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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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Solder-Plating Process Control
SBC: Contamination Studies Topic: N/AAt CSL, Inc. the Sequential Electrolytic Reduction Analysis equipment will be optimized for both board and component manufacturing processes. Six manufacturers will be suppling product during this project. Our approach to optimization will be through applying SERA technologies to all board and component processes that directly relate to the solderability issues. CSL, Inc. will use a four phase app ...
SBIR Phase I 1993 Department of DefenseArmy -
Memory-based Graphics: A New Technology For Visual Interfaces And Interactive Visualization
SBC: Infinite Graphics, Corp Topic: N/AThis project is based on a novel computer graphics technology for man/machine interfaces that relies on machine learning techniques, neural-like networks, and object recognition IU techniques. The key idea is to use a few "example" views of an object or person, to teach the computer to generate other views, under user control. WIth our technology we will develop an interactive (multimedia) interfa ...
SBIR Phase I 1993 Department of DefenseDefense Advanced Research Projects Agency -
Heat Stable Alkaline Phosphatase from Thermophiles
SBC: J.k. Research Topic: N/AN/A
SBIR Phase I 1993 Department of DefenseArmy -
Develop Enironmental Monitoring Capability for Intergrating Recent Technological Advancements into a Hybrid Artificial Neural Network System
SBC: SEACORP, LLC Topic: N/AWe propose to develop an Environmental Monitoring System by integrating various technologies to create a hybrid artificial neural network system. By functionally decomposing the requirements of environmental monitoring we can apply emerging technologies to fulfill these modularized requirements. Ten (10) years of experience indicate that the technologies directly applicable to specific requirement ...
SBIR Phase I 1993 Department of DefenseArmy