You are here
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.
SBC: FREEDOM PHOTONICS LLC Topic: 29d
Modern quantum information systems employ optical photons for long distance communication, operating at ambient temperature, between microwave cavities, which house microwave photons used in quantum computing and microwave detection. These optical photons, carried by fiber-optic or free-space links, offer a low-cost, uncooled alternative to bulky, expensive microwave coaxial cables, which are loss ...STTR Phase I 2018 Department of Energy
SBC: GLOBAL ALGAE INNOVATIONS, INC. Topic: 08c
For economically viable large-scale production of microalgae based food and biofuel to become a reality, significant improvements in algal productivity need to be achieved. With current regulatory guidelines, large scale outdoor cultivation of microalgae for these products restricts the use of transgenic algal strains, which in the laboratory, have thus far been the primary strategy taken to effec ...STTR Phase I 2018 Department of Energy
SBC: HIFUNDA LLC Topic: 22c
The discovery of large shale gas reserves in recent years has resulted in the reduction of natural gas price and a need to develop new applications for the available resource. Upgrading shale gas to liquid fuels which are more easily transportable and have greater economic value can result in significant benefits to the US. Coupled with this challenging problem the DOE has a goal of further develo ...STTR Phase I 2018 Department of Energy
Hybrid DNN-based Transfer Learning and CNN-based Supervised Learning for Object Recognition in Multi-modal Infrared ImagerySBC: TOYON RESEARCH CORPORATION Topic: 1
On this effort Toyon Research Corp. and The Pennsylvania State University are developing deep learning-based algorithms for object recognition and new class discovery in look-down infrared (IR) imagery. Our approach involves the development of a hybrid classifier that exploits both transfer learning and semi-supervised paradigms in order to maintain good generalization accuracy, especially when li ...STTR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency
SBC: SIGNATURE RESEARCH, INC. Topic: 1
Signature Research, Inc. (SGR) and Michigan Technological University (MTU) propose a Phase I STTR effort to develop a learning algorithm which exploits the spatio-spectral characteristics inherent within IR imagery and motion imagery.Our archive of modelled and labeled data sets will allow our team to thoroughly capture the variable elements that will drive machine learning performance.The overall ...STTR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency
SBC: MICROBIO ENGINEERING INC Topic: 08c
To advance a strong and economical biofuels and bioproducts industry, tools are needed for breeding microalgae to improve phenotypes of commercial interest, including biomass yield, culture stability, harvestability, and accumulation of valuable compounds. This project aims to increase biomass feedstock yields by the phototrophic green alga Scenedesmus obliquus by using classical breeding approach ...STTR Phase I 2018 Department of Energy