Quantum Science and AI Meet Nuclear Forensics
Detecting and analyzing nuclear materials is a critical challenge in global security, yet current methods often struggle with accuracy, efficiency, and scalability. One of the biggest gaps in nuclear forensics is the lack of advanced materials capable of reliably sensing radiation and providing clear, identifiable signals.
Ed Cazalas, a Professor in the Utah Nuclear Engineering Program (UNEP), is developing cutting-edge technologies that will more accurately detect and analyze nuclear materials.
Leveraging Advanced Materials
Supported by a $400,000 grant from the National Nuclear Security Administration’s Consortium for Nuclear Forensics, Cazalas’s project will leverage the unique properties of 2-D materials and quantum dots to enhance radiation detection. While fields like electronics and medicine have harnessed the power of 2-D and quantum materials, their potential in nuclear detection remains largely untapped. Cazalas and his team at the University of Utah are working to change that—exploring how these cutting-edge materials, combined with artificial intelligence and machine learning, could revolutionize the way we track, identify, and safeguard nuclear materials.
2-D materials are ultra-thin substances, often just a few atoms thick, with unique electrical and mechanical properties that make them highly sensitive to external stimuli like radiation. Quantum materials, including quantum dots, exhibit special properties which allow them to interact with radiation in ways that could revolutionize nuclear detection.
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