Colorado school of mines- new award control # 3590-1503, DE-FOA-0003590-magnetic acceleration generating new innovations and tactical outcomes (magnito) title: uranium based permanent magnets this…

The Department of Energy Advanced Research Projects Agency awarded a $378,588 cooperative agreement to the Trustees of the Colorado School of Mines on July 6, 2026, under the Advanced Research Projects Agency-Energy program (CFDA 81.135) to discover and develop uranium-based permanent magnets with superior energy density and performance under extreme conditions compared to existing rare-earth magnets.

Colorado School of Mines will employ advanced computational modeling, artificial intelligence, and materials science to predict uranium intermetallic compounds with exceptional magnetic strength and thermal stability using density functional theory and machine learning. The institution will synthesize and characterize promising candidates through techniques measuring magnetization, coercivity, Curie temperature, and hysteresis characteristics. The work will engineer microstructures by tuning grain size, strain, and domain wall pinning to optimize magnetic behavior. The research targets materials with strong spin-orbit coupling, complex chemistries, and unique 5F electron behavior to enable magnetic properties exceeding rare-earth systems, supporting the MAGNITO program's objectives to reduce dependence on imported rare earths and develop high-stability, radiation-hard, and energy-efficient technologies across energy, defense, and quantum applications.

Performance occurs in Golden, Colorado, with a period of performance extending from July 6, 2026, through July 5, 2029.

Colorado school of mines- new award control # 3590-1503, DE-FOA-0003590-magnetic acceleration generating new innovations and tactical outcomes (magnito) title: uranium based permanent magnets this project seeks to discover and develop a new class of ultra hard and strong permanent magnets based on uranium intermetallic compounds. While today's rare earth magnets are powerful, they face limits in energy density and performance under extreme conditions. Our goal is to identify materials with higher saturation magnetization or maximum energy product than any known magnet, requiring exploration of novel approach and chemical structures. We combine advanced computational modeling, artificial intelligence, and materials science. Using density functional theory, machine learning, and AI, we will predict uranium based compounds with exceptional magnetic strength and thermal stability. Promising candidates will be synthesized and characterized using techniques that measure magnetization, coercivity, curie temperature, and hysteresis characteristic. To further enhance performance, we will engineer microstructures, tuning grain size, strain, and domain wall pinning, to optimize magnetic behavior. This work supports the magnito program by targeting materials with strong spin-orbit coupling, complex chemistries, and unique 5F electron behavior, potentially enabling magnetic properties far beyond rare earth systems. Our team integrates expertise in computational materials discovery, solid-state chemistry and physics, and advanced magnetic measurements. If successful, the outcomes will redefine how anisotropy, coercivity, and magnetization are interlinked, transforming uranium intermetallics from subjects of fundamental physics studies into a transformational materials platform for high stability, radiation hard, and energy efficient technologies across energy, defense, and quantum domains. By reducing dependence on imported rare earths, this work directly supports arpa-e's mission to enhance U.S. Energy security and leadership in advanced materials innovation.