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The Award database is continually updated throughout the year. As a result, data for FY23 is not expected to be complete until September, 2024.
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SBC: Luminit LLC Topic: AF18BT004
To address the U.S. Air Force need for Developing innovative wave-optics Propagation methods to model laser systems that are faster, efficient and more accurate, Luminit, LLC, and University of Southern California (USC) propose to develop Wave-Optic Propagation Computation Enabled by Machine Learning Algorithms (WOPA). The proposed algorithms will be based on cutting off redundant frequencies upon ...STTR Phase I 2019 Department of DefenseAir Force
SBC: Electronics of the future, Inc.. Topic: AF18BT006
The project will develop and validate a geometry scalable CNTFET compact model for HF circuit design and extract the model parameters from the measured characteristics of the fabricated devices. The ballistic and quasi-ballistic transport, quantum and parasitic effects will be accounted for the predicted performance will be compared to 130 nm RF Si-CMOS to determine the conditions for breaking eve ...STTR Phase I 2019 Department of DefenseAir Force
SBC: J.T. McGraw and Associates, LLC Topic: AF16AT05
Commercially-derived telescope systems, consisting mostly of commercially available components assembled to optimally meet space surveillance goals, stand ready to temporarily replace, supplement and/or augment existing optical surveillance systems. In t...STTR Phase I 2016 Department of DefenseAir Force
SBC: Prioria Robotics, Inc. Topic: AF15AT01
ABSTRACT: Our focus in this proposal is to perform basic research to create bio-inspired 3-D morphing mechanical structures which are a gateway technology to enable true 3-D morphing flight. Prioria and Virginia Tech University will team to perform basic research into bio-inspired structure such as artificial bones/wings/feathers and artificial muscles. Prioria will establish technical feasibility ...STTR Phase I 2016 Department of DefenseAir Force
SBC: Information Systems Laboratories, Inc. Topic: AF19AT010
Recent advances and successes of deep learning neural networks (DLNN) techniques and architectures have been well publicized over the last several years. Voluminous, high-quality and annotated training data, or trial and error in a realistic environment, is required to achieve the promised performance potential of DLNNs. Unfortunately for DoD and/or Intelligence Community (IC) applications of mult ...STTR Phase I 2019 Department of DefenseAir Force
SBC: METRON INCORPORATED Topic: AF19AT009
The objective of this project is to develop human intelligence-inspired algorithms that exploit multi-modal sources of low and high quality data to achieve a series of objectives such as detection, localization, tracking, and classification. A Bayesian model-based hierarchical adaptive decision making (HADM) algorithm will be developed which includes multiple levels of decision making organized in ...STTR Phase I 2019 Department of DefenseAir Force
SBC: DOLCE Technologies, LLC Topic: AF09BT33
DOLCE Technologies, LLC, in collaboration with Professor Rick Averitt’s research group at Boston University and Eric Shaner’s group at Sandia National Laboratories, will develop and deliver a high performance room-temperature Terahertz detector array solution based on metamaterial absorbers integrated with bi-material cantilevers. The metamaterial approach is frequency scalable and can operat ...STTR Phase I 2010 Department of DefenseAir Force
SBC: ITN ENERGY SYSTEMS, INC. Topic: AF09BT33
This Small Business Technology Transfer Research phase I program will develop a new class of uncooled THz detectors for the 1-10THz band with a novel design using surface plasmon resonant cavities with integrated metal-insulator-metal tunneling diodes as the detecting element. Tunneling diodes provide ultrafast broadband response, potentially into the visible (300THz), but demonstrated performanc ...STTR Phase I 2010 Department of DefenseAir Force
SBC: ITN ENERGY SYSTEMS, INC. Topic: AF09BT39
This Small Business Technology Transfer Research phase I program will develop a new class of surface plasmon enhanced photovoltaic devices that exhibit increased current collection. Photon management, the manipulation of the incident optical field to increase the probability that a photon is absorbed in the active region of the cell, is critical to the development of next generation thin film sol ...STTR Phase I 2010 Department of DefenseAir Force
SBC: ITN ENERGY SYSTEMS, INC. Topic: AF08BT18
This Small Business Technology Transfer Phase I project will develop ultradense, low-power plasmonic integration components and devices for on-chip manipulation and processing of optical signals. Both passive and active components will be studied. Detailed performance predictions will be obtained through finite element modeling (FEM) of the harmonic Maxwell’s equations. The FEM provides detai ...STTR Phase I 2010 Department of DefenseAir Force