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Sanchez, Alec J., Maier, Sarah, Raghavachari, Krishnan (2024) Leveraging DFT and Molecular Fragmentation for Chemically Accurate pKa Prediction Using Machine Learning. Journal of Chemical Information and Modeling, 64 (3) 712-723 doi:10.1021/acs.jcim.3c01923

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Reference TypeJournal (article/letter/editorial)
TitleLeveraging DFT and Molecular Fragmentation for Chemically Accurate pKa Prediction Using Machine Learning
JournalJournal of Chemical Information and Modeling
AuthorsSanchez, Alec J.Author
Maier, SarahAuthor
Raghavachari, KrishnanAuthor
Year2024 (February 12)Volume64
Issue3
PublisherAmerican Chemical Society (ACS)
DOIdoi:10.1021/acs.jcim.3c01923Search in ResearchGate
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Mindat Ref. ID17156749Long-form Identifiermindat:1:5:17156749:8
GUID0
Full ReferenceSanchez, Alec J., Maier, Sarah, Raghavachari, Krishnan (2024) Leveraging DFT and Molecular Fragmentation for Chemically Accurate pKa Prediction Using Machine Learning. Journal of Chemical Information and Modeling, 64 (3) 712-723 doi:10.1021/acs.jcim.3c01923
Plain TextSanchez, Alec J., Maier, Sarah, Raghavachari, Krishnan (2024) Leveraging DFT and Molecular Fragmentation for Chemically Accurate pKa Prediction Using Machine Learning. Journal of Chemical Information and Modeling, 64 (3) 712-723 doi:10.1021/acs.jcim.3c01923
In(2024, February) Journal of Chemical Information and Modeling Vol. 64 (3) American Chemical Society (ACS)

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