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Award Data
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)
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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Development of Next-Generation Composite Flywheel Design for Shock and Vibration Tolerant, High Density Rotating Energy Storage
SBC: MOHAWK INNOVATIVE TECHNOLOGY INC Topic: N13AT022The overall objective of the Phase I and Phase II proposed effort is to design and demonstrate the ability to develop a high-speed shock tolerant composite flywheel energy storage system (FESS) using a low cost manufacturing process. The Phase I tradeoff design studies will assess the FESS size, operating speeds and material requirements needed to achieve the energy density levels and charge/disch ...
STTR Phase I 2013 Department of DefenseNavy -
On-Board Data Handling for Longer Duration Autonomous Systems on Expeditionary Missions
SBC: NOVATEUR RESEARCH SOLUTIONS LLC Topic: N13AT016This STTR Phase I project will demonstrate the feasibility and effectiveness of novel biologically-inspired computational memory models for on-board exploitation of long-duration sensor data streams to enable autonomous missions in unknown environments. The key innovation in this effort is a computationally and space-efficient computational memory model that is able to: i) handle long-duration dat ...
STTR Phase I 2013 Department of DefenseNavy -
Progressive Model Generation for Adaptive Resilient System Software
SBC: SECURBORATION, INC. Topic: N13AT014Complex software systems are typically developed by disparate engineering teams working concurrently. At the same time, software requirements are frequently dynamic, evolving even during active development cycles. Discrepancies between how software is defined and how it is implemented at the modular level can cascade into critical system errors when modules are integrated. More troubling is that i ...
STTR Phase I 2013 Department of DefenseNavy -
Maneuver Prediction and Avoidance Logic For Unmanned Aircraft System Encounters with Non-Cooperative Air Traffic
SBC: NUMERICA CORPORATION Topic: N13AT003For Unmanned Aircraft Systems (UAS) to operate seamlessly in both the U.S. National Airspace System (NAS) and abroad, it will be crucial that they possess a sense-and-avoid (SAA) capability that can ensure safe operations among maneuvering, non-cooperative aircraft. Numerica Corporation, in partnership with Johns Hopkins University, proposes to develop a set of algorithms to model the uncertaintie ...
STTR Phase I 2013 Department of DefenseNavy -
Compact robust testbed for cold-atom clock and sensor applications
SBC: COLDQUANTA, INC. Topic: N13AT018As strontium and other alkaline-earth metals become increasingly attractive for ultracold-atom applications, there is a growing need to develop compact, robust systems for cooling, trapping, and studying these elements. In this proposal, ColdQuanta will team with Dr. Jun Ye at JILA and the University of Colorado at Boulder to develop a portable, turn-key system that can produce, utilize, and optic ...
STTR Phase I 2013 Department of DefenseNavy -
Modeling of Integrally Bladed Rotor (IBR) Blends
SBC: SIMMETRIX, INC. Topic: N13AT002Integrally bladed rotors (IBR), also called blisks, are becoming increasingly common in the compressor and fan sections of modern turbine engines. The integration of the blades and disks into a single part has the advantages of reduced part count, reduced weight, increased reliability, and increased performance. However, a drawback of this technology is that individual blades cannot be easily repl ...
STTR Phase I 2013 Department of DefenseNavy -
Intelligence and Intuition for Enhanced Decision Making (I2EDM)
SBC: MODUS OPERANDI INC Topic: N13AT024The focus of our Intelligence and Intuition for Enhanced Decision Making (I2EDM) Phase 1 research is to provide efficient and timely automated production and dissemination of information products in support of doctrinal Decision Points for the Company and below in austere environments. Operating in the Cloud, I2EDM will continuously fuse tactical information with human intuition and experience to ...
STTR Phase I 2013 Department of DefenseNavy -
Integration of PALACE and Touchdown Planning Methods for Landing CUAS at Unprepared Sites
SBC: AURORA FLIGHT SCIENCES CORPORATION Topic: N10AT039Aurora Flight Sciences and MIT have been developing tools and techniques that, together with existing 3D environment decision-making and navigation tools developed by AMRDEC in the PALACE program, are well-suited to the problem of autonomous vertical landing on unprepared landing sites. In this program, Aurora will team with MIT researchers and UC Santa Cruz (UCSC licenses PALACE technologies for ...
STTR Phase I 2010 Department of DefenseNavy -
Adaptive Turbine Engine Control for Stall Threat Identification and Avoidance
SBC: AURORA FLIGHT SCIENCES CORPORATION Topic: N10AT008Aurora Flight Sciences and MIT propose to develop a model-based adaptive health estimation and real-time proactive control to identify gas turbine engine stability risks and avoid them through control action. In this concept, the engine control system actively monitors sensors and actuators, compares them against physical models, and infers which components may be performing poorly and may need to ...
STTR Phase I 2010 Department of DefenseNavy -
Multi-Modal Knowledge Acquisition from Documents
SBC: ObjectVideo Topic: N10AT019Images with associated text are now available in vast quantities, and provide a rich resource for mining for the relationship between visual information and semantics encoded in language. In particular, the quantity of such data means that sophisticated machine learning approaches can be applied to determine effective models for objects, backgrounds, and scenes. Such understanding can then be used ...
STTR Phase I 2010 Department of DefenseNavy