Grant List
Represents Grant table in the DB
GET /v1/grants?page%5Bnumber%5D=1391&sort=funder_divisions
{ "links": { "first": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1&sort=funder_divisions", "last": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1424&sort=funder_divisions", "next": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1392&sort=funder_divisions", "prev": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1390&sort=funder_divisions" }, "data": [ { "type": "Grant", "id": "15117", "attributes": { "award_id": "2418011", "title": "SBIR Phase I:Combinatorial Platform for the Discovery of Improved Molecular Recognition Components for Use in Therapeutic and Diagnostic Antibodies", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Technology, Innovation and Partnerships (TIP)", "SBIR Phase I" ], "program_reference_codes": [], "program_officials": [ { "id": 773, "first_name": "Erik", "last_name": "Pierstorff", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2024-09-01", "end_date": null, "award_amount": 273550, "principal_investigator": { "id": 31668, "first_name": "Christopher", "last_name": "Szent-Gyorgyi", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 2510, "ror": "", "name": "BIOCOGNON LLC", "address": "", "city": "", "state": "PA", "zip": "", "country": "United States", "approved": true }, "abstract": "The broader impact of this Small Business Innovation Research (SBIR) Phase I project is the fundamental improvement of crucial antibody components that recognize and bind therapeutic or diagnostic targets. Modern antibodies are usually engineered as protein chimeras comprised of different parts, including one to several molecular recognition domains that mediate binding. The proposed research will integrate breakthroughs in next generation DNA sequencing and synthetic and computational biology to create a combinatorial high throughput platform for generating better recognition domains. The core aim is to creatively and efficiently use genetic information from patients, pathogens and antibodies for the advancement of therapeutics and diagnostics across a spectrum of diseases. The platform could expedite the design and discovery of current antibody-based therapeutics to reduce the enormous costs and time required to bring these drugs to market. The platform is ideally suited for the development of new classes of therapeutics where very rapid, adaptable and inexpensive response is required, such as in truly personalized treatments of continuously changing tumors or in rapidly evolving viral pandemics where passive vaccines need to be generated at scale.<br/><br/>The proposed project will demonstrate that a novel yeast-based high throughput screening platform is able to efficiently generate molecular recognition domains that specifically recognize clinically important targets. The proof-of-concept target antigens are a human receptor/ligand pair important for the immunosuppression of certain cancers and a coronavirus surface protein that mediates infection by binding a human receptor. In these screens, the use of yeast cells that surface display antibody recognition domains, and secrete these target antigens from the same cell, enables next generation sequencing to identify the genetic information encoding both the domain and the target. This dual detection capability is made possible by innovative fluorescent biosensors and is unique to this screening platform. The project will utilize synthetic biology to construct a library with a rich variety of recognition domains that will be screened simultaneously against several target antigens of varying design. Next generation sequencing analysis will show that it is practical to implement combinatorial screens using engineered recognition domains and antigens to identify recognition domains with desired binding specificity and affinity.<br/><br/>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.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "14397", "attributes": { "award_id": "2038067", "title": "SBIR Phase I: Open Machine Learning Competitions with Private Data", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Technology, Innovation and Partnerships (TIP)", "SBIR Phase I" ], "program_reference_codes": [], "program_officials": [ { "id": 1211, "first_name": "Peter", "last_name": "Atherton", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2021-08-01", "end_date": null, "award_amount": 256000, "principal_investigator": { "id": 31002, "first_name": "Peter", "last_name": "Bull", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 2460, "ror": "", "name": "DRIVENDATA, INC.", "address": "", "city": "", "state": "CO", "zip": "", "country": "United States", "approved": true }, "abstract": "The broader impact of this Small Business Innovation Research (SBIR) Phase I project will be to expand access to artificial intelligence (AI) talent and spur innovation to solve hard problems while protecting privacy. Machine learning and AI are bringing transformational change to governments, private companies, and social sector organizations. Yet in the coming years, innovation will be hamstrung by limited access to AI talent. Open innovation, such as machine learning (ML) competitions, provides governments and firms the ability to tap into a global talent pool to solve some of their most pressing and vexing challenges. Yet there is currently an immense barrier to running these competitions: the data must be made available to participants, which can preclude running a competition if the associated data are too sensitive to release due to concerns about privacy, security, or confidentiality. With data talent in increasingly high demand, government agencies, companies, and others have demonstrated a willingness to invest in this fashion. The proposed project develops a method to maintain data privacy at scale. <br/><br/>This Small Business Innovation Research (SBIR) Phase I project will develop an end-to-end competition system that provides privacy guarantees for data used to build crowdsourced algorithmic solutions. Open ML challenges typically work by providing participants with training data to learn underlying patterns, then evaluating resulting predictions on unlabeled test data. For many important problems, making training data available in this way violates concerns about privacy or enables abuse. The critical gap is preserving the privacy of training data while enabling participants to build models that can learn from it. This project will bring together recent advances in three of the most promising approaches in privacy-preserving data analysis: homomorphic encryption, federated learning, and differential privacy. Each technique will be developed and tested in a dedicated challenge structure with two core properties: 1) to preserve the privacy of sensitive data; and 2) to ensure competitors are able to get feedback on submitted models during the competition to inform algorithm improvements. Each competition system will result in a set of performance measures, including benchmarked algorithm performance and data privacy guarantees, to assess system feasibility.<br/><br/>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.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "14404", "attributes": { "award_id": "2126156", "title": "SBIR Phase I: Real-time Predictions During Water Treatment: An Intelligent and Proactive Pathway to Preventing Environmental/Health Hazards and Reducing Operational Costs", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Technology, Innovation and Partnerships (TIP)", "SBIR Phase I" ], "program_reference_codes": [], "program_officials": [ { "id": 1782, "first_name": "Rajesh", "last_name": "Mehta", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2021-08-01", "end_date": null, "award_amount": 256000, "principal_investigator": { "id": 31011, "first_name": "Young", "last_name": "Lee", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 2462, "ror": "", "name": "AdvanceH2O Corp.", "address": "", "city": "", "state": "NY", "zip": "", "country": "United States", "approved": true }, "abstract": "The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I Project is to develop next-generation monitoring & data informatics for wastewater treatment plants (WWTPs). Industry standards to test WWTP performance typically measure the chemistry of the incoming wastewater (influent) and finished output (effluent), without insight into the intervening stages. This lack of data can result in significant environmental and human health hazards for end-users, as well as regulatory fines for WWTPs. This project advances advanced microbial analytics specifically for water treatment to proactively predict and prevent negative impacts at reduced energy, chemical, and financial cost. This project has global application. <br/><br/>This SBIR Phase I Project will combine: 1) Advanced microbial analytics tailor-made for water treatment, including global analysis of DNA, RNA, and profiles from the system microbiomes; and 2) Artificial Intelligence (AI)/Machine Learning (ML). This project identifies real-time WWTP performance predictions based on advanced microbial analytics (key drivers during treatment) to inform process control measures to optimize plant operations. For advanced microbial analytics, the objective is to prove reliable characterizations of microbial ecosystems in WWTP reactors, and to help maintain consistency and stability of the ecosystems over time. This project will propose and optimize a sampling, analysis, and reporting plan for infusion at scale.<br/><br/>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.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "15649", "attributes": { "award_id": "2451399", "title": "SBIR Phase I: Novel Peptide Immunomodulators for Treatment of Autoimmune and Inflammatory Disorders", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Technology, Innovation and Partnerships (TIP)", "SBIR Phase I" ], "program_reference_codes": [], "program_officials": [ { "id": 936, "first_name": "Henry", "last_name": "Ahn", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2025-03-01", "end_date": null, "award_amount": 305000, "principal_investigator": { "id": 32152, "first_name": "Masha", "last_name": "Fridkis-Hareli", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 2552, "ror": "", "name": "PALENA THERAPEUTICS, INC.", "address": "", "city": "", "state": "MA", "zip": "", "country": "United States", "approved": true }, "abstract": "The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is in developing a novel class of compounds capable of treating autoimmune and inflammatory conditions safely and effectively. With the constant threat of new COVID variants, influenza, and RSV, there is an unmet medical need for therapeutics that can effectively treat autoimmune diseases especially in pediatric patients without compromising the immune system to respond to infections. This problem has been overcome with the discovery of novel compositions that demonstrate efficacy equal or superior to many of the first line therapies used to treat immune diseases. The improved safety, efficacy and lower cost of these therapeutics should provide a significant benefit to patients by overall contributing to their quality of life as compared to current medications, as well as marketing and partnering advantage in its commercialization efforts, which will focus on rare diseases, such as juvenile idiopathic arthritis-associated uveitis and pediatric Crohn’s disease among others. In the era of socio-economic disparities, these affordable drugs will become available to the historically neglected low-income communities. If executed successfully, this proposal would validate the platform technology and demonstrate the feasibility of identifying candidates for further development into life-changing treatments. This Small Business Innovation Research (SBIR) Phase I project will demonstrate the unique design of novel compounds to augment and re-program the immune responses from pro- to anti-inflammatory, based on the binding to MHC class II molecules that leads to immunomodulation. The technical complexities of understanding the effects of peptide sequences on the outcomes of cellular interactions present challenges related to selecting the appropriate amino acids both for the random and specific components of these compositions. These hurdles will be addressed by design of several candidate compounds for each target condition, juvenile idiopathic arthritis-associated uveitis and pediatric Crohn’s disease, that will take into account the structure of autoantigenic peptides known to interact with both the MHC class II and T cell receptor (TCR). These candidate compounds will be initially tested in vitro in human macrophages to assess their potential to inhibit secretion of pro-inflammatory cytokines. Of these compounds, the most efficient ones will be tested for activity in relevant animal models. This approach will allow identifying and selecting the best drug candidates for further development into therapies for pediatric conditions as outlined above. 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.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "5130", "attributes": { "award_id": "1046488", "title": "SBIR Phase I: A Batteryless Wireless Impedance Sensor System For Gastroesophageal Reflux Diagnosis", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Technology, Innovation and Partnerships (TIP)", "SBIR Phase I" ], "program_reference_codes": [], "program_officials": [], "start_date": "2011-01-01", "end_date": "2011-12-31", "award_amount": 150000, "principal_investigator": { "id": 18269, "first_name": "Smitha", "last_name": "Rao", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 1372, "ror": "", "name": "Talus Atomics Corporation", "address": "", "city": "", "state": "TX", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 1372, "ror": "", "name": "Talus Atomics Corporation", "address": "", "city": "", "state": "TX", "zip": "", "country": "United States", "approved": true }, "abstract": "This Small Business Innovation Research (SBIR) Phase I project explores advanced technologies to develop a transformative miniature batteryless wireless impedance sensor that is suitable for endoscopic implantation through the mouth and esophagus for the comfort and convenience of patients in the diagnosis and prognosis of gastroesophageal reflux disease (GERD). An implantable miniature batteryless wireless device that does not require externally tethered connections and has the ability to detect acid and nonacid episodes is preferred for esophageal reflux monitoring by both patients and doctors. The proposed system consists of a miniature nanowire-based sensor which can be attached on esophagus wall for a long period of time and an external wearable reader. The impedance variations from the sensor can indicate episodes of reflux that are both acidic and non-acidic in nature. The intellectual merits in this project include the optimization of wireless power transfer efficiency for human implant applications, low-power circuitry design and miniature device fabrication/packaging, sensor surface modification with silicon nanowires, and characterization of the entire wireless sensor system.\n\n\nThe broader impact/commercial potential of this project will enhance greatly the scientific and technological understanding of passive wireless communication for miniature medical implants, improve healthcare procedures, reduce healthcare costs, and enable accurate measurements for regular screening methods to prevent the occurrence of incurable esophageal cancers. The proposed system provides an innovative and practical solution for gastroesophageal reflux monitoring with advantages of batteryless operation, portable wireless communication, impedance sensing method, and miniature size enabling comfortable endoscopic implantation. With these advantages, clinicians can precisely diagnose reflux with electronic records showing quantitative data with cost-effective and out-patient procedures that can be used for large population and potentially periodic screening. With 19 million adults who have consistent reflux symptoms in US and the global aging population, the proposed system for diagnosis and prognosis will have a significant impact on healthcare procedures and costs. With improved comfort level and accuracy, the system will enable regular screening procedures in clinics which in return offer a great commercial potential with a sustainable market size. The technology development also addresses commercial potentials for applications and manufacturing of semiconductor chips in miniature medical implants and portable wireless electronics in body sensor networking", "keywords": [], "approved": true } }, { "type": "Grant", "id": "5135", "attributes": { "award_id": "1047218", "title": "SBIR Phase I: A Pneumatically Actuated Robot System", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Technology, Innovation and Partnerships (TIP)", "SBIR Phase I" ], "program_reference_codes": [], "program_officials": [], "start_date": "2011-01-01", "end_date": "2011-12-31", "award_amount": 150000, "principal_investigator": { "id": 18277, "first_name": "Mike", "last_name": "Kriegsmann", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 1344, "ror": "", "name": "Sunstream Scientific Incorporated", "address": "", "city": "", "state": "IL", "zip": "", "country": "United States", "approved": true }, "abstract": "This Small Business Innovation Research (SBIR) Phase I project addresses the challenges of a decade's long unresolved technological barrier preventing a revolutionary increase in the performance of robotic systems. Enhanced productivity sought in many applications requires higher cycle rates placing great demands on robot kinematics, actuators and control systems. Further increase in operating speed must resolve dynamic challenges intrinsic in directly coupling servo actuators and robot linkages. When compared with existing electromechanical servo actuators - which route power through complex mechanical transmissions - direct-drive actuation of robot linkages enables simple mechanics and rapid motion, but does not provide dynamic isolation between the actuator and robot system. Consequently, direct-drive servo actuators are sensitive to variations in plant parameters, unknown disturbances, and un-modeled dynamics. This R&D investigates the feasibility of an innovative, direct-drive pneumatic robot actuator coupled with advanced control algorithms which rapidly accommodate dynamic system variations. Effectiveness of a new control strategy that is model insensitive, resolving unknown disturbances, un-modeled dynamics, and unknown system parameters, will be researched and developed. Success of this project will provide for a parallel delta robot that is significantly faster, more precise, possesses greater load capacity, and is substantially more affordable than contemporary delta robot systems. \n\nThe broader impact/commercial potential of this project involves engineering research conducted to enhance understanding of the dynamic interaction between direct-drive servo actuators and robotic mechanisms, and further to enhance the effectiveness and understanding of a novel control strategy which provides for an advantageous coupling between them, heretofore not practically feasible. This has the potential of introducing transformative change in the robotics industry, and to industrial automation in general. Furthermore, much of the controls knowledge gained from this research can be extended to systems employing AC linear motors, and to electromechanical servos with mismatched inertia ratios. Two market segments will be targeted: robotics and general motion control, both estimated at $7 billion. If software, peripherals and systems engineering are included, the robotics market is estimated at $19 billion. Parallel delta robots are estimated at 25% of the robotics market. The robotics industry significantly supports the national economy with applications ranging from manufacturing and food processing, to medical advances such as remotely controlled surgery, and to national defense. Well paying new hi-tech jobs are created in engineering and technical services. This research will develop revolutionary new robotic applications, educational STEM opportunities, enhanced scientific and technological understanding, making the U.S. more competitive globally.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "5254", "attributes": { "award_id": "0946111", "title": "SBIR Phase I: Low Cost, High Bandwidth RF Switch", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Technology, Innovation and Partnerships (TIP)", "SBIR Phase I" ], "program_reference_codes": [], "program_officials": [ { "id": 18539, "first_name": "Muralidharan", "last_name": "Nair", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2010-01-01", "end_date": "2010-06-30", "award_amount": 150000, "principal_investigator": { "id": 18540, "first_name": "Youngsoh", "last_name": "Park", "orcid": null, "emails": "[email protected]", "private_emails": null, "keywords": "[]", "approved": true, "websites": "[]", "desired_collaboration": "", "comments": "", "affiliations": [ { "id": 1385, "ror": "", "name": "Nano Liquid Devices, Inc", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 1385, "ror": "", "name": "Nano Liquid Devices, Inc", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true }, "abstract": "This Small Business Innovation Research Phase I project is aimed at developing Micro Metal Sphere (MMS) fabrication technology for Radio-Frequency (RF) Micro-Electro-Mechanical-System (MEMS) switch. The target applications are high-bandwidth RF switches and digitally-tunable RF modules that can be used in wireless communication systems including cell phones. The MMS technology is distinguished from conventional cantilever or bridge type MEMS switches in that it does not have a suspended element and no restoring force is involved in the switch actuation. In conventional MEMS switches, the restoring force is often not able to overcome interfacial forces over time and causes the infamous stiction that leads to permanent failure. Since the MMS switch is designed to switch with free body, it does not suffer from mechanical wear and possibly free from stiction. In addition, the MMS technology can provide an extremely cost effective packaging solution replacing commonly used labor intensive and costly wafer level packaging technology. Since the MMS technology is integration-friendly with conventional silicon CMOS technology, it can be placed on top of any CMOS IC. Therefore, anticipated benefit with the MMS technology extends to size reduction. Also the MMS technology is expected to lower the activation voltage below 10V.\n\nThe broader impact/commercial potential of this project is enabling mobile-phone makers to design smaller, lower-cost smart phones, entry-level handsets, and other mobile devices, which will accelerate the convergence of cell phones and computing devices for the next wave of mobile innovations. The MMS technology will enable lower-cost smart phones that will either complement or replace notebook PCs among mobile users who access data and communicate anywhere for work, study, social networking, and entertainment. The global impact will be enormous because, of about 1.3 billion cell phones to be produced in 2011, of which 57% will be multi-band handsets using RF MEMS components. The MMS technology will enable versatile and high-quality cell-phone communications at a lower cost integrating voice, text, data, and video for the average consumers worldwide. With the inherent stacking and scalability, the MMS technology will also be able to extend the life of popular silicon CMOS technologies currently facing the fundamental limits to further scaling. For RF components in cell phones, the total addressable market (TAM) is $1.9 billion and served available market (SAM) is $460 million by 2011.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "5286", "attributes": { "award_id": "0810026", "title": "SBIR Phase I: Highly Efficient CdTe Thin Film Solar Cells with Ordered Structure", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Technology, Innovation and Partnerships (TIP)", "SBIR Phase I" ], "program_reference_codes": [], "program_officials": [], "start_date": "2008-07-01", "end_date": "2008-12-31", "award_amount": 99998, "principal_investigator": { "id": 18613, "first_name": "Lisen", "last_name": "Cheng", "orcid": null, "emails": "[email protected]", "private_emails": null, "keywords": "[]", "approved": true, "websites": "[]", "desired_collaboration": "", "comments": "", "affiliations": [ { "id": 1389, "ror": "", "name": "NanoGreen Solutions Corporation", "address": "", "city": "", "state": "MA", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 1389, "ror": "", "name": "NanoGreen Solutions Corporation", "address": "", "city": "", "state": "MA", "zip": "", "country": "United States", "approved": true }, "abstract": "This Small Business Innovation Research (SBIR) Phase I project addresses an innovative device fabrication process and bulk hetero-junction structure to fabricate CdTe solar cells with unprecedented performance. Today's crystalline silicon based solar cell technologies are not cost effective as a viable alternative to existing energy sources. CdTe based solar cells have shown very promising as a low cost alternative to current crystalline silicon solar cells. However, the energy conversion efficiency of commercial CdTe solar cells is only ~ 10%. With this innovative approach it is intended to improve energy conversion efficiency up to the limit efficiency of ~29% for CdTe based solar cells, representing a real breakthrough in thin film solar cells and leading to tremendously wide applications.\n\nWorld solar photovoltaic (PV) market installations reached a record high of 1,744 megawatts (MW) in 2006, representing growth of 19% over the previous year. World solar cell production reached a consolidated figure of 2,204 MW in 2006, up from 1,656 MW a year earlier. Global industry revenues were $10.6bn in 2006. According to a new report from Solarbuzz, LLC, annual worldwide industry revenues will reach between $18.6bn and $31.5bn by 2011. Currently, the solar cell market is dominated by crystalline silicon solar cells with a market share of ~93%. If successful the proposed approach can improve the energy efficiency of CdTe based solar cells to the next level, which enables them to compete with (even outperform) current crystalline silicon solar cells. With improved efficiency and low cost, CdTe solar cells will get a significant share of the solar market. There is an extensive range of applications where solar cells are already viewed as the best option for electricity supply such as ocean navigation aids, telecommunication systems, remote monitoring and control, rural electrification, space power and domestic power supply. The proposed green technology harvests solar energy, reducing the emission of CO2 and global warming. This program also provides a route to enhance scientific and technological understanding of crystal growth process at the nano-scale.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "2491", "attributes": { "award_id": "2013819", "title": "SBIR Phase I: Zwitterion self-assembly during evaporation process correlated to thin film mechanical function", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Technology, Innovation and Partnerships (TIP)", "SBIR Phase I" ], "program_reference_codes": [], "program_officials": [ { "id": 7081, "first_name": "Erik", "last_name": "Pierstorff", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2020-06-01", "end_date": "2021-07-31", "award_amount": 222981, "principal_investigator": { "id": 7082, "first_name": "Bradley", "last_name": "Rodier", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 865, "ror": "", "name": "Rochal Industries LLC", "address": "", "city": "", "state": "TX", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 865, "ror": "", "name": "Rochal Industries LLC", "address": "", "city": "", "state": "TX", "zip": "", "country": "United States", "approved": true }, "abstract": "The broader impact of this Small Business Innovation Research (SBIR) Phase I project is to effectively treat skin tears, which when mismanaged, have a high propensity to become complex and chronic wounds involving infection, pain and delayed wound healing and impose health and financial burdens on individuals and care agencies. Skin tear injury effects at least 1.9 million institutionalized patients yearly and has a high probability to reoccur in high-risk categories, elderly and neonates. Though frequently under-reported, the literature suggests skin tears have a prevalence that is similar to pressure injuries. In USA long term care settings, the prevalence rate is 20% with skin tears principally on arms (60%) and legs (40%) occurring during daily routines. This research is to provide a skin tear treatment that requires less nursing time, reduces pain, and improves healing times resulting in improved patient quality of life and treatment cost savings. The estimated USA market for skin tear treatment is $646 million/year with 44% ($285 million/year) coming from nursing homes, wound care clinics and home health. The innovative chemistry developed through this research could be applied to other medical devices, separation membranes, and coatings/films to provide mechanical strength, anti-fouling, or size exclusion separation.\n\nThe proposed project is to investigate the premise that zwitterion-containing polymers can be created that retain epidermal-like membrane properties for wound healing and demonstrate mechanical strength when evaporated as thin films (e.g., Saran™ wrap-like). Each of these intellectually challenging goals is a technical hurdle to be addressed by the proposed R&D. The research findings are to direct the research for and subsequent development of a skin tear treatment product. The Phase I research focus is to synthesize and characterize this unique class of film-forming copolymers that contain zwitterions - with specific objectives to synthesize zwitterionic polymers, characterize polymers, determine mechanical properties and correlate morphology to mechanical properties. This research is to provide vital feasibility data for polymer synthesis, masking of zwitterion self-assembly, and zwitterion self-assembly parameters during solvent evaporation to form a strong polymer film. The resulting platform chemistry and body of knowledge is anticipated to be translated into a wound care product for skin tear treatment.\n\nThis 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.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "2503", "attributes": { "award_id": "2014689", "title": "SBIR Phase I: Advanced Artificial Intelligence for Robotic E-Commerce Pick-and-Pack Automation", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Technology, Innovation and Partnerships (TIP)", "SBIR Phase I" ], "program_reference_codes": [], "program_officials": [ { "id": 7122, "first_name": "Muralidharan", "last_name": "Nair", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2020-06-01", "end_date": "2020-11-30", "award_amount": 223071, "principal_investigator": { "id": 7123, "first_name": "Jeffrey", "last_name": "Mahler", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 249, "ror": "", "name": "Ambi Robotics, Inc.", "address": "", "city": "", "state": "CA", "zip": "", "country": "United States", "approved": true }, "abstract": "The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to advance the development of a reliable, flexible, and scalable logistics network for distributing essential items and supplies. Recent projections suggest that by 2022, total US e-commerce sales will exceed $900 B. The market for piece-handling automation across US e-commerce is estimated at $9.6B.The process for getting items from producer to consumer involves many touchpoints where operators pick and pack individual items. These processes are currently manual and highly repetitive, incurring a high rate of injuries. Errors in these processes are costly to e-commerce providers and may result in critical supplies getting lost or significantly delayed. However, automating pick-and-pack has been challenging due to significant diversity in warehouse processes and requires new Artificial Intelligence (AI) robotic control systems that can manipulate a large number of unique items in warehouses. Innovations in AI operating systems for robotic deployments can positively impact all aspects of the national supply chain and ensure a rapid and robust distribution network of essential items and consumer goods within the United States.\n\nThis Small Business Innovation Research (SBIR) Phase I project advance the translation of simulation-to-reality transfer learning for robotic picking. By generating millions of simulated robotic grasps and sensor readings, deep neural networks can be trained to reliably pick and place a wide variety of objects for a particular application. This project will develop and evaluate new algorithms for robotic piece picking to develop flexible robotic control software for material handling across a variety of physical instantiations. The research objectives are to decrease computation time for grasping policies, plan grasps across multiple tools simultaneously, and integrate grasp policies with order handling processes encountered in e-commerce distribution centers. The research objectives will be systematically tested on a standardized robotic picking system on a set of test objects to evaluate performance.\n\nThis 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.", "keywords": [], "approved": true } } ], "meta": { "pagination": { "page": 1391, "pages": 1424, "count": 14236 } } }