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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.
O. K. Tallent, J. C. Mailen
Nuclear Technology | Volume 34 | Number 3 | August 1977 | Pages 416-419
Technical Paper | Chemical Processing | doi.org/10.13182/NT77-A31806
Articles are hosted by Taylor and Francis Online.
The effects of Cu2+, Hg2+, Zn2+, La3+, Ce3+, Al3+, Pu4+, Th4+, and Zr4+ metal ion impurities on PuO2 dissolution in 8.0M HNO3—0.1M HF solution at 100°C have been investigated. Results based on 1.0 h of dissolution time show that such metal ions as Al3+, Pu4+, Th4+, and Zr4+, which form strong fluoride complexes, greatly decrease the dissolution rate, whereas such metal ions as Cu2+, Hg2+, Zn2+, La3+, and Ce3+, which form relatively weak fluoride complexes, have little or no effect. Fluoride ion activities in the dissolvents were calculated based on an empirical equation, K1aF + aF − 0.10 γs = 0, where K1, aF, and γs denote first metal ion fluoride complex stability constant, fluoride ion activity, and stoichiometric fluoride ion activity coefficient, respectively. The PuO2 dissolution rates were found to increase linearly with increase in the calculated fluoride ion activities.