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The Award database is continually updated throughout the year. As a result, data for FY23 is not expected to be complete until September, 2024.
Download all SBIR.gov award data either with award abstracts (290MB)
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A data dictionary and additional information is located on the Data Resource Page. Files are refreshed monthly.
The SBIR.gov award data files now contain the required fields to calculate award timeliness for individual awards or for an agency or branch. Additional information on calculating award timeliness is available on the Data Resource Page.
Seamless Wireless Charging of Micro and Small Unmanned Aerial System Through Local Power Transmission InfrastructureSBC: E H Group, Inc. Topic: N19AT019
Wireless charging of unmanned aerial system (UAS) platforms from the environment has the potential to greatly increase flight and mission times. A promising option is to use electromagnetic fields from the power transmission infrastructure as an energy source. EH Group and the University of Alabama propose a design for UAS wireless charging in the near-field environment of the commercial power tra ...STTR Phase I 2019 Department of DefenseNavy
SBC: Luna Innovations Incorporated Topic: N19AT019
Unmanned aerial systems (UAS) provide strategic advantage for our nation’s warfighters, and the use of micro- and small-scale platforms on the battlefield is expected to increase significantly in coming years. This presents a logistical challenge in managing how system batteries are recharged throughout the UAS lifespan. The desired goal is to develop power systems that enable persistent deploym ...STTR Phase I 2019 Department of DefenseNavy
SBC: ULTRA-LOW LOSS TECHNOLOGIES LLC Topic: N19AT023
Ultra-Low Loss Technologies (ULL Technologies) is proposing in collaboration with Prof. Arka Majumdar from University of Washington (UW), to develop a compact, low-cost spectrometer module to be used for chemical sensing applications and to be fabricated using the process design kit (PDK) available through AIM Photonics multi-project wafer run (MPW). The team will combine ULL Technologies expertis ...STTR Phase I 2019 Department of DefenseNavy
SBC: BCL Technologies Topic: N19AT024
In this SBIR, BCL proposes developing a Multi-lingual Social-media Crowd Manipulation Detector (MSCMD). The MSCMD will use natural language processing techniques to detect terms that arouse emotion using information out of context to trigger reaction from the audience and move them to act.The MSCMD will operate in Asian languages using a Natural Language Processor for each language. The MSCMD will ...STTR Phase I 2019 Department of DefenseNavy
SBC: PARTOW TECHNOLOGIES LLC Topic: N19AT023
A photonic integrated spectrometer based on high-index contrast thin film platform is proposed for Raman signal processing. Raman signal generation on the chip via waveguide collection integrated with a spectrometer is proposed to increase the efficiency and signal to noise ratio and significantly reduce cost and the size of Raman sensor systems. All components of the proposed Raman detection syst ...STTR Phase I 2019 Department of DefenseNavy
Data Analytics and Machine Learning Toolkit to Accelerate Materials Design and Processing DevelopmentSBC: CFD RESEARCH CORPORATION Topic: N19AT020
Navy has identified refractory high entropy alloy (RHEA) and metal additive manufacturing as two potential areas of interest. This includes designing new RHEA and optimizing metal additive manufacturing with specific material property requirements. Developing materials and processes via applying traditional experimentation and process optimization techniques is painfully slow due to the large numb ...STTR Phase I 2019 Department of DefenseNavy
SBC: METRON INCORPORATED Topic: N19AT017
Metron and Northeastern University propose to design, develop, and validate a proof-of-concept predictive Graph Convolutional Network (GCN) capability using open source Reddit and GDELT data. We propose: (1) to extract and preprocess open-source Reddit and GDELT data, (2) to design a predictive graph convolutional neural network model, (3) to implement and train that model, and (4) to validate the ...STTR Phase I 2019 Department of DefenseNavy
SBC: METRON INCORPORATED Topic: N19AT022
In Phase I, Metron and the University of Miami (UM) propose to develop a theoretic reduction of dynamics framework applicable to the prediction of oceanographic fields in geophysical fluid dynamic models for use onboard unmanned platforms. Our approach leverages, extends and combines modern advances in the renormalization group and Bayesian probability combined with fluid dynamics modeling and for ...STTR Phase I 2019 Department of DefenseNavy
SBC: APPLIED OCEAN SCIENCES, LLC Topic: N19AT022
This project delivers a system to assess local uncertainties and track the evolution of the maritime environment around unmanned platforms at sea. The system uses Navy ocean forecasts for initial environmental guesses and outlooks and implements a Reduced Order Model (ROM) derived from Dynamically Orthogonal (DO) solutions to deliver a local uncertainty picture (for the next 24-48 hours). The ROM- ...STTR Phase I 2019 Department of DefenseNavy
SBC: NANOSONIC INC. Topic: N19AT019
NanoSonic will work with Penn State to develop, demonstrate and manufacture materials and systems to allow unmanned aerial vehicles (UAVs) to scavenge magnetic field energy from electric power lines and operate continuously in the field. NanoSonic will work with energy harvesting researcher Dr. Shashank Priya and a major US aerospace company to design, fabricate and demonstrate a prototype system ...STTR Phase I 2019 Department of DefenseNavy