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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.
D. A. Lee, D. A. Constanzo, D. P. Stinton, J. A. Carpenter, Jr., W. T. Rainey, Jr., D. C. Canada, J. A. Carter
Nuclear Technology | Volume 34 | Number 1 | June 1977 | Pages 89-97
Technical Paper | Fuel | doi.org/10.13182/NT77-A31832
Articles are hosted by Taylor and Francis Online.
The carbonization, conversion, and coating processes in the manufacture of high-temperature gas-cooled reactor fuel particles have been studied with the use of a time-of-flight mass spectrometer. Noncondensable effluents from these fluidized-bed processes have been monitored continuously from the beginning to the end of the process. The processes monitored are these: uranium-loaded ion exchange resin carbonization, the carbothermic reduction of UO2 to UC2, buffer and low-temperature isotropic pyrocarbon coatings of fuel kernels, SiC coating of the kernels, and high-temperature particle annealing. Changes in concentrations of significant molecules with time and temperature have been useful in the interpretation of reaction mechanisms and optimization of process procedures.