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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.
Finis H. Southworth, Hugh D. Campbell
Nuclear Technology | Volume 30 | Number 3 | September 1976 | Pages 434-436
Technical Note | Uranium Resource / Reactor | doi.org/10.13182/NT76-A31656
Articles are hosted by Taylor and Francis Online.
Thermonuclear plasmas with a sufficient density-radius product, ρR, will degrade the energy spectrum of neutrons released in the plasma. This property may alleviate neutron damage, transmutation, and transient power loading in the first wall of laser-controlled thermonuclear reactors. In addition, degraded neutron energy spectra might be used as a diagnostic of compression in latter-stage laser fusion experiments. As an example of the degradation in the neutron spectrum, the energy spectrum of neutrons resulting from a thermonuclear deuterium-tritium plasma with ρR = 2 g/cm2 when using a simple model shows that ∼2.5 MeV of the neutron’s original 14.1 MeV is deposited in the pellet. As a figure of merit for the reduction of threshold reactions in the walls, the same model shows that ∼27%> of the neutrons are below 10 MeV in energy.