| Machine learning force fields: construction, validation, and outlook V Botu, R Batra, J Chapman, R Ramprasad The Journal of Physical Chemistry C 121 (1), 511-522, 2017 | 489 | 2017 |
| Toward complete statistics of massive binary stars: penultimate results from the Cygnus OB2 radial velocity survey HA Kobulnicky, DC Kiminki, MJ Lundquist, J Burke, J Chapman, E Keller, ... The Astrophysical Journal Supplement Series 213 (2), 34, 2014 | 291 | 2014 |
| A universal strategy for the creation of machine learning-based atomistic force fields TD Huan, R Batra, J Chapman, S Krishnan, L Chen, R Ramprasad NPJ Computational Materials 3 (1), 37, 2017 | 222 | 2017 |
| General atomic neighborhood fingerprint for machine learning-based methods R Batra, HD Tran, C Kim, J Chapman, L Chen, A Chandrasekaran, ... The Journal of Physical Chemistry C 123 (25), 15859-15866, 2019 | 44 | 2019 |
| A study of adatom ripening on an Al (1 1 1) surface with machine learning force fields V Botu, J Chapman, R Ramprasad Computational Materials Science 129, 332-335, 2017 | 37 | 2017 |
| Machine learning models for the prediction of energy, forces, and stresses for Platinum J Chapman, R Batra, R Ramprasad Computational Materials Science 174, 109483, 2020 | 22 | 2020 |
| Efficient and interpretable graph network representation for angle-dependent properties applied to optical spectroscopy T Hsu, TA Pham, N Keilbart, S Weitzner, J Chapman, P Xiao, SR Qiu, ... npj Computational Materials 8 (1), 151, 2022 | 21* | 2022 |
| Iterative-learning strategy for the development of application-specific atomistic force fields TD Huan, R Batra, J Chapman, C Kim, A Chandrasekaran, R Ramprasad The Journal of Physical Chemistry C 123 (34), 20715-20722, 2019 | 21 | 2019 |
| Hydriding of titanium: recent trends and perspectives in advanced characterization and multiscale modeling Y Zhu, TW Heo, JN Rodriguez, PK Weber, R Shi, BJ Baer, FF Morgado, ... Current Opinion in Solid State and Materials Science 26 (6), 101020, 2022 | 18 | 2022 |
| Efficient and universal characterization of atomic structures through a topological graph order parameter J Chapman, N Goldman, BC Wood npj Computational Materials 8 (1), 37, 2022 | 12 | 2022 |
| A comprehensive computational study of adatom diffusion on the aluminum (1 0 0) surface J Chapman, R Batra, BP Uberuaga, G Pilania, R Ramprasad Computational Materials Science 158, 353-358, 2019 | 10 | 2019 |
| Pairwise disagreements of Kekulé, Clar, and Fries numbers for benzenoids: A mathematical and computational investigation EJ Hartung, A Williams | 10 | 2018 |
| Nanoscale modeling of surface phenomena in aluminum using machine learning force fields J Chapman, R Ramprasad The Journal of Physical Chemistry C 124 (40), 22127-22136, 2020 | 8 | 2020 |
| Multiscale modeling of defect phenomena in platinum using machine learning of force fields J Chapman, R Ramprasad JOM 72, 4346-4358, 2020 | 6 | 2020 |
| Amorphization of T‐Nb2O5 Accelerates Intercalation Pseudocapacitance via Faster Lithium Diffusivity Revealed using Tunable Isomorphic Architectures W van den Bergh, S Wechsler, HN Lokupitiya, L Jarocha, K Kim, ... Batteries & Supercaps, 2022 | 5* | 2022 |
| Predicting the dynamic behavior of the mechanical properties of platinum with machine learning J Chapman, R Ramprasad The Journal of Chemical Physics 152 (22), 2020 | 5 | 2020 |
| Hydrogen in disordered titania: connecting local chemistry, structure, and stoichiometry through accelerated exploration J Chapman, KE Kweon, Y Zhu, K Bushick, LBB Aji, CA Colla, H Mason, ... Journal of Materials Chemistry A 11 (16), 8670-8683, 2023 | 4 | 2023 |
| Quantifying disorder one atom at a time using an interpretable graph neural network paradigm J Chapman, T Hsu, X Chen, TW Heo, BC Wood Nature Communications 14 (1), 4030, 2023 | 3 | 2023 |
| Score-based denoising for atomic structure identification T Hsu, B Sadigh, N Bertin, CW Park, J Chapman, V Bulatov, F Zhou arXiv preprint arXiv:2212.02421, 2022 | 2 | 2022 |
| Spectroscopy-Guided Discovery of Three-Dimensional Structures of Disordered Materials with Diffusion Models H Kwon, T Hsu, W Sun, W Jeong, F Aydin, J Chapman, X Chen, ... arXiv preprint arXiv:2312.05472, 2023 | 1 | 2023 |
Rohit BatraAssistant Professor IIT MadrasVerified email at iitm.ac.in
