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Shi, Zhiyu, Lele, Aditya Dilip, Jasper, Ahren W., Klippenstein, Stephen J., Ju, Yiguang (2024) Quasi-Classical Trajectory Calculation of Rate Constants Using an Ab Initio Trained Machine Learning Model (aML-MD) with Multifidelity Data. The Journal of Physical Chemistry A, 128 (17) 3449-3457 doi:10.1021/acs.jpca.4c00750

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Reference TypeJournal (article/letter/editorial)
TitleQuasi-Classical Trajectory Calculation of Rate Constants Using an Ab Initio Trained Machine Learning Model (aML-MD) with Multifidelity Data
JournalThe Journal of Physical Chemistry A
AuthorsShi, ZhiyuAuthor
Lele, Aditya DilipAuthor
Jasper, Ahren W.Author
Klippenstein, Stephen J.Author
Ju, YiguangAuthor
Year2024 (May 2)Volume128
Issue17
PublisherAmerican Chemical Society (ACS)
DOIdoi:10.1021/acs.jpca.4c00750Search in ResearchGate
Generate Citation Formats
Mindat Ref. ID17382496Long-form Identifiermindat:1:5:17382496:4
GUID0
Full ReferenceShi, Zhiyu, Lele, Aditya Dilip, Jasper, Ahren W., Klippenstein, Stephen J., Ju, Yiguang (2024) Quasi-Classical Trajectory Calculation of Rate Constants Using an Ab Initio Trained Machine Learning Model (aML-MD) with Multifidelity Data. The Journal of Physical Chemistry A, 128 (17) 3449-3457 doi:10.1021/acs.jpca.4c00750
Plain TextShi, Zhiyu, Lele, Aditya Dilip, Jasper, Ahren W., Klippenstein, Stephen J., Ju, Yiguang (2024) Quasi-Classical Trajectory Calculation of Rate Constants Using an Ab Initio Trained Machine Learning Model (aML-MD) with Multifidelity Data. The Journal of Physical Chemistry A, 128 (17) 3449-3457 doi:10.1021/acs.jpca.4c00750
In(2024, May) The Journal of Physical Chemistry A Vol. 128 (17) American Chemical Society (ACS)


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