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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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T3DDART – Tractable Tiered Task Decompositions for Decentralized Autonomous Resource Tasking
SBC: SCIENTIFIC SYSTEMS CO INC Topic: HR001121S000725The current state-of-the-art for autonomous unmanned vehicles is limited in comms-denied situations, where operators cannot assist with coordination and situational reassessment. Significant algorithmic development is needed for comms-challenged autonomous operations to achieve parity with operator-driven or manned equivalents, as autonomous agents are not currently equipped to anticipate and re ...
STTR Phase I 2022 Department of DefenseDefense Advanced Research Projects Agency -
sUAS Munition Teaming for Advanced Precision Strike
SBC: CHARLES RIVER ANALYTICS, INC. Topic: SOCOM21C001Precision-guided munitions have demonstrated dramatic effects with minimal collateral damage. New technology developed specifically to deny them accurate guidance information is now feasible, even for non-traditional adversaries. Further, digital communications are flooding the air with signals that interfere with communications many guidance methods rely on. Swarms of small, covert small Uncrewed ...
STTR Phase I 2022 Department of DefenseSpecial Operations Command -
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 -
Thermal Emission Control using Photonic Crystals
SBC: PSQUAREDT LLC Topic: HR001120S001925To achieve the requisite fast, dynamic thermal switching times, we postulate the use of a Photonic Crystal (PC) filament operating at l=1-2mm. Our electrically biased PC design will be super thin to allow for fast on-off intensity-switching. It will have a small thermal mass and exhibit laser-like input-output characteristics, i.e. “Planck laser”. We will provide a theoretical framework for ou ...
STTR Phase I 2021 Department of DefenseDefense Advanced Research Projects Agency -
Thermochromic Coatings for Emissivity Modulation
SBC: PHYSICAL SCIENCES INC. Topic: HR001120S001925Physical Sciences Inc. (PSI) and the University of Wisconsin, Madison propose to develop a multilayer emissivity control coating (MECC) for active and passive thermal emission control. PSI will fabricate a thermochromic emissivity control coating based on vanadium dioxide (VO2) and validate its ability to modulate broadband thermal signature contrast by >10:1 with a switching time of 1 µs. We wil ...
STTR Phase I 2021 Department of DefenseDefense Advanced Research Projects Agency -
Interface-Engineered microFerro and nanoFerri Composites for Present and Future Power Electronics
SBC: METAMAGNETICS INC Topic: HR001120S001922In this DARPA STTR Phase I program, Metamagnetics Inc., in collaboration with Northeastern University, proposes to address the challenges associated with performance of transformer and inductor materials operating at high power and frequencies equal to or greater than 50 kHz by developing ferromagnetic – ferrimagnetic composites with high saturation magnetization, high permeabilities, and ultral ...
STTR Phase I 2021 Department of DefenseDefense Advanced Research Projects Agency -
Variable Leg Length Ground Robot with Novel Prismatic Actuators
SBC: TRITON SYSTEMS, INC. Topic: HR001119S003523Triton Systems, Inc. will work in collaboration with Professor Mark Yim of the University of Pennsylvania (UPenn) to design a viable, robust ground robot with novel, reconfigurable actuators. This robot can reconfigure from a wheeled state to a legged state, enabling it to overcome tall obstacles and rough terrain. This ground robot will also be of a modular nature, able to be combined with others ...
STTR Phase I 2020 Department of DefenseDefense Advanced Research Projects Agency -
Patterned, Responsive Cellular Therapies Using Novel Mammalian Cellular Regulator Systems
SBC: General Biologics, Inc. Topic: HR001119S003516We propose to design, build and test genetic circuits and DNA constructs that will be expressed in human cells and that will ultimately have applications for the health of warfighters. The circuits will have physiological inputs representing, for example, (1) infection/sepsis, (2) altitude sickness or blood loss, and (3) radiation exposure; which will be mediated through signal transduction pathwa ...
STTR Phase I 2020 Department of DefenseDefense Advanced Research Projects Agency -
Aberration-correcting Topologically Optimized Metasurface (ATOM)
SBC: PHYSICAL SCIENCES INC. Topic: HR001119S003524Metalenses, with their ability to arbitrarily control the amplitude and phase of light across a band of wavelengths, have the potential to disrupt imaging and communication systems which rely on traditional lenses to focus, collimate, and otherwise manipulate optical signals, and are under increasing pressure to operate with reduced size and weight. We propose to design, develop, and demonstrate a ...
STTR Phase I 2020 Department of DefenseDefense Advanced Research Projects Agency -
Machine Learning and Data Fusion platform for Phenotype-based Pathogen Identification
SBC: TRITON SYSTEMS, INC. Topic: ST18C002Conventional methods for detecting pathogens, which are based on culturing the microorganism, are time-consuming and laborious. Machine learning provides an alternative path to identify pathogens using supervised learning algorithms. Most current computational tools utilize genomic or protein data to identify bacteria. These methods look for features in the whole genome that correlate to pathogeni ...
STTR Phase I 2019 Department of DefenseDefense Advanced Research Projects Agency