Award Data

"To enable the future needs of efficient computing for edge data centers, Flexnode and its partners, the University of Maryland (UMD), Boeing, Iceotope, SHoP Architects, and Arup, propose to develop a prefabricated modular micro data center with unprecedented energy efficiency and power density. The proposed system leverages four key component and system-level technology advancements: (a) a novel, ...

"To enable the future needs of efficient computing for edge data centers, Flexnode and its partners, the University of Maryland (UMD), Boeing, Iceotope, SHoP Architects, and Arup, propose to develop a prefabricated modular micro data center with unprecedented energy efficiency and power density. The proposed system leverages four key component and system-level technology advancements: (a) a novel, ...

"To enable the future needs of efficient computing for edge data centers, Flexnode and its partners, the University of Maryland (UMD), Boeing, Iceotope, SHoP Architects, and Arup, propose to develop a prefabricated modular micro data center with unprecedented energy efficiency and power density. The proposed system leverages four key component and system-level technology advancements: (a) a novel, ...

Development of hypersonic aircraft and weapon systems has become a critical focus for the Department of Defense to maintain global strike and projection of force capabilities. Despite decades of research, traditional computational fluid dynamics (CFD) methods are either incapable of adequately predicting complex features in hypersonic flows or too expensive to be of practical use for vehicle desig ...

Physical Sciences Inc. (PSI) proposes to develop a multimodal data fusion algorithm that is based on deep learning algorithms to detect previously unseen fentanyl analogs. The algorithm will be deployed on a hardware kit which contains a handheld Raman spectrometer and mass spectrometer (MS). The Raman spectrometer will be a handheld adaptation of PSI’s existing through-container Raman chem ...

IonicScale LLC is developing a handheld chemical sensor based on ion trap mass spectrometry (MS). The chemical analyzer has proven sub-isotopic mass resolution for gas phase analysis. For this project, it is proposed to demonstrated basic feasibility to extend the device's capability to sampling of solids (e.g., pills, powders, or other swabbed materials). In addition, the proposed effort will imp ...

Pendar Technologies is tackling the challenge posed by the rapid evolution of synthetic opioids, particularly fentanyl and its analogs, by developing a deep learning classifier for our Pendar X10 handheld Raman spectrometer. The effort would significantly advance the safety and detection capabilities of law enforcement officers and first responders in addressing the opioid crisis.Our approach invo ...

Synthetic opioids have been responsible for most drug overdoses in the US in the last several years. Specifically, the use of fentanyl and fentanyl analogues have led to an alarming 7.5X increase in the number of overdoses from 2015 to 2021. Developing a strategy for countering the proliferation of synthetic opioids and overdoses in the US is challenging for several reasons. First, the structure o ...

The Data Labeling and Curation at Scale (DLCS) project will create a system called CLARIFIER, which aims to revolutionize the way large volumes of complex data are processed and utilized for machine learning (ML) applications within the Department of Homeland Security (DHS). The primary purpose of this work is to develop an advanced system capable of ingesting, labeling, storing, and curating dive ...

Homeland Security operations create a large amount of data from millimeter-wave and Computed Tomography X-ray detection systems.The Transportation Security Administration’s Electronic Baggage Screening Program provides an excellent example of the immense volume of screening conducted and X-ray image data generated, since the Aviation and Transportation Security Act (Pub. L. 107-71, 2001) re ...