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Award Data
The Award database is continually updated throughout the year. As a result, data for FY22 is not expected to be complete until September, 2023.
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.
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A Range Segment Upgrade for Air Force Satellite Control Network with Smart Antennas and Cognitive Satellite Radios
SBC: INFOBEYOND TECHNOLOGY LLC Topic: AF14AT16ABSTRACT: A range segment upgrade for Air Force satellite control network (AFSCN) will significantly improve system effectiveness via spectrum sharing and seamless interoperation. However, the upgraded system requires new capabilities such as real-time and accurate RF interference detection and mitigation, array antenna backlobe/sidelobe suppressions, accurate performance degradation prediction, ...
STTR Phase I 2015 Department of DefenseAir Force -
Higher Order Mesh Generation for Simulation of Complex Systems
SBC: HYPERCOMP INC Topic: AF14AT07ABSTRACT: We propose here a robust production-level high-order mesh generation software for complex geometries. High order accurate numerical methods are becoming increasingly popular in the present time and have demonstrated a great measure of success in efficient error-controlled simulations for a wide variety of important problems. A curved geometry and mesh generation system is essential in m ...
STTR Phase I 2015 Department of DefenseAir Force -
Low Cost Repeatable Bio-FET Sensing
SBC: TRITON SYSTEMS, INC. Topic: AF14AT11ABSTRACT: The Triton team proposes to develop techniques for fabrication and characterization of high performance biofunctionalized field effect transistors (bio-FETs) for sensing applications. Nanoscale electronic materials such as silicon nanowires, carbon nanotubes and graphene are promising materials for biosensing applications. Field effect transistors (FETs) using nanomaterials have been de ...
STTR Phase I 2015 Department of DefenseAir Force -
Phase Transitions, Nucleation and Mixing Modeling through Trans-Critical Conditions
SBC: CASCADE TECHNOLOGIES INC Topic: AF14AT23ABSTRACT: In this proposal, researchers from Cascade Technologies and Professors Matthias Ihme and Ali Mani from Stanford University lay out a plan to develop predictive modeling tools for transcritical flows. Phase I of the three phase plan is outlined in detail and extensions are proposed for Phases II and III. Central points of the Phase I plan include: A comprehensive review and assessment ...
STTR Phase I 2015 Department of DefenseAir Force