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: N20BT030
In this program, we propose to adapt a new, high-performance integration platform for RF photonics to operation at 1um, and to realize integrated optical transmitters that meet the requirements of the program.STTR Phase I 2020 Department of DefenseNavy
SBC: TDA RESEARCH, INC. Topic: N21AT001
Hemp fibers have been used in textile applications for thousands of years, but have been limited to textiles for home furnishing, rope, sacks, and other non-clothing textile applications. However, new treatment methods for hemp fibers to improve their hand, as well hemp’s general softening properties with time and wear, make these fibers attractive for use in performance clothing due to hemp’s ...STTR Phase I 2021 Department of DefenseNavy
SBC: DYNAFLOW, INC Topic: N21AT013
Decompression sickness (DCS) can occur during rapid pressure changes such as when a diver ascends rapidly or during high altitude flights. Rapid decompression can causes gases dissolved in body fluids and tissues to come out of solution and form bubbles. The symptoms of DCS include painful joints, neurological dysfunction, dermal effects, and cardiopulmonary collapse. Currently, divers rely on dec ...STTR Phase I 2021 Department of DefenseNavy
SBC: INTELLIGENT FUSION TECHNOLOGY, INC. Topic: N21AT016
In order to facilitate collaborative decision-making during modern surface warfare situations, locally learned knowledge among sailors and warfighters must be shared effectively in a timely manner. Current Naval approaches for collecting and sharing knowledge are inefficient and inflexible, as new contents are examined over extended timelines with no ability to dynamically update the knowledge bas ...STTR Phase I 2021 Department of DefenseNavy
SBC: M4 ENGINEERING, INC. Topic: N20AT004
Advances in both software and computer hardware have made the finite element method the preeminent choice for analyzing highly complex systems that are of great value to the Department of Defense. The US Defense industry, however, continues to spend enormous time and resources in mesh generation, a key step in finite element analysis, despite progress that has been made in automated mesh gener ...STTR Phase I 2020 Department of DefenseNavy
SBC: Arete Associates Topic: N20AT007
Areté and the Machine Learning for Artificial Intelligence (MLAI) Lab at the University of Arizona (UofA) will develop and demonstrate new approaches that improve the performance of in situ machine learning (ML) algorithms as they evolve over time, adapt to new environments, and are capable of transferring their learned experiences across platforms. Technological advances that will be brought t ...STTR Phase I 2020 Department of DefenseNavy
SBC: INTELLIGENT FUSION TECHNOLOGY, INC. Topic: N20AT011
Modern US Navy ships and submarines are configured with an ever-increasing level of automation, including state-of-the-art embedded wireless sensors that monitor vital system functions. However, sensor nodes have the potential to serve as targets for cybersecurity attacks or be susceptible to corruption through accidental or malicious events. To address these shortfalls and minimize vulnerabilitie ...STTR Phase I 2020 Department of DefenseNavy
SBC: Objectsecurity LLC Topic: N20AT011
Condition-based maintenance plus (CBM+), and cyber-physical systems (CPS) in general, depend on correct sensor data for analysis, decision making and control loops. If the sensor data that arrives at the point of processing is not correct, or more accurate, is outside its accepted error range, then any further processing will be incorrect as well. This could result in, in the case of CBM+, not det ...STTR Phase I 2020 Department of DefenseNavy
SBC: Intelligent Automation, Inc. Topic: N20AT011
Navy is developing the concepts and methods to leverage Machine Learning (ML) techniques for the maintenance decision-making on condition-based maintenance plus (CBM+) platform. Effective health monitoring for condition-based and predictive maintenance requires intelligent sensor selection and placement, and context-aware interpretation of sensor data to detect the many possible fault modes. Moreo ...STTR Phase I 2020 Department of DefenseNavy
SBC: Intelligent Automation, Inc. Topic: N20BT026
NAVY seeks high strength, low density, and high corrosion resistant alloys for structural components which can be processed by additive manufacturing (AM). Magnesium (Mg) alloys are candidates for fuel-efficiency applications, especially the aircrafts. They satisfy density, strength, and stiffness for many designs. However, their low corrosion resistance cannot ensure design lifetimes. This limi ...STTR Phase I 2021 Department of DefenseNavy