Structure Analysis of LiF-NaF-ZrF4 Molten Salts with Deep Learning Potentials

Rajni Chahal, Stephen T. Lam

Research output: Contribution to journalConference articlepeer-review

1 Scopus citations
Original languageEnglish
Pages (from-to)113-116
Number of pages4
JournalTransactions of the American Nuclear Society
Volume126
DOIs
StatePublished - 2022
Externally publishedYes
Event2022 Transactions of the American Nuclear Society Annual Meeting, ANS 2022 - Anaheim, United States
Duration: Jun 12 2022Jun 16 2022

Funding

This work is supported by DOE-NE’s Nuclear Energy University Program (NEUP) under Award DE-NE0009204. A part of the computational resources were provided by Massachusetts green high-performance computing cluster (MGHPCC). This research also used resources of the National Energy Research Scientific Computing Center, a DOE Office of Science User Facility supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231.

FundersFunder number
U.S. Department of EnergyDE-AC02-05CH11231
Office of Science
Office of Nuclear EnergyDE-NE0009204
Massachusetts Green High Performance Computing Center

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