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Award Data

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The Award database is continually updated throughout the year. As a result, data for FY20 is not expected to be complete until September, 2021.

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.

Displaying 71 - 80 of 188030 results
  1. Rapid Design Space Exploration for Mapping Applications to Neuromorphic Processors

    SBC: BRISK COMPUTING LLC            Topic: N202108

    The objective of this SBIR proposal is to develop a design space exploration tool to rapidly evaluate different neuromorphic processing options for a given application. The neuromorphic options to be examined include deep learning accelerators, spiking neuron accelerators, memristive systems, and photonic accelerators. The tool will work with both individual algorithms and with chains of algorithm ...

    SBIR Phase I 2021 Department of DefenseNavy
  2. Spiking Neural Network Modeler (SpiNNMo)

    SBC: Chromologic LLC            Topic: N202108

    In order to meet the Navy’s need for a spiking neural network testing platform, ChromoLogic proposes to develop a Spiking Neural Network Modeler (SpiNNMo) capable of simulating a variety of neuromorphic hardware platforms. SpiNNMo will allow the Navy to test the performance of new spiking neural network architectures and hardware technologies in their RF signal processing pipelines. SpiNNMo simu ...

    SBIR Phase I 2021 Department of DefenseNavy
  3. Monolithic Low Cost Dual-Band Quantum Cascade Laser

    SBC: Pendar Technologies, LLC            Topic: N202115

    Pendar Technologies proposes to develop the next generation of compact, monolithic and dual-wavelength high power mid-wave infrared (MWIR) quantum cascade laser (QCL) platform for Navy and DoD applications. Our novel infrared laser source will be engineered to emit simultaneously output power more than 3 Watts in each of  the two optically transparent windows available in the MWIR, i.e. the 4.6-5 ...

    SBIR Phase I 2021 Department of DefenseNavy
  4. Monolithic Dual-Band Single-Mode Quantum Cascade Laser

    SBC: TransWave Photonics, LLC            Topic: N202115

    TransWave Photonics proposes to develop a monolithic, mass-producible quantum cascade laser emitting at two mid-wave infrared bands. Leveraging expertise in development of high power dual-wavelength mid-infrared quantum cascade lasers, we propose a heterogeneous active region capable to produce continuous-wave output power more than 3W for each band and wall-plug efficiency higher than 15% at roo ...

    SBIR Phase I 2021 Department of DefenseNavy
  5. Monolithic Dual-Band Quantum Cascade Laser

    SBC: IRGLARE, LLC            Topic: N202115

    The development of monolithic dual-band Quantum Cascade Lasers (QCLs) delivering continuous wave (CW) optical power exceeding 3W at ~4.6µm and ~4.0µm from a single emitter in a nearly Gaussian output beam (M2 < 1.5) with wallplug efficiency exceeding 15%.  The entire QCL package will have a volume size of less than 1 cm3 and will weigh less than 100g.

    SBIR Phase I 2021 Department of DefenseNavy
  6. Detailed Manufacturing Planning and Trade-off Analysis of Topology-Optimized Parts

    SBC: Medema Labs Corp            Topic: N202117

    While topology optimization can define parts that have minimal and nearly uniform strain energy, these solutions cannot be manufactured without modification. Numerous research papers have looked at ways to incorporate manufacturing constraints within the optimization. This has promise for additive manufacturing but has significant hurdles when subtractive manufacturing is used. There is not a clea ...

    SBIR Phase I 2021 Department of DefenseNavy
  7. Software Optimized Subtractive Manufacturing

    SBC: CREARE LLC            Topic: N202117

    Currently across the DoD and commercial sector, a part “optimized” for strength, stiffness, and weight is achieved using a tedious, multi-step process. Typically, optimization is conducted through a series of iterative design/engineering analyses, yet in some instances topology optimization is used. What the existing FEA software lacks is the ability to enforce constraints associated with subt ...

    SBIR Phase I 2021 Department of DefenseNavy
  8. Optimized Subtractive Manufacturing- MSC P4595

    SBC: Materials Sciences LLC            Topic: N202117

    Currently, commercially available structural optimization methods, e.g., topology, shape, etc., result in a mesh-based output.  This mesh-based output is not generally in a format directly usable to create a part by either additive manufacturing (AM) or subtractive manufacturing.  Further, optimization method that do not incorporate manufacturing constraints often result in complex geometries th ...

    SBIR Phase I 2021 Department of DefenseNavy
  9. Identifying and Characterizing Cognitive Sensor Systems in Tactical Environments

    SBC: Vadum, Inc.            Topic: N202121

    Adversary radar jamming capability will greatly increase in the near future.  Improvements in radio frequency (RF) hardware, especially in solid state RF electronics, will lead to improved jammer capability with reduced size, weight, and power requirements.  Moreover, improvements in embedded computer systems will give jammers access to powerful machine learning and artificial intelligence algor ...

    SBIR Phase I 2021 Department of DefenseNavy
  10. Identifying and Characterizing Cognitive Sensor Systems in Tactical Environments

    SBC: PERCEPTRONICS SOLUTIONS, INC.            Topic: N202121

    The proposed DEfeating Cognitive Sensors through Tactical Adversarial Machine Learning (DECTAM) system will intelligently probe adversary cognitive sensor systems, characterize how the adversary system responds to changing stimuli, and using that information to identify vulnerabilities in the adversary system. Our approach takes academic research into adversarial learning and transitions those con ...

    SBIR Phase I 2021 Department of DefenseNavy
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