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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.
W. Beyrich, G. Spannagel
Nuclear Technology | Volume 42 | Number 3 | March 1979 | Pages 337-342
Technical Paper | Analysis | doi.org/10.13182/NT79-A32190
Articles are hosted by Taylor and Francis Online.
If different laboratories using thermionic mass spectrometry determine in routine operation a 235U concentration of ≈0.7% in the same sample material, their measurement results deviate by at least 0.8% (relative) in ≈50% of the cases. The application of gas mass spectrometry reduces this deviation to 0.1 or 0.05%, the more favorable value being obtained by measurements in which the same reference material is used by all laboratories. These results were obtained by application of an empirical evaluation procedure that, contrary to the usual statistical tools, is not restricted to homogeneous data material. The data were taken from two interlaboratory evaluation programs performed recently on the isotopic abundance determination of 235U in uranium hexafluoride by mass spectrometry.