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: ISEA TEK, LLC Topic: N18AT027
The Internet of Things (IoT) connects people, data, and "things" (e.g., software, sensors, platforms), facilitating the translation of information into actions. Although naval platforms’ networks and communication suites have evolved significantly in the past few years to support such required connectivity, one of the greatest technical challenges still facing the military community is the proce ...STTR Phase I 2018 Department of DefenseNavy
High Throughput Static and Dynamic Testing of AM Materials for Uncertainty Quantification and QualificationSBC: MRL MATERIALS RESOURCES LLC Topic: N18AT028
Qualification of additively manufactured parts is hampered by the inherent uncetainty in properties due to heterogeneity in processing, microstructure, and defects. The proposed effort combines high-throughput testing of static and dynamic properties using tailored sample geometry, fixture design, and load application method with microstructure quantification and analysis. This system will drastic ...STTR Phase I 2018 Department of DefenseNavy
SBC: IERUS TECHNOLOGIES INC Topic: N18AT009
The US Navy operates a vast fleet of combat and support vessels with complex power control systems under the control and decision authority of human operators. Several current resources such as SPY-1D radar and Vertical Launch System (VLS) and future resources such as railgun, AMDR, and high energy laser (HEL) are energy hungry, exceeding current and planned power generation capability when deploy ...STTR Phase I 2018 Department of DefenseNavy
An Integrated Materials Informatics/Sequential Learning Framework to Predict the Effects of Defects in Metals Additive ManufacturingSBC: Citrine Informatics, Inc. Topic: N18AT013
In this project, Citrine Informatics and the ADAPT Center at the Colorado School of Mines propose to build an informatics-driven system to understand the effects of defects in additive manufactured parts. The entire history of each sample will be captured on this system; from specific printing parameters and details of precursor materials through to part characterizations and performance measureme ...STTR Phase I 2018 Department of DefenseNavy
SBC: CORNERSTONE RESEARCH GROUP INC Topic: N18AT012
Unmanned underwater vehicles (UUVs) are currently limited in the type of missions they can perform. Limited available power limits which sensors can be run or for how long, and also limits the duration and range of the mission. More efficient propulsion systems would increase the power available to the UUV payload. Improved power distribution systems and control systems would also increase the ava ...STTR Phase I 2018 Department of DefenseNavy
New Integrated Total Design of Unmanned Underwater Vehicles (UUVs) Propulsion System Architecture for Higher Efficiency and Low NoiseSBC: CONTINUOUS SOLUTIONS LLC Topic: N18AT012
In this proposal, a meta model-based scaling law will be used to represent each system component. A components meta model-based scaling law describes the tradeoffs between performance metrics for that component or subsystem as a function of its ratings in relation to the system. This greatly reduces the number of degrees of freedom for each component, and at the same time, retains the information ...STTR Phase I 2018 Department of DefenseNavy
SBC: D'Angelo Technologies, LLC Topic: N18AT014
There is a need to create an automated, adaptive, real time coaching module that can integrate the Conning Officer Virtual Environment (COVE) along with the associated Intelligent Tutor System (COVE-ITS) and the Conning-Officer Ship Handling Assessment (COSA) together. By automating the evaluation process, Surface Warfare Officers (SWOs) will have the opportunity to use the COVE simulations more f ...STTR Phase I 2018 Department of DefenseNavy
SBC: ATA ENGINEERING, INC. Topic: N18BT029
Traditional approaches to accelerated fatigue testing rely on heuristic methods with thresholds based mostly on experience and engineering judgment. These methods generally do not apply to the multiaxial dynamic loading situations characteristic of most aerospace applications and often result in uncharacteristic fatigue damage and failure modes during testing. To overcome the limitations of tradit ...STTR Phase I 2018 Department of DefenseNavy
SBC: ARCTOS Technology Solutions, LLC Topic: DLA18A001
Universal Technology Corporation (UTC) has teamed with the University of Dayton Research Institute (UDRI), Stratonics, and Macy Consulting to demonstrate not only the transitionability into commercial systems, but also to develop the data analytics and monitoring and control requirements to extract the full value fromseveral sensors, including the Stratonics ThermaViz, acoustic and profilometry se ...STTR Phase I 2018 Department of DefenseDefense Logistics Agency
SBC: CORNERSTONE RESEARCH GROUP INC Topic: N18BT031
Large aerospace composite structures currently require autoclaves and ovens to achieve desired performance which are expensive to purchase, costly to operate, and often limit part size and production rate. Ovens and autoclaves rely on convective heating which is inefficient, consumes large amounts of energy, and can be difficult to predict. Alternative cure processes using external heaters or hot ...STTR Phase I 2019 Department of DefenseNavy