| Regio-selectivity prediction with a machine-learned reaction representation and on-the-fly quantum mechanical descriptors Y Guan, CW Coley, H Wu, D Ranasinghe, E Heid, TJ Struble, L Pattanaik, ... Chemical Science 12 (6), 2198-2208, 2021 | 101 | 2021 |
| Group contribution and machine learning approaches to predict Abraham solute parameters, solvation free energy, and solvation enthalpy Y Chung, FH Vermeire, H Wu, PJ Walker, MH Abraham, WH Green Journal of Chemical Information and Modeling 62 (3), 433-446, 2022 | 81 | 2022 |
| Chemprop: A machine learning package for chemical property prediction E Heid, KP Greenman, Y Chung, SC Li, DE Graff, FH Vermeire, H Wu, ... Journal of Chemical Information and Modeling 64 (1), 9-17, 2023 | 38 | 2023 |
| Automated reaction kinetics and network exploration (Arkane): A statistical mechanics, thermodynamics, transition state theory, and master equation software AG Dana, MS Johnson, JW Allen, S Sharma, S Raman, M Liu, CW Gao, ... International Journal of Chemical Kinetics 55 (6), 300-323, 2023 | 27 | 2023 |
| Enhanced light extraction from free-standing InGaN/GaN light emitters using bio-inspired backside surface structuring CD Pynn, L Chan, FL Gonzalez, A Berry, D Hwang, H Wu, T Margalith, ... Optics Express 25 (14), 15778-15785, 2017 | 17 | 2017 |
| Autonomous, multiproperty-driven molecular discovery: From predictions to measurements and back BA Koscher, RB Canty, MA McDonald, KP Greenman, CJ McGill, ... Science 382 (6677), eadi1407, 2023 | 16 | 2023 |
| Kinetic Modeling of API Oxidation: (1) The AIBN/H2O/CH3OH Radical “Soup” A Grinberg Dana, H Wu, DS Ranasinghe, FC Pickard IV, GPF Wood, ... Molecular Pharmaceutics 18 (8), 3037-3049, 2021 | 16 | 2021 |
| Kinetic Modeling of API Oxidation:(2) Imipramine Stress Testing H Wu, A Grinberg Dana, DS Ranasinghe, FC Pickard IV, GPF Wood, ... Molecular Pharmaceutics 19 (5), 1526-1539, 2022 | 13 | 2022 |
| ARC-automated rate calculator, version 1.1. 0 A Grinberg Dana, D Ranasinghe, H Wu, C Grambow, X Dong, M Johnson, ... Zenodo https://doi. org/10.5281/zenodo 3356849, 2019 | 11* | 2019 |
| Predicting critical properties and acentric factors of fluids using multitask machine learning S Biswas, Y Chung, J Ramirez, H Wu, WH Green Journal of Chemical Information and Modeling 63 (15), 4574-4588, 2023 | 10 | 2023 |
| Towards Accurate Quantum Mechanical Thermochemistry:(1) Extensible Implementation and Comparison of Bond Additivity Corrections and Isodesmic Reactions H Wu, AM Payne, HW Pang, A Menon, CA Grambow, DS Ranasinghe, ... | 1* | 2024 |
| When Do Quantum Mechanical Descriptors Help Graph Neural Networks Predict Chemical Properties? SC Li, H Wu, A Menon, K Spiekermann, YP Li, W Green | | 2024 |
| Recent Advances in Predictive Kinetics W Green, X Dong, HW Pang, YT Wang, K Spiekermann, H Wu, Y Chung, ... 2023 AIChE Annual Meeting, 2023 | | 2023 |
| Assessing the Impact of Quantum Mechanical Descriptors on D-Mpnn Performance for Chemical Property Prediction SC Li, A Menon, H Wu, K Spiekermann, W Green 2023 AIChE Annual Meeting, 2023 | | 2023 |
| Dataset and Models for Predicting Critical Properties of Fluids S Biswas, Y Chung, H Wu, W Green 2023 AIChE Annual Meeting, 2023 | | 2023 |
| Quantumpioneer: Self-Evolving Machine for High-Throughput Automated Potential Energy Surface Exploration and Closed-Loop Chemical Reactivity Discovery H Wu, HW Pang, X Dong, JW Burns, K Spiekermann, A Menon, J Zheng, ... 2023 AIChE Annual Meeting, 2023 | | 2023 |
| An End-to-End Workflow for Diverse Transition State Conformer Generation Using Machine Learning L Pattanaik, X Dong, H Wu, K Spiekermann, HW Pang, W Green 2022 AIChE Annual Meeting, 2022 | | 2022 |
| MIT Climate Grand Challenge: Tough to Decarbonize Transportation. Appendix B: Fuels. Y Surendrath, Y Roman, W Green, F Allroggen, C Falter, R Field, ... https://t2dt.mit.edu/sites/default/files/documents/CGCT2DTappBv3.pdf, 2021 | | 2021 |
