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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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Machine Intelligence for Space Weather (MINTS)
SBC: NEXTGEN FEDERAL SYSTEMS LLC Topic: 95NextGen Federal Systems (NextGen), a Small Business Concern (SBC), is excited to propose a powerful software package, coupled database, and a machine-learning (ML) workflow to support streamlined evaluation and research-to-operations (R2O) of space weather ML models and techniques. In response to the NOAA Effect of Space Weather subtopic (NOAA SBIR 9.5), we propose the Machine Intelligence for Spa ...
SBIR Phase I 2023 Department of CommerceNational Oceanic and Atmospheric Administration -
Proposed Project Title Atlantis AI Based Long Range Space Weather Prediction System
SBC: Atlantis Industries, Inc. Topic: 95To date, no realizable method of predicting the occurrence or magnitude of a Solar Energetic Particle (SEP) event has been developed. There are multiple models currently available in the Community Coordinated Modeling Center (CCMC) through Goddard Space Flight Center that attempt to provide timely and accurate event propagation (e.g.MAG4, Enlil, and SEPMOD). None of these have yet achieved the goa ...
SBIR Phase I 2023 Department of CommerceNational Oceanic and Atmospheric Administration -
ALLVAR Alloys for Athermalizing SiC Telescopes with Reduced SWAP-C
SBC: Thermal Expansion Solutions, Inc. Topic: MDA21001The Ultimate Goal of these research efforts is to develop ALLVAR Alloy athermalizing strut components that enable size, weight, cost, lead time, and performance enhancements of SiC mirrored optical seekers that must withstand extreme exo-atmosphere, endo-atmosphere, and mechanical loading environments. ALLVAR Alloys offer a brand-new strong and ductile support structure solution that can offer low ...
SBIR Phase II 2023 Department of DefenseMissile Defense Agency -
Quantum-Computing-Aided Materials Research and Development
SBC: TEXAS RESEARCH INSTITUTE , AUSTIN, INC. Topic: MDA22T007Quantum computing has the potential to exponentially outperform classic computers for certain problems due to their use of qubits. The use of quantum computing could be particularly useful for the discovery of novel lightweight materials with high-temperature strength properties that far exceed traditional material systems. One exciting class of materials known as High Entropy Alloys (HEAs) are al ...
STTR Phase I 2023 Department of DefenseMissile Defense Agency -
Accelerated in-storage analysis of multi-dimensional data
SBC: AIRMETTLE INC Topic: 91AirMettle Inc. is transforming big data analytics for NOAA and the broader scientific community with a real-time smart data lake solution. Our innovative method utilizes massively parallel in-storage data processing within a versatile software defined storage framework, deployable on-premises or as a cloudbased service. Building upon our successful NOAA SBIR Phase I project, we strive to improve t ...
SBIR Phase II 2023 Department of CommerceNational Oceanic and Atmospheric Administration -
ALLVAR Alloys for Athermalizing SiC Telescopes with Reduced SWAP-C
SBC: Thermal Expansion Solutions, Inc. Topic: MDA21001This Phase I seeks to develop optical seekers that must operate in the endo-atmosphere and exo-atmosphere with high mechanical and thermal stability. ALLVAR Alloy support structures have the potential to create smaller, lighter, and lower cost athermalization solutions for Silicon Carbide (SiC) mirrored telescopes without sacrificing the thermal stability traditionally associated with monolithic o ...
SBIR Phase I 2022 Department of DefenseMissile Defense Agency -
3D Collaborative BattleSpace Visualization, Capture, and Playback
SBC: FoVI 3D, Inc. Topic: MDA21004FoVI3D is developing a 3-person, graphical workstation called PRISM to promote collaborative 3D visualization. The PRISM workstation consists of wide field-of-view monitors for rendering 3D content as well as high-resolution, 2D touch panels for the customized presentation of operator controls and data. The PRISM graphics API is based on ObjGL, a high-level, cross-platform, and display-agnostic gr ...
SBIR Phase I 2022 Department of DefenseMissile Defense Agency -
Thermally Resistant Polyimide Seals
SBC: TEXAS RESEARCH INSTITUTE , AUSTIN, INC. Topic: MDA21011There is an interest in new designs of solid propellant rockets which can provide greater impulse and thrust. Taking advantage of higher burn temperatures could facilitate these improvements, but it also requires rocket material components, such as dynamic seals, to be redesigned to meet the higher thermal demands. Dynamic seals are typically found in movable pintle valves inside a rocket nozzle t ...
SBIR Phase I 2022 Department of DefenseMissile Defense Agency -
Kill Enhancing Device
SBC: Energetic Materials & Products, Inc. Topic: MDA21016Ability to defeat hypersonic glide vehicles (HGV’s) requires innovative concepts. Increasing effective kill volume of a warhead is a key metric for evaluating probability of hit of an HGV. EMPI has a depth of experience developing lightweight fragmentation panels and will leverage over five years of experience in our proposed warhead to enhance the probability of kill. Our solution provides redu ...
SBIR Phase I 2022 Department of DefenseMissile Defense Agency -
Federated Learning based Cooperative Sensing for Efficient Threat Detection (FedSense)
SBC: KNOWLEDGE BASED SYSTEMS INC Topic: MDA21020Knowledge Based Systems, Inc. (KBSI) proposes to extend the federated learning (FL) architecture to support flexible and integrated interceptor discrimination and decision making. Specifically, KBSI will research, design, and demonstrate the Federated Learning based Cooperative Sensing for Efficient Threat Detection (FedSense) framework that allows models that are learnt locally at terminal nodes ...
SBIR Phase I 2022 Department of DefenseMissile Defense Agency