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The Award database is continually updated throughout the year. As a result, data for FY22 is not expected to be complete until September, 2023.
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A data dictionary and additional information is located on the Data Resource Page. Files are refreshed monthly.
Triton™: Active Imaging through FogSBC: SA Photonics, Inc. Topic: N18AT021
Active imaging systems are used in degraded visual environments, like those found in marine fog and other areas with a high level of attenuation and scattering from obscurants like rain, smoke and dust. These systems are still limited in range and resolution. SA Photonics is taking advantage of new eyesafe, hybrid fiber-bulk laser technology capable of high pulse energy at high repetition rate to ...STTR Phase II 2020 Department of DefenseNavy
Ultra-high gain solar-blind APD arrays based on AlGaNSBC: ADROIT MATERIALS, INC. Topic: ST18C003
The objective of this project is to develop a compact and efficient avalanche photodiode (APD), operating between 210-260 nm, for implementation in the next generation bio-chem-detectors. The proposed detectors will be based on the AlGaN materials system and will be solar blind, highly sensitive, smaller, less expensive, and more robust than current UV detectors. Development of such APDs will enab ...STTR Phase II 2020 Department of DefenseDefense Advanced Research Projects Agency
Highly efficient UV LEDs for disinfectionSBC: ADROIT MATERIALS, INC. Topic: A18BT006
Treatment of water with ultraviolet (UV) light, which destroys target DNA of microorganisms, is the safest, most reliable, and sustainable way of freeing water from microbial contamination. This process is desired in place of chlorination and is widely used in the US for wastewater treatment. We propose the development of a highly efficient UV LED with emission at 265 nm, with EQE>30%, and WPE>15% ...STTR Phase II 2020 Department of DefenseArmy
A Software Toolkit for Predicting the Neural Signatures of Cognitive StatesSBC: SONALYSTS INC Topic: AF18BT001
The United States Air Force (USAF) has a long history of using human performance models to increase the effectiveness of training, and predict the impact of physical factors (like fatigue) and environmental factors (like time pressures and information uncertainty). Within Phase I, Sonalysts and Miami University worked to improve the quality of these models through the development of the EEG Modeli ...STTR Phase II 2020 Department of DefenseAir Force
Conjugate heat transfer for LES of gas turbine enginesSBC: CASCADE TECHNOLOGIES INC Topic: N19BT027
Current design tools for gas turbine engines invoke a variety of simplifying assumptions to estimate heat transfer to solid/metal engine components (e.g., isothermal boundary conditions). These approximations are often not valid, result in inaccurate predictions of heat transfer, and ultimately compromise the thermal integrity of propulsion and power systems. Wall-modeled large eddy simulation (WM ...STTR Phase II 2020 Department of DefenseNavy