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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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High Voltage Encapsulant Material
SBC: LaunchBay LLC Topic: DMEA231003Encapsulation materials are crucial for long-term reliability of high voltage and high temperature power device packaging as they help prevent electrical discharges in air as well as protect the devices against humidity, dirt and shock. However, the currently available commercial encapsulants are severely deficient in their high temperature performance, especially above 250C. Although several diff ...
SBIR Phase I 2023 Department of DefenseDefense Microelectronics Activity -
Recycling Fast-Response Atom Interferometer for Navigation (ReFRAIN)
SBC: PHYSICAL SCIENCES INC. Topic: OSD221006Physical Sciences Inc. (PSI) will develop a Recycling Fast-Response Atom Interferometer for Navigation (ReFRAIN) as an atom interferometer (AI) accelerometer specially designed to improve inertial navigation systems (INS) on moving platforms. The ReFRAIN provides sensitivity, dynamic range, bandwidth, and bias stability that matches or exceeds state of the art mechanical accelerometers. PSI in ...
SBIR Phase I 2022 Department of DefenseOffice of the Secretary of Defense -
High-Resolution Temperature Mapping in a Scanning Transmission Electron Microscope
SBC: SIVANANTHAN LABORATORIES, INC. Topic: DMEA192001Sivananthan Laboratories proposes to develop an approach for measuring the temperature of materials with high spatial resolution and temperature accuracy in a scanning transmission electron microscope. The PIs will determine the bulk plasmon resonance using electron energy-loss spectroscopy, which has been demonstrated by the PIs to allow for a spatial resolution of better than 2 nm (when combined ...
SBIR Phase I 2020 Department of DefenseDefense Microelectronics Activity -
Photon Correlation Spectroscopy for Particle Counting and Sizing in Bulk Liquid
SBC: OPTOWARES INC Topic: DMEA182001There is a lack of in-situ, non-contact, non-destructive techniques to detect the presence of particulates contaminating bulk liquid samples in clean room environment during semiconductor processing. Leveraging our extensive experience building optical sensor systems, we will design and build an innovative handheld particle counter using diffusive wave spectroscopy. Our handheld system can be u ...
SBIR Phase I 2019 Department of DefenseDefense Microelectronics Activity -
Electro-optical Seeker
SBC: CERANOVA CORP Topic: OSD181002Execution of long-range weapons capabilities reduces risk and affords greater warfighter protection. Core enabling technologies for hypersonic projectiles include high-strength lightweight materials, precision avionics, and novel designs. System demands include the ability to withstand both high accelerations (up to 50,000 Gs) and aerothermal shock. Detailed structural engineering and shock modeli ...
SBIR Phase I 2019 Department of DefenseOffice of the Secretary of Defense -
Electro-optical Seeker Based on HgCdTe Photodetection
SBC: EPISENSORS INC Topic: OSD181002The capability to reliably and remotely detect and track tactical surface targets in a high-velocity projectile after launch is a critical need. The discrimination of man-made objects can be assisted by the detector technology, with options including two-color detectors and polarimetric filtering in the thermal infrared bands. The level of complexity in the focal plane array affects its survivabil ...
SBIR Phase I 2019 Department of DefenseOffice of the Secretary of Defense -
Low-Cost, Transmit-Only, Active Electronically Steered Array (AESA) with Phase-Only Nulling (1000-471)
SBC: SI2 TECHNOLOGIES, INC Topic: SCO182002SI2 proposes to leverage prior Government funded efforts to develop a transmit (TX) only, wideband (6:1 bandwidth), low-cost, scalable active electronically scanned array (AESA) that will utilize phase-only nulling to enable radar, Electronic Warfare / Electronic Attack (EW/EA), Information Operations (IO) and other capabilities on multiple platforms across DOD agencies. The array will employ digi ...
SBIR Phase I 2019 Department of DefenseOffice of the Secretary of Defense -
Maritime/Systems & Technology Research
SBC: Systems & Technology Research LLC Topic: SCO182008Airborne radars operating over open water must classify maritime vessels by measuring and exploiting highly-variable radar signatures. Sources of signature variability include within-class ship construction and equipment differences, complex in-situ 6-DoF ship motion caused by ocean waves across a range of sea state conditions, acquisition geometry including grazing angle and maritime-specific RF ...
SBIR Phase I 2019 Department of DefenseOffice of the Secretary of Defense -
Deep Automatic Target Recognition (DATR) Technology/R-DEX Systems, Inc.
SBC: R-DEX SYSTEMS, INC. Topic: SCO182008R-DEX Systems proposes to adapt its commercial discrimination technology used in industrial automation to develop Deep Automatic Target Recognition (DATR) Technology. DATR utilizes revolutionary deep learning processing (deep belief networks or DBNs, restricted Boltzmann machines RBMs, and convolutional neural networks or CNNs) to automatically identify hidden, nonlinear features that are not iden ...
SBIR Phase I 2019 Department of DefenseOffice of the Secretary of Defense -
Secure Private Neural Network (SPNN)/Charles River Analytics Inc.
SBC: CHARLES RIVER ANALYTICS, INC. Topic: SCO182009Deep Neural Networks (DNNs) are becoming widely used in the DoD for image classification, but recent research has shown DNNs are vulnerable to adversary attacks. Adversaries can monitor the DNN training and classification processes to learn attributes of the training data and the DNN. With this information, an adversary can gain valuable insight into the potentially sensitive data used to train th ...
SBIR Phase I 2019 Department of DefenseOffice of the Secretary of Defense