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2025 ANS Winter Conference & Expo
November 9–12, 2025
Washington, DC|Washington Hilton
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Latest News
Princeton-led team develops AI for fusion plasma monitoring
A new AI software tool for monitoring and controlling the plasma inside nuclear fuel systems has been developed by an international collaboration of scientists from Princeton University, Princeton Plasma Physics Laboratory (PPPL), Chung-Ang University, Columbia University, and Seoul National University. The software, which the researchers call Diag2Diag, is described in the paper, “Multimodal super-resolution: discovering hidden physics and its application to fusion plasmas,” published in Nature Communications.
R. L. Macklin, J. Halperin
Nuclear Science and Engineering | Volume 64 | Number 4 | December 1977 | Pages 849-858
Technical Paper | doi.org/10.13182/NSE77-A14500
Articles are hosted by Taylor and Francis Online.
Neutron capture by isotopically purified 232Th was measured at the Oak Ridge Electron Linear Accelerator. The pulse-height weighting method was used with small liquid scintillators to measure the prompt gamma-ray energy release following neutron capture. Resonance parameters were derived up to 10 keV. The average radiative width was (19.8 ± 0.2 statistical ± 0.4 systematic) meV for 50 resonances in the 2.6- to 4.0-keV interval. Strength functions 104S0 = 0.365 ± 0.024, 104 S1 = 1.078 ± 0.057, 104S2 > 0.842 ± 0.084, and y/D0 = 0.0198/(13.24 ± 0.71) were found to fit the average cross section well (to 105 keV) when allowance was made for p-wave inelastic competition above the ∼50-keV threshold. While the values stated gave the best fit (from 2.6 to 105 keV) when all four were allowed to vary, it is likely that “acceptable” fits could be forced for other values. Recent evaluations of the cross section range from 8 to 50% higher than results reported here.