Reinforcement Learning‐Guided Long‐Timescale Simulation of Hydrogen Transport in Metals
Reinforcement Learning‐Guided Long‐Timescale Simulation of Hydrogen Transport in Metals
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Author / Creator
Tang, Hao , Li, Boning , Song, Yixuan , Liu, Mengren , Xu, Haowei , Wang, Guoqing , Chung, Heejung and Li, Ju
Publisher
Germany: John Wiley & Sons, Inc
Journal title
Language
English
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Publication information
Publisher
Germany: John Wiley & Sons, Inc
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Scope and Contents
Contents
Diffusion in alloys is an important class of atomic processes. However, atomistic simulations of diffusion in chemically complex solids are confronted with the timescale problem: the accessible simulation time is usually far shorter than that of experimental interest. In this work, long‐timescale simulation methods are developed using reinforcement...
Alternative Titles
Full title
Reinforcement Learning‐Guided Long‐Timescale Simulation of Hydrogen Transport in Metals
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Author / Creator
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Record Identifier
TN_cdi_doaj_primary_oai_doaj_org_article_02e1f30309cf455bb4ea9abd1882640e
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_02e1f30309cf455bb4ea9abd1882640e
Other Identifiers
ISSN
2198-3844
E-ISSN
2198-3844
DOI
10.1002/advs.202304122
