William H. Green
Affiliations: | 1997- | Chemical Engineering | Massachusetts Institute of Technology, Cambridge, MA, United States |
Area:
Chemical KineticsWebsite:
http://greengroup.mit.eduGoogle:
"William H. Green"Parents
Sign in to add mentorC. Bradley Moore | grad student | 1983-1988 | UC Berkeley |
Nicholas C. Handy | post-doc | 1989-1990 | Cambridge |
Marsha I. Lester | post-doc | 1991-1991 | Penn |
Children
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Publications
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Tu Z, Choure SJ, Fong MH, et al. (2025) ASKCOS: Open-Source, Data-Driven Synthesis Planning. Accounts of Chemical Research |
Zheng Z, Florit F, Jin B, et al. (2024) Integrating Machine Learning and Large Language Models to Advance Exploration of Electrochemical Reactions. Angewandte Chemie (International Ed. in English). e202418074 |
Spiekermann KA, Dong X, Menon A, et al. (2024) Accurately Predicting Barrier Heights for Radical Reactions in Solution Using Deep Graph Networks. The Journal of Physical Chemistry. A. 128: 8384-8403 |
Li SC, Wu H, Menon A, et al. (2024) When Do Quantum Mechanical Descriptors Help Graph Neural Networks to Predict Chemical Properties? Journal of the American Chemical Society |
Wu H, Payne AM, Pang HW, et al. (2024) Toward Accurate Quantum Mechanical Thermochemistry: (1) Extensible Implementation and Comparison of Bond Additivity Corrections and Isodesmic Reactions. The Journal of Physical Chemistry. A |
Pang HW, Dong X, Johnson MS, et al. (2024) Subgraph Isomorphic Decision Tree to Predict Radical Thermochemistry with Bounded Uncertainty Estimation. The Journal of Physical Chemistry. A |
Chung Y, Green WH. (2024) Machine learning from quantum chemistry to predict experimental solvent effects on reaction rates. Chemical Science. 15: 2410-2424 |
Heid E, Greenman KP, Chung Y, et al. (2023) Chemprop: A Machine Learning Package for Chemical Property Prediction. Journal of Chemical Information and Modeling. 64: 9-17 |
Koscher BA, Canty RB, McDonald MA, et al. (2023) Autonomous, multiproperty-driven molecular discovery: From predictions to measurements and back. Science (New York, N.Y.). 382: eadi1407 |
Heid E, Probst D, Green WH, et al. (2023) EnzymeMap: curation, validation and data-driven prediction of enzymatic reactions. Chemical Science. 14: 14229-14242 |