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Argonne: Where AI research meets education and training
Last September, in the Chicago suburb of Lemont, Ill., Argonne National Laboratory hosted its first AI STEM Education Summit. More than 180 educators from high schools, community colleges, and universities; STEM administrators; and experts in various disciplines convened at “One Ecosystem, Many Pathways–Building an AI-Ready STEM Workforce” to discuss how artificial intelligence is reshaping STEM-related industries, including the implications for the nuclear engineering classroom and workforce.
Carleton D. Bingham, Morris W. Lerner
Nuclear Technology | Volume 23 | Number 2 | August 1974 | Pages 106-111
Technical Paper | Nuclear Safeguards (Presented at November 1973 Meeting) / Safeguard | doi.org/10.13182/NT74-A31442
Articles are hosted by Taylor and Francis Online.
Nuclear materials safeguards have spurred the development of faster, cheaper, and more reliable methods for the assay of uranium materials in the nuclear fuel cycle. These requirements have been met by an elegantly simple method suitable for both manual and automated operation. Dissolution of some samples remains a vexing problem, but some advances in this area are being made. Intra-and interlaboratory control programs are necessary to maintain the highest possible reliability of the analytical results.