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Award Data
The Award database is continually updated throughout the year. As a result, data for FY24 is not expected to be complete until March, 2025.
Download all SBIR.gov award data either with award abstracts (290MB)
or without award abstracts (65MB).
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.
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Large Form Factor Scintillators for Nuclear Battlefield Operations
SBC: N.P. PHOTONICS, INC. Topic: DTRA22D002The current state-of-the-art radiation detection materials have different drawbacks limiting their applications in the next-generation mobile radiation detection system. NP Photonics proposes to develop a novel scintillating glass that can be used to make large form-factor scintillators for nuclear battlefield operations. The proposed scintillating glass has the advantages of low cost, short decay ...
STTR Phase I 2023 Department of DefenseDefense Threat Reduction Agency -
Compact Laser Drivers for Photoconductive Semiconductor Switches- STTR Phase II Sequential
SBC: SCIENTIFIC APPLICATIONS & RESEARCH ASSOCIATES, INC. Topic: DTRA16A004For effective protection against radiated threats, produced by high altitude electromagnetic pulse (HEMP) caused by nuclear detonations and high-power microwave (HPM) Directed Energy (DE) weapons it is important to understand not only the physics of the threats, but also to quantify the effects on mission-critical electrical systems. EMP/HMP simulators enable threat level testing of MCS and provid ...
STTR Phase II 2022 Department of DefenseDefense Threat Reduction Agency -
Numerics-Informed Neural Networks (NINNs)
SBC: KARAGOZIAN & CASE, INC. Topic: DTRA21B002The overall goal is to develop numerics-informed neural networks (NINNs) and DeepOnets for chemical reactions and for PDEs with spatial derivatives improve the computational efficiency of the chemical kinetics models for chemical weapon agents and simulants. Based on the first NINN developed by the Karniadakis’s group in 2018, which blends the multi-step time-stepping with deep neural networks, ...
STTR Phase I 2022 Department of DefenseDefense Threat Reduction Agency -
SAR AI Training dataset generated using Reification
SBC: Arete Associates Topic: DTRA21B001The Synthetic Aperture Radar (SAR) Image Generation Data Augmentation (SIGDA) system is achieved using SAR simulators and the Arete’s Reification approach. Large, realistic datasets will be generated using the Arete Reification capability. These large Reified datasets are then used to train machine learning or Artificial Intelligence (AI), Automatic Target Recognition (ATR) classification algori ...
STTR Phase I 2022 Department of DefenseDefense Threat Reduction Agency -
Bounding generalization risk for Deep Neural Networks
SBC: Euler Scientific Topic: NGA20A001Deep Convolutional Neural Networks (DCNNs) have become ubiquitous in the analysis of large datasets with geometric symmetries. These datasets are common in medicine, science, intelligence, autonomous driving and industry. While analysis based on DCNNs have proven powerful, uncertainty estimation for such analyses has required sophisticated empirical studies. This has negatively impacted the effect ...
STTR Phase II 2022 Department of DefenseNational Geospatial-Intelligence Agency -
Hardened, Optically-Based Temperature Characterization of Detonation Environments
SBC: SA PHOTONICS, LLC Topic: DTRA19B001Improving the effectiveness of counter-WMD operations requires improved understanding of weapon-target interaction. Specifically, time-resolved measurements of temperature and composition are required to allow temporal evolution of a detonation fireball. To address this need, SA Photonics will develop MONITOR, a laser-based temperature diagnostic which will enable wide dynamic range temperature me ...
STTR Phase II 2022 Department of DefenseDefense Threat Reduction Agency -
Algorithm Performance Evaluation with Low Sample Size
SBC: SIGNATURE RESEARCH, INC. Topic: NGA20C001The team of Signature Research, Inc. and Michigan Technological University will develop and demonstrate methods and metrics to evaluate the performance of machine learning-based computer vision algorithms with low numbers of samples of labeled EO imagery. We will use the existing xView panchromatic dataset to demonstrate a proof-of-concept set of tools. If successful, in Phase II, we will extend t ...
STTR Phase I 2021 Department of DefenseNational Geospatial-Intelligence Agency -
General Purpose Radiation Detector Front End and Digital Processor
SBC: H3D INC Topic: DTRA20B002This project aims to create a general-purpose readout architecture that will allow the rapid deployment of next generation detection systems. The system will be based on the development of a programmable general-purpose integrated circuit (GPIC) that has the front-end electronics required to read out signals from a variety of radiation detectors, especially next generation scintillators and semico ...
STTR Phase I 2021 Department of DefenseDefense Threat Reduction Agency -
Integrated Circuits
SBC: NU-TREK, INC. Topic: DTRA20B002The Nu-Trek team is proposing to develop µDet, a low Size, Weight, and Power (SWaP) read out integrated circuit (IC) for gamma and neuron detectors. µDet offers pulse shape digitization, which in turn enables gamma-neutron discrimination. This is a game changing capability that brings laboratory-level functionality to the field. In Phase I the Nu-Trek Team will develop a baseline design for the ...
STTR Phase I 2021 Department of DefenseDefense Threat Reduction Agency -
Computer Vision Image Interpretation for 3D Model Reconstruction
SBC: TOYON RESEARCH CORPORATION Topic: DTRA18B001Toyon Research Corporation (Toyon) and the University of California, Santa Barbara (UCSB) propose research, development, and demonstration of algorithms and an efficient software prototype for 3D model reconstruction using single images collected via remote sensing. In particular, the effort is focused on processing of high-resolution commercial satellite images for 3D reconstruction of buildings. ...
STTR Phase II 2021 Department of DefenseDefense Threat Reduction Agency