Award Data

Advance warning of chemical and biological (CB) threats is of critical importance to our warfighters and continues to be a major challenge for the CB Defense Science and Technology (S&T) community. Recent research and development in the CBD S&T community has emphasized Integrated Early Warning (IEW) architectures that rely upon a layered sensing strategy that includes CBD-specific sensors such as ...

NDT of Fracture Toughness for Pipeline Steels3/16/2018Ultrasound-based technology to nondestructively determine fracture toughness of pipeline steels will be developed. Fracture toughness is the material parameter that, along with applied loading and flaw geometry, dictates the critical crack size, and therefore controls the flaw size that must be detected during inspections. A major challenge fac ...

Tragically, 936 children have died in hot cars since 1998. Wisely, NHTSA has prioritized evaluation of sensor systems in vehicles for “the ability to detect unattended children and prevent heat stroke occurrence.”Recently, innovators have developed systems that detect children present in the vehicle by measuring carbon dioxide (CO2) in the vehicle cabin, but there is no test method to assess w ...

Warfighters in far-forward deployed settings are at risk for exposure to weaponized opioids and subsequent opioid intoxication. Naloxone is ordinarily effective as an immediate opioid poisoning antidote. However, synthetically derived opioids such as carfentanil and fentanyl-derivatives have a half-life that exceeds that of naloxone, subjecting victims to a phenomenon known as renarcotization, req ...

Concealed chemical threats represent a significant hazard to field operators. Even brief exposure to chemicals can cause lasting physical, physiological, and mental damage. Field operators require tools and techniques to more quickly, safely, and reliably locate and identify chemical threats. Chemical detectors typically excel at either threat classification or threat localization, but seldom both ...

This SBIR effort proposes using live and continuous monitoring of metal tanks, pressure vessels, and pipelines using carbon nanomaterial-based sensing skins to detect excessive physical strains, cracks, and to inspect impact damage. The proposed research and development work leverages 15+ years of fundamental research. The key objective is to advance the TRL level and the scalability of carbon nan ...

In response to the DOT’s FY21 SBIR topic 21-FT2, Interphase Materials (IPM) proposes the development of a low-cost automated data collection system that uses machine learning (ML), a type of artificial intelligence (AI), to predict and alert transit agencies of biological and viral contamination risks making condition-based sanitization possible for more effective and efficient operations.The CO ...

In a battlefield or other active environment where hundreds or thousands of aerosol plumes may be generated every day, it is a challenge to identify the rare plume resulting from a deliberate dissemination. Machine learning (ML) algorithms can be trained to identify patterns and features based on training data and have the potential to distinguish between intentionally disseminated plumes that may ...

Nanoplastics (plastic debris

The standoff detection of potential threats to military personnel is of primary importance to the Department of Defense as a whole. Millimeter wave imagers are one class of sensor systems that have been employed for the detection of a variety of threats including chemical/biological agents, improvised explosive devices, land-mines, and unmanned aerial systems (UASs). More specifically, W-band (75 ...