Portfolio details
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Abstract

This Small Business Innovation Research (SBIR) Phase II project will develop and produce a robust, hand-held, video-rate three-dimensional surface metrology system with vertical and lateral resolution of several micrometers, in order to bridge a critical existing metrology gap for precision-machined surfaces. Many modern manufactured parts, such as turbine blades, drive shafts, orthopedics, and various additive manufactured components require in-situ metrology with high resolution for accurate characterization during manufacturing and/or maintenance operations. Current high-resolution surface measurement systems are slow, vibration-sensitive and laboratory-based and thus are impractical for everyday use by manufacturing technicians. Meanwhile, shop-floor inspection is often only visual, and thus qualitative rather than quantitative, leading both to rejections of acceptable components as well as potential acceptance of failing ones. The absence of high-precision, in-situ metrology has hindered manufacturers from applying real-time data analysis and closed-loop process controls that can improve yields and reduce manufacturing costs. This research program will yield a hand-held, easy-to-use, robust, and quantitative shop-floor measurement system, allowing manufacturers to improve lifetimes, performance, and yield as they rapidly assess the features under test and feed the results back to improve process control.

During Phase I, a breadboard system was designed and implemented using a polarization-based fringe projection method and micropolarizer phase-mask technology to achieve vibration insensitive measurement in a compact package. This Phase II program leverages that research to design a video-rate, compact, robust and portable system for handheld surface measurements in shop-floor environments. This will first involve improvements to measurement resolution with an improved optical design and new self-calibrating measurement modes; new optical elements will lower noise artifacts caused by imperfections in the earlier design and to reduce system size. Once performance of the new design is verified, an ergonomic, compact, robust, wireless housing for the instrument must be created to enable shop-floor use; the system must handle drops of over one meter onto concrete, have useful battery life for extended field operations, be light enough to not fatigue users and have intuitive controls and feedback. A final, critically important development effort will create automated software routines for measurement, analysis, and system diagnostics to enable adoption by unskilled personnel in manufacturing environments. Lastly, extensive applications testing in the field will allow optimization of the system to handle a wide range of potential use cases and environments.

Abstract

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project has the potential to help enhance disease resistance in poultry and increase yields due to the delivery of only healthy, fully vaccinated chicks to farms. These healthier chicks will reduce the need for antibiotics in poultry, aiding to combat antimicrobial resistance. This technology has immediate applications in other food animal industries and fisheries, and allows for data capture on numbers of animals and types of treatments given. Broader applications would include any image capture and analysis that relies on analytics to identify target areas for delivery of substances to live animals or humans.

This SBIR Phase II project will allow for the advancement and commercialization of imaging technologies for the use of screening and targeting live animals. This proposal brings innovation in the care of food animals allowing for producers to move away from flock health and focus on the care of individual animals. This will be a dramatic change for the poultry industry, but is necessary in the face of antibiotic removal to be able to improve the current vaccination efficiencies and screen chicks for health status. Individualized care is currently not possible due to the high throughput needed to keep pace with large scale commercial hatchery operation. The technical challenges this proposal will overcome include 1) the safe and effective handling of chicks in an automated system that can process 100,000 chicks per hour, 2) the development of imaging systems for health checks and target recognition, 3) the delivery of the appropriate dose of vaccine with the correct amount of agents (virus, bacteria, parasite, and other agents) while not damaging the agents during delivery, and 4) development of a system that is rugged and robust enough to survive in a hatchery environment.

Abstract

This Small Business Innovation Research Phase II project focuses on the development of a high-yield fermentation route for the production of levulinic acid (LA). LA is one of the best-suited C5 building blocks for bio-refinery production due to higher value, broad applications, and likely quick adoption by the chemical industry. During Phase I, this project has designed and experimentally validated the concept of a novel fermentation pathway for the production of LA. The focus of this Phase II work will be to transition from this technical proof-of-concept to the development of a lab-scale fermentation process. The limiting enzymatic steps in the designed pathway will first be optimized to reach levels of activity consistent with the flux/yield required for economical production. Variants of the designed pathway incorporating the original and optimized enzymes will subsequently be cloned into suitable fermentation organism(s). Using computational and experimental metabolic engineering tools, knock-out and knock-down mutations will be performed to further optimize flux/yield in the pathway while optimizing for host cell growth. This work represents the first commercial application of enzyme design to rationally engineer novel metabolic pathway that do not have any natural counterpart, bringing us closer to the dream of designer cell factories.

The broader impact/commercial potential of this project is the advancement of a U.S. green chemistry industry and to allow America to take the lead in the commercial production of a new renewable chemical building block. The lack of a high-yield alternative to costly thermo-chemical processes has been preventing widespread adoption of levulinic acid (LA). Because LA can be converted, chemically or biochemically, to synthetic rubber (through isoprene and butenes), bio-fuels (such as kerosene and HMF), polymers (for instance, nylons) and polymer additives (for changing polymer characteristics), the addressable market is in excess of $20B annually. When considered as the end product, LA trades at a considerable higher price than ethanol, the current product of most commercial bio-refineries, and thus can help diversify their product offering and considerably increase their margins.

Abstract

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is to develop a platform to rapidly design synthetic organisms to produce biochemicals, which will replace environmentally harmful, ecologically inefficient industrial chemical processes. The technology developed in this proposal will provide a competitive edge in the rapid engineering of synthetic organisms to produce biochemicals by fermentation that are currently produced from oil (reducing our CO2 emissions) or extracted from natural species (reducing our taxing load on existing ecosystems). This technology also has the potential to be used for the manufacture of drugs, and to engineer novel organisms to improve crop production and therefore help address the mounting challenges of providing food to a growing world population without tapping too much in Earth's resources. Commercially, the chemicals that will be enabled by application of the technology developed during the Phase I program open up billion dollar markets that are currently inaccessible to the chemical industry.

This SBIR Phase II project proposes to develop a platform that combines computational enzyme design with systems biology to create a fully integrated system for the design and testing of novel cell factories for the production of bulk and fine chemicals. During the Phase I project, the company, in collaboration with the University of Washington, has successfully developed a high-performance software code to rapidly design novel metabolic pathways to produce any target chemical from central metabolism. In Phase II, the company will further advance the concept by (1) developing a high-performance pathway prioritization module to estimate each designed pathway yield and impact on organism metabolism in the context of whole-genome models and (2) use the software platform to design libraries of pathways for the production of a variety of specialty chemical targets that are commercially valuable and not known to be produced by fermentation at scale. Then, (3) using an experimental screening setup, the DNA for all the proposed pathways will be assembled screened at high-throughput for detectable production of the target chemicals.

Abstract

The broader impact of this Small Business Innovation Research (SBIR) Phase II project will result from the development of a scalable, universal quantum computing platform. The range of applications are broad and will expand in parallel with the development of new quantum algorithms, with initial applications including molecular simulations for the chemical and pharmaceutical industries, currently limited by the approximations necessary to make calculations tractable for classical computers. In order to perform these simulations at a scale useful for commercial applications, quantum computing must be significantly scaled. The proposed system will develop a new method to trap and control individual atoms for scaling of quantum computers.

This Small Business Innovation Research (SBIR) Phase II project will develop technology for parallel, high-fidelity single- and multi-qubit gates in neutral atom quantum computers. The technology will enable neutral atoms as a platform for scalable quantum computing technology with fault-tolerant capabilities. The proposed project includes: 1) development of systems to control atomic qubits in parallel; 2) a methodology to enact high-fidelity gates; and 3) development of necessary infrastructure for a cloud-accessed quantum computer. With a previously unrealized degree of coherent control to atomic systems, the proposed system will serve as an entirely novel tool to study many-body physics, enabling new quantum simulations of new phases of matter or high-energy physics.

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.

Abstract

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is to improve clinical outcomes and quality-of-life for pancreatic cancer patients. Only 10% of pancreatic cancer survive five years after diagnosis because most cases are detected at later stages when clinical interventions are relatively ineffective. Earlier detection improves interventions, prevents unnecessary procedures arising from uncertain diagnosis, and leads to health system cost savings. Roughly 5 million individuals in the US are at higher risk, but there is no screening test available today for earlier stages, a surveillance market estimated at $3 B. This project will develop a diagnostic test for surveillance of people at high risk for developing pancreatic cancer, with methods potentially applicable to other types of cancer and other diseases.

This Small Business Innovation Research (SBIR) Phase II project will advance a technology using a small blood sample to detect the functional state of multiple biological signaling pathways known to participate in cancer inception and progression. This technology can analyze these low abundance proteins at a low cost suitable for a widely adopted surveillance test. A purpose-built bioinformatic system analyses and compares the bio-signature identified by the assay across many individuals. This Phase II project will optimize the panel of protein targets in the assay to detect high-performing differential bio-signatures for early stages of the disease, and it will enhance the machine-learning-based matching methodology.

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.

Abstract

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) project is to provide general commercial access to a new generation of affordable, high-efficiency aerosol samplers that will primarily be used in the Industrial Hygiene and Indoor Air Quality market. The collection technology in these new instruments is unique in that it captures, concentrates and preserves airborne microbes in the same physical state they exist as they are suspended in the air we breathe- a tremendous breakthrough for forensic aerosol analysis. This work optimizes a novel collection method that chronologically resolves air samples into a portable compact platform, which ensures purity, minimizes handling and is safe for mail. The sample output is delivered in small, sterile medical grade disposable plastics that are compatible with a broad range of users' analytical needs whether it be the military, health care, atmospheric researchers or indoor air quality sector. This instrumentation is portable, and requires no filters or chemical additions; it rapidly condenses airborne microbes out of ambient air by manipulating humidity, offering a reliable way to assess microbiological air pollution-indoors or out.

This SBIR Phase II project proposes to optimize the design of condensation growth-based bioaerosol samplers for commercial validation, rapid manufacture and high-quality reproduction. The accurate assessment of airborne biological agents remains a tremendous scientific and practical challenge. The intellectual merit of this work lies in finally overcoming the technical barriers posed by conventional air sampling equipment, which require extensive sampling time and significantly compromises the very information military, medical and building science professionals need: what is the identity, distribution and abundance of airborne microbes. This team will use the latest forensic genetic sequencing technology to isolate the detection limits of this new collection equipment for common airborne pathogens and allergens. The objective is to validate these new filterless aerosol recovery instruments in controlled laboratory experiments, with a broad range of common pathogenic bioaerosols. The team will demonstrate how the sample preservation benefits of this technology, can be realized for commercial benefit in monitoring high-density indoor environments, including health care settings and public schools. Operating this new equipment in occupied indoor spaces, we anticipate collecting bioaerosol in excess of forensic detection limits in less than 30 minutes, while maintaining exceptional sample fidelity.

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.

Abstract

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) project is to enable greater electric vehicle use; furthermore, the technology’s potential to double battery life will reduce the environmental impact of disposed batteries. This project accelerates electric car adoption by enabling use of 100% of battery operating ranges and maximize usable energy capacity, increasing ongoing driving ranges by 50-100x. This project is a key enabler for expected growth in the global lithium-ion battery market (expected to grow to $68 B by 2022) and the annual hybrid and electric car market (forecast to exceed 10 million vehicles annually by 2025).

This SBIR Phase II project proposes to optimize the technology for battery fast charge and capacity retention targets. Battery performance advancements are most often limited by chemistry and materials improvements to electrodes, electrolytes, or cell structure limiting the trade space (i.e., requiring power vs. energy tradeoffs). The proposed charging technology and associated software will selectively optimize cell design for various performance metrics by controlling electrode surface phenomena, such as lithium plating and dendrite formation, that otherwise cause permanent capacity loss during normal use and accelerate internal physical processes limiting charge rate. Technical tasks include: 1) Demonstration of performance improvements to commercial Li-Ion and fabricated Li-metal battery cells; 2) Adaptation of the process from small cells and modules to electric vehicle battery packs; 3) Development of refined sensing and feedback-based control algorithms using Predictive Learning (PL) and Machine Learning (ML) systems; 4) Verification and validation for Field Programmable Gate Array (FPGA) and System on a Chip (SoC) formats.

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.

Abstract

This Small Business Innovation Research (SBIR) Phase II project will develop an ultra-light, modular wind turbine for use in buoyant airborne wind energy systems. Reduced turbine weight has a cascading effect on total airborne system mass, allowing a significantly smaller, lower cost buoyant structure to be used to access high altitude winds. At heights up to 2,000 feet winds are strong and consistent, allowing for the production of low-cost, reliable power at a broad array of sites. High altitude winds have over five times the energy potential of ground winds accessed by tower-mounted turbines, opening the potential for a major new renewable energy resource to be harnessed. In addition, the containerized deployment of airborne wind turbines has the potential to expand wind development to sites that are not feasible today, including sites that are remote or have weak ground-level winds. Overall, the technology holds the potential to significantly lower energy costs and improve reliability for remote industrial, community, and military customers and represents a major step forward in unlocking the abundant high-altitude wind resource to help in the global pursuit of greater adoption of renewable energy sources.

This SBIR Phase II project will focus on reducing the total weight of the wind turbine system. Turbine weight is one of the most critical cost drivers of buoyant airborne wind energy systems. For each kilogram removed from the turbine, an additional kilogram can be removed from the inflatable shell and tethers, resulting in a significantly smaller and lower cost system. The lightest commercially available small- to medium-sized wind turbine weighs 31.1 kilograms per kilowatt of capacity, which is too heavy for an economically-viable airborne turbine. By incorporating a compact, modular architecture, a lightweight permanent magnet direct-drive (PMDD) generator and high-strength composite materials, the proposed Phase II research effort aims to double the power density of traditional medium size turbines, making the proposed system suitable for use in an airborne application, while maintaining a high level of reliability and cost performance.

Abstract

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is to develop a manufacturing platform for opioid medicines. Opioids enable physicians to provide compassionate care to patients suffering from acute or chronic disease and trauma. The need for opioid analgesics is even more salient for surgeons anticipating the post-operative recovery of their patients and planning for end-of-life care. However, opioids are highly addictive medicines, a property that has been exploited for commercial gain by certain players in the pharmaceutical industry. The impact of this project will be to deliver a technology that transforms the existing supply chain for opioids by removing the need to grow opium poppy as a drug crop. Instead of sourcing poppy materials from poppy-growing countries, this new technology will allow for complete production of opioids in a secure industrial facility located in the United States where federal agencies can provide oversight and regulation. Additionally, investment in this technology will enable the development of many more existing and experimental medicines derived from plants, including greatly improved opioids with improved efficacy and safety, and cardiovascular and chemotherapeutic therapies that will extend and enhance human lives.

This SBIR Phase II project will develop a bioprocess for opioid active pharmaceutical ingredients (APIs). To date, the only commercially-competitive method for manufacturing opioids and related alkaloids is to extract these molecules from plants. However, Baker's yeast was recently engineered to biosynthesize opioids, which is a technological advance that could enable opioid production by fermentation. However, many technical hurdles remain in developing a reliable and cost-effective, commercially-viable production system based on existing strains. The objective of this Phase II project is to provide a complete demonstration and pilot-scale operation of an API bioprocess that is ready for industrial scale up. The research employs four approaches: 1) Further development of the engineered yeast strains, 2) scale up of fermentation from laboratory scale to pilot scale, 3) optimization of downstream recovery and purification, and 4) evaluation of the resulting products to establish their validity as drop-in-replacements for existing opioid APIs. The outcome will be a process validated at pilot scale and ready for technology transfer to a secure industrial facility that will make and sell into the opioids API market. This research will replace opium poppies with a modern bioprocess that resembles established, standardized pharmaceutical industry methods for antibiotic and biologic APIs.

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.

Abstract

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is to generate inexpensive, reliable electricity through solar cells. As renewables such as wind and solar provide a new low-cost means of generating power domestically, energy storage systems capable of transforming these intermittent sources into dispatchable ones are increasingly commercially attractive. However, conventional energy storage technologies, such as advanced batteries, cannot provide the needed resiliency of on the length scale of days. Ultra-low-cost storage technologies, such as those based on thermal energy storage in earth-abundant materials, have the potential to address this large commercial opportunity. The proposed project will advance the development of a new type of heat engine to convert heat into electricity.

The proposed project aims to move this thermophotovoltaic (TPV) heat engine from the lab to the market. The goal of this project is to develop large-scale and high-yield manufacturing of these cells with industrial equipment and large-area substrates. The proposed project will explore the cost-performance trade space toward the goal of high-volume production of PV material.

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.

Abstract

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project will be to empower farmers to capture a greater share of revenue from the marketing of their crops. Agriculture is a significant engine to the U.S. economy, and farming itself is vital to creating economically vibrant rural areas. Farmers are often at a disadvantage when it comes to capturing good prices from their crops because there are significant information asymmetries in the marketing supply chain. We have developed a combination of hardware and analytics that greatly improves crop forecasts at dramatically more accessible prices, which allows farmers and their trusted buyers to make more informed marketing decisions. Whereas improved agronomy could raise yields by 5-10%, improved marketing could raise revenue >25%, especially for high value crops. In addition to the narrow application of sensing hardware and analytics for forecasting, the data collected by our platform can also be used by growers to make decisions that improve operational performance of complex agribusinesses and improve the agronomy of the farm. These tools make it easier to compare performance of crops to improve yields and reduce resource costs. Together this technology continues to raise productivity and profitability per farmer.

This Small Business Innovation Research (SBIR) Phase I project integrates a completely novel plant and weather sensing platform with analytics that synthesizes data into actionable forms that can drive agribusiness decisions. We have bundled a suite of capabilities into a single hardware unit that includes sensing, communications, GPS, mounting, and solar power, which dramatically reduces the cost and increases the simplicity of collecting agricultural data. These data are uniquely designed to monitor crop performance and its sensitivity to weather and management. Data synthesis is a critical pain point in transforming raw numbers into insights for growers to act upon. By creating an integrated hardware platform, the data is poised to provide useful advice that allow a farmer to act on emerging situations, anticipate upcoming events, and even predict the future. Our research objective here will be to generate probabilistic forecasts that use the unique data from our hardware to estimate key crop growth parameters and project forward for an operational yield forecast. This coupling between highly informative quantitative in-field data and sophisticated parameter estimation and forecast techniques could dramatically improve marketing decisions and help farmers capture better prices for their products.

Abstract

This Small Business Innovation Research (SBIR) Phase II project will demonstrate a prototype of a

high-throughput, agile, low-cost manufacturing system for tile mosaics. Mosaics have been a source of

visual splendor for millennia, but they have always required arduous and painstaking hand assembly.

Our Phase I proved the feasibility of a programmable, high-throughput robotic tile-assembly system to

enhance the production of mosaic tilings. Phase II R&D will build upon Phase I success to further speed

up, automate and scale the system, develop an effective agile manufacturing management system, and

analyze the economic viability of robotic mosaic assembly for Phase III. We will accomplish this by

enhancing the mechanical processes and reducing operator time - in addition to developing a productionflow

information system. After Phase II system optimization, we will evaluate the commercial potential

of the Artaic technology. The anticipated technical result will be providing a 5x faster manufacturing

process with a 75% reduction in the price per square foot of customizable mosaic tilings produced. The

intellectual merits of this SBIR project involve Artaic?s disruptive robotic technology, which transforms

mosaic installation from its current, time-consuming manual labor processes to a rapid, robotically

directed customizable process.

The broader impact/commercial potential of this project expands the utilization of artisanal mosaic work

while increasing the competitive advantage of U.S. manufacturing processes through increased

automation and customization. Successful development of this technology will enable a breakthrough

pricing structure that is 75% lower than the competition (based on manual and rudimentary automated

processes), leading to broad market affordability and widespread commercial adoption. Our robotic

system has the potential to revolutionize the $76B global tile industry, while creating numerous

domestic job opportunities. Artaic expects that the 5x increase in manufacturing speed realized during

Phase I will be maintained in Phase II during manufacturing scale-up without loss of placement

accuracy. The increased understanding of robotic agile manufacturing-enabled mass customization

processes will expand the scientific understanding of related robotic processes that utilize highthroughput

flexible assemblies, such as for medical or pharmaceutical technologies, or for consumer

products. In addition, classical mosaic techniques will become more accessible as an art form to all

students, while undergraduate students will increase their understanding of STEM concepts through

engineering courses utilizing this technology. Artists and designers will find the realization of their

design work much more practical and affordable as a business enterprise.

Abstract

This Small Business Innovation Research (SBIR) Phase II project will develop a computer-aided mosaic

design and robotic assembly system for automation of a centuries-old manual process. Despite their

prominence in art and architecture, mosaics are arduous to design and assemble. Labor-intensive

methods have stubbornly resisted automation, adding considerable cost and delay to projects. Artaic's

Phase I research proved feasibility of computer-aided design software to create renderings and digital

blueprints of artisanal mosaics by introducing a streamlined, procedural workflow for tile layout that

closely mimicked the workflow of mosaic artists, and did so over 10x faster than manual methods. The

goal of the Phase II research is to demonstrate the speed, effectiveness, utility, and artistic quality of this mosaic design and robotic assembly system. The key Phase II objectives are to: (1) demonstrate a

prototype artisanal mosaic design system and; (2) demonstrate a robotic mosaic production system, that

will be: (3) validated for accuracy, speed, and quality through user assessment, and; (4) evaluated for

economic and commercial potential. Anticipated technical results will enable a revolutionary

advancement from manual to automated processes in mosaic design and production, comparable to the

displacement of film by digital camera technology.

The broader impact/commercial potential of this project lies in art, design, construction, and

architecture. Software and robotic automation will lower the cost of mosaics and increase its traditional

societal impact of adorning public, commercial, and residential spaces. Artists, designers, and builders

will have a significantly faster method to produce artisanal mosaics without the high cost and

time associated with manual design and production. The efficiencies made possible by this proposed

computer-aided mosaic design and manufacturing system will enable Artaic to expand into the global

multi-billion dollar tile market and develop a domestic workforce to compete against global

manufacturers of handcrafted mosaic artwork. Additionally, the computational demands of the rendering

algorithms developed during Phase II will give impetus to further development of advanced GPUs and

CPUs -- with companies such as Intel, Nvidia, and AMD providing solutions for increasingly more

advanced rendering algorithms. Perhaps the most significant societal benefit from the development of

this technology is its potential to make artisanal mosaic design and production accessible and affordable

to the general public, and because this research enables any Photoshop artist to become a mosaic artist, it

also hold significant promise as an educational tool in our nation's schools.

Abstract

The broader impact/commercial potential of this project is that it addresses the bandwidth crisis, the problem of transmitting an exponentially growing amount of data through a fixed amount of increasingly congested spectrum. The bandwidth crisis limits economic growth by constraining communication, and also poses very serious challenges for national defense and disaster response. Making better use of limited spectrum is therefore of high societal and commercial importance. This project will study a new approach, called spiral modulation, for achieving much more spectrally efficient communication than previously thought possible and thereby directly addressing the bandwidth crisis. Commercially, this could facilitate much more rapid data transfer, enhancing existing business applications and enabling new ones. Spiral modulation is applicable to any form of electromagnetic communication, whether wireless or wire-based. It could lead to commercialization across a wide range of communication sectors including but not limited to wireless, mobile internet, unmanned vehicles, automotive, aviation, and Internet of Things. It is a dual use technology with both civilian and defense applications. Ultimately, spiral modulation could become the core technology for the worldwide telecommunications industry.

This Small Business Innovation Research (SBIR) Phase II project applies new mathematics to the problem of encoding information into waveforms for telecommunication. In current digital communication, information is transmitted using symbol waveforms constructed from sinusoids which have constant amplitude over each symbol period. This approach is known to produce a sharp upper bound on the highest spectral efficiency that can be achieved. By instead constructing symbol waveforms from sinusoidal waveforms with continuously-varying amplitude, spiral modulation bypasses the theoretical limitation on spectral efficiency. Building on prior Phase I research, this project will build an end-to-end hardware prototype to establish the implementation path and performance characteristics of spiral modulation. The research will progress in stages from waveform design and spectral efficiency measurement experiments, through end-to-end radio design in software, the hardware prototype development and documentation of best practices. It is anticipated that this research will show significant spectral efficiency advantages over existing signal modulation techniques. Other possible advantages for spiral modulation may also appear, such as greater tolerance for interference and phase distortion.

Abstract

The broader impact/commercial potential of this Small Business Innovative Research (SBIR) Phase II project is a significant reduction in the cost and time to remove hazardous contaminants from the soils and groundwater impacting communities.

Properties observed from thousands of contaminated sites serve as inputs to a computerized mathematical model of the site, forecasting the most likely shape and depth of a contaminant plume. This machine learning model gives remediation planners access to a fast delineation of volume to be remediated as well as the uncertainty of the modeled estimate. This saves time and money searching for these contaminants that are deep underground and in groundwater. This Phase II project will expand on the Phase I prototype, creating an operational product capable of reaching the needs of environmental engineers and scientists around the globe, providing the stimulus to cut remediation time and cost in half.

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.

Abstract

This SBIR Phase II project aims to develop a novel engineered microbiome as a potential therapeutic for a rare skin disease called Netherton syndrome. Netherton syndrome (NS) is a rare, severe skin disease with high mortality and few treatment options. This proposal aims to develop a new therapeutic for this disease, a microbe-based protein delivery system of LEKTI, the missing protein responsible for NS symptoms. At the end of this project, a candidate live biotherapeutic product candidate (LETKI-secreting strain of S. epidermidis) will be nominated and the Company will have sufficient data with which to proceed into formal preclinical studies and subsequent human testing. This proposed product will have the potential to address thousands of patients in the U.S., and the broader proof-of-principle of this microbe-based technology offers significant potential to treat millions of patients living with skin conditions. This offers significant advances in innovation in addition to broad commercial potential.

This project aims to develop a novel therapeutic candidate composed of an engineered strain of S. epidermidis that secretes LEKTI protein to the skin for the treatment of Netherton syndrome (NS). NS is a rare but severe autosomal recessive disease that affects the skin, hair, and immune system. NS is caused by mutations in in the SPINK5 gene encoding the serine protease inhibitor lymphoepithelial Kazal-type related inhibitor (LEKTI), which contains 15 serine protease inhibitory domains. The goal of this Phase II project is to demonstrate a proof-of-concept therapeutic for NS: an engineered commensal microbe that delivers discrete domains of LETKI to the skin. The proposed Phase II research plan will establish critical criteria for nominating a potential live biotherapeutic product (LBP) candidate composed LEKTI-secreting S. epidermidis. This research will perform key activities in preclinical development of an LBP: identify an optimal sequence of LEKTI; develop analytical methods for detecting LEKTI secreted from an engineered strain of S. epidermidis; and develop analytical methods for measuring biodistribution and adsorption of LEKTI secreted by S. epidermidis in a human in vitro model.

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.

Abstract

The broader impact of this Small Business Innovation Research (SBIR) Phase II project will be a fundamental advancement in the way people see, understand, and work with geospatial data. The proposed research will commercialize immersive analytics technology across the telecom, Internet of Things (IoT), and transportation industries, all of which use outdated 2D mapping tools. This technology can also improve visualization of data regarding environmental changes, health crises, and other changing situations.

This Small Business Innovation Research (SBIR) Phase II project fuses augmented reality and virtual reality with artificial intelligence to address data visualization pain points in the telecom sector. Like the buildings they inhabit, wireless signals exist in three dimensions and are difficult to represent through traditional 2D charts and graphs. The objective of this research is to develop a an immersive analytics platform where users literally step inside their geodata and manipulate it in real 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.

Abstract

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project will be in the field of healthcare. The United States spends approximately $9,000 per person per year on healthcare. Ultrasound medical imaging is a medical imaging technology that could lower costs by providing an alternative to higher-cost imaging techniques. The technology created during this Phase II project is expected to increase the quality, value, and accessibility of medical ultrasound, which would in turn reduce medical imaging costs in the US healthcare system. Furthermore, the company's technology is expected to bring ultrasound to more clinical settings and improve system-wide efficiencies in the diagnosis and treatment of disease. The technology also has commercial potential in the international market, with $5.8B spent annually on medical ultrasound devices worldwide. Finally, by improving the utility of ultrasound, the technology will lead to improved patient care and may ultimately save lives.

This Small Business Innovation Research (SBIR) Phase II project will develop deep learning technology for ultrasound imaging in medicine. Ultrasound imaging has numerous benefits including real-time image acquisition, non-invasive scanning, low-cost devices, and no known side-effects (it is non-ionizing). However, variability in quality has encumbered its adoption and utility. As a result, more expensive imaging is typically utilized, often exposing patients to ionizing radiation. Our objective is to develop, improve, and test machine learning techniques, based on deep learning, to improve ultrasound acquisition and interpretation. We expect this project will create novel technologies that make ultrasound easier to use and improve the quality of ultrasound examinations. The end result will improve the quality, value, and accessibility of medical ultrasound examinations, will result in cost savings to the healthcare system, will produce improvements in patient care, and will support a sustainable business opportunity.

Abstract

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) project includes advancement of the field of white biotechnology, which utilizes enzymes to create valuable industrial products. As biological molecules, enzymes are more difficult to manipulate than conventional chemicals and often need more extensive development before they can be adapted to industrial or pharmaceutical manufacturing. This SBIR project will demonstrate how enzymes' performance can be improved using stabilization with special synthetic materials known as polymers. Enzymes are characterized by precise, unique structure and function, which is in turn essential for their role in catalysis of complex chemical reactions. Synthetic polymers, on the other hand, despite being less precisely structured, can be rationally designed to withstand or respond to chemical, thermal or biological conditions. The synergistic fusion of enzymes and synthetic polymers results in an advanced enzyme with improved chemical properties, leading to new manufacturing processes for valuable products such as chemicals, biofuels, and pharmaceuticals; these processes should require less energy, utilize fewer hazardous reagents, and generate less waste.

This SBIR Phase II project proposes to develop a combinatorial synthesis device that can feed high-throughput screening of enzyme-polymer conjugates with desired properties (for instance, temperature, pH- or organic solvent stability). To date, only low-throughput synthesis and characterization methods have been applied to the preparation of enzyme-polymer conjugates, limiting development to only few types of polymer modification per protein and depending on stochastic guesswork to select the variants tested. Thus, in order to fully benefit from the diverse set of polymers currently available on the market, it is important to develop methods to scale the identification of optimally performing enzyme-polymer conjugates. This will be achieved through combination of high-throughput synthesis of enzyme-polymer conjugates and high-throughput screening of attained properties. The target application of the proposed research is focused on pharmaceutical biocatalysis. Application of a high-throughput method will not only result in faster research and development cycles, but also will accelerate our development of fundamental knowledge of identifying protein properties that can be achieved through polymer modification, thereby establishing this method for industrial 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.

Abstract

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project will be a user-friendly and scalable infection control surveillance software platform using advanced biotech and data analytics for monitoring hospital-acquired infection. There is a significant clinical problem in hospitals, where 1 in 25 people who check in will develop a hospital acquired infection. Currently, hospital infection control practitioners (ICPs) have few analytical tools to identify the source of these infections, which can be deadly and cost the health care industry an estimate of $45 billion year. The innovation under development harnesses advanced epidemiological approaches in an easy-to-use application that will enable ICPs to use bacterial genetics as a means to monitor infectious spread within their system so that their sources can be eliminated.

The intellectual merit of this SBIR Phase II proposal is to develop an infection control surveillance software system using whole-genome sequencing of pathogens and advanced data analytics. The innovation addresses the critical lack of accessible genetic analysis applications designed for local infection control surveillance. Hospitals are observing ever increasing rates of antibiotic resistant infections. These are expensive, endanger patients, and are becoming harder to trace as medical care becomes more complex and spread over multiple facilities. Unfortunately, ICPs have few new tools, other than best hygiene practices, to reduce their mounting infection rates. Decades of research has revealed that epidemiological surveillance using genetic analysis provides a robust level of pathogen traceability; however, this knowledge has not been transferred into hospitals where it is critically needed, due to a lack of technical infrastructure and analytical accessibility. In this Phase II project, the goal is to complete the development of a software application that will enable ICPs to easily and accurately process bacterial genetic data in their own offices and generate rich, meaningful and easy to interpret reports concerning bacterial spread in their networks. ICPs will be warned when infection sources relate to each other, suggesting that a deeper investigation is needed. The result is that infection sources, which are currently missed, will be proactively identified and targeted.

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.

Abstract

This Small Business Innovation Research Phase II project examines high throughput methods to quantify intacellular microRNA (miRNA) concentrations in cells that have shown to be associated with normal physiological processes, as well as diseases, including cancer. Currently there are no rapid, quantitative methods available to measure miRNA expression in living cells or tumor tissue. All current in vitro approaches require extensive preparation involving extraction, reverse transcription of miRNA into cDNA and amplification. These methods are not only time consuming, but require that the low abundance miRNA be several fold greater than background to give a meaningful result. To meet the demand for a diagnostic/prognostic tool, development of a biomolecular detection device is proposed based on a single electron transistor to bind and measure the concentration of miRNAs. This will provide a researcher or clinician an accurate profile to make proper clinical assessments. Bringing this device to market will provide scientists with direct information on intracellular miRNA levels, enhancing predictions of miRNAs that are essential for tumor maintenance or metastasis, and creating new diagnostic and therapeutic opportunities.

The broader impact of this project will be to enhance current diagnostic and prognostic tools for early detection of disease. Today, early cancer detection and treatment offers the best outcome for patients. This has driven the search for effective diagnostics. The identification of a universal tumor specific epitope or marker has remained elusive. While many types of serological and serum markers have included enzymes, proteins, hormones, mucin, and blood group substances, at this time there are no effective diagnostic tests for cancer that are highly specific, sensitive, economical and rapid. This deficiency means that many cases of malignancy go undetected long past the time of effective treatment. The goal of this research is to bring a device to market for the research market and a device that can examine miRNA profiles from patient samples immediately in a hospital or clinical setting. The current size of the in vitro diagnostic market was over $40 billion in 2008. Unique diagnostic kits developed from this technology will likely fulfill an unmet market opportunity with the potential to exceed $100 million in the first 3 - 5 years.

Abstract

This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5).

This Small Business Innovation Research (SBIR) Phase II project will develop technologies that optimize the use of RNA interference (RNAi) in animals. RNAi is an invaluable tool for characterizing gene function and is a promising candidate for gene therapy. The use of RNAi in tissue culture is well developed but is of limited use in experimental animals. RNAi agents must enter cells to exert their effects but this has proven to be challenging in animals. The current lack of such technologies is holding back the majority of important RNAi animal experiments. To open this bottleneck, kits and reagents will be developed based on Bioo Scientific?s Targeted Transport Technology (T3). Easy-to-use RNAi delivery products will be manufactured, validated and commercialized for use in animal experiments.

The broader impacts of this research are twofold. First, researchers will gain ready access to products that greatly simplify the use of RNAi in animals, thereby, stimulating a burst of validation experiments in animals to try to replicate prior results derived from tissue culture experiments. Animals are more complex than their tissue culture counterparts and it is uncertain that results can be duplicated in an animal. Second, T3 has the potential to be used for the therapeutic delivery of RNAi agents. In sum, this project will propel the validation of tissue culture results via T3 enabled animal experimentation, leading to a better understanding of cellular pathways, the identification of novel drug targets, and the potential to deliver RNAi agents as drugs.

Abstract

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is the development of a technology to accurately measure small RNA expression. This is an enabling life science research tool. Small RNAs are ubiquitous gene regulators found in the body. Products of the same microRNA gene that vary in length by one or two nucleotides may be involved in a host of diseases, including cancer. The value for developing a method to measure the true profile of microRNAs in a sample would be immense for the research community studying transcriptional regulation, and would open the doors to those interested in drug development and diagnostics. The goal of this proposal is to develop a library preparation kit for non-biased small RNA libraries for Next Generation sequencing. These kits will increase the quality and rate at which global microRNA profiles may be determined for research and clinical applications.

This SBIR Phase II project proposes to develop next generation sequencing technology for small RNA more quantitative and less biased. High throughput sequencing has transformed the landscape of genomic research with its ability to produce gigabases of data in a single run. This has enabled researchers to perform genome wide and high depth sequencing studies that would normally not be possible. Despite this capacity, amplification artifacts introduced during polymerase chain reaction (PCR) assays increase the chance of duplicate reads and uneven distribution of read coverage. Accurate profiling using deep sequencing also has been undermined by biases with over- or under-represented microRNAs. The presence of these biases significantly limits the incredible sensitivity and accuracy made possible by next generation sequencing. The goal of this proposal is to develop novel bias-reducing technology for making small RNA libraries. The proposed kits and protocols will increase the rate at which global microRNA profiles can be determined, and between-sample and within-sample differences (as well as newly discovered small RNAs) can be subsequently validated. This product will result in a major shift in the way small RNA sequencing is performed, and will pave the way for the discovery of new small RNAs.

Abstract

This SBIR Phase II project demonstrates and clinically validates a novel, non-invasive imaging technology to detect diabetic retinopathy before structural damage occurs. Diabetic retinopathy is among the leading causes of vision loss in the world. This devastating complication of both type I and II diabetes results in structural damage to the sensitive vasculature of the retina. Once structural damage is inflicted, it is difficult, if not impossible, to ameliorate it. Small changes in the retinal vasculature's oxygen saturation have been shown to be a reliable indicator of diabetic retinopathy before structural damage occurs. Since there is no clinical non-invasive technology capable of detecting these small functional changes, a major need exists for new retinal oximetry technologies. Diabetic retinopathy affects 200 million people worldwide. The American Diabetes Association reports that the cost of diabetes in the US in 2012 was $245 billion, including $69 billion in reduced productivity and $176 billion in medical costs. Since 40% of diabetics are anticipated to develop diabetic retinopathy, the estimated economic cost of diabetic retinopathy is $98 billion annually. By mitigating the occurrence of diabetic retinopathy, this technology will help reduce the cost of diabetic retinopathy treatment, its overall economic burden, and help save the vision of millions of people around the world.

The primary technical innovation behind the proposed technology is its use of a novel physics-based model to overcome the challenges of high-resolution retinal imaging. These challenges include the multi-layered structure of the retina, absorbance dynamics, and the need to produce an image in one snapshot to reduce motion artifacts. Compared with existing methods based on structural imaging, the successful outcome of this project will become a commercial technology-of-choice for ophthalmologists around the world, enabling cost-effective detection of early stage diabetic retinopathy or pre-retinopathy. The development of the technology proceeds through iterative optimization between laboratory and real-use environments to generate robust, validated data. Specifically, in Phase II, the research objectives of the project are pursued in two parallel tracks: 1) refinement of the core imaging system, and 2) validation using model and human subjects in a clinical environment. The outcome of this project will be an easy-to-use, reliable diagnostic imaging and monitoring technology with proven clinical utility in detecting the onset of diabetic retinopathy based on functional properties, before structural damage has occurred in the patient.

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.

Abstract

This STTR Phase II project supports standards-based math education in elementary school classrooms with a hands-on technology intervention. Research has shown that many elementary teachers suffer from low confidence and limited subject content knowledge in math and struggle to develop instruction designed to meet or exceed common core math learning goals. Teachers and researchers alike seek new approaches to engage students and improve teacher effectiveness to improve learning outcomes. The primary goal of this project is the development of a flexible, user-friendly, hands-on robotics kit with associated curriculum and support for teachers, that will engage students in learning math content, align with core curriculum, and measurably increase student achievement. The commercialization of this research-based classroom kit will enable school districts to adopt active learning into their math pedagogy. Ultimately, this promotes the NSF mission to increase national prosperity through science innovation by improving math preparation for students across the United States and preparing them to participate in careers that drive the advancement of science and technology.

The core contribution of this work is composed of a flexible hardware kit to enable active learning within the core elementary curriculum as well as more traditional maker activities, and a suite of apps that allow students to use this kit to learn specific math content while also providing options to learn computational thinking through general purpose programming apps. To accomplish this, the team employs a proven design process in which hardware, software, and curriculum are simultaneously designed to align to learner goals, evaluated in classroom studies, and iteratively refined. The kit will combine the ease of use and simplicity of a regular snap-together style electronics kit with the flexibility of a programmable microcontroller. The apps developed for this project will build on a new math-based paradigm for robot programming. These math-oriented apps will remove the barrier of programming skills for elementary teachers and students alike when using the electronics kit for math instruction. Simultaneously, programming apps will enable open-ended explorations of making and computational thinking. Another contribution of this project will be the testing and analysis of the hardware system and complementary math curricula. Formative evaluation will enable exploration and understanding of novel mechanisms for learning math, and evaluation of the program's efficacy will enable characterization of the impact on student outcomes in math achievement and attitudes towards math.

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.

Abstract

This Small Business Innovation Research (SBIR) Phase II project seeks to further develop a novel computer vision based plant identification system for commercialization in agricultural weed control. This system will provide a cost competitive alternative to chemical herbicides, a global $20B market. Existing computer vision based approaches can segment a 'splotch' of green vegetation from a brown background but are unable to provide the selectivity and precision necessary for mechanized, automated weeding. This project's objective is to create software algorithms that match the capability of the human eye and brain to quickly and reliably classify plants into crops and weeds in real-time. The project team will build a computer vision algorithm based on a hierarchical classifier. This classifier will utilize a field customized support vector machine (SVM) that uses point-of-interest rather than shape-based methods, a novel approach to visual object identification. The result of this research will be the creation of an algorithm integrated into an automated weeding system.

The broader impact/commercial potential of this project is significant, as the development of an alternative to chemical intensive agricultural weed control will impact technological understanding, create commercial opportunity, and positively impact society. Technologically, the project will advance the fields of computer vision and machine learning through development of a real-time, automated plant identification system based on point-of-interest and SVMs. Commercially, the system will offer conventional farmers an effective and chemical-free method to eliminate weeds, and it will offer organic farmers the first truly precise organic weed control method. The addressable market for weed control in food production is estimated to be $4B in the U.S. The system's ability to eliminate the use of chemical herbicides has a profound societal effect. U.S. farmers apply over 250M pounds of herbicide annually on corn and soybeans alone, with many unintended and detrimental side effects. Chemical concentrations in rivers, lakes and groundwater are rising, and the prevalence of herbicide resistant weeds is growing exponentially. An alternative to these chemicals limits society's exposure while protecting environmental integrity.

Abstract

This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5).

The Small Business Innovation Research (SBIR) Phase II project objective is to commercialize a novel technology for indexing video. The company's approach automatically integrates information from speech, text, and video through algorithms that generate rich semantic indexes for video. The Phase I results show that this approach can be incorporated into a system that indexes video with high accuracy and at a fraction of the cost of currently used methods. Further, during the Phase I research, the company has identified a large and growing consumer market (sports video) in which the technology can be applied. The technical objectives of the Phase II proposal focus on working with such partners to roll out initial Bluefin-powered applications, such as content-based search and video-enriched fantasy sports. Such applications are currently not feasible because of the low accuracy of automated indexing methods and the high cost of manual approaches to indexing video.

Millions of hours of new video content are coming online every month, feeding an exploding demand and reshaping the nature of the Internet. Just as text-oriented search engines were necessary to empower users to find what they needed during the first phase of the text-centric Internet, a new generation of technology will be necessary to organize and effectively find content in the fast-approaching video-dominated era of the Internet. Bluefin Lab is pioneering a new approach to video organization and search by commercializing cross-modal algorithms developed in Academe. While this differentiated technology can be leveraged in several target markets, the company's initial focus is on sports media where it will power a unique experience for video search, video-enhanced fantasy sports, and other video-centric applications.

Abstract

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is the development of a high-performance, economic, and sustainable carbon fiber material and associated processing technology for consumer electronics, aircraft interiors, and mass market automobiles. In current processes, roughly 30% of carbon fiber is typically scrapped during manufacturing. By 2024, an estimated 50,000 metric tons of virgin carbon fiber will be scrapped and disposed in landfills. The proposed technology will extract value from scrapped fiber and prevent disposal, offering up to 25% cost reduction compared with carbon fiber products commercially available today. This technology creates higher usage and new opportunities for this advanced material.

This Small Business Innovation Research (SBIR) Phase II project will support the development of a high-performance composite that utilizes low-cost and sustainable milled carbon fiber. An industrial roll-to-roll production process will be used to compound virgin carbon fiber with milled fiber. These reclaimed fibers are oriented in the Z-axis using a proprietary technology adapted from an industrial process originally developed to make thermoset products. The proposed project will develop a market-ready thermoplastic product with dense Z-axis reinforcement while retaining key in-plane properties. This new thermoplastic product will be targeted towards translation to high-volume consumer electronics, aircraft interiors, and automotive 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.

Abstract

This Small Business Innovation Research Phase II project is in support of Branch Technology's novel Additive Manufacturing (AM) process that combines 3D printing technology and conventional construction materials to enable a new way to create buildings. The construction market in the US is approximately 8% of GDP. Any portion of the market that could be enhanced would have a large impact in the US economy. To that end, Branch is creating a process similar to building found in the natural world. In the formation of natural systems, material is the most expensive commodity; a structure is derived by the efficient use of material, but shape is free to be created in almost any form. Branch can approach this efficiency with additive manufacturing, where form is created and material is deposited only when needed and little waste is created. At the core of Branch's method of AM-based construction are three key developments: a three-dimensional freeform structure (the cellular matrix or lattice) which serves as a scaffold for other materials, a robotically- controlled extrusion mechanism by which the cellular matrix is produced, and the algorithms necessary to control the robot for successful production. The proof of concept for this process and more have already been demonstrated by Branch in Phase I of this grant.

The technical objectives for Phase II focus on improving the procedures and technology already created. The focus areas for this phase are algorithm development, hardware improvements, the application of finishing materials, code compliance testing, and material science experiments. Algorithm development consists of refining and creating the software necessary to extrude the printed matrix and support a client base. Hardware improvements are necessary to improve the speed and efficiency of the process to create a commercially viable workflow. This research will necessitate the purchase of extra hardware for experimentation. American Society for Testing and Materials (ASTM) testing for load bearing capacity is necessary to enter the market and provide code compliant construction. Experimentation in the application of finished materials to the 3D printed lattice such as spray foam and concrete are vital to the realization of complete buildings.

Abstract

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is to improve diagnosis of pediatric otitis media (ear infection). Otitis media is the leading cause of unnecessary antibiotic use in children and the second most common pediatric physician appointment. It is estimated that more than 90% of children will suffer at least one case of otitis media before age 5. Despite its prevalence, there may be less than 60% diagnostic accuracy in primary care where the vast majority of cases are seen. Current clinical diagnostics have proven inadequate to address over-prescription of antibiotics and unnecessary specialist and surgical referrals. Otitis media is typically diagnosed using an otoscope to view the tympanic membrane (eardrum) and assess visual signs of an infection. Otoscope designs have changed little since the 1800’s. This SBIR Phase II project advances a novel device that integrates clinical standard otoscopy with a novel technique to non-invasively assess ear health using light in real time and with 98% accuracy. This new otoscope has the potential to create a new standard of care in diagnosis and management of otitis media, and stands to save billions in direct healthcare costs through more accurate diagnosis.

This Small Business Innovation Research (SBIR) Phase II project will advance translation of a device providing clinicians with an objective, real-time indicator of ear health during standard otoscopy. At the push of a button, the LED driven measurement will provide an instantaneous, accurate indication of the presence or absence of middle ear effusion (MEE) – the most sensitive and specific indicator of acute otitis media per established clinical guidelines. This project will meet the desired technical specifications of sufficiently sensitive visualization capabilities and reducing measurement time from 1.4 seconds to less than 300 milliseconds. This project will also: 1) Optimize manufacturability and assembly; 2) Develop a standard automated calibration system; and 3) Conduct standard electronic, photobiologic, and biocompatibility testing for safety and regulatory 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.

Abstract

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project comes from addressing the thermal challenges brought about by the significant increase in transistor density that semiconductors have experienced over the past few decades. This trend has enabled many advancements ranging from high performance servers to Internet of Things devices. Still, with every advance in chip technology, the difficulty of chip cooling continues to increase. Three major thermal interface material (TIM) market segments exist: polymer composites, metallic materials and phase-change materials. Commercial carbon nanotubes (CNTs) will create a fourth market segment that will supplant existing TIMs, initially in the chip testing market and eventually extending into servers, high performance computing and Internet of Things devices. CNT researchers and small businesses have made little progress towards a commercial TIM product. Among other factors, this failure is driven by poor positioning in the crowded low-cost TIM space, which is currently dominated by thermal greases and pads. Progress towards a viable solution lies in the strategic alignment of product features with industry pain points. This Phase II SBIR aims to develop a means to scale the ability to produce CNT based TIMs as well as to further improve their performance.

The technical objectives of this SBIR Phase II project are to: 1) scale up of the CNT TIM manufacturing process to achieve a production capacity of 200,000 sq. in of product annually and to 2) enhance the conductivity of the CNT array by a factor of 3x or more to facilitate entry into the TIM1 and TIM2 market. This project will ultimately develop processes that will translate into achieving production scale CNT based thermal interface materials for the first time in the world. Scale up will be achieved through a combination of physical vapor deposition and chemical vapor deposition processes developed on tools designed specifically for CNT production. In Phase I of this research effort, two commercial products aimed at the semiconductor chip testing market were developed and validated through collaboration with leading chip manufacturers. In addition to the chip testing market segment, in Phase II products will be developed for entry into the TIM1 and Internet of Things markets.

Abstract

This Small Business Innovation Research (SBIR) Phase II project may improve student achievement. Within U.S. higher education institutions, $47 billion per year is spent on academic support for roughly 22 million students. When a child struggles after a lecture ends, help has historically been delivered by tutors and homework hotlines; Those avenues can be inadequate in closing learning gaps for students after they exit the classroom. The Smart Study Recommendations Engine is expected to further democratize homework assistance and help with studies outside the classroom. As a peer to peer platform, the technology may shrink the cost of personalized homework and out of classroom assistance, enabling students to proceed at their own time and pace. This platform seeks to especially impact students from economically- or socially-challenged backgrounds. The goal of the project is to help make academic success more attainable, common, and inclusive for all students everywhere. The technology is initially being deployed in U.S. colleges and universities, with the goal of achieving a global impact.

This Small Business Innovation Phase II project harvests data from internet study resources, analyzes the resources to surface predictive insights, and automatically delivers wide-ranging, peer-reviewed, personalized study materials to help students close learning gaps, without requiring the students to perform complex internet searches. The project will also provide students with the ability to connect with capable peers who can provide additional support by listening to their issues and providing deeper subject clarity. The company is using machine learning as the underlying technology to enable the Smart Study Recommendations Engine.

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.

Abstract

This Small Business Innovation Research (SBIR) Phase II project proposes the development of an ultralow-power ultrasonic three-dimensional (3D) rangefinder system for mobile gesture recognition. The proposed 3D rangefinder uses an array of tiny piezoelectric ultrasound transducers which are built on a silicon wafer using microfabrication techniques. Custom electronics are used to control the transducers and the system emits sound into the air and receives echoes from objects in front of the transducer array. The proposed ultrasonic 3D rangefinder has the potential to be small and low-power enough to be left on continuously, giving devices such as smartphones, tablets, and wearable electronic devices a way to sense physical objects in the surrounding environment. Based on the smartphone market alone, the potential market size for this device is over one billion units per year. Mobile contextual awareness will enable 3D interaction with smartphones and tablets, facilitating rich user interfaces for applications such as gaming and hands-free control in automobiles. Looking beyond the smartphone and tablet market, the proposed rangefinder will feature size and power advantages that will permit integration into centimeter-sized devices which are too small to support a touchscreen.

During Phase II, the major technical goals of this project are to transfer the ultrasound transducer manufacturing from a university laboratory to a commercial production facility, to develop a custom integrated circuit for signal processing, and to develop engineering prototypes. In Phase I, micromachined ultrasound transducers having a novel structure designed to improve manufacturability were developed and a demonstration prototype was built using signal processing algorithms running on a personal computer. In Phase II, the ultrasound transducers will be manufactured in a commercial facility for the first time and signal processing algorithms will be realized on a custom mixed-signal integrated circuit. A prototype package for the transducer and integrated circuit chips will be developed and detailed acoustic testing of the packaged prototypes will be conducted.

Abstract

Diesel engines remain critical to global economies, but are under threat from increasingly-stringent emissions regulations. Many alternatives, like spark-ignition and electric vehicles, sacrifice some of the performance or range benefits of Diesel-style operation. This creates a market need for technologies that can maintain Diesel engine performance while remaining decoupled from the dirty emissions of Diesel fuel. This proposal centers on the development of the ?ClearFlame Combustion System? (CFCS): a novel combustion process that enables Diesel-style engines to combust low-carbon alternative fuels like ethanol and methanol without sacrificing the power possible with traditional Diesel combustion. Further, the sootless nature of alternative fuels such as methanol and ethanol obviates the need for a Diesel particulate filter, and enables stoichiometric air-fuel ratios to eliminate the need for selective catalytic reduction of NOx (smog). The engine technology has the potential to alter the dynamics of any market dominated by Diesel engines (including heavy-duty transportation, agriculture, rail, and power generation) and can be licensed to, or jointly developed with, OEMs for simple integration into their existing product lines. Phase I results have shown a 30% increase in engine torque at increased efficiency, while engine-out soot emissions are more than 100x lower than that of Diesel engines, falling under the 2010 EPA regulation limit without aftertreatment.

This Small Business Innovation Research Phase II project will continue development of the CFCS. The Phase I results showed that three critical CFCS subsystems?engine insulation, alcohol direct injection, and a combustion chamber optimized for stoichiometric combustion with exhaust gas load control?could be developed and integrated to achieve a previously unattainable combination of strong performance and low emissions. This Phase II effort will further advance these key components and demonstrate the benefits of the CFCS on a commercial engine platform, using CFD modeling and engine experiments to show the advantages of the CFCS compared to the Diesel baseline. The goal is to show how the CFCS enables a multi-cylinder heavy-duty engine to simultaneously improve power density by 30% at no loss of efficiency, while also achieving sootless stoichiometric exhaust conditions that are compatible with low-cost and highly-effective three-way catalysis (the same system that enables gasoline and natural gas engines to be much cleaner than Diesel). A Phase II prototype demonstration would realize a longtime industry goal of integrating three-way catalysis with a Diesel-style engine, allowing Diesel-style engines to achieve the emissions profile of the cleanest alternatives (like natural gas).

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.

Abstract

This Small Business Innovation Research Phase II project enables the development of the next generation of contact lenses for vision correction based on a novel photomodification technique called "LIRIC (Laser Induced Refractive Index Change)." More than 2.3 billion people world-wide suffer from refractive error in their visual system, while over 500 million have inadequate access to refractive correction. Glasses are an option for refractive correction, however there can be practical limitations and even social stigma associated with wearing glasses, particularly among adolescents. Meanwhile vision correction with contact lenses is limited to lenses whose optical prescription is determined by their thickness profile. This has negative consequences for visual quality, on-eye stability and corneal health. The research represents a fundamental shift in how vision correction is applied because it alters the refractive index of an optical material, enabling previously unavailable visual correctors in thin, stable contact lenses. LIRIC uses a high repetition rate, femtosecond laser to micro-modify the local medium to produce custom refractive corrections in hydrogels, and in living cornea. LIRIC works by accumulating localized refractive index (RI) changes in an ocular material to create a refractive lateral gradient index lens.

Changing the refractive index using LIRIC instead of the surface shape can lead to several fundamental advances for vision correction, with profound implications for vision care: 1) contact lenses can be manufactured specifically for patient fit and stability with the refractive correction decoupled from the lens shape; 2) difficult and irregular refractive corrections (i.e. for irregular astigmatism, presbyopia, and higher order aberrations) could be written more easily and with better spatial resolution than with existing methods; 3) multifocal and diffractive optical designs can be utilized for presbyopic and macular degenerative corrections. Patients viewing through LIRIC lenses, created in Phase I, had visual performance (visual acuity and contrast sensitivity) on par with a control lens. The objective of the Phase II work is to demonstrate that LIRIC works in contact lenses at process speeds necessary for commercial manufacturing. The goal of this work is to demonstrate that a 6.5 mm optical zone can be successfully processed in <15 seconds. To effectively do so, the LIRIC process has to achieve more than 1 wave of phase change (at 555 nm wavelength) at laser scanning velocities in excess of 10 meter/second.

Abstract

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is aimed at improving healthcare patient outcomes, potentially saving lives, and decreasing healthcare costs. The Drug Quality and Security Act of 2013 set stricter manufacturing standards on sterile injectable compounded medications that have closed many third party suppliers, thus creating shortages and higher prices. In response, the American Society of Hospital Pharmacists expects 40% of the US market, 2000 hospitals, by 2018 to receive insourced compounds. Hospitals that insource hope to decrease their costs and improve patient safety with higher quality product. Today, insourcing hospitals often have multiple information systems and use paper records cobbling together how a compound is made and to whom it has been administered. When an ingredient recall occurs, hospitals spend hundreds of man-hours identifying the problem source and affected patients. To prevent further patient risks speed is demanded. This SBIR Phase I project will provide hospitals the capability of an end-to-end quality management that will track every production process step and tracing medications to patients. Hospitals will be able to prevent patients from receiving recalled medications and identify quality production compromises thus improving patient outcomes and potentially saving lives.

The proposed project is a novel medication barcoded label encryption technology compatible with existing hospital scanners to provide track and trace capabilities of intravenous medication compounds. Key objectives include both patient specific and anticipatory workflows with labels, a Passive Auditing management system for compounding quality control, and an innovation to improve operating room environment medication barcode scanning compliance. Today, healthcare providers utilize multiple barcoded label technologies with minimal embedded medication data across disparate systems. Medication labels could be the link across these systems for ingredient traceability. However, existing solutions are inadequate to meet 2013 legislative traceability mandates. The project invention will encrypt serialization fields within the barcoded label connecting a specific medication to its production data, and eventually to the patient. Compounding process data, such as ingredients, environmental conditions, and production instructions, will be connected to individual medication labels and stored in the patient?s electronic record. When an ingredient is recalled or questionable process identified, an extraction algorithm will pull the encrypted data from the EHR and will be connected to production data. Success of this project will be label readability by existing hospital scanners and retrieval of the serialized data from the EHR

Abstract

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) project is to provide a solution to the problem of drinking water contamination by developing an advanced adsorbent for point-of-use/home filtration applications. Micropollutants, pharmaceutical residues, pesticides, industrial chemicals and other organic compounds present in water resources at trace concentrations of one part per billion and less, are recognized as a major factor of contamination. Consumers around the world no longer trust the safety of their drinking water due to the presence of micropollutants and other contaminants. These compounds are pervasive and can present toxicity at trace concentrations. As a result, consumers have significantly increased the non-sustainable use of plastic bottled water, now a $260 billion market. Current point-of-use filtration products are primarily designed to improve taste and odor, and are generally ineffective in removing micropollutants. CycloPure's technology has been developed specifically to target and remove micropollutants from water. This project focuses on the further development of the company's cyclodextrin adsorbent to improve the effectiveness of point-of-use filters. This material can be used as a drop-in replacement without changes in filter design. CycloPure's materials will allow households to safely use readily available tap water.

This SBIR Phase II project proposes to identify strategies to develop a suitable form factor to incorporate CycloPure's high-affinity cyclodextrin adsorbent into point-of-use filters. The company's adsorbent is formed by reacting cyclodextrins, which are derived from corn starch, with readily available monomers in a single step process. During the Phase I period of this project, scalable reaction conditions were identified for production of the adsorbent in powder form. Flow-through applications, such as gravity filters, frequently require granular particles to achieve desired flow rates. Early activities will focus on the preparation of the adsorbent in granular form to demonstrate scalability and retention of removal performance similar to powder form. Thereafter, column studies will be performed in order to assess the removal performance of granular media under flow-through conditions at environmentally relevant micropollutant concentrations. Following identification of adsorption characteristics and appropriate flow conditions, a prototype point-of-use filter will be constructed and tested for the removal of micropollutants from tap water using advanced analytical techniques, including a combination of target and non-target screening approaches.

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.

Abstract

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project will be to allow more consumers to make use of assisted and autonomous driving systems in automobiles. Fully Autonomous Vehicles (AV) will reduce traffic collisions and enable humans to spend less time driving and more time on productive activities. Commercially deploying AVs requires a number of key technologies including sensing, perceptual systems, motion planning, and actuation. Our discussions with leaders and decisionmakers at automotive companies have shown that the development of robust, accurate, and energy-efficient perception systems is a major technical obstacle to creating mass-producible autonomous road vehicles. Of particular interest to automakers is scaling down the computational requirements of perceptual systems while preserving high levels of accuracy and robustness.

This Small Business Innovation Research (SBIR) Phase II project will use deep learning to create perception systems that are (a) scalable across different computational platforms and (b) scalable across smaller or larger sensor sets. Specifically, the company will develop scalable systems from small compute platforms (used for Highly Automated Driving) to somewhat larger compute platforms (used for Fully Automated Driving). Further, the company will develop perceptual systems that scale from few sensors to many sensors. The goal is to "do more with less," advancing the pareto-optimal frontier of efficiency-accuracy and price-accuracy tradeoffs. The company has already engaged with automotive OEMs and suppliers to develop partnerships and to define metrics for success in this endeavor.

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.

Abstract

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project on hospital service robots is improving the quality of care in hospital systems that are under increased pressure to provide high-quality patient-centric care while functioning as profitable businesses. Hospitals face a shortage of qualified nurses and high rates of nurse turnover. Nurses play a critical role in communicating care plans, educating patients, and guarding against medical errors. The amount of time they spend in direct care activities is a key determinant of patient satisfaction, better patient outcomes, fewer errors, and shorter lengths of stay. In the face of nursing shortages across the U.S., it is increasingly important to have nurses performing at the 'top of their license'. Reducing the amount of time they spend on non-nursing tasks is crucial to this goal. Automation could address these challenges and labor shortage by allowing clinical staff to focus on providing skilled care. The proposed project aims to develop technology that is general-purpose enough to transfer to other markets, such as long term care facilities and, eventually, individual consumers. Robots that perform assistive tasks in homes could increase the feasibility of independent living for many older adults.

The proposed project will establish the technical and commercial feasibility of developing hospital service robots that act as assistants on acute care units, enabling nurses to spend more time at the bedside with patients. This project will make technical advances along three dimensions: the ability of the proposed robot to autonomously navigate within nursing units and across the hospital (navigation capabilities); to easily adapt its manipulation skills to specific tasks and to physical characteristics of a particular hospital/unit (adaptive learning of manipulation skills); and to work alongside humans in a socially acceptable manner, including appropriate navigation in crowded hallways, speech, and eye gaze behaviors that communicate the robot's intentions (socially intelligent interoperability). The team intends to collaborate closely with a single partner hospital to iteratively improve the reliability and robustness of the artificial intelligence software suite developed with NSF funding and to deploy production-quality versions of the three core competencies. The final 6 months will involve a long-term deployment, with the robot autonomously working on an acute care unit of the partner hospital. The impact of the robot on unit staff and workflows will be documented, with the ultimate goal of developing a service robot that hospital staff view as a competent member of the care team.

Abstract

The broader impact/commercial potential of this STTR Phase II project will result in significant economic activity through the utilization of waste carbon dioxide. The photo-catalytic reactors funded in the project will lead to novel methods to chemically store energy from the sun. Each year, human activity releases 38 billion tons of carbon dioxide into the atmosphere. Dimensional Energy envisions a future in which we can utilize this carbon dioxide as a feedstock for industrial production of hydrocarbon fuels and chemical intermediaries by harnessing the power of the sun.

This STTR Phase II project proposes to develop HI-Light - a photo-thermo-catalytic reactor platform technology that enables the conversion of CO2 and water to synthesis gas at a rate significantly greater than the state of the art. The unique feature of the technology is that it uses embedded optical waveguides to evenly distribute light within the reactor, increasing the efficacy of the catalyst and ultimately the productivity of the system. In Phase I a fully functional integrated prototype reactor was constructed, demonstrating continuous operation, and showing productivity in terms of the grams of hydrocarbon produced per gram of catalyst per hour more than 10x greater than the state of the art. The approach solves the two major roadblocks in photo-conversion of CO2: (1) the semiconductor catalysts can only use photons with energies greater than their bandgap, which is a small fraction of those present in sunlight and (2) a large fraction of the catalyst material in these reactors is under-utilized due to sub-optimal light and reactant delivery. Our unique reactor uses a patented, multi-scale approach to enhance light and reagent transport directly to the reaction site and makes use of traditionally unused photons to provide heat and enhance reaction efficiency.

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.

Abstract

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is empowering the 68 million U.S. natural gas consumers and their transaction managers and partners to access transaction status in real time, enjoy continuous control of their transactions, settle transactions in time scales less than the industry’s current monthly accounting cycle, and enjoy heightened levels of security. The United States natural gas industry has operated in its present physical form for more than a century, and over the past four decades the industry has evolved through various policy and regulatory actions to open transaction participation to thousands of parties. In other industries, the past two decades have introduced digital capabilities that share transaction information and automate select functions, but these developments have not enjoyed infusion in natural gas transaction management processes. The proposed solution will serve as a platform for industry innovation by multiple parties, reducing transaction cost and increasing speed. This innovation will have applications in other industries characterized by complex, multi-party transactions.

This SBIR Phase II project proposes to advance blockchain innovations and related technologies to transform complex natural gas utility transaction management processes across production, transmission, distribution and consumption functions. The proposed solution will accelerate the development of third-generation smart contracting frameworks with user-friendly/interactive human-machine-interfaces (HMI) and predictive and interactive smart contracting functionalities based on artificial intelligence, and with advanced cybersecurity measures.

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.

Abstract

This Small Business Innovation Research (SBIR) Phase II project seeks to further quantify the mechanical performance of mycological bio-composites that address the automotive and structural core industries, while concurrently scaling and demonstrating material production. The engineered composites market continues to grow steadily because of the high strength-to-weight and stiffness-to-weight ratios of these systems, as compared to conventional engineering materials. Engineered woods are ubiquitous in the construction and furniture industries, but due to domestic indoor air quality regulations (Toxic Substances Control Act), these materials are being phased out or are forced to use expensive formaldehyde-free adhesives. Similarly, the automotive industry is under regulatory pressure in Europe to find alternatives to fire-retardant foams that cannot be recycled due to inorganic filling agents. The technical results from the Phase I effort have demonstrated bio-composite materials which can compete both economically, and on mechanical performance, with the aforementioned competitors, while meeting these legislative demands. A preliminary cost analysis based on the process economics of our existing production facilities projects retail costs 45% and 35% below the current state-of-the-art in the automotive and furniture industries, respectively. We will work with key industry partners to meet performance metrics and demonstrate quality pilot production.

The broader impact/commercial potential of this project would be a customizable bio-composite for a broad range of markets, including automotive, transportation, architectural, furniture, sports, and recreation. These materials are truly sustainable, since both the laminates and cores used in the sandwich structure consist of renewable materials. They also require significantly less energy to make than other biocompatible composites, because the material is grown instead of synthesized, and the material is completely compostable at the end of life. The outcome of the proposed development and demonstration will ensure that the bio-composite properties meet the requirements for the target markets. Furthermore, over the course of this grant, and in cooperation with Rensselaer and Union College, we will demonstrate and scale the best manufacturing processes to a pilot stage capable of manufacturing high volumes of quality product. Since these materials leverage regional lignocellulosic byproducts from domestic agriculture and industry, a regional manufacturing model is presently being pursued to reduce transportation and feedstock costs. This will not only bring additional value to U.S. agricultural markets, but will spur rural economic development through domestic manufacturing. Finally, these advanced biological materials represent a new paradigm in manufacturing, offering safe, biodegradable alternatives to traditional petroleum-based alternatives.

Abstract

This Small Business Innovation Research (SBIR) Phase II project seeks to further develop, and demonstrate at scale, a biological disinfection process that has exhibited superior microbial inactivation to steam pasteurization at a lower cost. This process leverages dilute concentrations (0.5-0.875% by volume) of plant-derived phenols and aldehydes to inactivate lower level fungi and bacteria found on agricultural byproducts (seed husks and hulls). The application focus for this demonstration is a novel material technology th