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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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Memory Instrumentation and Performance Simulation (MIPS)
SBC: ATC-NY INC Topic: DTRA172003Next-generation high-performance computing (HPC) hardware, such as the Intel Xeon Phi Knights Landing Many-Integrated-Core processor, provide new deep memory architectures that offer the promise of increased performance. The challenge in taking full advantage of this architecture is selecting which data structures will be placed in the high-bandwidth memory. Optimizing data structure placement in ...
SBIR Phase I 2018 Department of DefenseDefense Threat Reduction Agency -
Development of Trumedicines Recognition Authentication Cloud Intelligence For Drug Product Surveillance (TRACI-4DPS) Software Solutions to Address FDA Post-Marketing Drug Surveillance Challenges
SBC: TruMedicines LLC Topic: FDATruMedicines Fast Track SBIR ApplicationProject Summary TruMedicines is a Seattle based software technology company that provides the Trumedicines Recognition Authentication Cloud IntelligenceTRACImobile software solutions to address requirements of theDrug Security Act to tracktraceand authenticate of drug packagesOur functional practice areas include mobile app developmentimage recognitionsecure ...
SBIR Phase I 2018 Department of Health and Human ServicesFood and Drug Administration -
Low-Cost Sensing Array for Infrasound
SBC: CREARE LLC Topic: DTRA172001Infrasound and seismic measurements are used by DTRA and the DoD for nuclear test monitoring, terrorist blast forensics, battle damage assessment, and environmental monitoring. However, these long wavelength physical signals are typically recorded through single-point sensors or sparse low density arrays. As a result, the critical signals of interest are often corrupted or masked by noise or inter ...
SBIR Phase I 2018 Department of DefenseDefense Threat Reduction Agency -
A Robust, Machine Independent, Software Toolkit for Topology Aware Process Mapping on Distributed Memory HPC Architectures
SBC: CONTINUUM DYNAMICS INC Topic: DTRA172002A significant performance gap exists between the theoretical number of Floating Point Operations (FLOPS) that a HPC machine is capable of sustaining and the number of FLOPS realized by real-world HPC applications. One of the principle reasons for this gap is the parasitic work that computational processes must do to communicate with one another. It has been shown that this communication work can b ...
SBIR Phase I 2018 Department of DefenseDefense Threat Reduction Agency -
Product tracking and security through design methodology in additive manufacturing
SBC: 3DP Security Inc Topic: FDAProduct tracking and security through design methodology in additive manufacturing Specific Aims Additive manufacturing AM is increasingly being used in the medical for applications as diverse as printing prosthesis and implants of ceramic and metallic materials and even organs using soft materials and live tissue bioprinting In AM a computer aided design CAD file is processed and sent t ...
SBIR Phase I 2017 Department of Health and Human ServicesFood and Drug Administration -
Machine learning for standoff detection of Special Nuclear Material (SNM)
SBC: CLOSTRA INC Topic: DTRA162001"Deep Learning for standoff detection of Special Nuclear Material (DLeN) applies the same deep learning techniques that allow computers to beat human performance in image recognition and the game of Go to detecting Special Nuclear Material. Spectral analysis and signal processing can in some cases be augmented by the use of much larger neural nets that conduct much deeper analysis of features of t ...
SBIR Phase I 2017 Department of DefenseDefense Threat Reduction Agency -
Archimedes: Automated invention for threat anticipation
SBC: ATC-NY INC Topic: DTRA162005"Anticipating future acts of creativity by our adversaries is very difficult. Yet, to avoid being blindsided by surprising new forms of WMD enabled by technology trends and scientific advances, DTRA must concern itself with exactly such future inventions. ATC-NY will develop the Archimedes system to give the DTRA an early heads up about anticipated technology, and scientific discoveries with po ...
SBIR Phase I 2017 Department of DefenseDefense Threat Reduction Agency -
Data-Driven Technology Discovery Application
SBC: Semandex Networks Inc. Topic: DTRA162005Automatically identifying emerging technologies and research trends from the high volume of the worlds scientific publications is of great significance in order to stay ahead of the critical advances that impact the development of new and disruptive technologies. Semandex and Barnstorm will implement a prototype tool, INSIGHT, that will scan large datasets from web content services and perform ana ...
SBIR Phase I 2017 Department of DefenseDefense Threat Reduction Agency -
Agent Defeat using a DWA Accelerator
SBC: BROOKHAVEN TECHNOLOGY GROUP INC Topic: DTRA08008A new type of compact induction accelerator currently under development at the Lawrence Livermore National Laboratory (LLNL) promises to increase the average accelerating gradient by at least an order of magnitude over that of existing induction machines. The machine is based on the use of high gradient vacuum insulators and advanced dielectric materials and switches. The system, called the Diel ...
SBIR Phase I 2008 Department of DefenseDefense Threat Reduction Agency -
The Characterization and Mitigation of Single Event Effects in Ultra-Deep Submicron (< 90nm) Microelectronics
SBC: Orora Design Technologies, Inc. Topic: DTRA07005Orora Design Technologies proposes to develop electronic design automation (EDA) tools employing minimally invasive circuit design-based methods to mitigate single event effects (SEEs) for next generation Ultra-DSM CMOS (
SBIR Phase II 2008 Department of DefenseDefense Threat Reduction Agency