accommodations and intervention to their students to improve their reading skills by automatically simplifying the text to match the individual student?s knowledge. PeTeS will be compatible with both independent use by students and teacher-driven data-driven instruction. PeTeS will be usable both in class and in remote education settings, which is a new critical demand in our schools caused by COVID-19 pandemic.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
Clairways LLC
SBIR Phase II: Medical Device for Monitoring Respiratory Disease
Contact
16 CAVENDISH CT
Lebanon, NH 03766--1441
NSF Award
2132716 – SBIR Phase II
Award amount to date
$999,612
Start / end date
09/15/2021 – 02/28/2027 (Estimated)
NSF Program Director
Errata
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Abstract
This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2).
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II Project is to aid the development of new and better respiratory therapeutics. Over 1 billion individuals suffer from chronic respiratory diseases including conditions such as asthma, chronic obstructive pulmonary disease (COPD), chronic cough, and bronchiectasis. COPD is the third deadliest disease in the U.S. and globally. Due to the prevalence and impact of these diseases, $8.6 billion is invested in respiratory clinical trials annually. Currently, in respiratory therapy research and pharma clinical trials, participants? coughing and wheezing can be a primary or secondary endpoint for measuring drug efficacy. Current solutions for capturing daily fluctuations in cough or respiration are burdensome to use and often produce unreliable data that is less helpful for drawing reproducible conclusions. Additionally, these current solutions add significantly to the cost of respiratory therapy clinical trials. This SBIR Project seeks to address these challenges by producing a wearable device that passively captures accurate, remote data that is essential to unlocking scientific discoveries in respiratory care. This project serves an urgent, unmet need for a reliable, low-effort, low-cost way to measure daily fluctuations in clinical trial participant respiratory signs.
The proposed Small Business Innovation Research (SBIR) Phase II Project employs advanced edge computing to address challenges in objectively monitoring respiratory signs. The proposed activity may make advances in the field of ultra-low power biomedical wearable devices. In particular, new nonlinear analog processing techniques will be developed to make it feasible for long-term monitoring of respiratory signs, including coughing and wheezing. The resulting analog techniques may also be used to implement other types of state-of-the-art medical wearable devices.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
Corsha, Inc.
STTR Phase II: Performant Distributed Ledgers for Cybersecurity Applications
Contact
8618 WESTWOOD CENTER DR STE 300
Vienna, VA 22182--2273
NSF Award
2304460 – STTR Phase II
Award amount to date
$994,567
Start / end date
08/15/2024 – 07/31/2026 (Estimated)
NSF Program Director
Errata
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Abstract
The broader/commercial impact of this STTR Phase II project is to allow distributed ledgers to naturally scale as their workloads do, reducing the barrier for companies to adopt and operate the technology over the long-term. A distributed ledger is a database shared by multiple participants in which each participant or node maintains and updates a synchronized copy of the data. Distributed ledgers allow members to securely verify, execute, and record their own transactions without relying on a central intermediary and provide benefits such as immutability, decentralization of data, and high availability. Distributed ledger technology (DLT) is quickly growing in adoption both in the US and globally. As is true with any emerging technology, distributed ledgers need solutions to support scale, particularly in the context of ledger growth, fast search, and tractable cost of deployment over time. Further the project will advance private, permissioned blockchains to become viable for production-scale, enterprise use cases spanning sectors like cybersecurity and finance, which both have uncompromising real-time, high transaction throughput constraints.
This STTR Phase II will tackle two key technical objectives: 1) Pruning in enterprise-type DLT systems and 2) Dynamic scaling of deployed DLT platforms. This research will be performed in the context of a widely adopted and open-source DLT technology but will study the implications of both pruning and scaling on factors including security, privacy, consensus, and implementation complexity on distributed ledger technology (DLT) more broadly. To accomplish these objectives, the project will rely on findings from experiments executed and methods developed during the Phase I SBIR research. These include the use of realistic, highly scalable load-testing infrastructure to simulate and benchmark thousands of simultaneous clients. A major research objective of this Phase II work is to develop algorithms for context-aware transaction compression pruning. This approach to DLT pruning is well suited for enterprise applications where the transaction itself may store a variable amount of data. This pruning mechanism would substantially advance the state-of-the-art in transaction and state pruning, as it would not require re-syncing of nodes, nor suffer information loss locally, nor damage the ability to reach consensus, and will be optimized for fast search. Further, this research will examine different classes of applications and discuss which of these could benefit from Corsha?s novel pruning technology.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
Cytocybernetics
SBIR Phase II: Developing a platform for superior predictive analysis of HERG Ion Channel-Drug Interactions for the Comprehensive In-vitro Proarrhythmia Assay (CiPA)
Contact
5000 B TONAWANDA CREEK RD N
North Tonawanda, NY 14120-
NSF Award
2151522 – SBIR Phase II
Award amount to date
$1,000,000
Start / end date
03/01/2022 – 02/28/2025 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact /commercial potential of this Small Business Innovation Research (SBIR) Phase II project is to improve drug safety. This project advances software to identify the potential of new drugs to provoke dangerous cardiac side-effects. Because sudden cardiac death is an infrequent and relatively rare phenomenon, predicting it with conventional tools is either impractical or impossible. The proposed technology will make the development of all new classes of drugs safer, faster, and less expensive. This will be integrated into investigational new drug submission packages for submission to the FDA for drug approval. This will improve pharmaceutical safety and clinical outcomes.
This Small Business Innovation Research (SBIR) Phase II project will address the critical problem of predicting the arrhythmogenic potential of new drugs seeking FDA approval. Current basic science research methods are based on trying to reproduce exact and infrequently encountered in vivo phenomena in an in vitro setting. The economic and practical constraints on drug development therefore requires industry to use proxies, primarily drug binding to the HERG potassium channel, as a predictor arrhythmogenicity. The intellectual challenge in this project is to combine mathematical modeling and quantitative analysis of rigorous experimental protocols to bridge this gap and identify underlying features which are strong predictors of arrhythmogenic behavior. Key to understanding this is the rapid development and deployment of state-dependent Markov models of drug action based on limited patch clamp data, which is both time-consuming and expensive to obtain. This project combines mathematical analysis directly to direct patch-clamp assay protocols to minimize time and expense while increasing predictive accuracy.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
DASION CORPORATION
SBIR Phase II: Geometric Unified Learning - DiMSuM for HealthCare: Trust, Patient Focus, Collaboration, Privacy, and Cost-Efficiency
Contact
12427 POPES HEAD RD
Clifton, VA 20124--1317
NSF Award
2330718 – SBIR Phase II
Award amount to date
$999,988
Start / end date
08/15/2024 – 07/31/2026 (Estimated)
Errata
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Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase II project encompasses both societal and commercial sectors. This project, centered around advancing healthcare technology, aims to significantly revolutionize the way healthcare providers approach diagnosing, monitoring, screening, and updating medical treatments. The core innovation of this project lies in its ability to facilitate early and precise disease detection, thereby potentially reducing healthcare costs and markedly improving patient outcomes, especially in managing chronic and age-related health conditions. In the commercial realm, this technology is set to make a substantial impact within the rapidly expanding healthcare AI market. Its unique approach to processing and interpreting complex health data positions it as a groundbreaking advancement in healthcare AI. Furthermore, this project can lead to enhanced scientific understanding and technological capabilities in the healthcare sector. The project?s success can result in efficient, accessible, and enhanced patient-centric healthcare delivery. This is crucially needed in a world where healthcare systems are increasingly strained and the need for innovative solutions is ever-growing.
This Small Business Innovation Research (SBIR) Phase II project is focused on the development and refinement of a healthcare technology platform that utilizes Geometric Unified Learning. This innovative approach is geared towards enhancing the efficiency and accuracy of healthcare diagnostics and monitoring. The project aims to address the significant challenge of processing and interpreting complex health care data, particularly focusing on diseases that can be diagnosed and monitored using minimal yet crucial data sources such as voice and EEG. The research objectives include refining the platform to handle real-world patient data effectively and expanding its capabilities to diagnose and monitor a broader range of diseases. The development of a versatile, user-friendly, and effective diagnostic tool is expected to set new benchmarks in the field of healthcare AI. Such a tool would not only provide significant advancements in medical diagnostics and patient care but would also contribute to the overall understanding of disease patterns and healthcare needs.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
DEEPCONVO INC.
SBIR Phase II: Voice-based telehealth interface for symptom monitoring and screening for chronic and acute respiratory diseases
Contact
317 CORNWALL DR
Pittsburgh, PA 15238--2643
NSF Award
2213110 – SBIR Phase II
Award amount to date
$999,994
Start / end date
03/01/2023 – 02/28/2025 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is a voice-based telehealth interface deployed on mobile devices for symptom monitoring and screening for respiratory diseases. This technology may improve the quality of respiratory care and could prevent costly hospitalizations by delivering monitoring and exacerbation warnings to healthcare providers and patients. Chronic and acute respiratory diseases affect over 70 million Americans and 1 billion people globally. This technology may help improve patient outcomes and save on patient care costs.
The proposed project will further develop the existing Chronic Obstructive Respiratory Disease (COPD) Early Exacerbation warning system to measure the earliest deterioration in a patient?s respiratory system through voice and breath data captured through mobile phones. The research objectives include (1) productizing lung function measurement by improving algorithms for measuring lung function in varied real-world environments and on datasets reflective of the target population of patients with respiratory conditions in the US; (2) productizing exacerbation prediction by further training the proof-of-concept algorithm with true respiratory exacerbations resulting in hospitalizations, emergency department visits, and prescription of new or increased medication and treatments; (3) developing and launching a direct-to-patient product with the goals of learning how to most effectively engage the patient to drive usage, communicating effectively with the patient, and bridging the gap between patient and provider to provide timely and effective interventions; and (4) exploring additional use cases by testing products with patients who suffer from varied lung diseases.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
DEXTROUS ROBOTICS, INC.
SBIR Phase II: Automated Perception for Robotic Chopsticks Manipulating Small and Large Objects in Constrained Spaces
Contact
802 ROZELLE ST
Memphis, TN 38104--5052
NSF Award
2321919 – SBIR Phase II
Award amount to date
$999,746
Start / end date
10/01/2023 – 09/30/2025 (Estimated)
NSF Program Director
Errata
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Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase II project supports the development of robotic solutions for unloading non-palletized packages of different shapes and sizes in logistics and similar industries. This technology may provide workers with more skilled jobs that remove the need for physically strenuous labor in unhealthy environments. The project seeks to increase US competitiveness in supply chain logistics ($150 billion / year market in the US) by helping solve long-standing and worsening employee recruitment and retention problems. The project helps the US become an early leader in the robotic manipulation of diverse objects in constrained, unstructured environments while simultaneously training a workforce capable of remote manipulation in safe environments.
This Small Business Innovation Research (SBIR) Phase II project supports the development of robotic solutions for unloading non-palletized packages of different shapes and sizes in logistics and similar industries. At present, there are few commercially-available automated solutions for this task. Those few machines are brittle, slow, and only work well with uniform packages. The research objectives include: 1) upgrading the robot?s perception system to fuse high-speed vision and force sensory inputs, which will enable closed-loop picking with greater speed, more robustness, higher safety, and less package damage; 2) upgrading the robot?s vision system to perceive object categories beyond boxes; 3) investigating a user interface to allow a human operator to most-easily correct inevitable perception system errors; and 4) field testing the robotic system. The cumulative result will be a rigorously validated system that safely (for packages and users) operates at high speed with little manual intervention.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
DIAMOND AGE TECHNOLOGY LLC
SBIR Phase II: Composing Digital-Twins from Disparate Data Sources
Contact
15714 CRESTBROOK DR
Houston, TX 77059--5218
NSF Award
2321894 – SBIR Phase II
Award amount to date
$999,757
Start / end date
10/01/2023 – 09/30/2025 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project relates to the creation of a digital twin, an interactive, 3-dimensional model of a real-world system, of complex industrial environments and assets. This digital twin provides infrastructure necessary for the application of virtual reality training and augmented reality live-guided procedures in industrial workplaces, at scale. By making the full-scale roll-out of these technologies possible, the technology seeks to impact human health and safety, operational efficiencies, and environmental risk reduction for process operations facilities, such as oil refineries and chemical plants. The long-term impacts of this technology may also enable automation and optimization, improving their efficiency, security, and safety. Such facilities are critical infrastructure and play a significant role in the national economy. The availability of this product may also enhance market opportunities for other businesses in the scanning, spatial computing, and training markets. The impact may be further broadened by adapting the process for digital twin production to new domains unrelated to the industrial market.
This Small Business Innovation Research (SBIR) Phase II project is advancing knowledge and understanding in both machine learning and spatial computing. This project focuses on a method for digitizing a complex, real-world system, in an efficient manner, sufficient to recreate the captured reality as an interactive digital twin. The primary technical hurdle is the combining of different data sources, that describe aspects of a particular real-world system, into a single, complete description. The initial physical systems being modelled are industrial process operations, but the core methods could apply to other types of systems, including natural systems, such as a rainforest. For industrial process operations, the goal is to encode the entire process operations facilities, at the component level, with sub-centimeter accuracy, at 10% of the current time and cost requirements. To achieve this, this project will combine physical scans with engineering documentation and relational probabilities. Once combined, the model will be used as the basis for a digital twin of the real-world system projected into spatial computed environments, such as virtual and augmented reality. These techniques replace a tedious and limited static scan and intensive human labor workflow with rapid scans, computer vision, and a combination of procedural and trained algorithms.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
DIFFRACT TECHNOLOGY, INC.
SBIR Phase II: Novel Holographic 3D Optical Metrology Tool for Precision Engineering and Manufacturing
Contact
6 SUNHILL ST
Portola Valley, CA 94028--8050
NSF Award
2414910 – SBIR Phase II
Award amount to date
$1,000,000
Start / end date
09/15/2024 – 08/31/2026 (Estimated)
NSF Program Director
Errata
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Abstract
This Small Business Innovation Research Phase II project is focused on developing reliable, precise, and scalable three-dimensional sensing solutions for manufacturing and industrial processes. The three-dimensional (3D) optical metrology tool to be developed uses a high-resolution, computer-defined 3D light field to perform rapid non-contact measurements on parts during the fabrication process. Computer-defined optics enable the tool to use an adaptive process to perform 3D metrology with sub-10-micron resolution, at a fraction of the price of competing technologies. Low-volume, high-precision manufacturing plays a critical role in the global economy and is currently a limiting factor in the creation of new assembly lines, larger volume manufacturing, research timelines, and tool creation. With modern-day reliance on process automation and tighter tolerance stack-ups, scalable in-process measurements can provide critical insights into manufacturing processes. Accelerating hardware markets, such as Industry 4.0, industrial automation, automotive and aerospace manufacturing, and construction require new, advanced 3D sensors with improved reliability, precision, and ease-of-use. Surface inspection systems already account for a global $4.0 billion market, and this number will grow rapidly as new technology meets the pressing needs of these broader industrial segments.
The intellectual merit of this project is founded in the underlying principles of how digital tools sense and interact with the three-dimensional world. Currently available digital tools are largely two dimensional (camera sensors and displays) or one-dimensional in nature (linear or rotary encoders). Attempts to digitally sense and interact with three-dimensional space are often based on interpolation between multiple two- or one-dimensional sensors such as stereo vision or gantry Coordinate Measuring Machines, respectively. These methods depend on several core assumptions and can result in significant errors or noise in the measurement process. By leveraging computer-generated, large field-of-view, high-precision holographic optical systems, digital measurement tools can collect precise, reliable measurements. This capability is based on the reconfigurable nature of a fundamentally three-dimensional digital technology: a computer-generated hologram. This project applies recent advances in computer-generated holograms, in conjunction with digital modeling and inverse design. The result is a novel digital measurement tool with sub-10-micron resolution over a half meter field of view.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
DOCUGAMI, INC.
SBIR Phase II: Authoring Assistance via Contextual Semantic Labeling
Contact
11335 NE 122ND WAY STE 105
Kirkland, WA 98034--6933
NSF Award
2233508 – SBIR Phase II
Award amount to date
$998,314
Start / end date
06/15/2023 – 05/31/2025 (Estimated)
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project comes from extracting meaningful, useful, specific information from ?dark data.? Dark data are the countless documents companies produce and receive, which contain unused information ? usually because they are in formats that computers do not understand. Many of these documents do not even contain accessible text: only pictures of text. Word-processing documents and emails do have text, but no information about what the text is. Computers can easily tell that ?10/05/2022? is a date, but knowing it is the date a particular agreement starts or ends (or something else) is needed to make it useful. This project uses a range of artificial intelligence (AI) techniques that work in real time while people are writing new documents or extracting data from old documents. The AI learns quickly from examples, finds patterns across similar documents, and uses that learning to save the user from having to search for items again and again in varying contexts. This saves a lot of tedious work and reduces errors. The extracted information helps companies understand, analyze, and make business decisions.
This Small Business Innovation Research (SBIR) Phase II project identifies and extracts useful information items from long natural language documents, especially contracts and agreements. The technology identifies items much more specifically than typical extraction methods; for example, not only as person, organization, or place names, but as to what role each plays. Likewise, addresses, dates, money amounts, and other data items only become useful when you know what they?re for. This is a valuable focus for advancing Natural Language Understanding. The team combine and extend Machine Learning technologies such as few-shot learning, fine-tuning, and semantic parsing to achieve these stronger, more ?semantic? results. This solution allows companies to generate value from huge troves of information they already collect but cannot yet automate or leverage.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
DYNOCARDIA, INC.
SBIR Phase II: Development of motion artifact correction systems for ViTrack: an accurate, continuous, and non-invasive blood pressure monitor
Contact
535 COMMONWEALTH AVE
Newton, MA 02459--1601
NSF Award
2423296 – SBIR Phase II
Award amount to date
$999,553
Start / end date
09/15/2024 – 08/31/2026 (Estimated)
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is to meet the urgent need for a wearable blood pressure (BP) monitor for accurate and continuous BP measurements. The current standard for arm cuff-based BP assessments is unreliable and limited to single time-point BP estimates, but an individual?s BP fluctuates significantly over 24 hours. In US hospitals, 35 million patients are admitted annually for critical illness and/or undergo major surgeries that require BP monitoring. Inaccurate, single-point, cuff-based BP monitoring during surgery leads to unrecognized low BP and contributes to 14 million heart attacks and kidney failures annually. ViTrack is a wrist-wearable device that utilizes a proprietary optomechanical sensor array and computer vision to accurately and continuously measure radial artery BP without requiring external calibration. However, continuously measuring BP in clinical settings is challenging due to artifacts from patient movements. In NSF Phase 1, ViTrack's sensor array was used to develop an advanced computer vision technology for motion artifact correction. Other than the hospital market, the multi-billion dollar market segments for an accurate and continuous BP monitor include remote patient monitoring for 104 million Americans with high BP and the consumer wellness markets.
The objective of this Small Business Innovation Research Phase II project is to improve computer vision technology for motion correction and make it suitable for use in various hospital settings with different types of motion artifacts. The project will begin by improving the effectiveness and adaptability of computer vision-based algorithms through testing and optimization using a wide range of patient data. Artificial intelligence (AI) will then be integrated to further improve the algorithms' ability to handle various motion artifacts. In order to achieve this goal, we will create thousands of synthetic 3D-rendered videos using various combinations of real-world ViTrack data, both with and without motion artifacts. These videos will then be utilized to train a specific type of AI algorithm known as a deep neural network, using a modern approach called a vision transformer. The main objective of this training is to enable the algorithm to recognize and address motion artifacts without compromising the physiological signal. After developing, we will test the algorithms' accuracy in providing continuous BP readings across a variety of clinical data. Once validated, the algorithms will be integrated into the ViTrack device through a software module following FDA guidelines for good machine learning practices.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
Diatomix, Inc.
SBIR Phase II: Improving Indoor Air Quality using a Biosilica Based Functional Paint & Coatings Photocatalyst
Contact
2634 SE STEELE ST
Beaverton, OR 97008--6414
NSF Award
1927040 – SBIR Phase II
Award amount to date
$1,167,050
Start / end date
09/15/2019 – 02/28/2025 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is that it will provide a next-generation commercial method of removing volatile organic contaminants (VOCs) such as benzene, formaldehyde and methylene chloride from indoor air. These compounds are potential carcinogens and also exacerbate allergies, asthma, and other respiratory problems. Indoor air quality is generally 5 times worse than outdoor air quality, and VOCs are prevalent indoors because they are emitted from carpets, adhesives, plastic products, typical household chemical cleaners and electronics. Children are especially sensitive to VOCs, and indoor environments pose greater health risks because of the time spent indoors. Alleviating the daily discomfort and financial burdens, estimated at around $50 billion annually in the U.S., posed by environmental air pollutants such as VOCs can significantly improve human health and comfort. The development and commercial deployment of this new technology will also provide enhanced scientific understanding of manufacturing for nanotechnologies.
This Small Business Innovation Research (SBIR) Phase II project will focus on validating the ability of a biosilica-based photocatalyst to actively and continuously improve indoor air quality by reducing total VOCs found in indoor environments when the photocatalyst is added to floor and carpet coatings. VOCs are emitted as gases from certain solids and liquids, and they include chemicals potentially causing short- and long-term adverse health effects--especially indoors, where concentrations may be up to ten times higher than outdoors. This project will test the performance of this unique additive when applied to floor and carpet coating systems to reduce total VOCs and will validate manufacturing processes to achieve scale-up quantities needed for commercial production. The technology works by first adsorbing VOCs and then degrading them to CO2 and H2O. Coated surfaces in test chambers simulating a typical indoor environment will be evaluated via continuous monitoring of airborne pollutants. It is anticipated that the ultimate deliverables of this project would include validation of a VOC-degrading additive for multiple products and advanced knowledge of nano-manufacturing processes.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
Drone Amplified, Inc.
SBIR Phase II: Intelligent Drone Ignitions To Manage Fires
Contact
1811 S PERSHING RD
Lincoln, NE 68502--4840
NSF Award
2025871 – SBIR Phase II
Award amount to date
$983,676
Start / end date
09/15/2020 – 12/31/2026 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project will be to transform how firefighters battle wildfires by improving safety, decreasing costs, and increasing effectiveness. Wildfires are increasing in number and severity, costing billions of dollars and resulting in thousands of lost homes and numerous deaths. Today, firefighters are unable to perform the backburns needed to contain wildfires without putting firefighters at risk. This project will result in technologies that directly address the critical pain points of firefighters by improving the intelligence and capabilities of drone systems. The research will develop algorithms for coordinating groups of robots, deep learning approaches and the development of novel datasets, algorithms that can predict fire activity and plan missions, and autonomous health monitoring approaches. This project will lead to safe, fast, affordable fire management.
This Small Business Innovation Research (SBIR) Phase II project will enable the development of the critical pieces of the technology that will transform fire management. More specifically, the proposed work focuses on the following key technical challenges and activities to incorporate intelligence into fire management: 1) Scaling to multiple drones intelligently operating in tandem and larger drones to cover complex, large terrain faster; 2) Transformation of pre- and post-fire mapping, currently a manual process taking more time than actual firefighting; 3) Creation of intelligent ignition planning and automated sensing capabilities that predict and take into account fire activity to increase safety and efficiency; and 4) Beta tests with customers to collect data for learning algorithms and to validate the research under field conditions. These challenges are especially difficult given the harsh fire environment, the weight and power constraints of commercial drones preferred for these activities, and the integration of two distinct domains, drone aerial navigation and fire management.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
EARTHSHOT Labs PBC
SBIR Phase II: Advancing an Ecosystem Forecasting Platform to Restore Nature at Planetary Scale
Contact
640 WAGNON RD
Sebastopol, CA 95472--9546
NSF Award
2335244 – SBIR Phase II
Award amount to date
$897,042
Start / end date
08/01/2024 – 07/31/2026 (Estimated)
NSF Program Director
Errata
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Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase II project is centered on addressing a critical environmental challenge: global reforestation and carbon sequestration. This endeavor is vital in the fight against climate change, aiming to revitalize ecosystems, enhance biodiversity, and contribute to carbon dioxide reduction. The project aligns with the National Science Foundation's mission by integrating innovative technology with environmental stewardship, offering significant societal benefits. It seeks to develop a tool that can guide effective reforestation efforts, thereby impacting the lives of U.S. citizens and others globally. This tool?s commercial potential lies in its ability to inform governments and organizations in planning and executing reforestation projects, generating income through the provision of essential ecological data services. Additionally, the project's success could create new job opportunities in environmental science and technology sectors. The anticipated outcome of this project is not only a technological advancement but also a positive contribution to environmental sustainability, resonating with the global movement towards greener practices.
The strong technical innovation of this project lies in developing a sophisticated forecasting model for global reforestation and carbon sequestration, a task presenting significant challenges due to the complex nature of ecological systems. This model represents a high-risk endeavor, employing advanced computational techniques and machine learning algorithms integrated with comprehensive environmental data, setting it apart from existing methods. The primary goal of this research is to create a tool capable of accurately predicting reforestation outcomes and carbon sequestration potential across various global landscapes. The approach combines satellite imagery analysis, environmental variable data, and advanced algorithms to model ecological restoration scenarios. The scope of the research includes refining data integration methods, enhancing model accuracy, and ensuring scalability for global application. These efforts aim to provide a valuable resource for guiding effective reforestation initiatives, aiding in climate change mitigation, and contributing to the preservation of global biodiversity. The successful development of this model would not only mark a significant advancement in ecological forecasting but also provide a crucial tool in global environmental conservation efforts.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
ECLIPSE ENTEROGENESIS, INC.
SBIR Phase II: Endoluminal Fixation of a Distraction Enterogenesis Device
Contact
1440 OBRIEN DR
Menlo Park, CA 94025--1672
NSF Award
2232550 – SBIR Phase II
Award amount to date
$970,484
Start / end date
05/01/2023 – 04/30/2025 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is the advancement of an innovative therapy for Short Bowel Syndrome. Compared to current non-curative treatments that are chronic and associated with dangerous complications, rehospitalization, and high mortality, the proposed solution has the potential to substantially improve outcomes and quality-of-life for patients and their families. The potential commercial impact of this project is likewise substantial. Treating short bowel syndrome currently costs hundreds of thousands of dollars per patient per year. adds more than $5 billion to US healthcare expenditures annually. Thus, the proposed curative solution can lead to enormous savings in dollars and in specialists? time.
This Small Business Innovation Research (SBIR) Phase II project will create a curative therapy for patients with Short Bowel Syndrome, which is currently managed with intravenous nutrition and lacks effective treatments. The proposed solution will lengthen the intestine, increasing the absorptive surface area and restoring the natural function of the gut, enabling patients to get sufficient nutrition from the food they eat. The proposed system comprises nondestructive tissue anchors and a spring that pushes against them to stretch the intestine and force it to grow. Having previously developed the tissue anchors, this project develops a delivery method that will allow the system to be implanted in the intestine through a minimally invasive procedure. Feedback will be gathered from pediatric gastroenterologists and surgeons about the delivery method, and device performance will be measured in pre-clinical large-animal studies. Successful completion of the proposed project will demonstrate intestinal lengthening in vivo, achieved via a minimally invasive procedure, and establish a foundation for planning subsequent preclinical testing that will be required for regulatory approval to commercialize the product.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
ECO-SHELTER, INC.
STTR Phase II: A non-woven bamboo-based strand composite process to manufacture low-cost roofing
Contact
3316 6TH AVE UNIT 1
Tacoma, WA 98406--5904
NSF Award
2136481 – STTR Phase II
Award amount to date
$998,164
Start / end date
02/15/2022 – 02/28/2026 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact of this Small Business Technology Transfer (STTR) Phase II project is to develop a viable and scalable process to manufacture a bamboo-based strand composite for application in low-cost roofing globally. This project develops a new production process for exterior-grade natural fiber composite building products, derived from a highly renewable resource, bamboo, through public-private partnership. The resulting roofing product will help protect users from extreme heat by passively cooling and reducing indoor temperatures. In addition, this solution can be used to create value-added energy-efficient building products from highly renewable natural fiber waste. The innovation holds immense potential to replace harmful and hazardous materials, including asbestos, in many regions of the world, store captured carbon into long-lifecycle products, and reduce heating and cooling energy use.
This Small Business Technology Transfer (STTR) Phase II project will: (i) refine the design of the 3D panel geometry used to make commercial-size panels with improved load-carrying capacity and constructability; (ii) improve the bamboo-stranding process, evaluate a bio-based adhesive system, impart fire-retardance, enhance panel durability, manufacture panels using the new geometry, and evaluate performance; and (iii) demonstrate and evaluate panel use as a roofing material through field tests and the versatility of the corrugated panel in interior and exterior energy-efficient building products. This research will advance the field of natural fiber composites by addressing challenges of long-term construction applications that can withstand hot and humid climates, including moisture resistance, biodegradation, and effective binders for functionality.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
ELATEQ, INC.
SBIR Phase II: Advanced electrochemical degradation of PFAS in water
Contact
240 THATCHER RD # 571
Amherst, MA 01003--9364
NSF Award
2413507 – SBIR Phase II
Award amount to date
$999,603
Start / end date
09/15/2024 – 08/31/2026 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research Phase II project is to create a sustainable technology for the degradation of per- and polyfluoroalkyl substances in water and ultimately protect human health and ecosystems from their adverse effects. These environmental pollutants are difficult to destroy, but advanced electrochemical processes can transform them into harmless byproducts. Without extensive energy requirements and the need for chemical use and post-processing, this technology will offer an affordable, easily operated, and maintained on-site solution to destroy ?forever chemicals.?
This Small Business Innovation Research Phase II project focuses on developing integrated advanced electrochemical processes for rapid mineralization of per- and polyfluoroalkyl substances in water. Phase II aims to incorporate novel electrodes and electrochemical cell design at scale and deliver a deployable pilot scale system. Tasks include testing the system in relevant operating conditions, assessing the longevity of the electrode performance, and optimizing the operational parameters relative to rapid defluorination and low-energy consumption. Furthermore, the project will enable an in-depth system optimization to create a robust solution that operates under environmentally relevant conditions.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
EMPO HEALTH, INC.
SBIR Phase II: Productization, Clinical Validation, and Quality & Regulatory Activities for In-Home Diabetic Foot Imaging Bathroom Scale System
Contact
881 SNEATH LANE
San Bruno, CA 94066--2412
NSF Award
2335289 – SBIR Phase II
Award amount to date
$1,000,000
Start / end date
08/15/2024 – 07/31/2026 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is a novel at home scale to reduce severe diabetic foot ulcers in patients with diabetic neuropathy, often sufferring from lost or impaired sensation. Ulcers affect approximatey one-fourth of diabetic patients over their lifetime significantly impacting their mobility and life expectancy. Estimates for diabetic foot ulcer treatments are as high as $40B per year and up to one-third of all direct diabetic healthcare spending. Long term effects include amputation of one or more extremities; accounting for a majority of non-traumatic lower extremity amputations each year. The proposed solution provides a remote at home monitor providing daily visual inspections for early signs of foot ulcers significantly improving current qualitative and often variable- inspection methods representing the current standard of care for detection.
This Small Business Innovation Research (SBIR) Phase II project will develop a novel in-home health monitoring product for diabetic foot complications within constraints required for commercialization. The proposal builds on the company?s proprietary imaging and algorithmic method and prototype developed during the Phase I project with three concurrent objectives: (i) Advance the design, engineering and manufacturing activities to ruggedize the product suitable for patient use; (ii) Complete a clinical study with a partner health system to demonstrate patient use adherence and provider usability with the images and data suitable for clinical adoption; and (iii) Perform quality assurance testing of the manufacturable product at scale. The activities aim to complete a product suitable for commercialization for use at home as intended at cost, scale and quality.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
EMTRUTH, INC.
SBIR Phase II: A Platform for Health Care Data Integration Using Blockchain and Artificial Intelligence
Contact
1830 DEERMONT RD
Glendale, CA 91207--1028
NSF Award
2304102 – SBIR Phase II
Award amount to date
$999,658
Start / end date
10/01/2023 – 09/30/2025 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is to provide the personal healthcare data needed to improve the patient?s outcome and experience]. Because healthcare data is protected, a secure way of sharing the right data, with the right people, at the right time is needed. Currently, attempts to harmonize data from many systems, and in many formats and sizes is very difficult and expensive and so such efforts are lacking. Advancing blockchain and artificial intelligence technologies for distributed data management and enabling radical data interoperability benefits patients and addresses a priority need in a $3.93 trillion healthcare market.
This team develops the technology for a platform that secures data of any type from anywhere in immutable blockchains while respective data owners retain ownership and control to securely share just-needed data following their data governance criteria. Data is transformed and normalized into more granular blockchains and that can be combined for individual or aggregated population health modeling. Natural language processing is combined with a curated thesaurus to automatically create metadata tags for encrypted blockchains, facilitating data searches, discovery, and advanced analytics. Because healthcare data is complex and diverse, this project demonstrates, through priority use cases, how data needs to become interoperable. Such use cases include 1) sharing patient clinical data for participation in clinical research with consent; 2) creating a more complete patient healthcare record that spans many services or treatments; 3) bridging an operational gap between clinical data and claims; and 4) collaborating among research organizations in severe disease treatment. Additional technologies include instantiating a "datamart on demand" from blockchains for analytics, machine learning, and automating sharing of data, via smart contracts, capturing criteria, and like consent.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
ENGENIOUSAG, LLC
SBIR Phase II: Low-cost in-planta nitrate sensor
Contact
1111 WOI RD
Ames, IA 50011--1085
NSF Award
2155110 – SBIR Phase II
Award amount to date
$998,683
Start / end date
05/01/2023 – 04/30/2025 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is to provide farmers with a low-cost plant sensor for direct, instantaneous measurement of nitrate-nitrogen (N) levels in crop sap. Widespread adoption of the sensor could support cost-effective and improved N fertilizer management, which may increase farmers? productivity and profitability. Low-cost, instantaneous nitrate testing readouts from plant stalks will provide more actionable information to guide farmers? fertilization decisions than current methods to test N levels in soil (e.g., collect soil samples, ship them to lab, and then wait ~1 week for lab analysis). The improvements in fertilizer-management decisions, enabled by more accessible and more actionable data, have the potential to reduce total N fertilizer applications in the US by some 2 million tons annually. This large reduction in N fertilizer applications would decrease the energy footprint of agriculture, reduce emissions of nitrous oxide, a greenhouse gas 300 times as potent as carbon dioxide, and improve water quality through reductions in N runoff, improving ecosystem services and human health through improved rural water quality and the reduction in hypoxic dead zones.
The proposed project represents an innovation in the function and application of an in planta nitrate sensor. The project goals are to: i) improve the sensor for reliable deployment in field measurements; ii) conduct research in farmers? fields to develop predictive models that input nitrate levels from sensor measurements of corn stalks and other data to output N fertilization recommendations; and iii) build a lab-based multi-probe nitrate sensor that extends the work to other crops in the existing plant and soil testing market. Anticipated results are that the data from the sensors will be used to build predictive models that output optimum N fertilization recommendations that will outperform conventional models. The accomplishment of this goal will lead to the commercialization of rugged low-cost sensors that provide rapid measurements of plant sap nitrate. This ability will make it possible to provide farmers with low-cost fertilizer recommendations based on data-driven, predictive modeling of N demand.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
ENVISION ENDOSCOPY, INC.
SBIR Phase II: Novel Image Guided Suturing System For Endoscopic Surgery
Contact
15 FAIRFAX ST APT 2
Somerville, MA 02144--1107
NSF Award
2111775 – SBIR Phase II
Award amount to date
$999,952
Start / end date
07/15/2021 – 04/30/2026 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is the development of a novel image-guided full-thickness suturing system that is simple, easy to use, and cost-effective for gastrointestinal (GI) defects. These issues are more likely to require intensive care and a long hospital stay and have high rates of morbidity and mortality. Managing gastrointestinal defects endoscopically has obvious advantages over surgical intervention, including shorter hospital stays, reduced post procedure pain, faster recovery, and reduced total cost of care. The proposed technology is single-use, disposable, and attached to an endoscope (such as colonoscope, gastroscope), for better patient outcomes.
This Small Business Innovation Research (SBIR) Phase II project will advance the development of a novel, low-cost, image-guided suturing device for flexible endoscopes simple and intuitive to use. Currently, no good solutions exist for endoscopic tissue approximation and closure of large gastrointestinal (GI) defects. Endoscopic clips are only effective for mucosa closure and small size defects and the only endoscopic suturing device is considered cumbersome, difficult to use, and expensive. The technical innovation of the proposed device comprises a circular needle and a novel needle drive mechanism for a simplified suturing technique. This project will be specifically focused on the advancement of the technology, product development, design verification and validation of the device.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
ENVIVO BIO INC
SBIR Phase II: Non-Invasive Sampling and Analysis of the Human Gasstrointestinal (GI) Tract to Advance Inflammatory Bowel Disease Research
Contact
733 INDUSTRIAL RD
Los Altos, CA 94022--2034
NSF Award
2126329 – SBIR Phase II
Award amount to date
$972,774
Start / end date
09/15/2021 – 12/31/2027 (Estimated)
NSF Program Director
Errata
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Abstract
This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2).
The broader impact of this Small Business Innovation Research (SBIR) Phase II project will be to understand, and eventually manipulate, the immune, metabolic and microbial activities that occur in the intestines for the purpose of improving human health. Many important diseases are caused or regulated by activities in our intestines, yet very little is known about this hard-to-access organ. This project will develop a pill-sized gastrointestinal sampling device for routine, non-invasive sampling of the human gut and the analysis of its metabolic, microbial, and immunological content for the first time. The discoveries enabled by this project may lead to new commercial opportunities in diagnosing and treating important disorders, such as inflammatory bowel disease.
The proposed project seeks to perform validations of a pill-sized gastrointestinal sampling device for routine, non-invasive sampling of the human gut using bench testing and evaluations of clinical samples. The team will also prepare the collected data for submission to the Food and Drug Administration for market clearance. Sampling the human intestinal tract safely, non-invasively and reliably is a daunting challenge due to the constraints on the size of a device that is safe to swallow and the variability of human physiology. The technology will lead to the commercialization of the first gut sampling device in the market. The device may help elucidate the roles of the gut microbes and their interactions with the immune system and metabolic processes in human health and disease.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
EPIImaging, LLC
SBIR Phase II: Epipolar-Plane Imaging for Robot 3D Vision
Contact
414 PACO DR
Los Altos, CA 94024--3827
NSF Award
2242216 – SBIR Phase II
Award amount to date
$999,407
Start / end date
09/15/2023 – 08/31/2025 (Estimated)
NSF Program Director
Errata
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Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase II project seeks to improve robotic interactions with the humans. Currently, robots are involved in large sectors of society including logistics, manufacturing, autonomous navigation, video communication, remote supervision of complex mechanical maintenance/repair tasks, support in battlefields and disasters, and interactions in various training, educational, and interventional scenarios including telemedicine. This technology may offer more effective automation in the workplace through higher quality 3D sensing, greater precision visualization and increased worker quality of life. The technology addresses precision and reliability of passive 3D scene measurements.
This Small Business Innovation Research (SBIR) Phase II project addresses the acquisition of reliable and precise three-dimensional representations of a scene from passively acquired image data for use in navigation, grasping, manipulation, and other operations of autonomous systems in unrestricted three-dimensional spaces. This technology has been a long-standing challenge in the computer vision field, with many efforts providing adequate solutions under certain conditions, but lacking applicability across a breadth of applications. Other approaches typically deliver inaccurate results where there are, for example, repeated structures in the view, thin features, a large range in depth, or where structures align with aspects of the capture geometry. Based on the matching of features across images, current technologies fail when features have similar appearance. This technology removes the uncertainty of this process through a low-cost use of over-sampling, using a specific set of additional perspectives to replace the ?matching? with deterministic linear filtering. Increasing the reliability and precision of 3D scene measurements will open new opportunities for robotic interactions with the world. Success in this project will advance the underlying light-field technology to broader application areas where human-in-the-loop operations using artificial reality/virtual reality (AR/VR) or mixed reality (such as remote collaboration and distance interaction) depend on accurate and responsive visualization and scene modeling, reducing influences of vestibular and proprioceptive mismatch that can cause disruptive effects such as nausea.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
EPIXEGO INC.
SBIR Phase II: A novel method to scaling mentoring and career development in Institutes of Higher Education
Contact
146 CELADA CT
Fremont, CA 94539--3011
NSF Award
2422894 – SBIR Phase II
Award amount to date
$970,989
Start / end date
09/01/2024 – 08/31/2026 (Estimated)
NSF Program Director
Errata
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Abstract
The broader/commercial impact of this SBIR Phase II project is to improve academic and career outcomes for first-generation and underrepresented students in higher education through an Artificial Intelligence (AI)-driven Software-as-a-Service (SaaS) platform which harnesses individual learning, self-reflection, and automation to make every course a high-impact learning experience. By integrating competency-based learning, self-reflection, and near-peer mentoring, the project aims to develop crucial social capital alongside essential skills and competencies, maintaining a human element in conjunction with technology. The technology creates comprehensive learner profiles and applies natural language processing to generate personalized recommendations for career guidance and academic navigation. This innovation addresses the critical shortage of counseling resources in public colleges, where student-to-counselor ratios can reach 1:1,800. The project applies natural language processing (NLP) techniques to student learning profiles and competency to tap into a unique experiential learning recommendation engine for career guidance and academic navigation in higher education classrooms. This innovation aims to expand the toolkits of each faculty member's high-impact practice to their course learning strategies to enhance classroom learning strategies.
This Small Business Innovation Research (SBIR) Phase II project aims to enhance academic and career outcomes for students by leveraging natural language processing (NLP) and machine learning (ML) algorithms. The research builds upon a proprietary data representation model developed in Phase I to analyze student competencies, interests, and self-efficacy. The project's objectives are twofold: 1) Integrate diverse pedagogical philosophies into a unified system for curriculum modularization, student work assessment, and mentoring evaluation; 2) Develop a conversational AI engine utilizing Large Language Models (LLMs) to support self-regulated learning reflection and career exploration. The research methodology involves applying NLP techniques to student learning profiles and competency data to identify patterns in self-efficacy and learning strategies. The proposed approach will then generate personalized recommendations for career guidance and academic navigation. Anticipated technical results include a robust AI-driven system capable of analyzing student learning trajectories, providing tailored mentorship matches, and suggesting career-connected strategies. This research aims to bridge the gap between academic learning and career readiness, potentially transforming how students engage with their educational journey and future occupational identities.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
ESM GLOBAL PRODUCTIONS LLC
SBIR Phase II: Artificial Intelligence (AI)-Enabled African Language Database
Contact
63 FEDERAL ST
Portland, ME 04101--4222
NSF Award
2423568 – SBIR Phase II
Award amount to date
$1,000,000
Start / end date
09/01/2024 – 08/31/2026 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project aims to develop a multilingual translation platform for African languages, addressing a critical gap in current technology. This innovation enhances scientific understanding by advancing natural language processing for underrepresented African languages, promoting inclusivity and accessibility in the digital realm. The platform's societal impact will enable speakers of African languages to fully participate in the global digital economy and fostering cultural understanding. Commercially, this technology has transformative potential across various industries requiring multilingual communication, such as e-commerce, education, and public services. It opens new business opportunities and drives economic growth in global markets by facilitating more effective cross-cultural communication. The platform can enhance international trade, improve educational resources, and streamline public services for African language speakers worldwide. Beyond its immediate applications, this project contributes to preserving and promoting Africa's rich linguistic heritage in the digital age, bridging communication gaps and fostering a more inclusive global technological landscape. By addressing this underserved market, the project not only advances linguistic technology but also creates substantial commercial opportunities in an increasingly interconnected world. This innovative solution has the potential to revolutionize how businesses, educational institutions, and governments interact with African language speakers, opening up new markets and improving service delivery across multiple sectors.
The proposed project aims to develop an advanced AI-powered translation platform specifically designed for African languages, addressing the unique challenges posed by dialects, tonal shifts, and guttural sounds characteristic of these languages. The research objectives include creating a robust database and developing novel machine learning models to significantly enhance translation accuracy and nuance for underrepresented languages. The project will employ a multifaceted approach, including designing and deploying a state-of-the-art web crawler to source vast amounts of linguistic data which will utilize advanced natural language processing techniques to identify and extract relevant linguistic information from diverse sources. The project will also create new recorded data to fill gaps in existing resources, employing sophisticated processing algorithms to capture and analyze the nuanced phonetic features of African languages. Unique machine learning models, including deep neural networks and transformer architectures, will be developed to process the collected data effectively. These models will be trained on the extensive dataset to recognize and accurately translate complex linguistic patterns. The integration of these components into a scalable and customizable platform will involve advanced software engineering practices to ensure optimal performance and user experience. The anticipated technical results include a translation service surpassing the accuracy of current tools for African languages, as measured during Phase I, while maintaining strict data privacy and open-source licensing compliance.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
ESTAT ACTUATION, INC.
SBIR Phase II: Rotary Electroadhesive Clutch for Lightweight and Energy-Efficient Actuators in Next-Generation Robots
Contact
1028 WELFER ST
Pittsburgh, PA 15217--2651
NSF Award
2208905 – SBIR Phase II
Award amount to date
$944,190
Start / end date
02/01/2023 – 01/31/2025 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project will be to create a lightweight and efficient rotary electroadhesive clutch that enables improved robotic hardware performance across the manufacturing, logistics, and medical industries. Despite decades of research and commercial effort, society has yet to realize the widespread availability of affordable robots that can safely work alongside humans and assist them in their daily lives. A central obstacle in achieving this vision is the prohibitive cost and poor performance of actuators. Efficient, lightweight clutches that can improve robot operation time and safety at a competitive price are a gateway to the proliferation of human-assistive robotic systems into everyday life. For example, inexpensive motion assistance exoskeletons could improve the quality of life for millions of physically impaired people who are otherwise unable to engage in normal daily activities. Affordable robots could also increase access to expensive labor-intensive services, such as daily physical rehabilitation or full/part-time in-home care.
This Small Business Innovation Research (SBIR) Phase II project will be used to develop new materials understanding and correlate parameters such as morphology, dielectric thickness, and chemical modification to rotary electroadhesive clutch performance. The materials will be assessed for electrical and physical properties, as well as ease of incorporation into electroadhesive clutch assemblies and lifetime. Selecting optimal materials will improve fundamental performance while continuing to lower the weight, footprint, and energy consumption of rotary clutch designs. These research and development activities will de-risk the technology and enable the construction of a production-ready product. To efficiently achieve these goals, testing capabilities will be improved through the development of automated test stands to aid in rapid materials assessment, lifetime testing, and iterative design. For fundamental materials understanding, novel testing protocols will be developed that assess the electrical and wear properties of new materials, producing a widespread scientific impact in fields such as corrosion, coatings, and adhesion.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
ESal
SBIR Phase II: Novel Water Flooding Technique to Enhance Oil Recovery
Contact
1938 HARNEY ST STE 255
Laramie, WY 82072--5388
NSF Award
1853136 – SBIR Phase II
Award amount to date
$949,876
Start / end date
05/15/2019 – 12/31/2025 (Estimated)
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) project is to deploy a revolutionary water-flood technology to increase oil recovery. The best current technology is limited to 30 - 50% recovery leaving significant resources in the ground. The available methods to further increase recovery are expensive, have limited application and can cause environmental damage. The proposed method is much less expensive and has minimal environmental impact. Our technique does not use chemicals or additives thus avoiding the risk of contaminating ground and surface water resources. Rather than drill thousands of new wells, our approach revitalizes old fields and requires little modification to the existing infrastructure and operational procedures. It would allow older fields to continue to operate, providing jobs and taxes while increasing and further diversifying our domestic oil reserves. Full success of enhanced oil recovery,could produce up to 21.7 billion barrels of additional oil generating over $1 trillion for the US oil industry over the next twenty-five years, thereby increasing the energy security of the U.S. and creating more jobs while stabilizing domestic oil production at much lower costs than other technologies.
This SBIR Phase II project proposes to validate the technology to optimize wettability in existing oil reservoirs through flotation experiments, computer modeling and field pilots. Once we have achieved good pH control during the flotation experiments, we will determine the impact on reservoir wettability, the effect of salinity on wettability and the equilibrium constants for the surface complexation computer model. Finally, we will conduct concept validation projects in field to verify a minimum of 5% OOIP increase in oil production. Thus, we will provide producers with a field-verified process operators can implement to yield significant results for little cost.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
ETHOS MEDICAL, INC.
SBIR Phase II: Low-cost needle guidance system for bedside lumbar puncture
Contact
311 FERST DR NW RM L1325A
Duluth, GA 30097--1661
NSF Award
2112322 – SBIR Phase II
Award amount to date
$1,000,000
Start / end date
07/01/2021 – 12/31/2025 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is to improve the quality and efficiency of bedside spinal access procedures by developing a needle guidance system that interfaces with existing ultrasound machines. Lumbar punctures (LPs) are performed to diagnose and treat neurological conditions such as meningitis. The traditional LP technique requires practitioners to manually feel for spinal landmarks to form a mental image of the anatomy before blindly inserting the needle into the spine, aiming for a small target containing spinal fluid. This methodology can be challenging, costly, and time-consuming and is highly dependent on practitioner experience and patient body type. Up to 42% of procedures fail to access the target. Failed cases require radiological intervention, increasing the cost of care, lengthening patient stay, and exposing patients to radiation. Hospitals in the United States lose an estimated $2 billion annually due to inefficiencies and failures in LPs. The proposed needle guidance system will enable bedside spinal access procedures to be performed under real-time ultrasound imaging, significantly improving first-attempt success rates. The guidance technology can further be applied in other clinical segments, improving the quality of care across a variety of needle-based procedures.
This Small Business Innovation Research (SBIR) Phase II project aims to accomplish two primary objectives: 1) Complete development of a needle guidance system designed to interface with existing ultrasound machines; and 2) Develop an AI-powered anatomy detection software feature for the guidance system. These combined objectives will generate a functional, intuitive, and accessible solution that minimizes barriers to adoption while maximizing clinical and operational value. The proposed research involves conducting an array of safety and reliability studies to investigate the performance of the guidance system under realistic conditions. In developing a robust anatomy detection software feature, a spinal ultrasound data set will be created from a variety of non-patient volunteers. The data will be analyzed, processed, and used to train a machine learning model for anatomy detection. It is anticipated that the results of this project will demonstrate a sufficiently safe and efficacious system that can consistently guide a needle to an intended target with an error of less than 3 millimeters. The anatomy detection feature is expected to perform with at least 93% sensitivity and 85% specificity in identifying five key spinal landmarks; this level of performance would significantly reduce the knowledge barrier to performing ultrasound-guided interventions.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
EYEDEA MEDICAL, INC
SBIR Phase II: Development of a novel, highly efficient Descemet's Membrane Endothelial Keratoplasty preparation device expands the donor pool
Contact
101 W DICKMAN ST STE 800
Baltimore, MD 21230--5025
NSF Award
2212687 – SBIR Phase II
Award amount to date
$1,000,000
Start / end date
12/01/2022 – 11/30/2024 (Estimated)
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project relates to the significant, unmet clinical and commercial need of more than 25 million individuals waiting for a corneal transplant to restore their vision. Corneal blindness leads to an increased risk of physical harm, mental disorders, social isolation, and cognitive decline, resulting in an over 15-year reduction in life expectancy. Fortunately, 95% of corneal diseases can be treated via a transplant. Partial thickness corneal transplants are innovative procedures that provide the best clinical outcomes for over 90% of patients with corneal disorders; however, the difficulty of safely and efficiently separating the layers of the cornea to prepare corneal grafts and perform transplants has led to under-utilization of these procedures. This project seeks to commercialize single-use, assistive devices for tissue separation in corneal graft preparation and corneal transplant surgery with the potential to improve the efficiency of eye banks and ophthalmologists, increase access to corneal transplants, and improve the outcomes of these procedures. These devices have a time- and capital-efficient path to improving patient outcomes and entering the $340 million global market, annually.
This Small Business Innovation Research (SBIR) Phase II project involves development of novel, first-in-class graft preparation and assistive surgical devices that standardize, de-skill, and improve the viability of the liquid bubble (LBT) and big bubble techniques (BBT) in corneal transplantation. LBT is a graft preparation technique shown to prepare grafts in minutes from all donor eyes; however, it is more difficult and rarely used by eye banks. BBT is a surgical technique shown to provide efficient, precise separation of layers of the cornea in transplant patients; however, it is extremely challenging and leads to high rates of tissue perforation, with even experienced surgeons reporting 5?39% failure rates. This project leverages a technology for controlled separation of tissue layers to overcome the major barriers of LBT and BBT and enable adoption of partial thickness corneal transplant procedures. This proposal will test the hypotheses that this technology can provide high quality grafts that fit into existing clinical workflows and can enable safe, efficient, and standardized separation of corneal layers without complications. These studies, in collaboration with leading eye banks/corneal specialists, will advance device designs to ensure functionality, usability, manufacturability, and efficacy in human donor eyes.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
EYSZ, INC.
SBIR Phase II: Assessing comorbidities in epilepsy using eye movement recordings
Contact
107 SANDRINGHAM RD
Piedmont, CA 94611--3614
NSF Award
2304297 – SBIR Phase II
Award amount to date
$997,668
Start / end date
06/15/2023 – 05/31/2025 (Estimated)
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is to improve the treatment and cognitive function of epilepsy patients by using eye-tracking measurements to detect neurocognitive symptoms associated with epilepsy as well as the side effects of anti-epilepsy drugs. Epilepsy results in an estimated $28 billion in direct costs annually in the United States, in addition to hurting the quality of life of patients and their caregivers. Eye tracking technology, paired with cognition monitoring modules, will have a positive economic and societal impact. For example, some patients with epilepsy may be able to return to work sooner and the burden on caregivers to monitor seizures and side effects may be reduced. Earlier identification of comorbidities can enable simple interventions, such as additional support in classrooms, to improve long term outcomes. In addition, the technology will help clinicians diagnose and refer drug-resistant patients to specialized epilepsy centers much sooner than the current average of 18 years. Finally, the solution will improve side effect monitoring in clinical trials for new antiepileptic drugs and help optimize dose recommendations. These advances will, in turn, accelerate the development of new anti-epileptic therapies.
This Small Business Innovation Research (SBIR) Phase II project aims to improve the lives of epilepsy patients by using passive observation of eye movements in a naturalistic setting to objectively and reliably identify seizures and monitor neurocognitive symptoms and drug side effects. The proposed solution will use a wearable device to collect eye movement data over time and this data will be analyzed to quantify changes associated with impairments in cognitive functions such as attention and reading speed. This data then will be used to develop a personalized therapy response profile to assist clinicians in managing epilepsy. The goal of this project is to collect non-seizure, spontaneous eye movement data and develop algorithms that provide insight into clinical features, including the improvement or worsening of symptoms and possible antiepileptic drug side effects. The outcome of this research will enable a fully powered, pivotal study to be designed and carried out to compare passive eye tracking data to the gold standard neuropsychiatric assessments for the treatment of naïve absence epilepsy patients over time and as medication adjustments are made.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
Emagine Solutions Technology
SBIR Phase II: Improved Maternal Health with Predictive Patient Monitoring
Contact
990 E CALLE DE LA CABRA
Tucson, AZ 85718--2929
NSF Award
2233743 – SBIR Phase II
Award amount to date
$975,040
Start / end date
06/15/2023 – 05/31/2025 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is to develop further a predictive model for health providers to address the life-threatening condition of preeclampsia in pregnant and postpartum patients. Preeclampsia affects 1 in 20 births, or 150,000 women in the U.S. each year. Not only does Preeclampsia cost 70,000 lives globally each year, it is also an expensive burden for healthcare systems. It costs nearly three times more to treat a patient with preeclampsia than one without this complication. When deployed at scale, the technology proposed in this SBIR grant could be a key factor to reducing maternal mortality in the United States, improving obstetric patient outcomes, reducing the cost of obstetric care, and helping to reduce health disparities.
The proposed project will research and develop a method to potentially detect preeclampsia. Preeclampsia is a hypertensive disorder of pregnancy. This dangerous condition also costs the U.S. healthcare system $2.18 billion per year or one-third of the total amount spent on maternal healthcare in our country. Research objectives include optimizing a machine learning model, integrating patient-facing software into Electronic Health Records systems, implementing the predictive model for preeclampsia, integrating with peripheral wellness devices, developing reminder notification mechanisms, determining appropriate interface enhancements, and defining commercialization and regulatory strategies. Improving maternal health outcomes advances the general health and welfare of American families and can improve our country?s economic competitiveness on the world stage.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
FAKHRO, LOUAY K
SBIR Phase II: Enhancing Performance and Achieving Commercial Readiness for the PQS1.0 Rapid Phenylalanine Blood Level Monitor
Contact
27061 MALLORCA LN
Mission Viejo, CA 92691--6111
NSF Award
2332518 – SBIR Phase II
Award amount to date
$997,142
Start / end date
05/01/2024 – 04/30/2026 (Estimated)
Errata
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Abstract
This Small Business Innovation Research (SBIR) Phase II project addresses a pressing need for a rapid and user-friendly method to monitor blood phenylalanine levels in individuals with phenylketonuria (PKU), a lifelong genetic disorder impairing phenylalanine processing, an amino acid found in many common foods. Left untreated or poorly managed, PKU can result in intellectual disabilities, behavioral issues, and severe health complications. In the U.S., an estimated 20,000 to 35,000 individuals grapple with PKU, demanding consistent blood phenylalanine level monitoring as part of their disease management. The annual costs of PKU care can vary from $15,000 to $200,000 per individual, with higher costs linked to inadequate management, leading to irreversible damage and substantial healthcare services. Currently, monitoring occurs with intervals of 3 to 5 days or even up to two weeks, constrained by factors like test sites, facility availability, and turnaround times. Ideally, PKU monitoring should align with individual needs, occurring daily in sync with diet, age, health factors, and gestational period. Enhanced monitoring frequency is widely recognized as beneficial, and this project aims to improve PKU care by providing accessible and frequent monitoring for improved patient outcomes.
This Small Business Innovation Research (SBIR) Phase II project aims to develop a rapid phenylalanine monitor for phenylketonuria (PKU) patients. The project offers rapid analysis of blood phenylalanine levels to enhance patient outcomes and improve the current standard of care. Consisting of a test strip and a test device, the system accepts a blood drop from a finger prick. The test strip conditions the blood sample with specific analytes before the test device analyzes the sample. The project's core focus is optimizing product design and system algorithms, enabling cost-effective manufacturing and deployment for end-users.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
FIELD PROPULSION TECHNONOGIES INC.
SBIR Phase II: Advanced propulsion system for spacecraft based on the Unresolved Longitudinal Ampere Tension Forces in Conductors
Contact
4824 S ELK ST
Aurora, CO 80016--5815
NSF Award
2423107 – SBIR Phase II
Award amount to date
$1,000,000
Start / end date
09/15/2024 – 08/31/2026 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of this Phase II Small Business Innovation Research (SBIR) project is a propulsion system that has far-reaching implications for the space industry and beyond. This propulsion system for spacecraft could revolutionize the space industry by reducing reliance on traditional propellants. The propulsion system is one of the critical satellite subsystems and the proposed technology will lower space mission costs, increase mission flexibility, and extend spacecraft lifetimes. It will enable zero-emission impulse for satellites, and facilitate efficient satellite re-entry into the atmosphere, mitigating the problem of space debris. The space industry is shifting toward a future in which large constellations of small satellites deliver all types of satellite services efficiently and in large geographical areas or across the globe. The size of the small satellite propulsion system market is estimated to grow at a continued 18% yearly, to reach $1.0 billion by 2032. This advancement is paving the way for a more sustainable and accessible future in space exploration. It fosters space exploration and innovation, enhancing global competitiveness and unveiling new possibilities for mankind's use of space.
This SBIR Phase II project proposes to develop an advanced propulsion device prototype suitable for small satellite operations in orbit. This will represent a first of a kind propulsion technology that can fulfill major orbital satellite maneuvering, and the current stage development of alternative technologies does not offer a solution in the short to medium term either. The key innovation behind the proposed solution is a new class of specially engineered metamaterial, based on a special graphene composite, that utilizes the unresolved longitudinal forces or Ampere Tension Forces in conductors to produce thrust. Technical proof-of-concept has been reached by building a lab prototype that produced external forces as large as a few millinewtons, using currents in the range of a few milliamperes. The proposed Phase II is aimed at scaling up this prototype, strengthening the metamaterial for use in a more space-like environment, and demonstrating sufficient thrust to move a small satellite in space. Phase II will generate a prototype generating up to tenths of newtons of force, that will be validated in conditions representative of the space environment. After Phase II, the technology will be ready to be integrated into a real satellite propulsion system and utilized for in-space demonstration.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
FIRELINE SCIENCE LLC
SBIR Phase II: Offline Edge Learning Management System
Contact
5501 S COLLEGE AVE
Tempe, AZ 85283--1815
NSF Award
2233395 – SBIR Phase II
Award amount to date
$996,783
Start / end date
06/01/2023 – 05/31/2025 (Estimated)
NSF Program Director
Errata
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Abstract
The broader/commercial impact of this Small Business Innovation Resesarch (SBIR) Phase II project will be in helping to close the homework gap in the United States. The homework gap has been a long simmering problem where 12 ? 17 million K-12 students do not have reliable home internet to complete digital homework. Students that could benefit the most from learning applications that require home access are disproportionately from lower-income, rural, and at-risk minority populations. While new broadband funding initiatives may make incremental improvements to the situation, millions of students in low-income and rural areas continue to be left behind. This project aims to use new advances in web technologies and intelligent agents to provide a software solution that will enable any student to participate in a complete digital homework workflow including interactive lessons, videos, and robust teacher feedback even when they have unreliable or no access to the internet. Unconnected adult learners will also benefit from the project as technical skills training including computer programming will be supported. This solution will assist in filling the key technical skill gaps in the American workforce.
This SBIR Phase II project will advance a new homework management system that will support digital learning with a consistent experience for learners that are online, offline, or in degraded network conditions and on any available devices. Through an innovative offline-first distributed architecture that solves complex problems around state divergence and conflict resolution, user identity, system integrations and offline content management, this system attempts to bring equitable access to learners who have historically had limited or no access to at-home digital homework solutions. The system will utilize intelligence at the edge to facilitate effective, research-based, pedagogical approaches to improve learning outcomes and minimize teacher overhead. Pilot programs and user feedback studies, along with custom-built learning model simulators will be used to evaluate and iteratively refine the system's efficacy. The goal of this project's research and development will be the release of a production-ready, scalable homework management system that makes positive progress toward bridging the homework gap.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
FRONTLINE BIOTECHNOLOGIES INC.
SBIR Phase II: Development of an End-to-End Solution for High-Volume Water Microbiological Testing
Contact
1000 WESTGATE DR STE 140
Saint Paul, MN 55114--1963
NSF Award
2423051 – SBIR Phase II
Award amount to date
$995,600
Start / end date
09/15/2024 – 08/31/2026 (Estimated)
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is to enhance public health and safety through advanced water microbiological testing technologies. This project's innovation enables the early detection of pandemics by identifying waterborne viruses such as SARS-CoV-2 which causes COVID-19, and norovirus, which is notorious for causing gastroenteritis, potentially weeks before outbreaks manifest. Such early detection is vital for policymakers, allowing more effective intervention strategies and reducing both human casualties and healthcare costs. Moreover, the technology promises to improve the safety of drinking water, particularly important as many states increasingly turn to recycling wastewater due to drought. This could decrease the incidence of waterborne illnesses, which currently affect millions and cost the U.S. healthcare system billions annually. Additionally, the innovation facilitates more accessible and efficient water testing in remote and underserved communities by reducing costs and processing times, supporting healthcare equity. Finally, this new approach not only promises to transform drinking water safety monitoring practices and wastewater-based pandemic surveillance but also drives the implementation of new water quality standards and regulatory frameworks, aligning with the Best Available Technology practices.
This Small Business Innovation Research (SBIR) Phase II project addresses significant gaps in water microbiological testing. Monitoring the presence of viruses such coronavirus and norovirus in water is crucial for pandemic surveillance and drinking water safety. Waterborne viruses are present in low concentrations and their detection requires the analysis of large sample volumes. However, current tools are designed for small volumes, resulting in low sensitivity and high variability in testing results. The goal of this project is to develop a comprehensive technological solution to enhance the reliability and standardization of wastewater epidemiology and drinking water testing, a pressing need identified by health agencies to improve data quality and comparability. The current effort focuses on developing a scalable platform that integrates a novel filtration cartridge and reagent kit, capable of processing up to two liters of water in less than five minutes. This capability enhances the yield and purity of viral nucleic acids and improves the detection limit by two orders of magnitude, enhancing accuracy and reducing false positives. By improving our ability to monitor pathogen spread through community water systems, this project is expected to enhance pandemic preparedness and drinking water safety and facilitate more effective public health interventions.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
FROSTDEFENSE ENVIROTECH, INC.
SBIR Phase II: Budbreak Delay Gel Technology for Frost Management and Mechanization of Vineyards
Contact
509 S GARFIELD AVE
Champaign, IL 61821--3831
NSF Award
2125182 – SBIR Phase II
Award amount to date
$995,228
Start / end date
12/15/2021 – 06/30/2025 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact of this SBIR Phase II project is to allow America?s grape industry to reduce crop losses due to spring frost, estimated at over $1 billion per year, as well as related job losses ? more than 11,000 individuals in the State of Washington alone. The encapsulating bud break delay technology and predictive analytics support farmers with decision making tools ahead of impending frost events during bud break season. Such tools may enable rural communities to achieve economic stability by decreasing yield losses and lowering production costs. The technology fills gaps in knowledge needed to make informed decisions on individual farms, resulting in better management decisions in the face of increasing complexities of spring freeze threats. Additionally, use of the encapsulation technology may reduce carbon emissions and water usage from current fossil fuel-intensive conventional frost mitigation measures such as burners, wind machines and sprinklers.
The proposed encapsulating bud break delay technology involves two main advances. First, a gel encapsulation spray biologically delays the process of bud break consistently up to 14 days and increases cold resistance up to 6 degrees Celsius. Second, to guide growers in delivering this product, a Decision Support System (DSS) aids grape growers in deciding when it is necessary to mitigate pending frost conditions. The Phase II project focuses on increasing the predictive accuracy of the DSS and scaling the system. Specifically, the team will focus on: a) optimizing the formulation and testing in the lab, b) field-testing and data collection at five sites, c) enhancing DSS capabilities with additional data and analysis, d) scaling up for large-scale manufacture and application, and e) gathering data for regulatory approvals. This gel encapsulation solution for frost protection of vineyards may find future applications in other fruits crops such as apples and stones fruits that are even more susceptible to spring frost damage than grapes.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
Fortiphyte, Inc.
SBIR Phase II: Identification of disease resistance traits to improve the productivity and sustainability of soybean cultivation
Contact
2151 BERKELEY WAY RM 220
Berkeley, CA 94707--1517
NSF Award
2112394 – SBIR Phase II
Award amount to date
$991,857
Start / end date
09/01/2021 – 08/31/2025 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2). The broader impact of this Small Business Innovation Research (SBIR) Phase II project is to improve the productivity, environmental sustainability, and profitability of soybean cultivation. Soybean cultivation is a major driver of rainforest deforestation, motivating improved yields for environmental sustainability. In addition, current commercial soybean varieties are highly susceptible to Asian soybean rust, an aggressive fungal disease that is especially severe in tropical and subtropical climates and can decimate soybean yield. This disease is controlled by chemical fungicides that are expensive, pose risks to the environment and human health, and are becoming less effective as the pathogen develops tolerance to over-used chemicals. This project will enable the development of soybean varieties immune to this disease. This will reduce the need for fungicide use in soybean cultivation, reduce yield loss caused by the pathogen, and improve grower profitability. In addition, this technology can be expanded to other crops.
The proposed project will result in the identification of new plant disease resistance traits with activity against the pathogen that causes Asian soybean rust. The typical plant species has hundreds of immune receptor genes which surveil for the presence of invading pathogens. Plant breeders routinely use plant immune receptor genes to develop new disease-resistant crop varieties. However, traditional methods to identify and translate these traits are time-consuming. The proposed work utilizes a rapid gene discovery platform to accelerate identification of new disease resistance traits. This project will identify and test several resistance traits. The identification and cloning of these resistance gene sequences will allow them to be quickly moved into elite soybean varieties, resulting in significant time and labor savings relative to traditional breeding. These traits can be stacked together to confer durable resistance against a broad range of Asian soybean rust strains.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
GAIA AI, INC
SBIR Phase II: Registration of Below-Canopy, Above-Canopy, and Satellite Sensor Streams for Forest Inventories
Contact
444 SOMERVILLE AVE
Somerville, MA 02143--3260
NSF Award
2423614 – SBIR Phase II
Award amount to date
$1,000,000
Start / end date
09/15/2024 – 08/31/2026 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase II project will be in scaling current resources available for collecting the data that is needed for making decisions on how to best manage trees and forests. This technology will be used broadly for scaling conservation work and scaling adoption of sustainable forest management practices, for identifying areas at high risk of wildfires that need to be proactively treated to mitigate that risk, and for verifying stewardship work that enhances biodiversity values in a given forest. This technology will help address the growing labor challenges currently facing the forest management industry, enabling foresters and indigenous forest stewards to manage much more land with the constrained resources they have available. This work will create new jobs and market opportunities for US citizens from the stewardship projects that come from the identified opportunities, be it around wildfire risk management treatments or restoring forests for carbon projects. All of these benefits for the country and its citizens align with the National Science Foundation?s core mission of advancing the nation?s health, prosperity, and welfare.
The technology being developed is a hardware sensor backpack and an AI tool for processing the collected data into useful forest biometric indicators. This undertaking involves designing a sophisticated AI technology similar to that used in autonomous vehicles for building a map of the world around them, but designed from the ground up to work for processing data in natural environments to map out forests. This research will refine this technology to create an operationalized product for use by forestry professionals to support the decisions they make around actively managing working forests. This includes conserving areas of old growth trees, verifying the carbon sequestered in sustainable forestry stewardship projects, prescribing targeted treatments for mitigating risk for wildfire, and auditing forest management practices for maintaining and enhancing the biodiversity values of a given forested area. Specifically, the scope of this project will be to extend the capabilities of the AI technology built out in the Phase I work to be able to measure more dense forests, to output broader biomass measurements to be used in carbon verification and fuel load measurements to assess wildfire risk, and to reliably and accurately scale the below-canopy measurements with satellite imagery over very large forested areas.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
GATE SCIENTIFIC, INC.
SBIR Phase II: Development of a Wireless pH Sensing Stir Bar
Contact
950 YOSEMITE DR
Milpitas, CA 95035--5452
NSF Award
2036372 – SBIR Phase II
Award amount to date
$999,656
Start / end date
06/15/2021 – 03/31/2025 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
This Small Business Innovation Research (SBIR) Phase II project will develop networked, wireless chemical and biological sensing for use in wet laboratory and manufacturing environments. The technology to be developed addresses a $16 billion chemical and bioprocessing equipment market with a large growth potential. The ability to cost-effectively monitor these parameters from the research phase to large-scale manufacturing will accelerate the development of critical products such as vaccines and cell therapies, as well as better ensure the quality of everyday consumer goods produced from advanced chemical and biochemical processes.
The proposed project includes technical and manufacturing advances that must be made to bring these sensors to market. This effort combines engineering development in networked, wireless communication and miniaturization with analytical chemistry development of key sensing technologies. The innovations include development of manufacturing processes for a novel pH stir bar, development of wireless dissolved oxygen sensing modalities, and methods for achieving wireless sensing in larger-scale, metallic manufacturing vessels. Technology will be developed that enables wireless sensing of key wet process parameters such as pH and dissolved oxygen for chemical and biochemical process monitoring in research and larger-scale manufacturing environments.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
GENCORES LLC
SBIR Phase II: Rapid and scalable production of high-performance 3-dimensional foam cores
Contact
163 SUMMER STREET APT P4
Somerville, MA 02143--2636
NSF Award
2408705 – SBIR Phase II
Award amount to date
$999,739
Start / end date
09/01/2024 – 08/31/2026 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase II project is to democratize the use of high-performance composites across industries, especially within all segments of the automotive sector. When produced on a large scale, a widespread adoption of composites will revolutionize automotive manufacturing, unlocking the creation of ultra-light and highly efficient vehicles. Transportation is the largest contributor to global air pollution. Currently, an estimated 150 million Americans and 9 out of 10 people in urban areas worldwide, live in areas that don't meet federal air quality standards. Reducing harmful emissions from transportation has therefore become a crucial social and techno-economical challenge. As per the Department of Energy, extensive integration of composites in light-duty vehicles - 300 kg per vehicle - could result in OEMs producing up to 50% higher efficiency gas powered vehicles and electric vehicles requiring only half the current battery capacity to achieve a target range. Such a shift would decrease the U.S. reliance on rare minerals such as lithium, cobalt, and nickel. Consequently, Gencores? scientific endeavor aims to bolster U.S. industrial resilience, fortify the nation's advanced energy sector, enhance national security, and contribute to global decarbonization efforts.
This Small Business Innovation Research (SBIR) Phase II project aims at demonstrating transitioning a niche high-performance polymer foam into an ultra-high performance, widely available low-cost commodity material, unlocking significant processing innovation and mass manufacturing of structural composites through existing and mature high-volume molding technology. In detail, this award will demonstrate Gencores proprietary synthetic route and material structuration process enable the cost-efficient production of foams featuring tailored and outstanding thermal properties at low weight. These foams will withstand the pressures and temperatures encountered during high volume composite molding technologies, ensuring the integrity of the final 3D composite components and their production in a 90 second cycle time. The architecture of these highly structured materials will be optimized using a set of proprietary numerical design and simulation tools. Many polymers are currently confined to high-value markets because of their unconventional production methods, leading to either high manufacturing costs or limited production volumes. Gencores groundbreaking scientific advancements in synthesizing high-performance polymers offer the potential to extend to other aerospace-grade polymer varieties, transforming them into commodities. This endeavor is crucial, as material performance and accessibility are fundamental to advancements across all domains of human activity.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
GENERATE LLC
SBIR Phase II: A Digital Design-Delivery System for the Large-scale Deployment of Mass Timber Building Technologies
Contact
334 BEACON ST APT 6
Boston, MA 02114--2813
NSF Award
2111626 – SBIR Phase II
Award amount to date
$1,000,000
Start / end date
07/01/2021 – 06/30/2025 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase II project is to accelerate the digitization of the AEC (Architecture, Engineering and Construction) industry, while democratizing the use of sustainable building materials. The technology is a first-of-its-kind Computer Aided Design for Manufacturing (CADfM) software. It enables architects to design for code compliance, cost management, and environmental sustainability. The proposed software will enable greater flexibility, lower cost, greater project speed, wider product selection, and enhanced human creativity in design.
This Small Business Innovation Research (SBIR) Phase II project will enable architectural design-for-manufacturing. Current design processes lack the pre-rationalization of manufacturing. To deliver sustainable, economically efficient and high-density buildings, architects need tools to quickly test design options in a data-rich space. Manufacturers need their products digitally integrated into architects? early designs, to prevent value-engineering and rework. This software is uniquely built on a game engine, and hosts a geometry kernel with smart building elements (façade, corridor, spaces, etc.) aware of their type, purpose and adjacencies, permitting data communication between assemblies and integration with data libraries for rapid evaluation of potential design changes and estimation of associated costs and effects.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
GLOBAL COOLING TECHNOLOGY GROUP, LLC
SBIR Phase II: Innovative Two-Phase Cooling with Micro Closed Loop Pulsating Heat Pipes for High Power Density Electronics
Contact
13856 SOUTH 36TH WAY
Phoenix, AZ 85044--8211
NSF Award
2321862 – SBIR Phase II
Award amount to date
$978,431
Start / end date
04/01/2024 – 03/31/2026 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is that it enables significantly enhanced cooling performance for consumer and embedded electronics of mobile devices in the worldwide race for more efficient products. Compared with the current state of the art, this project?s micro Closed-Loop Pulsating Heat Pipes (CLPHPs) will provide over 40% higher cooling capacity, increase battery life by more than 30%, and reduce electricity consumption by over 25%. It will be made of a recyclable material (aluminum) or ceramic with a new environmentally friendly working fluid inside. The primary source of revenue will be via product sales of CLPHP-based heat sinks to laptop OEMs and other OEMs, integrators, and end users. We anticipate entering the market in 2026/2027 for mainstream and gaming ?thin and light? laptops and electronics with discrete GPUs and CPUs/processors requiring advanced cooling. CLPHPs provide a direct replacement for existing vapor chamber, heat pipe, and heatsink solutions for these devices. The main deliverable is to develop an industry-leading heat spreader- that operates passively, creating its coolant flow from its self-pulsating mechanism, critical for thin mobile electronics for which fans or other auxiliary powered non-passive solutions are avoided.
This SBIR Phase II project proposes to address the urgent cooling challenges presented by next-generation 5G/6G mobile devices and other advanced electronics (Artificial Intelligence, Internet of Things) for which a solution has yet to be found. The objectives are to build on the fundamental and practical knowledge developed in the Phase I project to geometrically enhance the micro-channels to increase the internal surface area, the evaporation and condensation processes, and the flow rate to achieve even greater heat-spreading capability. This will be accomplished through fabricating and testing two novel CLPHP designs (generations 2 and 3) under various heating conditions and orientations representative of mobile device applications. The goal is to enter the market with this disruptive cooling technology that will enhance the performance of millions of mobile devices, save battery/grid energy, and unlock the barriers created by today?s lack of advanced cooling solutions. The novel CLPHP is an important ?enabler? of numerous new devices yet to be conceived and for improvement of existing advanced technologies, nearly all of which are electronically ?throttled? by the limiting performance of current cooling technologies. This project is well-positioned to provide the US/worldwide market with the needed cooling solutions.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
GLOBE BIOMEDICAL LLC
SBIR Phase II: Feasibility of a Wearable Blindness Prevention System
Contact
25014 LAS BRISAS S
Murrieta, CA 92562--4029
NSF Award
1951039 – SBIR Phase II
Award amount to date
$714,786
Start / end date
04/01/2020 – 03/31/2025 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader/commercial impact of this SBIR Phase II project aims to further advance novel wearable technology for glaucoma patients and prepare the technology for broad adoption. Glaucoma, the leading cause of irreversible blindness, has an unknown cause and affects more than 70 million people worldwide. Currently, there is no cure for glaucoma, but early can often save one?s vision. Eye pressure is the most commonly used measure for predicting and monitoring glaucoma. The wearable technology developed under this SBIR project will monitor eye pressure throughout the day and allow clinicians to provide a higher quality of care for at-risk patients. The technology uses photographs to measure how the eye stretches under high pressure. This project aims to adapt the imaging technology into stylish eyeglass frames and develop custom software for converting photographs to eye pressure measurements, informing providers and improving compliance associated with at-home medication.
This project aims to advance a novel technology in which wearable eyeglass frames are used to track intraocular pressure (IOP) by imaging the level of pressure-induced mechanical strain associated with the tissue at the front of the eye - specifically, exposed sclera. IOP is, by far, the most commonly used metric for predicting glaucoma, the leading cause of irreversible blindness. In this project, a custom machine learning algorithm will identify characteristic patterns residing in small regions of the scleral images and, by tracking pressure-induced displacement of the regions, calculate IOP. The key objective of Phase II is to accurately measure IOP in real-world conditions with human in-vivo studies, incorporating necessary electronics in the frames. The technology will be further developed in order to improve correlation of the algorithm with conventional IOP captured during the image collection period.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
GMJ TECHNOLOGIES, INC.
SBIR Phase II: Next-Generation Capillary Electrophoresis with Mass Spectrometry for Biopharmaceutical and Biomedical Applications
Contact
4820 148TH PL SE
Everett, WA 98208--8812
NSF Award
2025299 – SBIR Phase II
Award amount to date
$1,195,701
Start / end date
02/01/2021 – 01/31/2025 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase II project will be the development of a new instrument for biological research, biomedical research, and biopharmaceutical drug development. Capillary electrophoresis (CE) is a powerful technology with great potential for bioanalysis. It was the workhorse tool for the completion of human genome project that contributed to the DNA sequencing revolution. The technology will offer benefits to biopharmaceutical drug development companies by increasing the efficiency of product characterization for quality improvement. This new system could lead to breakthroughs in drug development, early diagnosis, and treatments for deadly human diseases such as cancer, diabetes, and neurodegenerative disorders. The technology may be of value not only in biopharmaceutical and biochemical research markets but also in food, clinical, and environmental analyses.
The project will develop a next-generation capillary electrophoresis with electrospray ionization mass spectrometry (CE-ESI-MS) for protein characterization. CE-ESI-MS allows efficient separation and characterization of several biochemical species, including proteins. The CE-ESI-MS technology will be developed for ease of use. It will use a novel fluidic nanoport for sample and buffer manipulation to allow analysis from 1 microliter or less volume for small samples. In addition, the instrument will utilize a novel electrospray ionization interface with integrated optical detection. Combining CE's ultrahigh efficiency with robust quantitative characteristics of optical detection and the molecular identification of mass spectrometry will be a powerful tool for bioanalysis. This combination may represent a significant advancement over the state-of-the-art and enhance the means of interrogating proteins and their biochemical functions in biological samples. With simple automated design and ease of use, the technology may significantly enhance the robustness and capabilities of CE-ESI-MS for fast, efficient, and deep bioanalysis.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
GODWIT KEY COMPANY
SBIR Phase II: Platform for providing long haul support for species conservation through biodiversity credits
Contact
4967 NEWPORT AVE STE 12 PMB 318
San Diego, CA 92107--3167
NSF Award
2345382 – SBIR Phase II
Award amount to date
$997,954
Start / end date
08/01/2024 – 07/31/2026 (Estimated)
NSF Program Director
Errata
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Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase II project is in addressing biodiversity loss through its unique conservation platform that provides dual-sided marketplace for biodiversity credits. The platform would support local communities engaged in on-the-ground conservation activities, advance conservation efforts by engaging with individual funders, and work with corporations to hit their biodiversity targets. It also would empower corporations to meet their social responsibilities and be compliant with emerging environmental regulations. The innovative platform is designed to connect corporations directly with conservation organizations with the aim to address the critical need for sustainable funding for conservation initiatives by streamlining the process of the development, sale, and marketing of biodiversity credits. Through the development and facilitation of biodiversity credits the project has the potential to advance scientific research and progress, generate substantial economic benefits, and enhance social welfare and environmental sustainability. These outcomes align directly with the National Science Foundation?s mission, ultimately improving the quality of life for U.S. citizens.
The primary technical innovation of this project is the development of an integrated platform that provides a dual-sided marketplace for biodiversity credits. The intake tool within the platform is intended to help conservation organizations identify, develop, and sell biodiversity credits to increase sustainable funding while connecting corporations to a centralized marketplace to search and purchase these credits to meet their biodiversity targets and comply with new environmental laws and regulations. The project would leverage artificial Intelligence to analyze large datasets, provide personalized recommendations, and advance scientific research. The Application Programming Interface tool would enable businesses to streamline sustainable options for their consumers while expanding their target demographics. The project integration would enhance the platform?s efficiency while ensuring both corporations and conservation organizations have the tools and support needed to address biodiversity loss.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
GRAIN WEEVIL CORPORATION
SBIR Phase II: Improving farmer safety and grain storage efficiencies via an autonomous grain management and extraction robot
Contact
1845 CRAIG RD
Aurora, NE 68818--1014
NSF Award
2321441 – SBIR Phase II
Award amount to date
$994,390
Start / end date
09/15/2023 – 08/31/2025 (Estimated)
NSF Program Director
Errata
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Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase II project includes the development and implementation of a robot for post-harvest grain management with the goal of reducing waste, increasing efficiency, and improving the overall sustainability of the agricultural sector. Post-harvest grain management is a crucial aspect of agriculture; However, it can also be a challenging and labor-intensive process for farmers. The incorporation of robots in this process has the potential to alleviate these difficulties and improve overall productivity. By reducing waste and increasing efficiency in grain storage and processing, farmers can ensure that a greater proportion of their crops are utilized, resulting in a more substantial yield. Additionally, the use of automation can enhance working conditions for farmers, allowing them to devote more time to other important tasks. The findings of this research have the potential to have a significant impact on national security, food security, and the rural economy.
This Small Business Innovation Research (SBIR) Phase II project addresses farmer/worker well-being with research and development on a grain bin management robot. This robot has the potential to transform the field of post-harvest grain storage through its ability to autonomously perform novel and innovative tasks within granular bulk storage environments. Additionally, the robot's ability to safely and effectively operate in harsh, hazardous environments through the implementation of robust safety measures and the use of specialized, hardened electronics further demonstrates the significance of this technology in advancing the field of agricultural robotics. As this technology develops, the autonomous robot will change the way grain is stored. Advances from this research expand the focus from safety to the ability to do the work that no human could. The robot will positively impact labor issues, grain quality improvements, and workflow efficiencies throughout the grain-based supply chain.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
GRAVEL CAPITAL LLC
SBIR Phase II: FlashPCB Service Commercialization and AI Component Package Identification
Contact
2025 WASHINGTON AVE
Philadelphia, PA 19146--2632
NSF Award
2335464 – SBIR Phase II
Award amount to date
$1,000,000
Start / end date
05/01/2024 – 04/30/2026 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase II project is to create an artificial intelligence-powered printed circuit board assembly (PCBA) service that allows new products to get to market faster and that allows engineers to develop more sophisticated designs by decreasing the time to iterate on PCBs designs. Prototyping PCBAs is a key element in the innovation process for all electronics from consumer goods to medical devices, but current PCBA prototyping services are limited by manual steps and supply chain shortages. The artificial intelligence innovation of this project will save the customers time through strategic automation, shortening innovation timelines, and bringing new products to market faster. Currently, other countries are still dominating the PCBA market share, serving many customers from the United States. There is an opportunity to provide high-quality, cost-competitive manufacturing in the United States to better serve the market and meet the rising demand for PCBAs. Additionally, investment in domestic manufacturing will strengthen electronic manufacturing capabilities, reduce dependence on foreign markets, and protect intellectual property.
This Small Business Innovation Research (SBIR) Phase II project will create a service that provides customers with a rapid PCBA prototyping service. The project employs computer vision and artificial intelligence techniques to ensure the manufacturability of customers? designs and find components to satisfy the customers? designs while ensuring the designs can be manufactured in a blistering three days. The project will automate many of the manual steps associated with quoting and manufacturing a PCBA. One of the most time-consuming steps of quoting a PCBA is determining a set of components that will satisfy a customer?s design and which can be sourced within the manufacturing time frame. Building on the component selection algorithm developed in the SBIR Phase I project, which reads the property text from the customer?s designs to find components that satisfy the customer?s specifications, will build a system for matching components to a footprint (the copper landing pad on the board onto which a component is soldered). This will allow for rapid quoting, component substitution, and manufacturability checks, all of which will make PCBA prototyping fast and easy for the customer.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
GREEN SUN MEDICAL, LLC
SBIR Phase II: Development of a pad and sensor system for a dynamic scoliosis brace
Contact
938 W MOUNTAIN AVE
Fort Collins, CO 80521--2510
NSF Award
2102167 – SBIR Phase II
Award amount to date
$965,903
Start / end date
09/01/2021 – 08/31/2025 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is to improve clinical care for scoliosis patients. Scoliosis, a sideways curvature of the spine, affects 6-9 million individuals in the US, or 2-3% of the population, and has estimated healthcare costs of $3.5 billion by 2028. Current treatments for scoliosis include bracing and/or spinal surgery. Patients are often treated with a rigid thoracic scoliosis brace that does not typically provide curve correction. Compliance with wearing the brace can be challenging. The proposed technology is an intelligent, active brace that applies corrective forces to the spine via a dynamic, adjustable platform and reports compliance through its sensors. This personalized system may improve clinical outcomes at reduced cost.
This Small Business Innovation Research Phase II project seeks to advance the development of an innovative scoliosis brace. The proposed system is designed to be comfortable to increase wear compliance by patients. The brace has a dynamic mechanism that can be adjusted to provide continuous pressure, and will have Bluetooth-connected sensors allowing parents and physicians to ensure treatment quality. The new technology will accommodate patient growth and curve correction while maintaining a precise fit, and may lessen the social stigma of wearing a brace. In this Phase II proposal, functionality and durability of the smart pad and sensor system in a clinical setting will be verified, feedback from end users (orthotists, spine specialists, patients and families) on the mobile application and physician dashboard will be collected, and the system economics and fabrication will be optimized.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
GREENSIGHT AGRONOMICS, INC.
SBIR Phase II: High Resolution Environmental Sensing Using Nanodrones
Contact
12 CHANNEL ST
Boston, MA 02210--2333
NSF Award
2233583 – SBIR Phase II
Award amount to date
$940,743
Start / end date
06/01/2023 – 05/31/2025 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase I project is enabling enhanced prediction of severe weather formation to a timing resolution of hours instead of days. Improved weather predictions have a significant impact on people?s lives, allowing for better planning, proactive evacuations, and reducing deaths, injuries and property damage, especially in vulnerable populations. With climatologists predicting dramatic increases in damaging and dangerous severe weather over the next decades, accurate prediction of severe weather is even more critical. This project will launch a robotics-as-a-service business around the technology which can rapidly reach sustainability, generating economic impacts while providing significant environmental, scientific, and societal benefits. As the technology matures and becomes more widespread, entirely novel analysis and predictive models will be developed around the data being produced, unlocking even higher value economic insights for insurance, energy, financial, and transportation industries.
The part of the atmosphere from the ground up to about 3,000 feet is called the atmospheric boundary layer. This area is difficult to monitor but has a huge impact on gas, heat, and energy exchange between the earth and the atmosphere. This project enables better monitoring and understanding of this area, unlocking scientific, logistical, and policy advancements that will drive new innovations in climate, environmental, and weather science with high impact on humanity. The proposed technology enables gathering high spatial and temporal resolution atmospheric data with a swarm of synchronized sampling aircrafts. The swarm system will use lightweight design approaches and proprietary optimization techniques for portability, swarm capability, flight endurance, and low cost. Using automation and robotics, including remote operational support, this project will enable data that can potentially be deployed globally to be gathered in a scalable and low-cost manner.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
HABITAWARE, INC.
SBIR Phase II: New Wearable for Body Focused Repetitive Behavior Detection
Contact
6465 WAYZATA BOULEVARD, SUITE 720
Saint Louis Park, MN 55426--1733
NSF Award
2026173 – SBIR Phase II
Award amount to date
$1,006,258
Start / end date
09/15/2020 – 12/31/2027 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project will help people who suffer from body-focused repetitive behaviors (BFRBs). Over 4% of Americans suffer from skin picking, hair pulling, and nail biting, the majority of whom resort to covering up the problem with makeup, gloves, wigs, and even tattoos due to treatment cost barriers and lack of effective tools to facilitate behavior change. While behavior therapy, and in particular habit reversal training, has shown efficacy, this method is traditionally burdened by unreliable journaling, a lack of access to treatment, and difficulty for patients to perform in real-time because of a lack of awareness. While real-time awareness devices do exist, there is room for improvement in detection accuracy. This project will integrate a novel sensor system into a wearable device that can lead to state-of-the-art detection accuracy of BFRB-related behaviors. This wearable sensor solution is the first of its kind, using the novel sensor to extract meaningful biomechanical information.
This Small Business Innovation Research (SBIR) Phase II project will result in new behavior recognition algorithms, a new remote monitoring system, and new data generated from in-field experiments. The project will: 1) develop a new sensor calibration system and characterize signal artifacts that may influence detection accuracy; 2) develop new behavior detection algorithms using data captured in the lab; 3) conduct self-guided experiments in the field using the remote monitoring system proposed; and 4) refine recognition algorithms. Such sensitive measurements require ideal signal integrity, be sufficiently immune to signal artifacts, and tight electronics integration within wearable design constraints. This wearable system can profoundly impact the efficacy of habit reversal training during cognitive behavioral therapy, the leading method for reducing the negative effect of these behaviors.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
HELIOS POMPANO INC
SBIR Phase II: Detection of High-Risk Lightning Strikes for Wildland Fire Management
Contact
747 SOUTHWEST 2ND AVENUE
Gainesville, FL 32601--7160
NSF Award
2403902 – SBIR Phase II
Award amount to date
$955,736
Start / end date
07/15/2024 – 06/30/2026 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase II project includes a notable reduction in the area burned by lightning-initiated wildfires. Such wildfires are responsible for over 70% of the area burned in the environmental catastrophes in the western United States. Globally, wildfires are responsible for 6.45 Gigatons of CO2 emissions annually (18% of total emissions). This technology can identify a fire in seconds, unlike the present heat or smoke identification products that can take hours or days. This would help in significantly reducing loss of life, habitats, property, and forests. The reduction of wildfires would reduce large evacuations and smoke-related health conditions, thereby improving the health and welfare of the American public. Additional benefits could come for businesses and homeowners from lower insurance rates due to the decreased risk of wildfire damage. If such a technology is implemented in California alone, it has the potential to reduce economic losses by an estimated $84B-$112B per year.
The intellectual merit of this project lies in the ground-based characterization of Extremely-Low-Frequency (ELF) lightning emissions through electrostatic field changes to identify Long-Continuing Current (LCC) strikes, with a 95% target detection efficiency with 40 m accuracy. Long-continuing-currents are those that last for 40 ms or longer and are essentially responsible for excessive heating. Wildfires start when a long-continuing-current strikes the ground at a location where the environmental conditions are conducive for fire ignition. The project will use machine learning algorithms to pinpoint High-Risk-Lightning ignitions, by analyzing the environmental conditions at the LCC strike location. While Phase I has successfully demonstrated the technical feasibility of the ELF-based detection of LCC on a relatively flat landscape, Phase II of the project will focus on research for the technology?s deployment in diverse fire-prone terrains, including hilly or mountainous landscapes, with vastly different topographical, connectivity, and forest conditions, with minimal loss of the lightening detection range.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
HEYKIDDO, LLC
SBIR Phase II: A Parent Coaching App to Help Support Children's Mental, Social and Emotional Health
Contact
123 BECK ST
Philadelphia, PA 19147--3417
NSF Award
2302407 – SBIR Phase II
Award amount to date
$949,863
Start / end date
08/15/2023 – 01/31/2025 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase II project is to empower parenting adults of children ages 5-12 years with the evidence-based tools they need to promote positive mental, social, and emotional health outcomes in their children. Approximately 5.7 million U.S. children between the ages 5-12 are diagnosed with a mental health condition, with an additional 20-60% suspected of being undiagnosed. Despite the importance of early intervention, only about 20% of these children receive treatment. Barriers to care, including access and affordability, become even more glaring in rural areas and in low income and communities of color. Innovative smartphone solutions can reach parenting adults from all backgrounds, as 85% of adults in the U.S. own a smartphone. This project offers an innovative, affordable, and accessible digital parenting solution, built by psychologists, educators, and developmental specialists, that seeks to close the child mental healthcare equity gap, in line with the NSF?s mission. Reduction solutions need to be prioritized to give children a chance at growing into healthy adults.
The goal of the project is to build a parent coaching app, for parenting adults of children ages 5-12 years, that can tailor the content it delivers based on the specific physical, mental, social, and emotional needs of each child and parent. The key technical innovation at the heart of the app is its adaptive algorithms, which allow it to tailor the content journey based on a myriad of inputs. This core technology includes algorithms that deliver developmentally appropriate content suited for each unique family. In addition, the technology allows the app to detect when a higher level of care is needed and provides parents with education on seeking support. Integrating algorithms that track variable input allow the content to change over time, becoming more relevant and effective for evolving needs. This phase of research will be longitudinal and will include a significant sample size of parenting adult users in an effort to examine the functionality and positive impacts of the app, as well as to prepare the app for commercial launch in terms of scalability and security.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
HYPRLIFT, INC.
SBIR Phase II: Hyprlift Vertical Transportation System Prototype
Contact
2010 EL CAMINO REAL
Santa Clara, CA 95050--4051
NSF Award
2232924 – SBIR Phase II
Award amount to date
$999,991
Start / end date
07/15/2023 – 06/30/2025 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercialization potential of this Small Business Innovation Research Phase II project will facilitate the development of the next generation of vertical transportation within the ever-taller skyscrapers of future urban centers. Successful commercialization will enhance the economic competitiveness of the United States in an expanding $26 billion market for elevators with ?smart? technologies. The resulting products will allow building owners to meet their intra-building transportation needs of throughput and ride quality with fewer elevator shafts, freeing up more valuable lettable space within building cores. Aside from this and other value propositions delivered to the target customer segments, these products could reduce urban sprawl and the carbon footprints of buildings that utilize them, enhancing the quality of life for citizens of densely populated cities. Further, technologies developed as part of this project may be applied to other sustainable industries, such as electric vehicles and energy storage.
The intellectual merit includes the development and verification of all core subsystems required for a complete vertical transportation system built around a novel dynamic tractive drive technology. This research will be conducted in four primary phases. First, a revised tractive drive unit (TDU) will be created that repackages the initial proof-of-concept design into a more compact and efficient mechanism that also fully implements both an active suspension and parking brake. Next, a complete elevator cab prototype will be constructed that incorporates four of the new TDUs, a proprietary control system, and all standard off-the-shelf electromechanical systems required for a passenger elevator cab. Third, a lateral transfer station (LTS) prototype will be constructed, which will allow cabs to transfer between adjacent shafts (and thus ?circulate? within a building), a key feature of the eventual system. Each of these subsystems will be validated individually, and these experiments will culminate in the fourth phase of the project: repeated travel of the prototype cab to designated ?stops? with all normal elevator operations, as well as fully-automated LTS docking and transfer.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
HYQ RESEARCH SOLUTIONS, LLC
SBIR Phase II: Incorporating High Dielectric Constant Materials into clinical imaging: A Novel Approach for Accelerating 1.5T Magnetic Resonance Imaging (MRI)
Contact
2151 HARVEY MITCHELL PKWY S STE 208
College Station, TX 77840--5241
NSF Award
2242209 – SBIR Phase II
Award amount to date
$998,104
Start / end date
06/01/2023 – 05/31/2025 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is to provide the basis for advancing magnetic resonance imaging (MRI) hardware solutions for ultra-fast image acquisition. The proposed effort will target clinical MRI scanners where there is limited MRI access by a large patient population. Long scan times reduce the efficiency of radiology department processes and increase the overall cost to clinics and patients. A successful solution which decreases scan times by half will provide improved patient access and care, especially with regard to measuring metabolic activities, brain activity, and cognition.
This Small Business Innovation Research Phase II project will develop high resolution MRI as a powerful tool for understanding metabolic activity in humans and animals. High dielectric constant (HDC) materials provide a low impedance pathway between the patient and magnetic coil of the MRI. The goal of this project is to increase the signal-to-noise ratio of the MRI by over 50%, thereby cutting the scan time by half. The HDC materials will have an immediate impact on animal and human behavior studies where neuroscientists are using MRI techniques to monitor brain activity and cognition. An integrated development approach includes electromagnetic simulation, ceramic processing, and phantom testing. A working prototype will be tested in clinical MRI scanners thus creating an innovative ecosystem comprised of original equipment manufacturers, hospitals, and researchers with clinical experience.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
Heliobiosys, Inc.
STTR Phase II: Scaling the Purification of Mycosporine-like Amino Acids to Replace Chemical Ultraviolet (UV) Filters and Protect Human and Environmental Health.
Contact
16363 SKYLINE BLVD
Redwood City, CA 94062--4438
NSF Award
2222582 – STTR Phase II
Award amount to date
$937,595
Start / end date
04/15/2023 – 03/31/2025 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact of this Small Business Technology Transfer (STTR) Phase II project will be to bring a new class of full spectrum Ultraviolet A and B (UVA and UVB) protective materials to market. Current chemical sunscreen ingredients raise health concerns for consumers. Additionally, some ingredients are banned for causing potential damage to coral reef ecosystems. Consumers increasingly want products that are safe for them and for the planet, and that are aesthetically pleasing. This project will explore ways to meet the growing demand for better sunscreen ingredients that are produced sustainably. This team will investigate methods to cost-effectively extract naturally-occurring materials from photosynthetic bacteria that can replace current chemical and mineral sunscreen active ingredients. These will also replace a significant portion of the UV filter ingredients. Sunscreens and other related products that might use these naturally occurring, safe, and effective ingredients will help people reduce UV damage to their skin and help reduce skin cancer (including deadly melanoma) and ameliorate skin aging. The project supports the US economy by creating jobs in the algae biotechnology field and in the cosmetic industry including testing, manufacturing, distribution, and sales.
The technical innovation at the core of this proposal is to improve the yield and reduce the cost of extracting mycosporine-like amino acids (MAAs) from a complex mixture of compounds contained within cyanobacterial cells (or other MAA producing organisms). Small volumes of MAAs are currently obtained using expensive and hazardous solvents and expensive equipment. The innovation is focused on the use of synthetic nucleotides (aptamers) to selectively bind to the MAAs and purify them from a cell lysate. Mycosporine-like amino acids arose on early Earth to protect microbes from harmful UV radiation. Their prevalence and longevity substantiate their value in protecting cells from UV radiation and other forms of oxidative stress. Their presence in the Earth?s oceans for millennia speaks to their safety in marine ecosystems and suggests their safety for use on human skin; Safety will be verified using standard pre-clinical tests. Technical hurdles include the isolation and identification of the specific MAAs produced, identifying aptamers that are highly specific for the MAAs produced, determining MAA yield from several purification processes and assessing process scalability. These data will be compared to other isolation techniques (filtration and chromatography) to assess comparative yields and economic performance.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
Hyphae Design Lab
SBIR Phase II: Ecosystem Design Tool
Contact
942 CLAY ST STE ACCT2
Oakland, CA 94607--3906
NSF Award
2218499 – SBIR Phase II
Award amount to date
$999,592
Start / end date
02/01/2023 – 01/31/2025 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase II project is to enable communities impacted by air pollution and extreme heat to design and implement solutions to these problems in a fast and cost-effective way. Air pollution increases the risk of cancer, stroke, heart-disease, and respiratory infections, and may play a role in Alzheimer?s and diabetes, resulting in human suffering and trillions of dollars of health care costs globally each year. Extreme heat is a growing source of additional health-care concerns and costs. These costs are shouldered by insurance companies, governments, businesses, and citizens. Air pollution can be reduced by carefully placed trees. These trees also reduce extreme heat by shading and evaporation of water. There is potential for improving human health via targeted engineering of tree placements. This project will develop analysis and design tools to help with such tree plantings to generate the maximum possible health and financial benefits, at the lowest cost and with the shortest timelines. Local businesses can use this tool to make sure that they get paid fairly for reducing health care cost burdens of health insurance companies, governments, and pollution producers, while making communities and the environment more resilient.
While existing literature indicates that trees may provide an effective air pollution and heat-island mitigation strategy. Stakeholders seeking to implement such strategies need tools to ensure that the plantings are as effective as possible. Existing planning tools are not of sufficient resolution or site specific, and often do not employ evidence-based design strategies. This project will perform high resolution vegetation analysis on a wide variety of neighborhoods. This data will be used to train a set of algorithms to infer high resolution vegetation properties from widely available, low-cost data streams. These inferred vegetation metrics will be integrated with a geospatial ecosystem design automation pipeline to create a software tool. The software tool will provide environmental justice communities, ecosystem designers, health insurance companies, governments, and local businesses with the ability to implement cost-effective ecosystem interventions with quantifiable air quality and heat island benefits. These benefits can be used to calculate financial health benefits. Because the benefits quantification will be based on ongoing validation and monitoring projects, the tool can be used to leverage private financing for improving public health and improving the environment.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
IAMBIC INC.
SBIR Phase II: AI-DRIVEN PERSONALIZATION FOR SCALABLE CUSTOM-FIT FOOTWEAR
Contact
1740 BROADWAY, FLOOR 15
New York, NY 10019--4605
NSF Award
2335226 – SBIR Phase II
Award amount to date
$990,900
Start / end date
07/15/2024 – 06/30/2026 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II
project addresses the limitations of mass-produced footwear sizing by introducing size-inclusive bespoke custom-fit shoes. Poorly fitted footwear is an increasingly costly and painful problem with growing human, economic, and environmental implications.
Incorrect footwear fit is a significant driver of foot pain and disorders, including toe deformities, corns,
foot ulceration, and ankle pain. Additionally, e-commerce is on the rise, wherein up to 40% of shoes
purchased online are returned with poor fit as the biggest driver. These reduce retail margins and increase
footwear?s carbon footprint. Custom-fit shoes can solve the problem of poor fit; however, traditional
custom-fit is a labor-intensive process. Advancements in artificial intelligence can modernize and scale
custom-fit shoe manufacturing, potentially reducing price points and lead times.
The proposed project aims to implement an automated solution for custom-fit footwear with three methods: (1) smartphone-based foot scanning and fit survey to obtain foot measurements and footwear construction preferences utilizing artificial
intelligence, (2) automation of shoe last personalization, and (3) adaptive shoe componentry for custom-fit shoe construction.
The project utilizes artificial intelligence and machine learning, 3D modeling, computer vision, and 3D manufacturing to: (i) develop and deploy a highly accurate virtual foot image-to-measurements machine learning model; (ii) expand a shoe
last library to train and implement a machine learning model for foot measurement-to-shoe last
prediction; (iii) manufacture custom-fit shoes by combining personalized last with a compatible adaptive
sole; and (iv) establish a customer feedback system for iterative shoe modification by incorporating user
qualitative responses and sole wear patterns.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
ICTERO MEDICAL, INC.
SBIR Phase II: High Surface Area (HSA) Intraluminal Cryoablation for the Treatment of High-Risk Patients with Gallstone Disease
Contact
2450 HOLCOMBE BLVD
Houston, TX 77021--2041
NSF Award
2214634 – SBIR Phase II
Award amount to date
$966,649
Start / end date
12/15/2022 – 11/30/2024 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project will be the development of the first minimally invasive cryoablation solution to treat high-risk patients with gallbladder disease. The current gold standard for treating gallbladder disease is surgical removal of the gallbladder. While this procedure works well for healthy patients, the use of general anesthesia has been shown to increase complications in elderly patients with underlying chronic medical conditions, leading to a $675 million cost to the US healthcare system each year. Furthermore, patients too sick for surgery have no definitive treatment options, underscoring the need for a safer alternative. Phase I efforts demonstrated the ability to safely deliver cryoablation energy via a minimally invasive catheter system to chronically defunctionalize porcine gallbladders without removal. Phase II efforts will focus on product development of the cryoablation system and optimization of clinical delivery parameters. The goal of the technology is to allow clinicians to provide their patients with the benefits of surgery, without the risk.
This Small Business Innovation Research (SBIR) Phase II project proposes to continue the development of a minimally invasive cryoablation system capable of safely and effectively targeting the gallbladder. Initial testing of the cryoablation system has demonstrated the ability to uniformly generate lethal cryoablation temperatures (<-20?) across the gallbladder lumen, leading to durable gallbladder scarring and defunctionalization in porcine animals up to 60 days post-procedure. Key technical objectives of this project are to develop the industrial design of the introducer, cryoablation catheter, and control system for improved clinical usability and manufacturability, to further test and characterize clinical delivery parameters to inform treatment planning, to improve sensor reliability and control system response time to optimize safety profile, and to validate the integrated system in vivo to demonstrate system performance with optimized dosing parameters. The system will be evaluated in an advanced benchtop model gallbladder under a thermal load, ex vivo gallbladder tissues, and an in vivo chronic animal model to optimize and validate the cryoablation catheter and integrated control system. The anticipated result of this project is a clinically viable gallbladder cryoablation system with established clinical delivery parameters and dosing guidelines.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
IMMERGO LLC
SBIR Phase II: An immersive virtual reality platform for remote physical therapy and monitoring
Contact
250 NATURAL BRIDGES DR
Santa Cruz, CA 95060--5710
NSF Award
2304278 – SBIR Phase II
Award amount to date
$1,000,000
Start / end date
05/01/2024 – 04/30/2026 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II
project concerns greater affordability, accessibility, and accuracy of physical therapy for patients and
therapists. The product to be commercialized will contribute to developing innovation around immersive
telehealth experiences, exploring the future of work for physical rehabilitation in the metaverse,
establishing standards in embodied telehealth, and grounding novel scientific research methods within VR
for healthcare from a California-based startup with the goal of increasing access to care. Establishing a
remote immersive virtual platform will provide a means for in-patient success metrics and full-body virtual
guidance. Patient throughput potentially could be doubled through remote visits in virtual environments
and automated physical health documentation. The platform will be designed with accessibility in mind
with patients from "medical deserts," where patient care is significantly limited by hospital capacity,
physical distance, doctors per population, and cost. Remote physical rehabilitation tools and predictive
physical therapy analytics will benefit patients without adequate insurance coverage. This technology
could lower hospital visits, enable clinics to remain open during future pandemic periods, decrease costs
for patients and clinics alike, and begin detecting physical health needs earlier to help manage the pace
of recovery.
The proposed project aims to expand a novel physical rehabilitation telehealth solution through the
continued research of an instrumented and gamified immersive virtual reality platform for physical therapy
and healthcare monitoring. This technology addresses the shortcomings of widely used telehealth platforms (often videoconferencing) where therapists find it difficult to perform common evaluations
such as movement abilities and balance coordination tests. The solution will expand upon an embodied
telehealth platform with 3D virtual avatars and predictive AI tools to assess user biomechanics in real-time
extending to full-body assessment while providing normative assessment metrics, creating a goal
standard for remote physical therapy care. The development method will continue to utilize user-centered
design with a panel of therapists to ensure accessibility and usability of the prototype systems by their
relevant stakeholders. Such research will incorporate predictive biomechanical analysis to increase the
reliability and repeatability of physical therapy measures and exercise programs for remote monitoring
at the clinic or the patient?s home. Iterative prototyping with user experience will be conducted to
establish in-patient success metrics and full-body virtual assessment. This innovation will enable greater
affordability, usability, and effectiveness of physical therapy for patients and therapists.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
IMPRESSIO INC
SBIR Phase II: Mimicking Metatarsophalangeal Joints Using Tailored, Ultra-Dissipative, Liquid-Crystalline Elastomers to Treat Hallux Rigidus
Contact
7270 GILPIN WAY
Denver, CO 80229--6564
NSF Award
2242770 – SBIR Phase II
Award amount to date
$1,000,000
Start / end date
09/01/2023 – 08/31/2025 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase II project stems from its potential to treat arthritis in joints. This research will be the first investigation into the use of liquid-crystal elastomers (LCEs) for joint repair to treat hallux rigidus. Hallux rigidus (HR) is a joint disorder at the base of the big toe affecting approximately 2.5% of people over 50 years old and roughly 2-3 million people in the US. It is the second most common condition for the metatarsophalangeal (MTP) joint. If successful, this LCE-based MTP joint implant would advance the standard of care in treating joint degeneration and open the way for novel uses of LCEs in the body. The unique nature of LCEs will permit devices to mimic the natural tissues in the body and provide anatomically correct support. In addition to LCE's ability to mimic the MTP joint, other potential advantages may lead to the advancement of patient-specific devices such as treatments for arthritis in other joints in the foot, hand, knee (e.g., total knee replacement), and spine (e.g., total disc replacement). Other soft tissue applications include osteochondral defects (OCD) and the repair of any load-bearing orthopedic tissue such as meniscus.
The proposed project focuses on developing, verifying and validating, and commercializing an LCE-based cartilage replacement device for the MTP joint to treat hallux rigidus. LCEs have superior energy dissipation properties relative to traditional elastomers such as silicone or hydrogels. This proposal seeks to demonstrate how LCEs can be used to treat degenerated joints by combining the fields of liquid-crystal elastomers, rheology, and bioengineering. LCEs are known for their unique behavior which is similar to biological tissues. This project will be accomplished through several main research objectives to support and accelerate the research and development effort: completion of the device pilot production, verification and validation, development of surgical kits and procedures for the device, and transfer of the technology into high volume manufacturing for the commercial device launch.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
INFINID LEARNING LLC
SBIR Phase II: Helping Students Acquire 21st Century Skills Through Immersive Group STEM Simulations
Contact
2230 N UNIVERSITY PKWY STE 6A
Provo, UT 84604--1584
NSF Award
1853212 – SBIR Phase II
Award amount to date
$969,999
Start / end date
04/15/2019 – 01/31/2025 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
This Small Business Innovation Research Phase II project will contribute to the introduction into the educational market of a product uniquely designed to help educators prepare today's students for the challenges of tomorrow's workforce. The ability to think critically and creatively, to communicate effectively, and to solve problems in a collaborative, technology rich environment previously defined 21st Century Skills. New research indicates that in addition to the need for literacy, numeracy, and these advanced cognitive skills, students must also be equipped with social and emotional skills. These social-emotional skills range from self-awareness to empathy for others and from self-management to leadership.
The demand for higher order skills makes it more important than ever for school administrators and teachers to find the answer for students who are disinterested and difficult to motivate, especially in the areas of science and math. Students complain that they are bored and do not see the purpose for what they are being taught; they desire meaningful application for what they learn and the ability to direct their own learning. Designed to address these needs, the proposed program offers students a distinctly different learning experience. The immersive platform gives students the ability to exercise autonomy and a new opportunity to interact and work together. Important life skills come to the forefront as students begin to understand how one's ability to negotiate interactions with others in socially, ethically, and culturally appropriate ways is key to achieving one's goals.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
INFUSENSE LLC
SBIR Phase II: Point-of-Care Electrochemical Platform for the Rapid Detection of Drug Toxicity
Contact
3614C W END AVE
Nashville, TN 37205--2403
NSF Award
2309437 – SBIR Phase II
Award amount to date
$999,852
Start / end date
06/15/2023 – 05/31/2025 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is that poisoning by drugs of abuse affects almost 3 million people annually and is the leading cause of injury-related death in the United States. There were 100,306 opioid overdose deaths in the US in 2021, the majority of which were due to fentanyl poisoning. Screening patients for toxic drug levels currently requires specimen processing in hospital laboratories, taking hours to obtain results. Immediate, accurate detection of fentanyl poisoning at the point of contact, in the ambulance or emergency room, will create a new paradigm for the rapid diagnosis and improved care of poisoned patients and save lives. The SBIR Phase II project outcome will be an FDA-ready, hand-held sensor device capable of accurately measuring fentanyl and other drug levels from a drop of blood or saliva within minutes. The platform device uses disposable sensor strips and is low cost and scalable, permitting broad commercial adoption. Future potential applications for this point of care testing technology include its use by physicians for office-based screening for therapeutic drug monitoring to confirm compliance and optimize medication use and efficacy.
This Small Business Innovation Research (SBIR) Phase II project will test an innovative, prototype biosensor device that provides the user with real time, accurate detection and quantification of toxic drug levels in the blood using inexpensive, disposable test strips similar to a diabetes glucometer. The research to be performed in the Phase II project will utilize electroanalytical methods to optimize the performance of the sensor to improve its selectivity and lowest limit of detection for fentanyl and other drugs commonly associated with poisoning. Additional methods, sensor coatings, and testing conditions will be used to detect total-drug levels in the blood and demonstrate that the biosensor can distinguish between classes of medications and potential clinical interferents as well as show equivalent results to current clinical laboratory methods. The biosensor will detect drugs of overdose and other medications below therapeutic levels, without specimen processing. Pilot large animal studies will seek to validate the correlation of drug levels in the blood with saliva to establish a proof of concept for rapid sublingual testing for drug toxicity.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
INITIUM AI INC.
SBIR Phase II: AI for Enhanced Processing of Digital Conversations
Contact
245 HUNTERS TRL
Ann Arbor, MI 48103--9525
NSF Award
2304322 – SBIR Phase II
Award amount to date
$969,389
Start / end date
09/01/2023 – 08/31/2025 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project lies in its potential to positively impact the sales process by enabling easier, faster, and better access to previous sales conversations and improving sales management oversight. These improvements, in turn, will lead to increased sales efficiency and customer acquisition and retention, and will enable companies to achieve a greater profit margin, while maximizing customer satisfaction. The insights gained in this project may also facilitate communication in other markets including interviews, counseling, etc. The project will diversify the technical workforce by engaging women and underrepresented minorities in research and development activities and will help increase tech-related employment and talent retention opportunities.
This Small Business Innovation Research (SBIR) Phase II project is to significantly increase the productivity of sales representatives and their managers by providing them with advanced technology to streamline their sales processes. The platform developed in this project will significantly reduce the time it takes a sales agent to process or recall their sales conversations, decrease the sales training time through more effective management oversight, and facilitate the transition between sales agents. The platform will use a subscription-based Sofware as a Service (SaaS) business model that provides fast and centralized development and maintenance, while also allowing for a broad outreach. Specifically, this project will develop novel methods and tools to process and analyze sales conversations by: (1) producing summary notes; (2) extracting action items; (3) allowing for smart access to conversation content; and (4) measuring engagement metrics. The project will leverage the recent advances in
natural language processing and a large database of proprietary sales conversations that will allow the platform to learn the intricacies of effective sales communication.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
INNATRIX, INC.
SBIR Phase II: Development of eco-friendly peptide bioprotectant for devastating late blight control
Contact
250 BELL TOWER DR
Chapel Hill, NC 27599--0001
NSF Award
2233590 – SBIR Phase II
Award amount to date
$997,056
Start / end date
08/01/2023 – 07/31/2025 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project will be to control several critical pathogens and pests on multiple crops, in order to help feed the growing world population more sustainably. The global crop pest and disease control landscape is facing big challenges: many diseases are not well controlled and important chemical pesticides are restricted or banned due to their toxicity. There is a critical need for new types of disease control products that will be effective and will not harm the environment or human health. This proposal will lead to the development of a platform that can quickly generate new products to target poorly controlled pathogens, mitigating the development of resistant pathogens. This solution will increase farmers? productivity and reduce their financial losses, while ensuring a more secure food supply.
The proposed project will identify ecologically-safe peptides that will protect crops from diseases. The peptides will be designed to bind to, and interfere with, the function of proteins that the disease organisms produce, and which are essential to the disease process. The peptides will be designed to bind only to those proteins, so they will not have off-target effects. The ability to rapidly design and test such peptides will make it possible to target multiple proteins from a pathogen, reducing the risk that the pathogen will develop resistance. It will also be possible to target a wide range of diseases with similar life cycles, providing farmers with broad protection. The project will choose the optimum target proteins, design the peptides, and optimize the peptides to maximize binding to the targets. The peptides will be tested for their ability to prevent infection in the lab, and then will be produced at a larger scale and tested under the field conditions. The peptides will also be tested for safety as required for regulatory approval.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
INNOGIZED TECHNOLOGIES, INC.
SBIR Phase II: Advanced in-home technologies for infant thermoneutrality
Contact
11240 W WALNUT RIDGE RD
Chesterland, OH 44026--1243
NSF Award
2051808 – SBIR Phase II
Award amount to date
$981,746
Start / end date
07/15/2021 – 03/31/2025 (Estimated)
Errata
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Abstract
The broader impact/commercial potential of this Phase II project will be to empower and educate caregivers to make scientifically guided decisions that enable safer and optimally nurturing sleep environments for infants. Every year more than 130 million babies are born and over 4 million of those are born in the U.S. Due to Sudden Infant Death Syndrome (SIDS), 300 babies every month may not live to see their first birthday. SIDS remains the leading cause of death for babies aged one month to one year. Infant mortality rates in the U.S. are higher than in the 20 wealthiest nations. Innogized Technologies has developed a transformative Internet of Things technology (IoT) that combines hardware and analytics to enable caregivers to make better sleep-time decisions, avoiding overheating, a known stressor for SIDS. The technology guides caregivers to deliver optimal conditions for safe, regenerative and developmental growth for their infants anywhere and anytime, while at the same time relieving anxiety. This technology is poised to immediately capture a sizable portion of the rapidly growing $1 billion US baby monitoring solutions market.
This Small Business Innovation Research (SBIR) Phase II project will support the development of a novel consumer product that works with caregivers to proactively mitigate the risk of under/overheating events in newborns. Sleep-time clothing choices are thermodynamically matched with environmental conditions to create baby-specific safe sleep environments. The temperatures are maintained by leveraging the inherent connectivity of the IoT platform. The technology integrates thermal resistance measurements, thermal models and maps, advanced algorithms, and predictive monitoring. The research objectives of the project tackle the most important remaining technical challenges driving towards successful commercialization and adoption of a product that is essentially an intelligent system, capable of understanding context and tracking and managing complex interactions while anticipating requirements. The technical product of this research will advance caregiver knowledge and increase understanding of the applied thermodynamics leading to the advantageous state of thermoneutrality as well as increase infant wellbeing.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
INSOMA BIO INC
SBIR Phase II: An Injectable Protein Matrix to Enhance the Stability of Autologous Fat Grafts
Contact
701 W MAIN ST
Durham, NC 27701--5010
NSF Award
2304430 – SBIR Phase II
Award amount to date
$979,197
Start / end date
09/01/2023 – 08/31/2025 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact of this Small Business Innovation and Research (SBIR) Phase II Project will improve clinical outcomes for the thousands of patients globally who undergo craniofacial repair surgery each year. Facial disfigurement, whether congenital or acquired, can have profound physical and psychosocial implications including altered body image, reduced quality of life, and poor societal integration. Fat grafting is one of the most rapidly growing procedures in facial reconstructive surgery due to its lack of reliance on foreign or synthetic materials, safe harvest, and minimal surgical risk. While fat grafting has potential to make groundbreaking strides in facial reconstruction, the technique is held back by unreliable volume and shape loss. Craniofacial repairs are particularly challenging for surgeons given the requirement for exquisite control of graft shape and volume. The product supported by this proposal has the capacity to dramatically improve the shape, volume, and survivability of grafted fat. This technology has the potential to not only provide a novel and innovative option for clinicians facing challenging craniofacial cases, but success in this beachhead market will also support the rapidly growing utility of fat grafting in other procedures such as breast reconstruction, amputation site bulking, and hand/foot pad repair.
The proposed project is focused on the development and commercialization of a recombinant, protein-based biopolymer engineered from human elastin to enhance the use of fat grafting in craniofacial reconstruction. This product is one of the first materials to make use of a new paradigm in understanding protein engineering: that highly disordered proteins with defined 3D structure play key roles in the mechanical and biological activity of the body. Using iterative design and molecular engineering of specific protein ordered and disordered domains, the team has generated a new class of biomaterials that are uniquely suited to meet the key criteria for a fat grafting support matrix including: (1) a temperature-dependent phase transition from a liquid to a moldable solid at body temperature, (2) a porous matrix that allows cellular infiltration and supports long-term viability of the tissue in vivo as well as the vascularization required for tissue viability, and (3) enhanced protein stability that allows simple use at the point-of-care with minimal modification to current clinical practice. This Phase II project will focus on core needs for scale-up, toxicity studies, biocompatibility, and large animal efficacy evaluations in preparation for regulatory submission, clinical evaluation, and commercial approval.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
INTACT THERAPEUTICS
SBIR Phase II: A thermogel-based drug delivery platform for the upper gastrointestinal bleeding treatment
Contact
2627 HANOVER ST
Palo Alto, CA 94304--1118
NSF Award
2307164 – SBIR Phase II
Award amount to date
$999,783
Start / end date
05/01/2024 – 04/30/2026 (Estimated)
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project will be to transform the upper gastrointestinal bleeding (UGIB) treatment market. UGIB represents 75% of all GI bleeding cases worldwide and it is one of the leading causes of emergency hospital admission for gastrointestinal complications in the US. Currently, there are no products on the market that can be utilized to quickly stop UGIB prior to endoscopic treatment. Intact Therapeutics? (IT) proprietary thermogel can rapidly stop UGIB due to its faster gelation time, mucoadhesive properties, and ability to deliver clot-promoting drugs topically at the site of bleeding, all without the need for endoscopy. Topical administration of the medications results in lower required doses, improved efficacy, and fewer side effects. Stabilizing the patient without endoscopy reduces the risk of morbidity and mortality, hospitalization time, the need for blood transfusions, and healthcare system costs. The current lack of a pre-endoscopic treatment for the stabilization of UGIB patients will ensure the broad adoption of IT?s thermogel product. Additionally, the range of therapeutics that could be delivered via thermogels is wide: including but not limited to small molecules, peptides, antibodies, and cells.
This Small Business Innovation Research (SBIR) Phase II project seeks to develop a thermogel-based drug delivery platform that combines mechanical and clotting-promoting actions to provide a rapid initial blockade in the upper GI tract and stabilize patients before endoscopy. The prehospital management of UGIB is pivotal to safeguard the conditions of patients prior to an effective endoscopic treatment. IT?s proprietary thermogel?s action is based on two synergistic effects: (1) In-situ gelation (liquid at ambient temperature and becomes a gel when heated to body temperature) provides a mechanical barrier against the blood flow. (2) The slow release of loaded drugs enables complete hemostasis of the haemorrhage site. In this project, the R&D efforts will be dedicated to the further development of the lead formulation identified in the Phase I project and to establish its long-term stability and comprehensive release profile, demonstration of the efficacy of the lead formulation via in-vivo study in a large animal model, and investigation of the pharmacokinetics to establish product safety. The successful completion of Phase II activities will bring the development of IT?s thermogel-based product to the clinical trial-ready stage.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
INTERSPHERE, INC.
SBIR Phase II: Sub-Decadal Weather and Climate Forecast System to Mitigate Risk for Energy and Natural Resource Applications
Contact
320 E VINE DR
Fort Collins, CO 80524--2332
NSF Award
2233387 – SBIR Phase II
Award amount to date
$1,000,000
Start / end date
05/01/2023 – 04/30/2025 (Estimated)
NSF Program Director
Errata
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Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase II project is in potentially reducing the detrimental impacts of weather and climate on the United States energy and insurance markets. To help the American economy prepare further in advance for impactful weather and climate events, this project will develop a forecast system that can translate climate forecasts into likelihoods of impactful weather events. This information will be used to inform the energy and insurance markets of financial risk, particularly within the renewable energy sector where weather and climate control the amount of energy produced. Renewable energy is produced locally within the United States, which means this project will improve the nation?s energy security by informing when and where renewable energy will be most available. Conservative estimates of the technology?s potential include a $2.5 million per year benefit to the renewable energy industry, with a similar multi-million dollar impact to the more general parametric insurance market.
This project will enhance a climate forecast system developed during the company's NSF SBIR Phase I award that issues climate forecasts up to a decade into the future. The enhancements include increased forecast accuracy through automated machine learning model parameter tuning, forecast post-processing, and the translation of the climate forecasts into realistic weather patterns. The technology uses machine learning to identify patterns in the land, atmosphere, and ocean that help determine how the climate system will evolve on timescales of one month to one decade. These climate forecasts will then be translated into realistic possibilities of future weather patterns on daily timescales. These daily weather patterns can then be used to inform renewable energy power production forecasts and extreme weather event risk for numerous industries, including the energy sector and the general insurance industry. A key technical benefit to the proposed forecast system is its high computational scalability, which enables the rapid creation of climate forecasts that are typically produced using supercomputers.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
IONICSCALE LLC
SBIR Phase II: An ultra-compact, remotely programmable chemical analyzer utilizing a novel ion trap mass spectrometer
Contact
501 BOULEVARD PL NE
Atlanta, GA 30308--2886
NSF Award
2409270 – SBIR Phase II
Award amount to date
$1,000,000
Start / end date
11/01/2024 – 10/31/2026 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase II project is that it promises to greatly expand the power of mass spectrometry for chemical detection and analysis to a far broader user base than currently exists. The ultimate goal is to produce a miniaturized sensor package sufficiently affordable that it can be a replaceable component in an ultra-compact, autonomous sensor. This is enabled by a microfabricatable ion trap geometry that circumvents key short-comings of previous chip-scale mass analyzer efforts. The company aims to one day bring this technology to the consumer market where it can inform household residents of harmful trace or odorless chemicals present in their homes. With advances in artificial intelligence and deep learning, the company?s products may also be able to inform household residents of volatile organic compound signatures from their own bodies that might be indicative of the early onset of disease, in a manner similar to dogs? noses that have a demonstrated ability to smell certain types of cancer, Parkinson?s disease, and CoVID-19, among other conditions. Prior to entry into the consumer market, handheld instruments can be leveraged for important in-situ analytics in fields such as defense, energy production, pharmaceutical research, and other industrial and academic applications.
This Small Business Innovation Research (SBIR) Phase II project will enable the development of a novel, patented ion trap mass analyzer and its utilization and commercialization as an ultra-portable chemical analyzer. Mass spectrometers are the gold standard for chemical analysis and have wide ranging applications, however, widespread utilization of these powerful instruments is hindered by their high cost, size, weight, and power. Current portable instruments are ~$100k USD, roughly the size of a small suitcase, and operate for only a few hours on a single battery charge. The proposed innovative ion trap mass analyzer geometry scales down gracefully, enabling microfabrication or other batch manufacturing techniques to be utilized to drive significant cost savings in production to the point where the ion trap can be incorporated in an instrument physics package that is a replaceable cartridge, thus eliminating the need for expert maintenance. Coupled with modern computational methods and processing power, these mass spectrometry-based chemical sensors could be utilized for chemical analysis applications for which mass spectrometry is currently not a cost-effective solution. This goal of ubiquitous, high specificity chemical analysis technology could generate massive amounts of novel raw data informing and creating future collective research and advanced applications/solutions.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
IQInetics Technologies Inc.
SBIR Phase II: An innovative calibration software to suppress torque ripple and improve performance of electric motors.
Contact
3401 GRAYS FERRY AVE
Philadelphia, PA 19146--2701
NSF Award
2233023 – SBIR Phase II
Award amount to date
$989,878
Start / end date
04/15/2023 – 03/31/2025 (Estimated)
NSF Program Director
Errata
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Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase II project will improve the electric motor market and provide the competitive advantage to the US in mobile robotic applications. Electromagnetic flaws in brushless direct current (DC) motors and sensorless controllers have severely limited the performance of mobile robots and stymied the potential growth of the industry. High performance servo motors and motor controllers do exist, but they are too heavy, large, and expensive to be incorporated into many robotic applications, particularly mobile robots. By combining a unique hardware design with a software solution to eliminate intrinsic hardware problems, this project will result in an ultra-compact, high performance, and low-cost electric servomotor. The drone industry is expected to be the first to benefit from the proposed solution, as many commercial and defense drone companies are in need of industrial-grade propulsion components. A superior propulsion solution will accelerate the mass adoption of drones and other mobile robots.
This Small Business Innovation Research (SBIR) Phase II project seeks to create the next generation of drone propulsion technology: an innovative drone motor and controller. Currently, drone companies are forced to use hobby-grade, sensorless motors and controllers, which suffer from poor performance and reliability issues. The Phase II project is rooted in the results obtained during Phase I activities, which led to the development of a calibration suite and a novel motor design. Phase I laid the foundation for creating an ultra-compact, high-performance motor and controller solution that is ideal for drone propulsion. The novel hardware design minimizes mass and production costs and, when combined with the calibration suite and angle compensation algorithm, the solution offers a substantial enhancement in propulsion efficiency, controllability, and reliability. The team will test its product with industrial drone manufacturers to verify its ability to increase vehicle flight time, enhance maneuverability, and minimize critical vehicle failures.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
IRIS LIGHT TECHNOLOGIES, INC.
SBIR Phase II: Foundry-scale production of on-chip silicon photonic light emitters enabled by printed photonic ink
Contact
2307 W THOMAS ST
Chicago, IL 60622--3517
NSF Award
2411435 – SBIR Phase II
Award amount to date
$1,000,000
Start / end date
09/15/2024 – 08/31/2026 (Estimated)
NSF Program Director
Errata
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Abstract
This Small Business Innovation Research Phase II project will develop black phosphorus-based inks to create on-chip embedded lasers, enabling fully functional silicon photonic (SiP) chips. Silicon is the fastest-growing material choice for photonic chip products because SiP leverages the foundry-processing capabilities that have been built for the electronics industry over decades. Currently, the primary laser solution being employed in SiP uses off-chip bonded lasers where system integrators assembling SiP products rely on a cumbersome method of bonding individual lasers to silicon chips. The main on-chip approach, heterogeneous integration of III-V materials bonded to silicon, was developed for a single spectral band for optical communications and is challenging for adoption in broader markets. The lack of a scaled-up method for fabricating multi-spectral band, silicon-compatible lasers is a major unsolved problem for the $1 billion-per-year SiP market. The technical leap envisioned in this effort will be a key enabling technology of photonic chips that will first be supplied to support defense customers and wearable medical sensor developers to generate more physiological data per dollar and drastically shrink the size and weight of such sensors. This will mean smaller, lighter aircraft and flexible, wearable sensors in applications where the size and cost have historically been too high.
The intellectual merit of this project builds upon Phase I results that showed a minimum viable prototype photodiode component with a state-of-the-art photo response of 800 mA/W under 980 nm illumination. This milestone was enabled by a new method for creating inks and ink-printed films with high-quality opto-electronic properties. Importantly, the electronic quality of the inks was increased to commercially viable levels and the current improved to levels on par with commercially available LEDs. While this work established the feasibility of the approach, further technical demonstrations in light emission are required to validate the technology and position it for investment and commercial launch via integration into foundry libraries for use by defense companies, medical device manufacturers, and beyond. In Phase II, photonic inks emitting at 1450 nm will be integrated directly onto a foundry chip to demonstrate critical on-chip laser components demanded by the Integrated Photonics Systems Roadmap (IPSR). This achievement will demonstrate the scalability of the approach and increase the viability of photonic integrated circuits as a platform for developing sensors. Photodetection will also be explored to further expand the impact of ink-printed components. This will close the loop of silicon-based photonic integrated circuits, enabling large-scale production and implementation of this potentially transformative technology.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
ISEECHANGE, Inc.
SBIR Phase II: Real-time Community-in-the-Loop Platform for Improved Urban Flood Forecasting and Management
Contact
4532 BANCROFT DR
New Orleans, LA 70122--1206
NSF Award
2404540 – SBIR Phase II
Award amount to date
$1,000,000
Start / end date
06/15/2024 – 05/31/2026 (Estimated)
NSF Program Director
Errata
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Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase II project is in the potential to transform flood management tools by combining community insights with artificial intelligence to generate information on urban flood dynamics from those experiencing flood impacts. Changing hydrological cycles, sea level rise and inadequate infrastructure have made urban flooding a global issue. This project will improve efficiency and speed of flood responses and design of urban flood management infrastructure by combining disparate data sources including resident posts on local flood and geospatial data on infrastructure and community characteristics. It aims to improve environmental justice by giving residents the ability to report flood incidents and impacts in data that can be used by stormwater managers. By tracking real-time impacts in areas most vulnerable to flooding, which disproportionately affect marginalized communities, it would help cities respond more efficiently to flooding events, prioritize flood adaptation maintenance, and facilitate stewardship to improve the health and well-being of underserved communities. This project serves as a technical platform for novel multi-sector approaches critical for the effective implementation of climate solutions. By engaging directly with the public, the project educates users on local climate risks and mitigation strategies.
The goal of this project is to improve flood incident response and infrastructure planning by cities, counties, and utilities by providing hyper-local community-generated data and artificial intelligence (AI) enabled flood impact insights not accessible with current approaches. The synthesis of multiple forms of environmental and community-generated data into quantitative insights for stormwater managers represents a significant technical challenge. This project aims to fill critical data gaps by developing accurate algorithms for extracting flood height, detailed flood characteristics, personal impacts, and root causes for flooding of all severity levels, as well as methods to aggregate information from different sources and modalities. Combined with an automated prompting workflow, the tool will provide a platform for positive reinforcement feedback for improving the data quality, coverage, and engagement across residents and flood managers in flood prone areas.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
Impactivo LLC
SBIR Phase II: Linking eLearning to patient outcomes
Contact
1606 AVE PONCE DE LEON SUITE 703
San Juan, PR 00909--1827
NSF Award
1926846 – SBIR Phase II
Award amount to date
$750,000
Start / end date
05/01/2020 – 01/31/2025 (Estimated)
NSF Program Director
Errata
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Abstract
The broader/commercial impact of this SBIR Phase II project focuses on improving the management of chronic disease by enabling team-based primary care is key to achieving clinical results and taking advantage of new ?value based" payment reforms. According to the United States Centers for Disease Control, six out of ten adults have a chronic disease and 90% of the national annual healthcare expenditures are spend on people with these conditions. Our technology proposes to apply precision-education instructional theory to enhance primary care team competencies and promote situational awareness, enhanced communication, defined role clarity, improved coordination and leadership support to improve patient outcomes which is directly aligned to the National Science Foundation?s mission of promoting science to advance the nation?s health. This project is being designed for commercial use in Federally Qualified Health Centers (FQHCs) which serve one in twelve people in the United States. There are 1,373 FQHCs in the US serving 27 million patients annually in medically underserved areas. Public and private payment models are rapidly moving toward incentives/bonuses for team-based care and demonstrated outcome improvements. Improvements in the cost and outcomes of care for this patients with chronic disease will have enormous social and economic benefit for the Nation.
This SBIR Phase II project uses machine learning to integrate individual-level clinical and social characteristics into suggested treatment paths and to apply precision training techniques that improve the skills of individual members of the care team. Our objectives focus on validating the feasibility of machine learning to provide health professionals with recommended workflows and continued education based on trends and gaps in care identified from patient data. The method includes a computational engine to guide reinforcement learning. Machine learning has made possible the development of statistical models to establish effect sizes of clinical interventions, enabling personalized instruction and support to health team members based on patient outcomes.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
JELIKALITE LLC
SBIR Phase II: EEG-guided intelligent transcranial photobiomodulation to reduce symptoms of autism
Contact
30 WALL ST STE 811
New York, NY 10005--2201
NSF Award
2415307 – SBIR Phase II
Award amount to date
$959,066
Start / end date
09/01/2024 – 08/31/2026 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project involves developing a personalized home-based treatment for autistic children. Autism Spectrum Disorder is a common neurodevelopmental disorder requiring lifelong management. The prevalence rate is globally rising, with nearly 3% of U.S. children afflicted. A lack of clinically validated solutions places a heavy emotional and financial burden on families with annual costs of care projected to reach $461 billion by 2025. Autism currently has no approved medications or medical device treatments for core symptoms, and the only current treatment is intensive behavioral therapy. This project aims to develop an effective personalized treatment for improving communication, learning, and social skills, thereby increasing individual independence, create new employment opportunities, and reduce government spending on special education and support services. Additionally, it aims to enrich knowledge through personalization, monitoring, and data aggregation of neurological measures for further elucidating the mechanisms of autism and enhancing the efficacy of other therapies.
This Small Business Innovation Research (SBIR) Phase II project aims to develop a non-invasive therapeutic brain stimulation medical device to improve the communication, responsiveness, and social integration of autistic children. The project's objectives are to finalize the current prototype into a manufacturing-ready product, and implement a platform for personalizing transcranial photobiomodulation (tPBM) treatment based on individual sensor derived patient characteristics. The proposed development consists of two main technological components - The first is a wearable device worn on a child?s head that delivers transcranial Photobiomoldulation (tPBM) therapy to reduce autism symptoms based on integrated electroencephalogram (EEG) measures - The second is a software and data platform providing analyzed reports to evaluate intervention efficacy and personalize treatment through machine learning. The anticipated technical results include completion of the final version of the device suitable for clinical adoption and future approval.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
KILELE HEALTH LLC
SBIR Phase II: In-vivo validation of a volume-manufacturable and factory-calibrated wearable NT-proBNP monitoring system for heart failure treatment
Contact
201 E DIXON AVE
Oakwood, OH 45419--3545
NSF Award
2335105 – SBIR Phase II
Award amount to date
$999,758
Start / end date
03/15/2024 – 02/28/2026 (Estimated)
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project will directly address the growing national economic and individual burden of cardiovascular disease as it becomes a reality for more than half of all Americans entering their sixties. Heart-failure is a cardiovascular disease that is particularly challenging given that many patients end up readmitted to the hospital just months after initial hospitalization. Greatly improved outcomes for patients are already possible, keeping patients from returning to the hospital, but only if the patient treatment can be rapidly optimized for the medications prescribed for heart failure. This rapid optimization requires multiple trips back to the doctor for blood tests to guide the treatment plan, adjusting patient medication levels accordingly. Cardiologists have therefore been asking for new technologies to aid their ability to care for heart-failure patients, with an increasing call for remote monitoring technology.
This Small Business Innovation Research (SBIR) Phase II project will create the first-ever wearable, heart-failure monitor for a peptide molecule released by the heart when the heart is struggling, therefore providing a direct and continuous measurement of how well heart-failure treatment is progressing. Specifically, aptamers, which are oligonucleotides, will be used to capture heart-failure peptide molecules on a tiny electrical wire sensor embedded painlessly a few millimeters beneath the skin surface. As these aptamers capture the peptides, they provide a continuous measurement of the peptide concentrations in the form of an electrical signal. The project will create a working prototype that is like the proven success of wearable continuous glucose monitors, leveraging decades of investment in glucose monitors and significant doctor and patient trust in glucose monitors. Under the Phase II project, the wearable heart-failure monitor prototype will be validated for more than one week of operation in an animal model, a key proof point that will enable further commercial investment in developing the wearable heart-failure monitor for human use.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
KISMET TECHNOLOGIES LLC
STTR Phase II: Nanomaterial-based Residual Active Disinfectant for Decreasing Surface Acquired Infections
Contact
2331 BANCHORY RD
Winter Park, FL 32792--4703
NSF Award
2208717 – STTR Phase II
Award amount to date
$995,798
Start / end date
07/15/2023 – 06/30/2025 (Estimated)
Errata
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Abstract
The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase II project is the development of a nanotechnology-based coating to combat the rise in Healthcare Acquired Infections (HAIs). HAIs spread in hospitals through healthcare workers? hands and exposed surfaces. The coating technology developed through this project will disinfect surfaces contaminated with viruses and bacteria. The antimicrobial coating provides protection on these surfaces between cleanings. In the United States, 1 in 25 patients get a preventable HAI from hospital visits. HAIs cost hospitals an estimated $40 billion annually to treat. Commercialization of this technology will lead to fewer preventable illnesses and deaths, while decreasing the financial burden on the healthcare system for each HAI case. Other markets that will benefit from this work include businesses impacted by norovirus (stomach flu) such as cruise ships, restaurants, schools, nursing homes, chip manufacturing facilities, and food processing plants.
This project develops a novel, nanoparticle-enabled coating to combat the rise in HAIs. A novel nanoparticle with a high output of Reactive Oxygen Species (ROS) and potent antimicrobial behavior has been developed. Because the antimicrobial mechanism is a secondary surface reaction, the technology can effectively deactivate viruses and bacteria without being consumed. Phase I demonstrations were achieved using bench top batches of nanoparticles. Phase II research and development creates a manufacturing process appropriate for the synthesis of the novel nanoparticles, creating a shelf stable formulated product, while ensuring the advances in nanoparticle production and formulation do not degrade the nanoparticle's antimicrobial efficacy. The synthesis allows for a decrease in the nanoparticle cost at scale. Shelf stability of the formulated product is important to the overall logistics and supply chain of the product. Improvements to both the scaled synthesis and formulation chemistry will be evaluated for impacts to the disinfection efficacy of the final product.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
Kalion, Inc.
SBIR Phase II: Low-Cost, High-Purity Biobased Glucaric Acid
Contact
92 ELM ST
Milton, MA 02186--3111
NSF Award
1951200 – SBIR Phase II
Award amount to date
$946,155
Start / end date
07/01/2020 – 12/31/2027 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact of this Small Business Technology Transfer (STTR) Phase II project is the low-cost, high-purity biobased production of glucaric acid, a compound with a broad range of applications. This production of glucaric acid will enable a broad change from petroleum-based sources for everyday materials, such as nylon in clothes or PET in two-liter bottles, to a bio-based product generated from renewable resources. Similarly, this technology will allow an evolution beyond the traditional phosphates used in water treatment systems to a safer, cost-effective alternative.
The proposed project will develop a strain, fermentation process, and scalable downstream separation workflow to produce low-cost, high-purity glucaric acid from glucose as a feedstock. Microbial fermentation represents an attractive option for the production of fuels and valuable chemicals from renewable resources, such as cellulosic sugars. Microbes are well suited for the conversion of carbohydrate feedstocks; several examples of their metabolic engineering have been demonstrated to direct these feedstocks to non-natural chemicals and materials of industrial value, often as drop-in replacements for petroleum products. On the other hand, products derived from sugar oxidation pose a new, less explored challenge because of the need to direct glucose into the product pathway rather than the competing path to catabolize the sugar for biomass and energy production. Initial methods, such as deletion of glycolysis and other competing pathways, result in poor glucose uptake because of the cell's complex regulatory circuits. This project proposes to develop strains of E. coli that can efficiently take up glucose while also directing it to the glucaric acid pathway.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
Kapalya Inc
SBIR Phase II: Advanced Ransomware Countermeasure
Contact
1935 ADDISON ST
Berkeley, CA 94704--1354
NSF Award
2304216 – SBIR Phase II
Award amount to date
$994,413
Start / end date
02/01/2024 – 01/31/2026 (Estimated)
NSF Program Director
Errata
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Abstract
This Small Business Innovation Research (SBIR) Phase II project will develop the first universally aware software for ransomware protection with a proactive approach to stop incoming file-based and file-less attacks. The number of ransomware attacks launched globally has grown substantially over the years. To exploit previously undiscovered weaknesses and conduct more effective attacks, cybercriminals take advantage of the rising number of workers accessing business networks from home through a virtual private network (VPN) while working remotely. Current ransomware countermeasure solutions are not comprehensive and generally fail in tackling sustained and persistent attacks. Moreover, the current solutions track threats only at the operating system level and can be disabled. This solution features universal awareness based on a combination of characteristics related to user, ransomware, non-specific environment indicators, and non-ransomware metrics. The comprehensive ransomware detection, remediation, eradication, and data recovery solution enable unmatched protection from cyberattacks and allow timely detection and shutdown of cyberattacks thus, significantly reducing the amount of compromised data. This enhanced protection will have security benefits for a wide range of critical infrastructures, ranging from energy and finances to the protection of medical data.
This Small Business Innovation Research (SBIR) Phase II project seeks to develop an advanced ransomware countermeasure (ARC) platform which will represent the most advanced and effective protection against ransomware attacks. The technology will enforce four synergistic actions: (1) precondition observation and characterization, (2) incoming interactions validation, (3) internal contents observation and characterization, and (4) outgoing interactions validation. In this project, the research and development efforts will be dedicated towards the (1) the development of the framework of communication between the inoculator and watch-dog and its deployment for effective countermeasure, (2) design and development of user-friendly interface providing simple user experience, (3) seamless integration of the ARC platform with existing Security Information and Event Management (SIEM) tools, (4) implementation of artificial intelligence/machine learning models in the ARC platform for the effective defense against zero-day ransomware exploits, and 5) validation of the ARC platform against known ransomware to ensure the proper function of all the modules. The successful completion of the SBIR Phase II activities will deliver a fully functional, commercially viable product with general availability that can seamlessly run/work along with existing SIEM tools and successfully defend against known ransomware attacks and zero-day exploits.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
Kepley Biosystems Incorporated
SBIR Phase II: A Rapid, Sensitive Pathogen Typing and Antibiotic Sensitivity Test for Bloodstream Infections (COVID-19)
Contact
2901 E GATE CITY BLVD
Greensboro, NC 27401--4904
NSF Award
2212920 – SBIR Phase II
Award amount to date
$999,999
Start / end date
12/01/2022 – 11/30/2024 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase II project seeks to develop an improved era of infectious disease management, allowing rapid intervention for antibiotic therapy to stem the 30% mortality rate and associated cost impact of sepsis. With some 49 million cases worldwide and a 25-30% mortality rate, sepsis claims 11 million lives annually. Sepsis cases have been increasing 8.7% per year. To address the full spectrum of infectious diseases, innovations must deliver simple and affordable testing capabilities similar to routine hospital admission blood analyses. The proposed antifungal and antibacterial susceptibility test for the detection and treatment of bloodstream infections could benefit patients by improving patient management and hospital logistics. Sepsis is the most expensive healthcare challenge, with an estimated financial impact of more than $62 billion per year. This bloodstream infection screening assay could impact the entire continuum of care ? from initial hospital interactions through patient care and discharge ? by identifying infections early, optimizing treatment, and increasing survival. Direct customer survey-based estimates and independent information sources project a U.S. commercial opportunity of 226 million annual assays (36 million hospital admissions, 40 million intensive care patients, 130 million emergency walk-ins, and 20 million presurgical evaluations).
The proposed project could result in the development of a user-friendly and affordable analytical tool for early detection of bloodstream infections that differentiates bacterial and fungal pathogens associated with sepsis and determine their antibiotic sensitivity in hours. Sepsis is a major public health and economic concern that results in one human death every 2.8 seconds. If bloodstream infections go undetected or untreated, patients can quickly escalate into sepsis or septic shock with mortality chances increasing by 8% per hour without appropriate antibiotic administration. Rapid and accurate detection of a bloodstream infections prior to the onset of sepsis is critical to limit the extent of tissue and organ damage, mortality, and associated hospital costs. The proposed innovation includes the use of an FDA-approved reagent called Limulus Amebocyte Lysate for clinical bloodstream infections and antifungal antibacterial susceptibility testing to guide therapeutic interventions, and routine surveillance of high-risk patient populations. The technical approach for this Phase II encompasses proficiency studies that would validate high-throughput detection of pathogens, as well as their antimicrobial sensitivity and resistance profiles in clinical blood specimens. Additionally, assay miniaturization and automation would be performed and are considered critical for future in vitro diagnostic partnership adoption.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
Kytopen Corp
SBIR Phase II: An Automated Platform for Rapid Discovery in Cell Biology
Contact
501 MASSACHUSETTS AVE FL 3
Cambridge, MA 02139--4018
NSF Award
1853194 – SBIR Phase II
Award amount to date
$798,461
Start / end date
03/01/2019 – 03/31/2025 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is to develop a fast, efficient, and scalable cell engineering technology that is easily automated through integration with liquid handling robots. Currently, there is a bottleneck in the process of cell engineering, especially in the engineering of cells for discovery of new therapeutics. The field of delivery of genetic or other material to cells has not kept pace with advancements in genetic modification and high-throughput screening technologies. The proposed platform will offer an alternative to the time-consuming and labor-intensive methods of transfection including lentiviral transduction and cuvette-based electroporation, which are difficult to automate. Applications of cell engineering technology range from fundamental research in cell physiology to the discovery of new targets for cellular therapies. The platform will allow scientists and clinicians to more rapidly and reliably engineer immune and other cells for discovery of new therapeutic targets and therapeutics.
The intellectual merit of this SBIR Phase II project will be to develop a scalable, automated, non-viral cell engineering platform with the potential to operate up to 10,000 times faster than conventional electroporation using high-throughput liquid handling. Using the core cell engineering technology developed in Phase I, the goal is to develop an automated protocol for gene transfection on a liquid handling robot compatible with 96 or 384 well plate technology. The first objective is to demonstrate the manufacturability of cell engineering devices for high-throughput cell engineering. Preliminary work in this area has shown that these devices can be injection molded, thus reducing cost while increasing the potential for production at scale. In the Phase II project, injection molded prototypes of the cell engineering devices will be developed to prove manufacturability and determine the cost to manufacture at scale (millions of parts per year). Second, there are several supplemental systems that must be integrated with a liquid handling apparatus to enable the proposed high-throughput cell engineering. Supplemental systems include a power source and power distribution manifold that interacts with each sample of the 96 or 384 well array. In this project, these systems will be integrated with the cell engineering devices and automated liquid handling robot. Third, the integrated system will be used to generate a large library of primary human T cell variants as proof-of-concept to demonstrate the potential for high-throughput cell engineering for therapeutic target discovery.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
LABBY INC.
SBIR Phase II: Artificial intelligence powered optical spectrometer technology for farm-level milk testing
Contact
17 HENSHAW ST STE BA
Brighton, MA 02135--2905
NSF Award
2233881 – SBIR Phase II
Award amount to date
$885,991
Start / end date
09/15/2023 – 02/28/2025 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
This Small Business Innovation Research (SBIR) Phase II project develops a cow's milk testing system using mobile spectroscopy and machine learning to provide rapid and automatic milk testing. The team aims to address the annual $32 billion global loss from bovine mastitis, an udder disease, due to the lack of farm-level early detection technology. The project helps farmers detect mastitis early, allowing them to increase farm operation efficiency, lessen the use of antibiotics, improve animal health, and reduce greenhouse gas emissions. The expanding herd size of dairy farms, shortage of labor, and rising dairy consumption across the globe are driving growth in the global livestock monitoring market which is expected to reach $19 billion by 2030. Globally, the total addressable market size is estimated at $12 billion. The technology under development in this Phase II project will enable precision dairy production by bringing cutting-edge technology to the farm and creating opportunities to attract and retain a new generation of dairy workers. The project?s mission is to support the dairy industry in delivering the best quality milk in an efficient and sustainable way.
The intellectual merit of this project involves on-farm, real-time, and reliable testing of milk components such as somatic cell counts, fat, and protein, using mobile optical spectrometer technology that is controlled by physics-informed machine learning. An improved industrial design of the inline milk testing unit will be developed that is tailored for robotic dairy farms. Additionally, an embedded sampler prototype will be tested in conventional dairy farms to fully automate milk sampling and testing with the goal of developing a universal device that works for most parlor configurations. The operating wavelength range of the devices will be broadened using near-infrared and shortwave-infrared chips, which will not only increase the accuracy of fat and protein measurements but will also expand the testing to components such as lactose and milk urea nitrogen. From the data perspective, time-series measurements of somatic cell counts will be combined with historical herd-level and individual cow-level data such as days-in-milking, lactation, and yield, to build predictive models for mastitis and milk yield. Finally, optical signals such as fluorescence will be used to ascertain the presence of harmful pathogens in milk, to aid in the diagnosis of infections and prevent contaminated milk from entering the supply chain.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
LAMBDA FUNCTION, INC.
SBIR Phase II: An artificial intelligence system for autonomous numerical control programming for advanced manufacturing
Contact
1960 DECANTER CIR
Brentwood, CA 94513--2438
NSF Award
2321728 – SBIR Phase II
Award amount to date
$999,942
Start / end date
09/15/2023 – 08/31/2025 (Estimated)
NSF Program Director
Errata
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Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase II project includes an increase in efficiency and productivity in manufacturing supply chains, which can lead to economic growth, job creation, improved product quality, and reduced waste. The project can also enhance the U.S. industrial base, which is critical to national security by mitigating manufacturing supply chain risks. This technology can provide new learning opportunities for students, facilitate increased partnership between academia and industry, and advance scientific knowledge on precision manufacturing, leading to the development of new artificial intelligence algorithms and techniques with applications beyond manufacturing. The solution will be a step towards addressing the challenge of reshoring manufacturing given the technical skills gap crisis in the U.S. by helping increase the productivity of computer numerical control machinists and sparking greater interest in this field among new workforce entrants. The manufacturing landscape is shifting to more automation, and this solution could help train the next generation of artificial intelligence-augmented machinists. This solution has broad applicability across commerce, government, and academia, in a range of end market applications such as aerospace, defense, and MedTech.
This SBIR Phase II project will result in a fully functional ?beta? prototype of an artificial intelligence-assisted, autonomous, numerical control programming software that can be tested within an operational environment and be near-ready for commercial launch. The end product will be an artificial intelligence-powered software embedded in the computer numerical control programmers? existing workflow environment. The software will provide machining strategy, cutting tool and machining parameters, and tool path recommendations across milling, drilling, and turning operations. By offering these recommendations to the end user (i.e., the numerical control programmer), the product has the potential to: 1) shorten the learning curve for new talent, 2) reduce the degree of variability across skill levels, 3) reduce the time / iterations needed to generate computer numerical control programs, and to 4) increase the probability of generating optimal (i.e., lowest overall machining cost) programs. The product has the potential to significantly increase productivity of the existing and new workforce, while also reducing the non-recurring and recurring costs for precision machining.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
LEARN COLLABORATE INC.
SBIR Phase II: AI-Augmented Mentorship: Bridging Education to Workforce Preparedness
Contact
11220 MOORPARK ST.
Studio City, CA 91602--2659
NSF Award
2420287 – SBIR Phase II
Award amount to date
$999,942
Start / end date
08/15/2024 – 07/31/2026 (Estimated)
NSF Program Director
Errata
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Abstract
This SBIR Phase II project tackles the critical skills gap through Collaborative Project-Based Learning (CPBL). By seamlessly integrating real-world projects with curriculum, students gain essential soft skills like problem-solving, communication, and teamwork, and hard skills relevant to specific industries, making them adaptable across fields. CPBL provides students with authentic challenges through project-based learning enhanced with industry mentors to foster project management and critical workplace skills essential for professional success. Meaningful projects not only boost engagement and understanding but, when coupled with industry partnerships, offer mini-internships and career guidance. Industry professionals further bolster this collaborative environment by sharing their expertise and facilitating team dynamics, providing invaluable mentorship and real-world context to student learning. The software also empowers academic institutions to evaluate and assess student acquisition of these core workforce skills through embedded assessments within the CPBL framework, ensuring graduates are truly prepared for the demands of the modern workplace. This innovative approach bridges the gap between education and workforce preparedness, empowering students with the skills they need for future success.
To bridge the workforce skills gap, this project proposes an AI-powered collaborative project-based learning (CPBL) software platform. We will first establish a baseline by evaluating the platform's core collaborative functionalities ? including group formation, progress tracking, and mentorship integration ? from the perspectives of students, instructors, and industry mentors. This initial evaluation will utilize a mixed-methods approach, combining quantitative data and qualitative feedback. The findings will serve as a crucial benchmark to assess the added value of the AI component once integrated. The platform itself is designed to address the issue of limited practical skill development by enabling instructors to design CPBL activities within their curriculum, seamlessly group students based on skill sets, and track progress. It further integrates industry mentors for real-world guidance and utilizes embedded assessments to evaluate student acquisition of core competencies. Development will leverage both quantitative and qualitative analysis, with real-time user feedback driving iterative improvements throughout. The platform's AI component, distinct from existing solutions, will be designed to model student profiles, provide personalized learning support, and operate with minimal supervision. This innovative approach, measured through a mixed-methods evaluation post-AI integration, will determine the platform's overall effectiveness in promoting skill development, fostering engagement, and preparing graduates for the modern workforce.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
LEARNING NETWORK, LLC, THE
SBIR Phase II: Video Game Tool for Navigating the College Admission Process
Contact
1915 NATCHEZ TRCE
Allen, TX 75013--4873
NSF Award
2402468 – SBIR Phase II
Award amount to date
$989,117
Start / end date
06/15/2024 – 05/31/2026 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase II project will address the critical issue of low college enrollment rates among underserved high school students. With limited access to guidance counselors, particularly in schools serving large minority populations, students often struggle to navigate the complex college preparation, admissions, and financial aid processes. By leveraging the power of gaming technology, this project aims to engage and educate youth about college-going habits and persistence strategies during their recreational gaming time. The innovative gaming system will provide a cost-effective solution to supplement the limited resources available for college counseling at under-resourced middle and high schools. The technology has the potential to become a key factor in the commercial success of the company, with school districts being the initial target market. This initiative not only enhances scientific and technological understanding but also addresses a significant societal challenge by promoting educational equity and increasing access to higher education for underserved communities. Ultimately, this project aligns with NSF's mission to advance national prosperity and welfare by empowering students with the knowledge and skills necessary to pursue post-secondary education and contribute to the nation's workforce.
This Small Business Innovation Research Phase II project aims to shift the college-going culture at under-resourced middle and high schools by developing an innovative video game that educates and prepares students for the college application process. The research objectives are to measure students' knowledge acquisition about college admissions criteria, deadlines, acceptance and enrollment processes, and financial aid options as they progress through the game's levels. The proposed research involves validating and refining the instruments and measures developed during the pilot phase to assess students' readiness based on their performance at each level. The anticipated technical results include a comprehensive set of reliable and valid measures that will enable schools and stakeholders to identify and address students' knowledge gaps, ultimately strengthening their pathways to college. This project is particularly crucial for underrepresented students who often face significant barriers during the college application process. By leveraging the engaging nature of video games, this project offers a unique and transformative approach to democratizing college access. The outcome of this research has the potential to set a new standard for learning solutions and progressive practices in the field of college preparation, providing a scalable and effective model for empowering all students to navigate the complex college admissions landscape successfully.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
LIFENGINE ANIMAL HEALTH LABORATORIES INCORPORATED
SBIR Phase II: Clinical scale and testing of the first virus-free precision gene edited cell therapy for veterinary oncology
Contact
221 1ST AVE SW STE 202-22
Rochester, MN 55902--4504
NSF Award
2243587 – SBIR Phase II
Award amount to date
$973,924
Start / end date
10/01/2023 – 09/30/2025 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase II project is the development of a commercially-ready cell engineering platform that will enable a curative therapy for cancer in the veterinary market. An estimated 250,000 dogs get B cell lymphoma every year. Chimeric Antigen Receptor (CAR)-T cell therapy offers hope for a treatment for this disease. The project platform for engineering CAR-T cell therapy at scale enables the generation of a potential new therapeutic product that is affordable on the veterinary market. The potential societal and commercial impacts of the project have the potential to translate successful therapies from dogs into human cancer care. This solution also offers a new model for the testing, development, and translation of novel CAR-T cell therapies for the human pharmaceutical industry, potentially resulting in benefits to humans as well as dogs.
This project addresses a major bottleneck in the transition from research phase experimentation to clinical and commercial phase manufacturing. During the research phase, cell engineering platforms that process only 5,000,000 CAR-T cells per gene editing experiment or per manufacturing pilot study are sufficient. However, to expand to clinical scale manufacturing and to reach full market scale treatment of 50,000 dogs per year, the ability to make 50-500 doses per manufacturing run is required. Scaled electroporation systems can process up to 500,000,000 cells in a single experiment, a 100x increase from the research phase system. While the scale-up in cell programming reagents is expected to be 1:100, optimization is likely to be required to reach the same or better cell programming efficiencies, while the downstream outgrowth of this scale-up of cells also needs to be optimized in small scale bioreactors. The proposed engineering platform enables engineering of up to 500 doses of CAR-T cell therapy for under $500/dose at full scale.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
LISA FITZPATRICK & ASSOCIATES MD PC
SBIR Phase II: HealthText: Providing digital healthcare navigation for underserved communities in the US
Contact
475 K ST NW UNIT 1112
Washington, DC 20001--5272
NSF Award
2329425 – SBIR Phase II
Award amount to date
$999,904
Start / end date
10/01/2023 – 09/30/2025 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project aims to further develop HealthText, an artificial intelligence (AI) driven digital health information and navigation platform tailored to support the Medicaid population. The project's broader impact lies in its potential to address health disparities in under-resourced communities by providing trusted and relatable health literacy content through a user-friendly Short Message/Messaging Service (SMS). Under-resourced and minority communities often experience poor health outcomes and disengagement from care due to low health and science literacy and distrust. Technology-based engagement strategies have not adequately reached these underserved populations, making HealthText a valuable solution to bridge this gap. The core focus of this project is to deliver targeted and culturally appropriate health information campaigns directly to Medicaid beneficiaries. Through relatable content and intuitive SMS messaging, the platform aims to foster trust, increase healthcare engagement, and reduce avoidable emergency room visits, hospital admissions, and preventable, health-related deaths. The commercial opportunity associated with improving healthcare engagement in underserved and minority communities is significant, given the annual US Medicaid market size of over $720 billion. By addressing health literacy and navigation support issues, this technology can help achieve substantial cost savings that could exceed $100 million annually, while improving health outcomes.
This project has demonstrated successful engagement outcomes among Medicaid populations, suggesting the potential for widespread commercialization to Medicaid insurance companies. The project involves refining the delivery of tailored health information using AI-based communications tools like chatbots and generative AI. Existing AI resources lack consideration for communication nuances prevalent in underserved populations with lower educational achievements. To address this, the AI components will be specifically designed for underserved and minority communities, thereby minimizing concerns about bias in existing health-related AI solutions. The solution include: 1) gap analysis with high priority quality measures; 2) utilization of custom content and delivery platform to send targeted messaging via text, video, and on-demand AI chat to patients; and 3)
evaluation of improved clinical outcomes.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
LITERASEED, INC.
STTR Phase II: Advancing Health Equity using Interactive Condition Assessment and Monitoring
Contact
1220 SAWGRASS CIR
State College, PA 16801--7700
NSF Award
2336417 – STTR Phase II
Award amount to date
$997,693
Start / end date
08/15/2024 – 07/31/2026 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase II
project is to potentially improve patient outcomes and reduce healthcare costs by enhancing communication
between patients and their medical providers. In the U.S., 78.9% of misdiagnoses are caused by
miscommunication, resulting in 80,000 to 200,000 avoidable hospital deaths each year, and 56.3% of
those communication gaps are related to the history-taking during the patient-provider encounter.
Enhancing communication in healthcare is crucial for improving both the efficiency and quality of
healthcare services. LiteraSeed?s project proposes Electronic Health
Record (EHR) integration and Natural Language Processing (NLP) data extraction to enable automated
chart review, facilitating possible access to critical patient data and allowing health systems to reclaim previously
lost revenue due to the misclassification of patient risk.
This project aims to improve the long-term efficiency of our healthcare system by addressing incomplete
and conflicting EHR information, providing alerts of vital medical history, and mitigating the effects of
poor health literacy, all in an effort to help empower the patient.
The proposed project performs Electronic Health Records (EHR) integration of the platform and integrates it with Natural Language Processing (NLP) to extract valuable information from complex and unstructured medical records. These learnings led to the prioritization of three major technical
objectives: (1) EHR integration to simplify workflow and enhance access to patient data, (2) enhancing
the ML/AI risk assessment model by incorporating NLP techniques for extracting valuable information
from complex, fragmented, incomplete, and contradictory medical records, and (3) conducting validation
testing by clinicians to ensure the reliability and efficacy of ML/AI outputs. The integration of NLP for
data extraction, combined with the patient?s self-reporting, ensures a comprehensive and accurate
representation of the patient's present condition and medical history. This innovation could enable
real-time risk adjustment, expedite patient care, address missed care opportunities, and boost revenue
in global capitation and value-based care delivery models.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
LUMENASTRA
SBIR Phase II: A Wearable Non-Invasive Deep Tissue Thermometer
Contact
12416 N 63RD ST
Longmont, CO 80503--9134
NSF Award
2233629 – SBIR Phase II
Award amount to date
$1,000,000
Start / end date
03/15/2023 – 02/28/2025 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project begins with a wearable, non-invasive device providing vital brain and internal organ temperature measurements in a clinical setting that can dramatically reduce mortality and the risk of permanent brain damage for tens of thousands of patients experiencing cardiac and aortic repair surgery. This impact extends to protecting the brain from additional permanent brain injury and lifelong disability for the 4.8 million people hospitalized annually in the US after stroke, cardiac arrest or traumatic brain injury and 1 million infants born with impaired blood-oxygen flow needing constant brain temperature management in their first hours of life. Finally, this technology offers a more consistent and meaningful internal body temperature measurement for millions of consumers through next generation handheld and wearable thermometers monitoring general wellness and providing advanced notice of changes in health conditions. True internal body temperature will be a powerful complement to the inevitable next generation wearable sensors that integrate many health indicators into a comprehensive and actionable snapshot of personal health.
This Small Business Innovation Research (SBIR) Phase II project fulfills the more than 30-year expectation that true internal body temperatures providing a meaningful metric of wellness. Such technologies measure extremely small electromagnetic thermal noise radiated from within the body. Through the intersection of disparate microwave technologies and biological science, this novel wearable sensor became possible. Research challenges include the development of a design methodology for an ultra-low noise receiver utilizing a near-field wearable probe, the discovery of efficient interference mitigation techniques, and the development of an algorithm for accurate and fast temperature estimation, all within a low-power wearable package. This project will develop the needed sensitivity, spatial resolution, and mitigation of the significant microwave noise from GPS, Wi-Fi, cellular and other common electronic sources. After leveraging off-the-shelf components in Phase I, the company is moving to miniaturized and specialized chips to meet the application need.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
LUMINA INSTRUMENTS INC.
SBIR Phase II: Innovative Glass Inspection for Advanced Semiconductor Packaging
Contact
2109 OTOOLE AVE
San Jose, CA 95131--1338
NSF Award
2335175 – SBIR Phase II
Award amount to date
$999,999
Start / end date
03/15/2024 – 02/28/2026 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase II project is to enhance the semiconductor industry. The development of the proposed technology will advance the creation of and reduce the cost of high-quality electronic products such as smartphones, laptops, televisions, AR/VR devices, 5G components, and data storage devices that will be commercially available to individual consumers. This research project will have a substantial societal benefit on the revitalization of the US semiconductor industry by creating more American jobs, boosting national security and reducing the vulnerability of semiconductor devices to tampering and counterfeiting and giving the US a competitive edge in the global market.
This Small Business Innovation Research (SBIR) Phase II project will create technology that will advance the creation of high-quality electronic products that will be commercially available to individual consumers. The increasing use of glass panels for semiconductor packaging presents an opportunity to develop technology which will perform full surface inspection of these panels for defects. No nano-particle inspection technology exists for ?300 mm glass substrates for particles ?300 nm in diameter, such as those used in advanced semiconductor packaging. The successful development of this highly sensitive process control technology will address these glass inspection pain points, with substantial improvements in yield for semiconductor packaging companies.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
LUMO IMAGING LLC
STTR Phase II: Dermatologist-level detection of suspicious pigmented skin lesions from high-resolution full-body images
Contact
10801 PLEASANT HILL DR
Potomac, MD 20854--1512
NSF Award
2335086 – STTR Phase II
Award amount to date
$996,367
Start / end date
03/01/2024 – 02/28/2026 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
This Small Business Technology Transfer (STTR) Phase II project includes early detection of skin cancers, resulting in better outcomes and a reduction in mortality and healthcare expenditures. Each year in the United States, nearly 5 million people are treated for skin cancer, with an annual cost estimated at $8.1 billion. Annual productivity losses are estimated to cost an additional $4.5 billion. There is a considerable health disparity in the diagnosis of skin cancer within the U.S.; The average wait time to see a dermatologist is currently 32.3 days but it varies greatly by location. Early detection reduces disfigurement by reducing the size and extent of surgical removal and reducing the side effects that late-stage patients experience from systemic therapies. Furthermore, the project increases the economic competitiveness of the U.S.
This Small Business Technology Transfer (STTR) Phase II project is to productize a novel, pigmented, lesion analysis system for wide field-of-view images. The product will be built on a previously developed total body photography system and proof of concept lesion classification software as a medical device that was developed in Phase I. The dermatoscope-like resolution provides a solid foundation for a system that can automatically (without the involvement of a dermatologist) detect and classify various skin conditions in a clinical setting and/or a radiology center (similar to how mammograms are done). Skin cancers, including both melanomas and non-melanomas, are the most common types of cancer in the United States. Early-stage identification of suspicious pigmented lesions in primary care settings can lead to improved melanoma prognosis and a possible 20-fold reductions in treatment cost. This technology provides the healthcare system with a highly sensitive, specific, and economical means of providing annual skin cancer screening to all at risk individuals.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
Lapovations, LLC
SBIR Phase II: AbGrab Laparoscopic Lifting Device
Contact
700 W RESEARCH CENTER BLVD STE 1420
Fayetteville, AR 72703--9203
NSF Award
2025984 – SBIR Phase II
Award amount to date
$999,429
Start / end date
09/15/2020 – 09/30/2025 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is a reduction in the negative effects of laparoscopies, procedures to enter the abdomen through a small incision. Over 15 million laparoscopies are performed worldwide each year, particularly gynecologists, who represent roughly half the surgeons performing these procedures in the U.S. The proposed procedure does not require surgeons to alter their surgical techniques and requires minimal training. It uses equipment already in the hospital. The benefits will include better surgical outcomes, decreased patient post-op pain, and increased surgeon and patient satisfaction. Furthermore, it can ultimately be used in other surgical interventions, such as pannus retention, wound management, and liposuction.
This Small Business Innovation Research (SBIR) Phase II project addresses the need for a less invasive and more reliable method for lifting the abdominal wall during laparoscopic surgery. Current lifting techniques include manually grasping the abdominal wall and using invasive perforating towel clips. With manual grasp it can be difficult for the surgeon to maintain grip and proper elevation, especially with lean or obese patients. Alternatively, using perforating towel clips is invasive because the towel clips perforate the abdominal wall tissue to provide a handle by which to lift and elevate. The perforations can be a significant source of post-op discomfort and bruising for the patient. This project focuses on developing a medical device that uses suction to attach to and lift the abdominal wall more reliably than manual grasp and less invasively than perforating towel clips.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
MADISON SCIENTIFIC, INC.
SBIR Phase II: Smart Shunt to Treat Hydrocephalus
Contact
17 SAINT LAWRENCE CIR
Madison, WI 53717--1827
NSF Award
2322905 – SBIR Phase II
Award amount to date
$999,959
Start / end date
09/15/2023 – 08/31/2025 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is the development of an advanced electromechanical cerebrospinal fluid (CSF) shunt system for the treatment and monitoring of hydrocephalus. Hydrocephalus is caused by an accumulation of CSF occurs within the brain, often causing an increased pressure inside the skull. Most shunts used to remove this pressure fail within a few years of placement, often with significant diagnostic uncertainty, which leads to both poorer patient outcomes and higher, often multi-billion dollar healthcare costs. The development of a smart shunt that more appropriately drains CSF and monitors function may reduce shunt failure rates and diagnostic uncertainty, thus reducing healthcare costs and improving patient outcomes.
This Small Business Innovation Research (SBIR) Phase II project advances the development of a smart shunt for CSF drainage. Electronic-based control may improve shortcomings in shunt drainage as the currently used valves are vulnerable to gravity, altitude, activity level, and abdominal pressure fluctuations. The proposed multi-system technology is designed to (1) measure intercranial pressure (ICP) to determine when shunts require drainage, and (2) accurately and intelligently perceives the difference between transient pressure spikes vs. sustained, elevated ICP and respond appropriately (e.g., remain closed vs. drain CSF, respectively). The new technology will further allow patient and physician interaction to obtain on-demand ICP readings, monitor CSF dynamics, and non-invasively adjust valve settings. In this Phase II project, final development testing will be conducted, system performance and safety will be verified, and physician and patient usability will be analyzed.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
MAIJKER CORP.
SBIR Phase II: A Manufacturing Monitoring System Using Sound Spectrograms and Artificial Intelligence
Contact
1041 ONYX ST
West Lafayette, IN 47906--7232
NSF Award
2335395 – SBIR Phase II
Award amount to date
$1,000,000
Start / end date
03/15/2024 – 02/28/2026 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase II project lies in its sound-based AI sensing technology. This innovation is poised to significantly elevate the quality and productivity of our nation's manufacturing sector. Central to this mission is its ability to "listen" to the subtle languages of machinery, translating every hum and rattle into actionable insights. This ensures early detection of potential issues, minimizes downtime, and drives optimal performance. Collaborative tests with large manufacturing enterprises are set to showcase its potential in not only averting costly disruptions but also championing a culture of accurate diagnostics and continuous improvement. The societal implications stretch beyond factories. This technology could be embedded in vehicles, bestowing even age-old models with a modern-day protective insight, or in homes, warding off unexpected appliance mishaps. By unlocking the 'speech' of machines, this SBIR project propels us towards a future where our relationship with machinery becomes more intuitive and proactive. Ultimately, this project is a stride towards a seamless conversation between machines and humans, ensuring enhanced safety, efficiency, and an enriched quality of life for all Americans.
This Small Business Innovation Research (SBIR) Phase II project aims to push the boundaries of machine condition monitoring by harnessing the underexplored potential of internal machine sounds. Merging Industrial IoT (IIoT) with advanced AI, the project crafts a system primed to provide real-time health and status updates for industrial machinery. The innovation's intellectual merit is in its pioneering method of capturing and analyzing internal machine sounds, paralleling techniques used in AI-based speech recognition systems. The project?s mission is to develop a "machine speech" recognition system that decodes the subtle intricacies of machine sounds for humans. This initiative will enhance our understanding of machine operations and introduce cutting-edge predictive maintenance systems, drawing from a largely untapped data source: internal sounds of machines. Mirroring the precision of a medical doctor using a stethoscope to assess human health and fueled by robust neural network models behind human speech recognition, this project represents the fusion of AI and manufacturing. Empowering workers to "tune in" to machine sounds assures a profound understanding of equipment processes and performance nuances. Diverging from traditional solutions that lean on vibration or current monitoring, this sound-centric approach promises a comprehensive view of machine health, marking a pivotal evolution in manufacturing.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
MANUS ROBOTICS INC.
SBIR Phase II: A Novel Human Machine Interface for Assistive Robots
Contact
24 HARTWELL AVE
Lexington, MA 02421--3132
NSF Award
2223169 – SBIR Phase II
Award amount to date
$1,000,000
Start / end date
01/15/2023 – 12/31/2025 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project seeks to benefit more than 200 million people around the globe who are currently living with limb loss or impairment. With the rapid growth of an aging population and longer life expectancies, assistive technologies that can improve the independence and self-sufficiency of people, enabling them stay in their homes longer, are urgently needed. The proposed wearable sensor will be a step towards making robots designed to assist in activities of daily living more effective, affordable, and easy to use. In addition to empowering people to achieve higher levels of functionality and quality of life, this sensor may also further the fundamental understanding of physiological changes as manifested in hemodynamic patterns, which could be used to better monitor patient status and allow clinicians, as well as assistive device manufacturers, to develop more personalized and mindful solutions.
This Small Business Innovation Research (SBIR) Phase II project aims to develop a compact and low-cost optical sensor for detecting gesture commands from disabled users and to translate the gestures to assistive robots. The human-machine interfaces currently adopted by most assistive robots are expensive and inherently noisy, requiring extensive processing and user training. A more practical, intuitive, and reliable solution is needed to better accommodate the diverse and often evolving conditions of end users. This research will focus on enhancing the reliability, usability, and compatibility of the sensor as an embeddable component for wearable assistive robots. Sensor modules that can be daisy-chained together in various arrangements will be designed to optimally monitor different muscle activities on the arm. Advanced signal processing and machine learning techniques will be used to expand the existing gesture detection algorithm and achieve more robust performance during daily device usage, addressing practical issues such as detecting multiple commands simultaneously and enabling long-term algorithm learning.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
MAP-COLLECTIVE, INC.
SBIR Phase II: Development of a Distributed Ledger System to Track Environmental Sustainability
Contact
3030 K ST NW 102
Washington, DC 20007--5156
NSF Award
2223081 – SBIR Phase II
Award amount to date
$925,833
Start / end date
06/01/2023 – 05/31/2025 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase II project centers around its potential contribution to the coordination of climate change mitigation performance of governments, industry, and individuals towards a carbon negative future. The automated system for carbon tracking and visualization that this project is evolving could allow it to network many organizations that are trying to pursue carbon reduction activities on a verifiable map, coordinating otherwise disparate efforts. Regional, national, and global coordination are important as the world attempts to solve the global climate change problem. The proposed platform not only envisions aggregate multisector information on the global level, it allows for collaboration among organizations by sharing carbon goals and decarbonization investments through carbon easements or credits. The solution also contextualizes carbon footprints on the entity or region-level within the planetary carbon usage and planetary carbon boundaries. This visualization tool used for coordination is expected to help accelerate public-private partnerships in the sustainability space, and help organizations collaborate around resource management, and support economic activities and job creation through connectivity.
The technical innovation in this research is the visual coordination of all the simultaneous, multi-level, decarbonization efforts onto one map. Regional coordination remains one of the biggest obstacles to widespread climate action. Even when a county-level climate action plan is pursued, cities within the counties may not implement goals evenly, as there are often inequities in resource distribution. Similarly, there is often a lack of coordination within industries; Companies may have trouble mapping scope data, let alone collaborating with other industries. The project is likely to make collaborations more accessible for companies and governments by visualizing potential partners? goals and trajectories publicly. Companies that provide verified footprints may have advantages of more thorough data, more accurate data, and recommendations offered to them. In this research, the team intends to pursue the development of a carbon negative budget for users, map out past and future carbon usage, automate emissions data uploads, build out maps for internal facilities or assets of a user, and build out a decarbonization model tool for users to explore solution scenarios enabling tokenized on-platform carbon trading.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
MAPLESS AI, INC.
SBIR Phase II: Autonomous active safety systems for verifiably safe operation of ground vehicles
Contact
104 LAURELWOOD DR
Pittsburgh, PA 15237--4033
NSF Award
2240322 – SBIR Phase II
Award amount to date
$1,000,000
Start / end date
06/15/2023 – 05/31/2025 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase II project will result from addressing the gap between the ride hail and vehicle rental markets via the creation of a new, more accessible ?car hailing? mode of transportation. Based on technical advancements in vehicle safety and fleet logistics, car hailing technology offers the potential for direct and desirable social impacts, including: more equitable transportation that can improve quality of life and decrease cost of living; less personal vehicle ownership and less pollution as a result of more efficient vehicle fleet utilization; centralized, managed parking, which could free land for pedestrians, housing, and businesses precisely where it is needed most; and significant job creation due to the need for remote human vehicle operators. These societal and environmental benefits also directly translate into increased economic competitiveness of the United States: more equitable and available transportation for workers enables businesses to compete more successfully in the global markets, and improved quality of life and wage opportunities leads to more productive workers.
This Small Business Innovation Research (SBIR) Phase II project will help enable scalable commercial deployment of vehicle teleoperation technology and services by further developing and improving previous advances in robotics control, perception, and safety engineering. There are two primary objectives for the Phase II research. The first is to develop new techniques and methodologies in safety engineering that will enable the systematic testing and safety assurances necessary for large-scale public road deployments of vehicle teleoperation technology. The second is to revise and improve the novel control and perception technologies developed during the Phase I project to satisfy new requirements derived from the company?s safety engineering advances. The results of the Phase II research will include robotics control and perception capabilities that significantly advance the state of the art, as well as a new set of safety engineering practices and methodologies that could serve as a foundation for the emerging industry of vehicle teleoperation and autonomous vehicle safety.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
MENTE, INC.
SBIR Phase II: Mentelist: Predictive Management of Surgical Instruments
Contact
12 CHANNEL ST STE 502
Boston, MA 02210--2326
NSF Award
2300005 – SBIR Phase II
Award amount to date
$999,981
Start / end date
08/15/2023 – 07/31/2025 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is focused on helping hospitals use data to increase efficiency in operating room resource management. The outcome of this work is a product that could deliver predictive management of surgical instruments; It has the potential to possibly deliver significant direct-to-margin savings to Operating Rooms (OR) at a time when hospitals are struggling to remain financially solvent. This effort may enable hospitals to achieve a 50% reduction in instruments, a 25% reduction in OR setup time, and a 33% reduction in tray weight. It could also reduce instrument-related delays and frustration in the ORs, making surgery safer and more efficient. The technology will establish the commercial viability of a new data stream, enabling applications in predictive OR scheduling, outcomes analysis, and surgical team education.
This project advances the field of healthcare analytics by capturing and applying a data stream that describes how surgery is performed. Every surgical instrument is specialized for a very specific task. This means each time an instrument is used by a surgeon, there is information about their goals, the state of the patient, and the phase of surgery. Under the proposed project, this information is captured by tracking instrument usage. This technology may facilitate a number of predictive tools that can be used to improve the efficiency of the OR and even inform surgical techniques. At a certain level, this application could enable quantification of how the best surgeons in the world deliver care, revealing insights that may not be widely known.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
MFNS TECH, INC.
SBIR Phase II: An Oleophilic Hydrophobic Multifunctional (OHM) Media for Environmental Remediation
Contact
940 QUEENS LN
Glenview, IL 60025--1971
NSF Award
2415632 – SBIR Phase II
Award amount to date
$992,014
Start / end date
09/01/2024 – 08/31/2026 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase II project lies in addressing the critical environmental challenge of water contamination, which poses significant risks to aquatic ecosystems, drinking water quality, and recreational water bodies. Traditional remediation technologies are often unsustainable and generate large amounts of waste. This project aims to develop an innovative solution that is both sustainable and cost-effective. This would enhance the ability and capacity to manage and remediate contaminated water sources. Environmental pollution, particularly water contamination, often impacts marginalized and resource-limited communities due to cost and deployment challenges. The proposed technology addresses these challenges comprehensively. By advancing the technology for sustainable environment remediation, this project aligns with the National Science Foundation's mission to promote the progress of science and secure national health, prosperity, and welfare. The successful implementation of this project is expected to result in substantial environmental benefits and improved sustainable practices. Additionally, the project holds significant commercial potential, as it addresses a widespread industrial need. This could create opportunities for job creation.
The primary technical innovation of this project is the development of a nanocomposite coating with oleophilic (oil-attracting) and hydrophobic (water-repelling) properties that can be applied to any porous materials (such as sponge or foam) for efficient oil capture from water. This novel approach ensures that the absorbed pollutant can be selectively removed and recovered, and the sponge can be reused. The goals of this research include scaling up the synthesis of the nanocomposite while maintaining its complex nanostructured architecture. Also, to validate its multifunctionality via ?mix-n-match? due to its flexible form factor that renders a ?Swiss Army knife? remediation approach for various pollutants, including oil, heavy metals, excess nutrients, and toxic substances. The project will use a vertical integration approach to understand and control factors such as flow rate, reaction time, and nanoparticle nucleation and growth. Large-scale pilot studies will replicate real-world conditions to ensure the practicality of the technology in industrial applications. Analytical characterization techniques will be used to continuously validate the consistency of the nanocomposite properties, ensuring its effectiveness and reliability. Additionally, the project will fabricate a mobile prototype for industrial-scale testing, replicating real-world conditions to demonstrate the technology's easy adaptability.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
MILLIMETER WAVE SYSTEMS, LLC
STTR Phase II: Versatile Low-Noise Traveling-Wave Parametric Amplifier for Quantum Information Processing
Contact
9 RESEARCH DR STE 8
Amherst, MA 01002--2775
NSF Award
2025848 – SBIR Phase II
Award amount to date
$965,773
Start / end date
01/01/2021 – 12/31/2025 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase II project is to advance quantum technologies. Currently, the construction of larger quantum computers, measured by the number of quantum bits or qubits, is hampered by the many wired connections that must connect between the cryogenically-cooled circuits and room-temperature electronics. This project will advance a method to simultaneously boost the weak signals from many quantum bits (qubits) at the same time, and therefore reduce hardware complexity and size. This product will help increase the density of hardware, enabling more powerful quantum computers that will drive new breakthroughs in science, drug development, materials, machine learning capabilities for disease diagnostics, weather predictions, and algorithms for the efficient direction of resources.
This Small Business Innovation Research (SBIR) Phase II project will advance the development of amplifiers for quantum computers. Quantum computers require quantum noise-limited amplifiers for efficient operation, but such devices are not commercially available due to the difficulty in fabrication and lack of universal solutions. This project will develop specialized amplifiers that can be fabricated in commercial foundries for deployment at scale. The technology uses an innovative arrangement of superconducting elements to form a novel amplifier. This process will be tolerant to manufacturing variations to enable production at scale.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
MINERALOGIC LLC
SBIR Phase II: Predictive Tools for Characterizing Carbon Sequestration in Mined Materials
Contact
3371 W TISCHER RD
Duluth, MN 55803--9786
NSF Award
2212919 – SBIR Phase II
Award amount to date
$998,806
Start / end date
02/15/2023 – 01/31/2025 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is to fully realize the potential for weathering of mine waste to remove carbon dioxide (CO2) from the atmosphere. By helping mining companies in this effort, this project will positively impact human health and welfare while potentially producing a competitive advantage to the domestic mining industry. The project implementation been designed to maximize positive broader impacts including developing a future workforce and improving public scientific literacy through deliberate public communications on geochemical weathering, carbon emissions, and climate change.
This project advances the characterization of carbon mineralization potential of mined materials by incorporation of a novel framework for conceptualizing silicate mineral weathering and a custom test apparatus for direct measurement of carbon mineralization rates. A working prototype geochemical model was developed in SBIR Phase I to simulate enhanced rock weathering of representative mine waste. The prototype predictive model reflects the unique chemical and surface characteristics of mine waste through incorporation of novel kinetic modules and opportunistic parameterization methods. While this product represents an advance over existing geochemical reactive transport codes, it is most effective as a screening tool. In order to advance from screening for carbon mineralization potential to optimization of carbon mineralization strategies, this Phase II project will develop an innovative test apparatus and related methodologies for carbon mineralization characterization. The design of this test method flows from preliminary application of the Phase I predictive model and the results feed back into refined parameters that are needed to meet industry requirements for design basis precision. The test apparatus and model will be deployed to demonstrate the utility of this new service to the mining industry and other stakeholders.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
MODENDO INC.
SBIR Phase II: Ultrathin endomicroscope
Contact
1815 BLUEBELL AVE
Boulder, CO 80302--8021
NSF Award
2415645 – SBIR Phase II
Award amount to date
$994,138
Start / end date
08/15/2024 – 07/31/2026 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is to empower brain scientists with a high-resolution optical imaging instrument to reach currently inaccessible regions of the brain with minimal damage. There are compelling reasons to conduct animal neuroscience research, including improving our understanding of biology, investigating the brain in action, and most importantly developing new therapies for diseases affecting the brain. Animal neuroscience research contributes to studying potential new treatments for mental disorders like Alzheimer's disease which, according to estimates, will affect more than 10 million people in the US by 2050. The availability of novel neuroscience imaging probes for animal studies could have a significant impact on the development of therapies and drugs to tackle mental disorders. The proposed imaging approach will enable high-impact instrumentation for biomedical applications by advancing neuroscience through animal model studies.
This Small Business Innovation Research (SBIR) Phase II project will advance the design, optimization, and validation of a robust and compact commercial endomicroscope prototype instrument that is amenable for use with animal models in neuroscience labs. The company?s key innovation is in achieving the fundamentally thinnest mechanism to acquire and transmit a high information content image in real time. The ultrathin endomicroscope has a cross-area more than ten times smaller than the thinnest existing endoscope. Current solutions are appropriate for insertion in large cavities but they produce excessive damage in applications such as deep brain imaging. Furthermore, the ultrathin endomicroscope enables multiple 3D imaging modalities with micrometer resolution as well as arbitrary laser pattern projection for photo-stimulation. The objective is to develop a new class of fundamentally less invasive techniques and to validate a prototype instrument in animal models. It is anticipated that in-vivo imaging of neurons with subcellular resolution at depth will become routine with minimal tissue damage.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
MOLTEN SALT SOLUTIONS, LLC
SBIR Phase II: Enhanced Lithium Isotope Separation
Contact
3900 PASEO DEL SOL STE D33
Santa Fe, NM 87507--4072
NSF Award
2233542 – SBIR Phase II
Award amount to date
$1,000,000
Start / end date
05/01/2023 – 04/30/2025 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase II project is a new domestic commercial source of enriched lithium isotopes. The U.S. nuclear power industry requires enriched lithium-7 hydroxide to prevent corrosion in its present fleet of pressurized water reactors. Currently, this strategic material is supplied outside the U.S. and recent supply disruptions jeopardize 20% of the U.S. electrical generation capability. Longer term, the development of safer, lower-impact, new technologies for nuclear power generation is critical to meet the U.S. and global goals of reducing carbon emissions. One of the most promising technologies, molten salt reactors, will require commercial production of large quantities of enriched lithium-7. Even longer term, many of the fusion energy technologies in development will require enriched lithium-6. The planned production of lithium isotopes will enable the development and commercialization of safer, lower-impact nuclear energy.
This Small Business Innovative Research Phase II project proposes the implementation of a liquid/liquid extraction method for lithium enrichment in a pilot-scale production system. To date, this type of extraction has not been employed for commercial lithium isotope enrichment. The Phase II work will result in the design of the first commercial-scale production process. The innovative approach to lithium isotope enrichment will also have applicability in the purification of other stable isotopes.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
MONSTR SENSE TECHNOLOGIES, LLC
SBIR Phase II: Rapid-scanning Ultrafast Imaging Microscope for Material Inspection
Contact
3830 PACKARD ST
Ann Arbor, MI 48108--2053
NSF Award
2208201 – SBIR Phase II
Award amount to date
$1,000,000
Start / end date
01/01/2023 – 12/31/2025 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
This Small Business Innovation Research Phase II project will address the widespread industry challenge of improving yield in compound semiconductor device production. Compound semiconductors with a wide bandgap are needed for high power devices in electric vehicles (EVs), high frequency components in 5G electronics, and energy-efficient displays. The compound semiconductor market, valued at $36+ billion in 2022, has increased recently with growing consumer demand for EVs. The annual growth rate of silicon carbide (SiC) semiconductors, the most prominent devices, is estimated at over 20%. Despite the wide-scale production of these components in an industry that expects near perfection in manufacturing, the current yield of power electronic components is less than 50%. Poor yield results largely from an inability to adequately inspect substrates and epitaxial wafers used for power electronics. Instead, the industry currently relies on inspection tools with poor defect selectivity or destructive methods that can only provide statistical information about the defects in a wafer batch. To increase wafer yield, the team will develop a new type of optical inspection tool for selectively measuring defects in every wafer. If successful, this novel inspection technology will enable the industry to help drive down costs and increase performance of energy-efficient power electronics.
The intellectual merit of this project is the novel way in which technology developed for use in fundamental science is being applied to rapid semiconductor inspection. The proposed method, called ultrafast imaging, uses the nonlinear optical response of a semiconductor induced by an ultrafast laser to isolate defects that measurably impact the electronic structure of the semiconductor. Though the semiconductor industry has typically focused on measuring morphology to find defects, measurement of compound semiconductors requires a tool that is sensitive to the electronic structure. This project will validate ultrafast imaging through benchmark testing against industry standards and develop an easy-to-use device for getting this technology into the hands of manufacturers. Partner manufacturing and inspection companies will provide inspection data and corresponding wafers, allowing correlation of ultrafast imaging defect measurements with data provided by other industry tools. Additionally, the team will develop and demonstrate an easy-to-use commercial product for user facilities and industrial research and development facilities, another essential step in the development of a high-throughput inspection tool. This benchtop product will not only improve current semiconductor technologies but will also be useful for scientists to characterize the next generation of semiconductors.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
MSTATT LLC
SBIR Phase II: Brillouin Microscopy for Early Detection of Dental Caries
Contact
11201 CEDAR AVE STE 725
Cleveland, OH 44106--2606
NSF Award
2212766 – SBIR Phase II
Award amount to date
$997,400
Start / end date
01/15/2023 – 12/31/2025 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project will be to facilitate effective use of tooth remineralization treatments by introducing a new tool that is both highly sensitive to demineralization and robust to confounding factors. If patients are compliant with the generally recommended dental visit schedule of twice a year, it is conceivable that the patient may never need to have a primary filling again. This change in practice has significant patient, dentist and broader economic benefits. The remineralization treatment may increase the number of patients who visit their dentist on a regular basis as they can avoid dreaded fillings. The savings from reducing the time spent on primary filings will provide dentists with the opportunity to take on new patients and procedures, while reducing more mundane drilling activities.
This Small Business Innovation Research Phase II project will build on the technology developed for early dental caries detection and will develop the technology for clinical use and evaluation by dentists. This technology will enable dentists and hygienists to diagnose caries earlier than previously possible, enabling early treatment, and significantly reducing the amount of drilling in dentistry. This Phase II project will develop a probe designed for use in dental offices, a miniaturized and a ruggedized Brillouin spectrometer. The project will also conduct lab and user testing, develop software, and develop a scientific version of the spectrometer. At the end of this Phase II effort, a validated prototype that will be ready for a clinical trial is expected.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
MUUKLABS INC.
SBIR Phase II: Artificial Intelligence Powered Software Testing
Contact
400 W NORTH ST
Raleigh, NC 27603--1568
NSF Award
2223011 – SBIR Phase II
Award amount to date
$971,804
Start / end date
05/01/2023 – 04/30/2025 (Estimated)
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader/commercial impact of the Small Business Innovation Research (SBIR) Phase II project reduce the cost and speed of software quality assurance (SQA) end-to-end testing by enabling artificial intelligence (AI) to automate tests without the need for coding or highly experienced coders. As innovative high-growth Software as a Service (SaaS) companies go to market faster with more confidence and fewer software defects, industries will benefit economically by saving time and money.
This SBIR Phase II project will build an AI solution which, although used by less experienced software engineers, will allow software companies to identify software defects with minimal user interactions. The real-time and guided process gathers information directly from the web browsers, handling traditional and unresolved problems with test automation such as software test design, automation, coverage, and maintenance. The AI solution will make SQA highly efficient by performing two major tasks: simulating real-time users' exploration of web applications and identifying unexpected behaviors. The architecture enables AI agents to self-learn and interact with the application, improving on each observation. The AI learning cycle implements thorough communication within the system as it communicates requests to apply specific actions based on its own knowledge analyzing the resulting effect. Phase I research proved that the architecture can be upgraded to a commercial version, providing value to customers looking to improve software quality in their products and go to market faster. The anticipated technical results in Phase II will enhance the categorization of unexpected software behaviors, optimize the data analysis time, and reduce the learning cycle.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
Mechanismic Inc.
STTR Phase II: A Design-Driven Educational Robotics Framework
Contact
133 VILLAGE HILL DR
Dix Hills, NY 11746--8335
NSF Award
2126882 – STTR Phase II
Award amount to date
$1,000,000
Start / end date
09/15/2021 – 08/31/2025 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact of this Small Business Technology Transfer (STTR) Phase II project is in teaching K-12 and college students STEM concepts in the fun-filled context of designing, building, and programming machines and robots and preparing them for the future technology-driven jobs. This project seeks to make robotics education affordable, equitable, and inclusive for students at all grade levels. By taking a multi-disciplinary and cross-curricula approach, the product developed through this project engages students, especially women and minorities from diverse backgrounds, effectively in STEM disciplines and helps them make suitable career choices. The ultimate goals of this project are aligned with the NSF's mandate to support development of a strong STEM workforce and help fill the 2.5 million STEM jobs that are vacant according to the current US Department of Labor Statistics. The technological innovations emerging from this project would result in a computational tool for synthesis of robot motions, which can be used broadly in industrial automation and invention of machines and robots. The proposed design-driven educational robotics product has the potential to improve engagement with science and technology and positively impact the U.S. educational robotics market, which is expected to grow to $2.7 billion by 2021.
This Small Business Technology Transfer Phase II project aims to bring together rigid body kinematics, machine learning, and engineering design to create a new product for design-driven robotics education for K-12 schools, freshman college programs, and STEM camps. The leading commercially available educational robotic systems emphasize 1) instruction-driven prototyping of robot structures using many specialized parts, and 2) programming them without providing any intuition behind the design process or guidance to creating mechanism design concepts for the realization of the motion of the robots. Driven by a need to keep pace with the evolving techno- and socio-economic requirements, new science standards, and remain competitive, schools and camps are increasingly adopting STEM and Robotics programs and products. This product would fill that void that currently exists in the educational market. If successful, this project would result in a state-of-the-art motion design software, a novel hardware kit, and standards-aligned curriculum and learning resources for schools and colleges. The software based on the machine learning in mechanism design research will allow creation of robot assemblies and their motions before constructing their corresponding physical models and provide students necessary skills and experience in the design process.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
Metalmark Innovations, Inc.
SBIR Phase II: Nanostructured 3D Catalytic Coatings for High-Efficiency Pollution Control and Air Purification
Contact
127 WESTERN AVE
Allston, MA 02134--1008
NSF Award
2026128 – SBIR Phase II
Award amount to date
$1,198,136
Start / end date
08/01/2020 – 12/31/2025 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is addressing the growing societal need for indoor air purification, as indoor air quality (IAQ) directly affects human health, productivity, cognitive function, and quality-of-life. Awareness of the long-term consequences of poor IAQ has recently witnessed an increase due to research results, improvements in monitoring and sensing technology, public awareness campaigns by organizations such as the American Lung Association, World Health Organization, and Environmental Protection Agency, and, most recently, the COVID-19 pandemic. Finding sustainable, economical, and effective solutions to the problem of poor IAQ will greatly benefit public health and wellbeing and will help curtail the spread of pathogens, minimizing the need for social distancing. This project will develop a new system air purification, addressing viruses, harmful chemicals, odors, and ultrafine particulates.
This Small Business Innovation Research (SBIR) Phase II project aims to scale up the production methodology and coating process of novel catalytic materials. The materials are 3D nanostructured porous powders that are designed at multiple length scales to achieve enhanced catalytic activity, stability, and longevity, while reducing costs and utilizing raw materials in an environmentally responsible manner. The system uses a synthetic approach based on self-organization of nanoscale building blocks and wet chemistry tools in order to assemble finely structured coatings for integration in air-purification units. This project focuses on expanding it to production scale, wherein achieving control over the composition, structure, porosity, and placement of nanoparticles on a production scale is challenging. The materials platform development will include adaptation to high-throughput instrumentation and scale-up of the material production and coating process to pilot production. In the process, this project will develop tools and guidelines for manufacturing hierarchically-structured functional materials more generally.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
Microgrid Labs Inc.
SBIR Phase II: Intelligent Planning and Control Software for EV Charging Infrastructure
Contact
903 GROGANS MILL DR
Cary, NC 27519--7175
NSF Award
1951197 – SBIR Phase II
Award amount to date
$949,881
Start / end date
05/01/2020 – 01/31/2026 (Estimated)
NSF Program Director
Errata
Please report errors in award information by writing to awardsearch@nsf.gov.
Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) project is to develop a modeling, simulation and optimization software for fleet electrification projects. Electric vehicles (EVs) are expected to comprise 70% of all new buses and 15% of all commercial trucks by 2030. Electric vehicles are more expensive than diesel buses and need additional investments in charging infrastructure; furthermore, electrification is complex as several factors influence its design, cost and performance. The transition from diesel to electric buses could impose significant loads on the local electrical network, entailing significant upgrades to the electrical infrastructure at the facility and the utility grid. The proposed software will offer the electric vehicle industry a platform to analyze the battery, charging infrastructure, and energy infrastructure.
This Small Business Innovation Research (SBIR) Phase II project addresses the problem of planning and operating electric vehicle fleets, especially medium and heavy-duty fleets. The technology uses stochastic optimization and discrete event simulation to optimize fleet sizes to minimize costs and meet operational requirements. The proposed work will create a model of the joint transportation and energy processes (i.e., the driving and charging processes). The proposed software will enable real-time optimization of system operations.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
NALA SYSTEMS, INC.
SBIR Phase II: Chemically Resistant Membranes for Water Purification
Contact
2 DAVIS DR
Chapel Hill, NC 27516--4654
NSF Award
2038543 – SBIR Phase II
Award amount to date
$999,437
Start / end date
05/01/2021 – 07/31/2025 (Estimated)
NSF Program Director
Errata
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Abstract
This SBIR Phase II project will develop breakthrough polymeric membranes to purify water by reverse osmosis. It will address the recognized global need for clean drinking water driven by increasing population and urbanization that affect billions of people living in water-stressed lands. The impurities in water from different geographical locations and different types of water (e.g., seawater, industrial wastewater, tap water reuse) differ, and separation membranes that can selectively remove different combinations of impurities will be critical to addressing this world challenge. The technology provides a means to greatly eliminate costly cleaning operations and minimize plant downtime in this ~$5 billion market. Industrial and Enhanced energy and operating efficiency will be achieved through reduced required pretreatment and enhanced fouling resistance, leading to extended use cycles and improved water flux over the lifetime of the membranes.
This SBIR Phase II project will produce thin film composite reverse osmosis (RO) membranes comprised of precisely sulfonated polysulfone polymers in the ~100-nm thick range on a porous support. These novel membranes will provide a long sought after revolution in water purification membranes with their high resistance to chlorine for disinfection and ability to prevent biofouling. For the first time, they will also efficiently remove monovalent salts that contaminate seawater and brackish water from their mixed salt compositions. Sulfonated polysulfones have been considered previously for RO membranes due to their inherent chemical resistance, but they failed due to low salt rejection at high ionic strengths and their inferiority in salt rejections in mixed salt feedwater. Municipal water requirements are high and their process water is often contaminated with toxic products (boron and arsenic moieties, hydrocarbons, perfluorinated surfactants, biofilms), making reuse difficult to impossible technically and economically. This project advances material synthesis and material processing through precisely sulfonated polymers. Phase II will take advantage of these advances to optimize the membrane coating process, scale it to pilot quantities, and measure resistance to a range of impurities found in tap water reuse, industrial water purification, as well as in purification of brackish surface and groundwater and highly saline seawater.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
NANOPATTERN TECHNOLOGIES, INC.
SBIR Phase II: Photopatternable Quantum Dot Downconverters for Microdisplays
Contact
1452 E 53RD ST
Chicago, IL 60615--4512
NSF Award
2052728 – SBIR Phase II
Award amount to date
$999,428
Start / end date
09/01/2021 – 10/31/2025 (Estimated)
NSF Program Director
Errata
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Abstract
This Small Business Innovation Research (SBIR) Phase II project seeks to demonstrate product-scale properties of photo-patternable quantum dot (QD) inks. These include: 1) scalability, 2) long lifetime under device operation, and 3) compatibility with display manufacturer protocols and facilities. Following the demonstration of these parameters, the ink can be commercialized in partnership with a large chemical manufacturer for global distribution. The photo-patternable QD ink is a novel product that will enable display manufacturers to produce the next generation of high color gamut, triple energy efficiency, and high refresh rate displays for consumer electronics (e.g. TVs, monitors, laptop screens, smartphones, wearables, and virtual reality and augmented reality headsets). Such an ink can broadly impact an $8.4 billion market by 2024 by simplifying the manufacturing and improving the performance of organic light emitting diode (OLED) and micro light emitting diode (microLED) displays recently announced by companies such as Apple, LG, BOE, and Samsung. Furthermore, the efficiency improvement in displays made by the project?s success could reduce carbon emissions by as much as 110 million tons of carbon dioxide equivalent (MTCO2e), contributing to broader environmental impacts.
The intellectual merit of this project focuses on converting a ligand chemistry into an ink product by demonstrating performance at production scale. The intended product is a photo-patternable QD ink that enables high resolution patterning of red and green QD downconverters to enable a tri-color display with excellent color gamut, energy efficiency, and refresh rate. To date, resolution and conversion efficiencies meeting customer requirements have been demonstrated for the ink at the film level. In this project, the focus will be on the end product - a functioning display enabled by this ink technology. To accomplish this, the project objectives are: 1) to develop lifetime metrology tools and techniques; 2) to develop a protocol and demonstrate the film lifetime simulating device conditions; 3) to scale the ink formulation to 20 L/y to enable a sufficient number of tests; and 4) to produce a prototype at production scale with an industry collaborator. The successful completion of these objectives will yield a working display device that is enabled by the QD ink product. A demonstration of a device is critical evidence to engage customers and convince them of the compatibility of the ink with their product.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
NANOXORT LLC
SBIR Phase II: Novel size-changing, gadolinium-free contrast agent for magnetic resonance angiography
Contact
540 DEVALL DR STE 101-1A
Auburn, AL 36832--5888
NSF Award
2322379 – STTR Phase II
Award amount to date
$999,676
Start / end date
09/01/2023 – 08/31/2025 (Estimated)
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project will provide a tool for vascular imaging, an area of medicine with a large clinical need. The developed blood pool contrast agent (BPCA) has the potential to disrupt the current magnetic resonance angiography (MRA) contrast agent market because of its improved safety profile and enhanced imaging of the vascular system compared to current gadolinium-based contrast agents (GBCAs). The proposed technology has the potential to improve the diagnosis and safety of contrast-enhanced MRA. This creates a win-win-win scenario for everyone involved. For patients with vascular disease, this solution provides a safer alternative with a more accurate diagnosis that will allow doctors to prescribe safer, more effective treatments. For the patient?s family, it reduces financial and social burdens by enabling preventive treatment due to earlier disease detection. For radiologists, the clearer MRA images may lead to more accurate diagnoses. The product will be marketed to radiologists and medical institutions that perform MRA to diagnose vascular thrombosis, renal stenosis, and pediatric MRA.
This Small Business Innovation Research (SBIR) Phase II project seeks to optimize an iron-based BPCA for use in MRA for the detection of vascular diseases. Contrast-enhanced MRA is a staple diagnostic procedure for imaging blood vessels. The market is currently dominated by gadolinium-based contrast agents (GBCAs) due to their excellent contrast enhancing effects; however, due to their potential toxicity, GBCAs are designed to be rapidly cleared, leaving only a short window for MRA image acquisition and resulting in suboptimal image quality of blood vessels. To address the need for a safer contrast agent able to provide enhanced vascular imaging, the Phase II project will optimize an iron-based contrast agent that will enable an extended imaging window for improved MRA resolution, but which is removed by kidney filtration. The research objectives include: (1) optimizing the minimum viable product to enable dose reduction and enhance the safety profile; (2) evaluating diagnostic imaging efficacy and toxicology; and (3) demonstrating a scale-up manufacturing process for the synthesis of the final formulation. This solution addresses the major points required to de-risk commercialization and bring the technology closer to the market.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
NASUS MEDICAL INC.
SBIR Phase II: Development of a Novel Miniature Spray Mechanism for Nasal Drug Delivery
Contact
245 W 2ND ST
Mesa, AZ 85201--6503
NSF Award
2410803 – SBIR Phase II
Award amount to date
$999,926
Start / end date
08/15/2024 – 07/31/2026 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is developing an innovative, noninvasive drug delivery technology for treating chronic sinusitis (CRS), a condition characterized by chronic runny nose, congestion, facial pressure, and loss of smell. CRS affects ~10% of the US population, annually costing $8-12 billion in direct healthcare costs and ~$5 billion in lost productivity. By optimizing drug delivery to the target nasal anatomy, this technology can enhance health outcomes and quality of life for millions. The device allows patients to self-administer nasal spray deeper in the nose, improving drug delivery and adherence compared to current costly and problematic treatments such as oral steroids and invasive sinus surgery. By providing faster, improved symptom control and reduced need for invasive procedures, this solution will reduce the CRS-associated economic burden. Moreover, the research will yield a noninvasive delivery platform technology with potential therapeutic applications that include migraine, seizure, and vaccines. Partnerships with industry leaders will facilitate commercialization; collaborations with key opinion leaders and insurance providers will drive adoption and demonstrate health economics. This project is committed to maximizing societal impact through commercial translation and public availability.
This Small Business Innovation Research Phase II project aims to advance non-invasive, self-administered nasal drug delivery. The current problem is that standard nasal sprays do not reach the deeper anatomy implicated in chronic sinusitis. Therefore, patients either end up with cyclical courses of oral medications that have significant side effects or they must undergo expensive, invasive surgeries. Even after these treatments, most patients continue to suffer with symptoms for years. The proposed technology consists of a self-administered device that enhances drug delivery to target intranasal anatomy, improving outcomes for patients early in the disease pathway. The prior Phase I project developed a catheter-based nasal spray technology equipped with a miniature atomizer that can comfortably and reliably access deep target nasal anatomy when self-administered by the patient. This Phase II project will finalize the device design and test it with viscous drug solutions to achieve design freeze, conduct human factors testing, optimize the design for large-scale manufacturing, and perform verification and validation testing. This project will position the device for FDA clearance as a pioneering solution for non-invasive nasal drug delivery that offers improved treatment options for patients and opens new avenues for non-invasive therapeutic interventions.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
NATRX, INC.
SBIR Phase II: Resilience for Waterfront Infrastructure
Contact
6220 ANGUS DR
Raleigh, NC 27617--4752
NSF Award
2322073 – SBIR Phase II
Award amount to date
$995,338
Start / end date
10/01/2023 – 09/30/2025 (Estimated)
NSF Program Director
Errata
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Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase II project is to drive restoration and preservation of coastal wetlands by unlocking their ecosystem value. Many coastal communities are underserved and do not have resources to adapt to increasing risks from erosion, storms, and sea level rise. Enhanced coastal resilience and restoration promotes biodiversity, which bolsters coastal communities through improved fisheries, tourism, and water quality, as well as other "blue economy" benefits. This project will enable coastal communities to access funds from monetizing project co-benefits and promote nature-based solutions with economic and environmental benefits. This project advances NSF?s mission by developing analytical tools that can directly benefit national welfare. The project can create significant impact by enabling more environmentally sustainable adaptation techniques, expanding financing alternatives for coastal wetlands restoration, and promoting equitable actions. This solution creates ecological and socio-economic benefits by addressing the need for more sustainable communities given coastal migration trends and rising sea levels and increased storm intensities.
This approach utilizes high-resolution satellite imagery and artificial intelligence to accurately and systematically measure the carbon stock in coastal wetlands. The project will include an integrated suite of technologies for new datasets, a modeling framework to identify coastal shorelines at risk of erosion, high fidelity maps of blue carbon stock, and the characterization of biodiversity in relation to the environment. This project is expected to make significant contributions to the protection of coastal wetlands and the development of novel methods to analyze blue carbon stocks. The project will build on the existing software platform developed during Phase I and extend its application to determine the different blue carbon pools in marshes and mangrove ecosystems. By accurately measuring erosive conditions and carbon stock at a high spatial resolution in coastal wetlands, this solution has the potential to enable markets to meet sustainability goals while preserving the numerous benefits that wetlands provide to the environment and communities. The project would also decrease the uncertainty in the measurement of blue carbon at a high spatial resolution, a critical factor for creating trustworthy and reliable carbon credits, which can be used to finance the restoration and preservation of coastal wetlands.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
NBN TECHNOLOGIES, LLC
SBIR Phase II: Affordable, Multi-wavelength Imager plus Light Detection and Ranging (LIDAR) for Autonomous Vehicles
Contact
136 WILSHIRE RD
Rochester, NY 14618--1221
NSF Award
2037859 – SBIR Phase II
Award amount to date
$920,766
Start / end date
08/01/2021 – 11/30/2024 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research Phase II project based on this SBIR sensor solution, with its high quality and low cost, will enable the advanced driver assistance systems (ADAS) industry to accelerate the progress to greater functionality of assisted driving, ultimately reaching full autonomy. The subject focal plane array (FPAS) chips may reduce the current US 36,560 annual vehicles deaths (the leading cause of death for those 1-54 years old) as well as reduce the 4.4 million injuries requiring medical attention and the $ 871 billion in damages and health costs. Additionally, improved assisted driving will enhance the mobility of seniors/disabled. Finally, the technology may reduce the societal carbon footprint by reducing congestion as a result of more fuel-efficient acceleration and braking.
This Small Business Innovation Research Phase II project seeks to improve the current ADAS sensor suite to increase safety. Current ADAS systems require many different sensor technologies to be implemented simultaneously. These sensors are insufficient to achieve higher levels of autonomy limiting the vehicle?s used in poor conditions. The proposed sensor solution will function in low light and harsh weather conditions with high performance. The added sensor functionalities will reduce the processor bandwidth required to integrate and analyze sensor data and detect road hazards, increasing the accuracy of the system. Overall, this improvement in performance may increase the overall safety in ADAS vehicles. An evaluation system will be developed to characterize the sensor.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
NEOCARE INNOVATIONS, INC.
SBIR Phase II: An Integrated Biomedical Platform and Custom Algorithm to Optimize Feeding Protocols for Preterm Infants
Contact
827 10TH ST APT 2
Santa Monica, CA 90403--1616
NSF Award
2335207 – SBIR Phase II
Award amount to date
$943,819
Start / end date
03/15/2024 – 02/28/2026 (Estimated)
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project addresses the economic burdens of healthcare for preterm infants in Neonatal Intensive Care Units (NICUs) across the US by lowering expenses through cost effective technology. On average 400,000 preterm infants are born in the US each year and 49% experience difficulty feeding after discharge. Preterm infants who cannot successfully feed are at increased risk of hospital readmission resulting in significant financial and emotional burdens for their families. In the US the average length of stay for an infant born less than 32 weeks gestation is 13.2 days. The current practice is for babies to remain longer in the NICU at an average cost of $7,000 per day and a national cost of more than $26 billion a year. An estimated 2-day reduction in length of stay with this biomedical device will lower the financial cost of overall neonatal healthcare expenditure by $8.9 billion annually and will reduce the need for future medical interventions because infants are discharged with a stronger early-stage health baseline. Once this product is commonly used in US hospitals, it can be distributed globally to meet demand and benefit infants worldwide.
This Small Business Innovation Research (SBIR) Phase II project can save hospitals thousands of dollars while delivering better care and positive patient outcomes. For infants admitted to the NICU, successful oral feeding is a prerequisite for discharge home, but preterm infants often struggle with oral feeding skills largely due to problems coordinating swallowing with breathing. Achieving safe and efficient oral feeding in preterm infants is challenging because of these neurodevelopmental immaturities. Feeding progress is therefore limited by difficulties in maintaining cardiorespiratory stability. This biomedical platform and clinical algorithm interface use big data based on breathing patterns to quantify the synchronization of breathing and swallowing. A precise method of measuring infant breathing patterns during feeding gives clinicians a diagnostic tool to better inform decisions related to feeding advancement. This device provides objective metrics of feeding success and discharge readiness and may result in decreased readmissions for failure to thrive, substantially reducing healthcare utilizations and post-discharge expenditures. Creating technology that helps infants feed better so they can go home sooner promotes improved parent-infant interactions and optimizes infant development.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
NEURODYNE, INC.
SBIR Phase II: Analog front end (AFE) platform for lightweight, long-term, cortical monitoring
Contact
7000 CORSICA DR
Germantown, TN 38138--1528
NSF Award
2317290 – SBIR Phase II
Award amount to date
$963,459
Start / end date
09/01/2023 – 08/31/2025 (Estimated)
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project provides next generation ambulatory seizure data acquisition. The advent of mobile health advances during the COVID-19 health crisis have enabled new innovations to be considered. This effort provides a framework for the next line of remote neurological data acquisition capabilities for the implementation of military helmet designs that detect battlefield traumatic brain injuries, football helmet designs that detect sports-related brain injuries, caps for first responder teams that detect trauma, at-home monitoring headsets for remote migraine assessment, etc. A complete analogue front end (AFE) will be developed in order to provide digitized electroencephalograph (EEG) signals to the downstream stages. The project will have a major impact in several areas, namely, wearable bio-devices, data fusion, and neurological data extraction and visualization of complex biological systems. This device can be utilized for first responders at the scene of neurological trauma such as emergency medical technicians, battle front medical areas, and sports related events.
This Small Business Innovation Research Phase II project will provide a robust mobile device that can be worn in an at-home setting for remote neurological monitoring. The solution will remove noisy artifacts from the electroencephalograph signal in order to perform neurological diagnoses and provide neurological reporting to the neurologist as an aid to quantify the patient?s seizure instances. The analogue front end (AFE) provides the foundation for a portable electroencephalograph (EEG) device for neurological data acquisition for the clinical, academic, and research communities. The ambulatory seizure monitoring device will enable an end-to-end system for robust, lightweight, data transmission to a cloud service, which will generate reports for the physician to analyze a patient neurological data for treatment. This system will extend the current rise of health devices into the complex environment of neurological states, as well as the eventual development of neuro-analytics.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
NEUROSMART INC.
SBIR Phase II: Self Awareness and Stress Regulation Training via Intelligent Biofeedback
Contact
221 EASY ST APT 10
Mountain View, CA 94043--3772
NSF Award
2409291 – SBIR Phase II
Award amount to date
$999,647
Start / end date
08/01/2024 – 07/31/2026 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research Project (SBIR) Phase II project is to develop a technology that trains law enforcement officers for better stress regulation and decision-making in stressful situations. Police officers are tasked to confront highly stressful, potentially lethal encounters regularly, however, they may not receive sufficient stress management training leading to poor tactical decision-making, unnecessary use of force, and tension between themselves and the communities they serve. Officers also accumulate stress over time leading to a high prevalence of mental and physical health issues including PTSD, substance abuse, and cardiovascular problems. Agencies across the country are under immense pressure to revamp their training to meet the public demand for better behavior by officers. The technology being developed under this proposal monitors officer stress via a wearable sensor. Using state-of-the-art neuroscience and machine learning algorithms calculates if the officer?s stress level is sub-optimal for performance and offers insights and interventions for improvement. This project will enhance our understanding of how physiology impacts police officer performance and the best methods to improve performance under stress. It is serving a rapidly growing U.S. law enforcement training market
of $540,000M.
The proposed project will complete the development and testing of a novel biofeedback-based law enforcement training program. The project goals are (1) Developing and implementing brief and effective stress management interventions such as guided audio scripts on the mobile application. These interventions will be coupled to algorithms that measure stress regulation. Their usability, feasibility, and effectiveness in reducing immediate stress during officer training will be measured. (2) Improving existing
machine learning algorithms that predict poor performance from physiological and other training data to offer more actionable data to trainers. With better predictions, trainers can identify officers needing more training and deliver more targeted training with objective data. These algorithms can also be used in the academy setting for selecting recruits. (3) Testing the effectiveness of using biofeedback in combination with stress management techniques on police key officer performance and wellness metrics. The effectiveness of this novel training on tactical decision making, appropriate use of force, defensive tactics, perceived stress and anxiety will be evaluated. Upon completion of the mentioned tasks, a stress management training program specifically designed for law enforcement training will be developed and scientifically validated.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
NEUROTECHR3 INC.
SBIR Phase II: A machine learning-driven telerehabilitation solution designed to promote the personalized recovery of hand and arm functions post stroke
Contact
23 CHERRY TREE LANE
Warren, NJ 07059--2600
NSF Award
2226174 – SBIR Phase II
Award amount to date
$997,735
Start / end date
06/15/2023 – 05/31/2025 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is to potentially improve the quality of life for individuals suffering arm and hand impairments from stroke, through a medical device for telerehabilitation. Each year, ~800,000 people have a stroke in the United States, and about 65% of them suffer long-term upper extremity impairments. Due to many barriers such as cost, transportation, and time, many individuals do not obtain enough therapy for recovery. The telerehabilitation approach may reduce some of these barriers, allowing therapists and their patients to have meaningful remote sessions. For therapists, this may improve fiscal outcomes by automating the flow of reviewing patient progress, adjusting their rehabilitation treatments, and billing for services.
This project will advance the development of a personalized telerehabilitation system, specifically for hand and arm motor recovery, for individuals suffering from a stroke. New exergames designed for rehabilitation of the fingers, hand, and arm will be developed and added to the current library of games. Machine learning will be added to the system to create a versatile, engaging, and customizable solution. This novel approach to rehabilitation will personalize treatments that may be more effective by addressing individual user needs with predictive analytics. Machine learning will drive the recommendation system to synchronize the rehabilitation plan with the patient recovery trajectory. This synchronization will help the therapist provide personalized therapeutic exercises and possibly increase their patients? recovery outcomes. The games and machine learning algorithms will be evaluated with clinicians and individuals with stroke. The final step will be to test the feasibility of the system in a comprehensive stroke center. These capabilities of personalized virtual rehabilitation, remote clinician supervision, and progress tracking may offer a cost-effective way to improve patient outcomes.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
NEXILICO, INC.
SBIR Phase II: An omics-based computational drug design and discovery platform for next generation microbiome therapeutics
Contact
98 AMBERFIELD LN
Danville, CA 94506--1332
NSF Award
2228069 – SBIR Phase II
Award amount to date
$1,000,000
Start / end date
06/01/2023 – 05/31/2025 (Estimated)
NSF Program Director
Errata
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Abstract
The broader/commercial impact of this Small Business Innovation Research (SBIR) Phase II project focuses on the human gut microbiome, the complex and dynamic community of microorganisms residing in the gastrointestinal tract. The gut microbiome influences a variety of human diseases, such as Type 2 Diabetes and inflammatory bowel disease. Collectively, these diseases afflict more than 120 million people and cost more than $580 billion in patient treatments in the US annually. The current standard care of treatments for many of these diseases have variable efficacy and serious side effects. There is increasing interest in modulating the gut microbiome using microbiome therapeutics, i.e., therapeutics comprising living bacteria, as a new generation of drugs for difficult-to-treat diseases. However, the industry currently lacks a reliable approach to systematically and cost-effectively developing effective microbiome therapeutics. Specifically, the largest barrier to microbiome therapeutic development is the lack of predictive preclinical models to translate early-stage research into drug discovery and development.
The proposed project seeks to address the barrier to the use of microbiome therapeutics by developing a first-of-its-kind computational platform, as the first comprehensive, computational, drug design and discovery platform. Currently, the development of microbiome therapeutics is based on a series of experimental and statistical steps that identify the potential microbial strains for target therapeutic candidates in an empirical and iterative process. As a result, this approach requires extensive iterative in vitro and in vivo experiments, which substantially increase the length and cost of the development programs. These challenges have resulted in an inefficient and unpredictable microbiome therapeutic development process, limiting the number of efficacious microbiome therapeutics that could save millions of lives worldwide. This project addresses these challenges by reliably and cost-effectively identifying therapeutic candidates for a wide range of indications. This platform could replace the current iterative and unpredictable development process in the drug discovery stage. The utility of the platform will be demonstrated by developing new therapeutic candidates for Type 2 Diabetes and validating the efficacy of these candidates in preclinical studies.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
NOBLE GAS SYSTEMS LLC
SBIR Phase II: Conformable Hydrogen Storage for Aviation
Contact
40000 GRAND RIVER AVE STE 105
Novi, MI 48375--2133
NSF Award
2223187 – SBIR Phase II
Award amount to date
$969,214
Start / end date
01/15/2023 – 12/31/2025 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase II project is to enable the reduction of greenhouse gases by the aviation industry by advancing the development of a lightweight conformable tank capable of storing hydrogen at a gravimetric efficiency of over 10% hydrogen by mass. The development of a conformable tank with a > 10% storage efficiency, which exceeds the potential of existing technology, would have an immediate impact on the potential for hydrogen to replace existing transportation fuels. While the aviation application introduces unique challenges for hydrogen storage, the results of this project will benefit a wider variety of transportation fuel markets, where demand for lightweight, safe, and economically viable storage solutions is increasing. The storage of high-pressure gaseous hydrogen is a significant obstacle for zero emissions fuels, and meeting the standards for minimum burst pressure, cyclic operation, extreme temperature operation, and hydrogen permeation with a conformable tank will open the door to a wide variety of near-term applications, enabling the reduction of transportation-related emissions and reducing the burden of sending carbon fiber tanks to landfills at the end of their lives.
This Small Business Innovation Research (SBIR) Phase II project will address the challenges related to the commercialization of a lightweight hydrogen tank for aviation fuel. The decarbonization of the aviation industry requires zero-emissions powertrain technologies. However, current battery technologies lack the storage efficiency to support long-range flights, and existing hydrogen storage tanks are too heavy and cumbersome to be practical. The research objectives of this project are to increase the gravimetric efficiency of conformable tanks, close the gaps in the remaining barriers to component certification compliance, and produce prototype tanks suitable for bench testing and evaluation for flight testing. The research will involve the optimization of the pressure vessel reinforcement structure, the production of conformable tank samples, the testing of samples for the existing hydrogen tank regulations, and the collaboration with airplane manufacturers and regulators to identify and address additional performance requirements. Once completed, the project will result in full-scale (2.5 kg and above), standards-compliant, production scalable tanks for continued component and flight-worthiness evaluations.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
NOON ENERGY INC.
SBIR Phase II: Rechargeable Carbon-Oxygen Battery for Ultra-Low-Cost Renewable Energy Storage
Contact
470 RAMONA ST
Palo Alto, CA 94301--1707
NSF Award
2222588 – SBIR Phase II
Award amount to date
$1,000,000
Start / end date
11/15/2023 – 10/31/2025 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of this SBIR Phase II project is a new ultra low-cost carbon-oxygen battery that provides high energy density long-duration storage with unique fundamental properties needed to enable 100% renewable energy. This closed-loop stationary energy storage system will turn intermittent solar/wind power into on-demand power at lower cost than fossil fuel generation. Additionally, its high energy density (3x lighter and smaller than Lithium-ion batteries at system level) will enable longer range electric ships, trucks, etc. ? a secondary target market ? and a much more compact size for stationary storage than other batteries at the same energy capacity. The project will provide insight into the scale-up potential and design parameters of key battery components. Achieving 100% sustainable energy will have a wide range of societal impacts including minimizing environmental impact and improving human health.
This Small Business Innovation Research (SBIR) Phase II project for the carbon-oxygen battery will thus focus on key technology development of the core components by modeling, building, and testing. This will involve assembling an array of small-scale prototype reactors to screen configurations and iterate on the design, followed by scale up to a larger megawatt-hour (MWh) scale reactors to integrate into a demo system. The objectives of the Phase II project will focus on optimizing the reactor to achieve the key target metrics, including objectives to: 1) create and validate a multi-physics model of the optimized reactor, 2) design the optimized reactor, operating conditions, and materials, and 3) build and test several optimized reactors and show that the best design has the potential to fulfill the target metrics.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
NORCON TECHNOLOGIES HOLDING, INC.
SBIR Phase II: Chalcogenide Polymer Infrared Optics
Contact
7623 E CAMINO DEL BRIOSO
Tucson, AZ 85750--7087
NSF Award
2129415 – SBIR Phase II
Award amount to date
$984,268
Start / end date
11/15/2021 – 08/31/2025 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact and commercial potential of this Small Business Innovation Research (SBIR) Phase II project is to improve the optics and lenses used in near infrared 3D imaging. Glass lenses, which have excellent transmittance and thermal properties, are used in light detection and ranging (LiDAR) and rangefinders for distances beyond a few tens of meters. Polymer lenses, which are moldable and lower cost, are typically used in consumer-mobile 3D cameras and emerging automotive LiDAR systems. The refractive indices of these lenses limit the numerical aperture and require longer-than-desired lens barrels. The proposed polymeric chalcogenide lenses combine infrared transmittance, index, and thermal properties with the cost and moldability of optical polymers. The innovation enables the molding of freeform polymer lenses with increased numerical aperture and reduced barrel lengths. These properties make possible more compact, lighter, and lower cost 3D imagers. With these advantages, rangefinders can be more easily carried and scan faster and smartphone cameras can have wider viewing angles. Additionally, LiDAR systems can image more accurately around a vehicle and improve both driver and pedestrian safety.
This Small Business Innovation Research Phase II project seeks to advance sulfur polymer chemistry and materials processing for the development of a new class of near infrared (NIR) optical components. Innovative chemical synthesis and infrared fingerprint engineering has led to the development of a new class of optical polymers with the potential for imaging applications in the NIR. As a result of extensive optical and mechanical characterization, including the determination of the optical constants over the full infrared spectrum, measurement of mechanical properties such as the coefficient of thermal expansion, measurement of thermo-optic coefficients, and determination of stress-optic coefficients, the materials will now be developed and integrated for product applications with innovative optical designs based on material's unique property set. Freeform optical design concepts will be used which, to date, have not often been used in infrared imaging. Such designs may lead to more compact, lighter, and higher performance optical systems for infrared imaging applications, further leveraging the advantages of the material's transmission spectrum, incorporating absorption, bulk scattering and surface scattering, and surface scattering contributions.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
NOSTOPHARMA, LLC
SBIR Phase II: Improved drug delivery platforms for localized and sustained drug deposition for traumatic injuries
Contact
7600 CODDLE HARBOR LN
Potomac, MD 20854--3251
NSF Award
2415332 – SBIR Phase II
Award amount to date
$1,000,000
Start / end date
08/15/2024 – 07/31/2026 (Estimated)
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is the development of the safe and efficacious treatment for orthopedic and trauma surgery complications. This treatment includes localized and sustained drug delivery platform that will address the unmet medical needs for orthopedic patients. The successful commercialization of this technology is also expected to spur more nanomedicine and nanofabrication research for the medical field. The goal of the proposed project is to create a medication delivery system for soft tissue trauma consequences using sustained, biodegradable nanoparticles. The state of sustained-release technology will be greatly advanced, and the rehabilitation care provided to trauma patients will be substantially improved with this technology. The treatment to be developed will decrease the number of complications. New pharmacoeconomic research shows that cost/revenue over the long term is positively affected by fewer complications. Currently, there are major industry initiatives underway to create localized drug delivery systems for ophthalmic and cancer treatments. However, there are currently no approved or in-development treatments for this unmet medical need in orthopedic surgery. Support from the NSF will function as a spark to significantly increase the commercial effect of this first orthopedic nanomedicine project.
This Small Business Innovation Research (SBIR) Phase II project will address an innovative approach by utilizing anti-inflammatory nanoparticles embedded with potent Hedgehog pathway antagonist-Arsenic trioxide (NP102nano). This innovative and distinctive approach for developing a sustained-release, biodegradable drug delivery that delivers post-traumatic medication locally within the injured tissue is based on the desire to obviate unnecessary systemic drug applications and create a safe and effective off-the-shelf therapy. Such a product has the potential to improve outcomes for patients with post-traumatic injuries and reduce societal costs associated with additional surgeries and rehabilitation among trauma surgery patients. Current orthopedic treatments utilize systemic, untargeted administration of medications that result in unintended side effects, implant failure, and/or lack of intended efficacy. Moreover, the lack of an efficient delivery vehicle requires drug application at supraphysiological doses to reach clinical efficacy. The application at supraphysiological doses significantly increases the risk of side effects. It, therefore, is desirable to provide formulations and methods that target the delivery of medications only to the tissues needing treatment. This platform under development offers exactly this benefit. The goal of this project is to produce sufficient data for the pre-Investigational New Drug meeting with the regulatory authorities (such as Food and Drug Administration).
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
NOVEL FARMS, INC.
SBIR Phase II: Microbe-based scaffold for the generation of structured cell-based meat
Contact
2988 SAN PABLO AVE
Berkeley, CA 94702--2471
NSF Award
2303802 – SBIR Phase II
Award amount to date
$999,967
Start / end date
09/15/2023 – 08/31/2025 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact of this Small Business Innovation Research (SBIR) Phase II project is to combat the profound negative impacts of the animal farming industry through the development of new technologies to advance cultivated meat production. Approximately 30% of the Earth?s surface, 70% of all arable land, and 29% of the global freshwater supply is dedicated to animal farming. Livestock is responsible for 18% of global greenhouse gas emissions and is one of the largest threats to earth?s biodiversity. A significant fraction (70%) of all antibiotics used in the United States are used on farm animals and this is a primary cause of the emergence of antibiotic-resistant bacteria, leaving the United States with an economic burden of $55 billion and a healthcare system overwhelmed with 2,000,000 infections, 250,000 hospitalizations, and at least 23,000 deaths per year. An emerging industry poised to combat the negative impacts of animal farming is the cultivated meat industry, which is estimated to decrease energy use by 7-45%, greenhouse gases by 78-96%, land use by 99%, water use by 82-96%, and could eliminate the need for antibiotics use in meat production. The project aims to further develop a novel technology that will allow for the economically feasible production of cultivated meat.
The proposed project aims to solve one of the major barriers impeding the economic feasibility of cultivated meat ? cell culture media cost. Cultivated meat must be priced competitively with conventional meat if it is to be a viable alternative to meat produced via industrial farming. Thus, as with animal feed, cell culture media must be as inexpensive as grass or government-subsidized corn to allow for the production of cultivated meat at a comparable profit margin. The goal of this project focuses on reducing media costs by eliminating expensive media components through further development of proprietary scaffolding technology and reducing the overall volume of media required to generate cultivated meat through the adaptation of ultra-efficient, high-density bioreactors. To do this, the scaffolding technology generated during the Phase I effort will be further developed to incorporate growth factors, the most expensive elements of cell culture media, thereby reducing the overall cost of media. Then, the scaffolds will be adapted for use in high-density, perfusion-based bioreactors that use a fraction of the media as conventional stirred-tank bioreactors, thereby reducing the overall consumption of media. Together, these two strategies will lower the overall cost of cultivated meat production.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
NUTRAMAIZE LLC
STTR Phase II: Developing High Carotenoid Orange Corn for Large-scale Commercial Adoption
Contact
1281 WIN HENTSCHEL BLVD, UNIT 046
West Lafayette, IN 47906--0000
NSF Award
1926952 – STTR Phase II
Award amount to date
$1,012,916
Start / end date
08/01/2019 – 01/31/2027 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of this Small Business Technology Transfer (STTR) project will be the development and commercialization of a novel variety of corn that is high in carotenoids and orange in color, and with yields that are competitive with today's commercial hybrids. In the diets of Americans, two important antioxidant carotenoids, lutein and zeaxanthin, are in low abundance. This deficiency has been associated with higher risk for degenerative diseases such as age-related macular degeneration, and potentially, dementia. The ultimate goal of the proposed research is to provide a way for Americans to consume more lutein and zeaxanthin, which will be achieved by increasing significantly the levels of these antioxidants in the U.S.'s most widely grown staple crop: Corn. Since corn is used in a wide variety of popular processed food formats, improving the carotenoid content of corn provides an opportunity to significantly increase the amount of health benefiting antioxidants that Americans consume, without changing consumers eating habits. However, in order for this strategy to be economically feasible, corn varieties that are high in carotenoids must be developed that also are high in grain yield.
This STTR Phase II project proposes to use genetic markers to select for favorable alleles of genes associated with carotenoid biosynthesis and stability in corn bred for commercial production. There is considerable genetic variation in genes associated with carotenoid biosynthesis and stability, however, the most favorable alleles are typically not found in varieties that are commercially relevant to US corn production. Thus, the use of genetic markers developed previously will enable favorable alleles to be moved from lower yielding germplasm that is not well adapted to the US Corn Belt into elite inbreds suitable for the production of yield-competitive commercial F1 hybrids for the US market. The primary goal of this Phase II research is to use the user-friendly genetic markers associated with favorable alleles for 18 key genes associated with carotenoid biosynthesis and stability developed in Phase I to rapidly develop fixed inbreds for use in the production of yield-competitive high carotenoid F1 hybrids suitable for large-scale commercial applications.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
Nanopath Inc.
SBIR Phase II: Integrated Point-of-Care System for Rapid Pathogen Identification and Characterization
Contact
10 PINEWOOD VLG
West Lebanon, NH 03784--3120
NSF Award
2321834 – SBIR Phase II
Award amount to date
$997,781
Start / end date
09/01/2023 – 08/31/2025 (Estimated)
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is improved access to state-of-the-art molecular diagnostic technologies in areas of significant unmet clinical need, such as women?s health. During the NSF I-Corps Program, the team identified urinary tract infections (UTIs) as pressing problem due to the currently lengthy clinical workflows, significant unmet clinical need, and large disease incidence. UTIs are one the most common causes of a healthcare visit for women in the United States and represent one of largest sources of antibiotic prescriptions in the country. Untreated UTIs can lead to severe complications for the patient, including systemic bacterial infections such as bacteremia. Despite the severity and prevalence of UTIs, diagnostic methodologies remain extremely time-consuming and rely on antiquated, culture-based methodologies for pathogen detection. This time-intensive diagnostic workflow typically leaves women in pain for up to three days before they are prescribed the appropriate antibiotic therapy. As a result of shortcomings in current healthcare workflows, women who have limited access to care are subject to longer result wait times, and often never receive the appropriate treatment.
This Small Business Innovation Research (SBIR) Phase II project utilizes a novel nanosensor embedded into an integrated diagnostic consumable for rapid detection of target nucleic acid sequences directly from patient samples. The consumable is coupled to a proprietary bench-top readout instrument for test analysis and result reporting at the point-of-care. The technology eliminates the need for bacterial culture and nucleic acid amplification through an ultrasensitive optical detection modality, providing species-level information and genotypic antibiotic resistance data within minutes. Applications of the proposed platform translate beyond UTIs to other clinical scenarios that currently employ lengthy culture-based or amplification-based diagnostic workflows, such as sexually transmitted infections and respiratory infections. Successful product commercialization will require meeting clinically actionable timescales and assay performance benchmarks. Of importance is the development of a simple, integrated workflow for healthcare workers to enable single-step operation at the point-of-care. The Phase II technical objectives focus on the development and pilot-scale fabrication of the nanosensor, the optimization of sensitivity and robustness of data analysis methodologies to inform down-selection of reader optical hardware, and system integration and user testing.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
New Iridium
SBIR Phase II: Utilizing Carbon Dioxide (CO2) as a Feedstock to Produce Commodity Chemicals
Contact
2870 E COLLEGE AVENUE UNIT 106
Boulder, CO 80303--1961
NSF Award
2151548 – SBIR Phase II
Award amount to date
$1,000,000
Start / end date
05/01/2023 – 04/30/2025 (Estimated)
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) project is abating carbon dioxide (CO2) emissions in the production of terephthalic acid, a large-scale commodity chemical. Development of this technology will provide a pathway for direct utilization of CO2 in everyday products. For example, implemented at scale, the proposed process has potential to sequester about 20 million metric tons of CO2 annually, equivalent to the emissions from 4.3 million cars. This project also has significant commercial potential. By delivering a lower-carbon product at lower cost than the current technology, the proposed innovation has the potential to become the de facto standard for manufacturing this commodity chemical. Annual licensing and ancillary revenue from a single plant is estimated at $30 million, and at 70-80% market share, typical for the dominant process, annual revenue could grow to over $1.5 billion. The success of this project will also provide a scientific and entrepreneurial blueprint to spur similar efforts thus advancing the state of the art of CO2 utilization technologies.
This SBIR Phase II project proposes to develop a light-driven chemical technology that enables the use of CO2 as a raw material in large scale chemical production of terephthalic acid. This project abates CO2 emissions by converting CO2, captured from point sources such as industrial flue stacks or direct air capture, to useful chemical and consumer products. Carbon dioxide is a stable compound and is typically unreactive and therefore incompatible with traditional heat-driven processes. The proposed project will help mature the technology of CO2 activation by photocatalysis, which has been shown to be effective in inducing CO2 reactivity. The first step is to demonstrate the feasibility of using CO2 to produce the target chemical at bench scale. Next, the reaction performance will be optimized using high-throughput experimentation techniques. Finally, the process will be scaled up in a photo flow photoreactor. In this part of the project, engineering scale up issues will be addressed as a precursor to realizing a production plant.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
Niche Biomedical, Inc.
SBIR Phase II: An Ingestible, Intraluminal, Bioelectronic Capsule (IBC) for Closed-Loop Diagnosis and Treatment of Gastrointestinal Disorders
Contact
10940 WILSHIRE BLVD STE 2030
Los Angeles, CA 90064--3783
NSF Award
2052272 – SBIR Phase II
Award amount to date
$999,999
Start / end date
09/01/2021 – 12/31/2025 (Estimated)
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project focuses on a new gastrointestinal therapeutic device supporting multi-modal gastrointestinal measurements and treatment of post-surgical complications. Over 300,000 patients in the US undergo abdominal resection surgery each year. These patients often experience serious complications, such as post-operative ileus, gastrointestinal hemorrhage, and anastomotic leakage, that significantly impact quality of life. The success of this project would not only benefit patients undergoing abdominal surgery and their families, but also would significantly reduce health care expenditures by decreasing the length of hospitalization as well as associated medical resources. Furthermore, this interdisciplinary research brings together academic collaborators from different fields of expertise. The project provides a unique experience and training for engineers and scientists in the fields of neural interface design and medical device experiments, bridging the gap between the engineering and medical communities, as well as promoting and cultivating future neural engineers to focus on developing emerging/unmet diagnostic and therapeutic devices for improving human health.
This Small Business Innovation Research (SBIR) Phase II project develops and demonstrates a wireless, miniaturized, intraluminal bioelectronic capsule capable of performing on-demand neuromodulation and multi-modality sensing on the gastrointestinal tract, supporting closed-loop neuromodulation. The device will be tested and characterized on benchtop and also through porcine models to demonstrate its potential for treating and monitoring post-surgical complications. The lengthy process of diagnosing and treating post-surgical complications significantly increases healthcare costs. Costs from hospitalization time alone exceed $2,000 per day for post-operative ileus alone. Additional costs due to prolonged hospitalization time exceed $1.5 billion annually. Rapid detection and treatment of these complications could reduce hospitalization time, accelerate recovery, enable closed-loop therapies, and increase quality of life for patients. The success of this project has the potential to bring disruptive impact and revolution to the current pharmaceutical-based post-surgical management and treatment. In addition, the technology developed during this project may be useful to treat other chronic diseases and injuries that are incurable pharmaceutically. The technique may be used as research tools for investigating the biological mechanisms and new therapeutics for different diseases.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. -
OAM PHOTONICS LLC
SBIR Phase II: Focal Plane Array for Active Coherent Imaging
Contact
6100 CORTADERIA ST NE
Albuquerque, NM 87111--8009
NSF Award
2241921 – SBIR Phase II
Award amount to date
$1,000,000
Start / end date
06/01/2023 – 05/31/2025 (Estimated)
NSF Program Director
Errata
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Abstract
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is in developing technology that will enable the use of a 3-dimensional (3D) light detection and ranging (LiDAR) system in smaller and more economical drones for mapping, surveying, and navigation. The 3D LiDAR has important applications in environment management, forestry, land and corridor mapping, construction, land surveying, precision agriculture, powerline and infrastructure inspection, and countless other areas. The technology will bring significant economic impacts to the industries by reducing the ownership costs of a high-performance LiDAR system and the drone that can carry this system. The reduction of the entry-cost for LiDAR applications with drones will in turn benefit small businesses to perform smaller-scale projects in mapping and surveying. Other than drone-based applications, the innovation is poised to significantly reduce the costs and provide seamless integration of 3D LiDAR sensing in self-driving vehicles and other industrial applications including robotics, smart city infrastructure, surveillance, and security, as well as consumer applications like 3D sensing for augmented reality. The numerous applications enabled by the proposed project not will only help increase the economic competitiveness of the U.S. but also improve quality of life, security and safety.
The proposed project aims at developing a high-performance, compact, and light-weight 3D LiDAR sensor to meet the increasing needs of drone-based, high-precision LiDAR applications. Current commercial high-performance drone-LiDAR systems are notorious for their high cost, bulkiness, heavy weight, and high power-consumption. Current drone-LiDAR systems are also prone to mechanical damage. These issues inevitably shorten the drone flight time, inhibit the installations of high-performance LiDAR systems on the more common consumer-grade small drones, and increase the operation costs. The proposed LiDAR sensor will mitigate all of these issues by leveraging a high-performance coherent LiDAR detection approach with silicon photonics technology in an innovative design. The coherent LiDAR detection method allows more sensitive measurements than the method used in most existing LiDAR systems. The technology achieves a longer detection range and larger number of returns given the same laser power. Based on highly scalable Complementary Metal-Oxide-Semiconductor (CMOS)-compatible silicon photonics technology, the LiDAR sensor is able to achieve high spatial resolution in a compact size. The entire system will have a form-factor similar to a palm-sized compact camera commonly used for photogrammetry in small drones. The solution requires no mechanical mechanisms for beam scanning nor high-precision alignment of optical components, making the system inherently durable, compact, lightweight, and power efficient.
This award reflects NSF's statuto