Generative models as an emerging paradigm in the chemical sciences DM Anstine, O Isayev
Journal of the American Chemical Society 145 (16), 8736-8750, 2023
81 2023 Machine learning interatomic potentials and long-range physics DM Anstine, O Isayev
The Journal of Physical Chemistry A 127 (11), 2417-2431, 2023
43 2023 Effects of exchange-correlation potentials on the density-functional description of versus photoionization J Choi, EH Chang, DM Anstine, MEA Madjet, HS Chakraborty
Physical Review A 95 (2), 023404, 2017
35 2017 A molecular dynamics study of water-soluble polymers: analysis of force fields from atomistic simulations SJ Rukmani, G Kupgan, DM Anstine, CM Colina
Molecular Simulation 45 (4-5), 310-321, 2019
27 2019 Two-dimensional energy histograms as features for machine learning to predict adsorption in diverse nanoporous materials K Shi, Z Li, DM Anstine, D Tang, CM Colina, DS Sholl, JI Siepmann, ...
Journal of Chemical Theory and Computation 19 (14), 4568-4583, 2023
23 2023 Incorporating Flexibility Effects into Metal–Organic Framework Adsorption Simulations Using Different Models Z Yu, DM Anstine, SE Boulfelfel, C Gu, CM Colina, DS Sholl
ACS Applied Materials & Interfaces 13 (51), 61305-61315, 2021
20 2021 Adsorption space for microporous polymers with diverse adsorbate species DM Anstine, D Tang, DS Sholl, CM Colina
npj Computational Materials 7 (1), 53, 2021
17 2021 Sorption‐induced polymer rearrangement: approaches from molecular modeling DM Anstine, CM Colina
Polymer International 70 (7), 984-989, 2021
14 2021 Screening PIM-1 performance as a membrane for binary mixture separation of gaseous organic compounds DM Anstine, AG Demidov, NF Mendez, WJ Morgan, CM Colina
Journal of membrane science 599, 117798, 2020
14 2020 Attosecond structures from the molecular cavity in fullerene photoemission time delay M Magrakvelidze, DM Anstine, G Dixit, MEA Madjet, HS Chakraborty
Physical Review A 91 (5), 053407, 2015
14 2015 Effects of an atomistic modeling approach on predicted mechanical properties of glassy polymers via molecular dynamics DM Anstine, A Strachan, CM Colina
Modelling and Simulation in Materials Science and Engineering 28 (2), 025006, 2020
10 2020 AIMNet2: a neural network potential to meet your neutral, charged, organic, and elemental-organic needs D Anstine, R Zubatyuk, O Isayev
9 2024 PEGDA hydrogel structure from semi-dilute concentrations: Insights from experiments and molecular simulations J Mercado-Montijo, DM Anstine, SJ Rukmani, CM Colina, JS Andrew
Soft Matter 18 (18), 3565-3574, 2022
9 2022 New Pd (ii) hemichelates devoid of incipient bridging CO⋯ Pd interactions C Werlé, DM Anstine, L Karmazin, C Bailly, L Ricard, JP Djukic
Dalton Transactions 45 (2), 607-617, 2016
9 2016 An insight into structural and mechanical properties of ideal‐networked poly (ethylene glycol)–peptide hydrogels from molecular dynamics simulations SJ Rukmani, DM Anstine, A Munasinghe, CM Colina
Macromolecular Chemistry and Physics 221 (3), 1900326, 2020
8 2020 In silico design of microporous polymers for chemical separations and storage DM Anstine, DS Sholl, JI Siepmann, RQ Snurr, A Aspuru-Guzik, ...
Current Opinion in Chemical Engineering 36, 100795, 2022
7 2022 Sulfonyl PIM‐1: A diverse separation membrane with dilation resistance DM Anstine, NF Mendez, CM Colina
AIChE Journal 67 (3), e17006, 2021
5 2021 Temperature effects in flexible adsorption processes for amorphous microporous polymers WJ Morgan, DM Anstine, CM Colina
The Journal of Physical Chemistry B 126 (33), 6354-6365, 2022
3 2022 Defect engineering of porous aromatic frameworks via end capping improves dioxane removal from water A Yang, BC Bukowski, DM Anstine, CM Colina, RQ Snurr, WR Dichtel
Matter 6 (7), 2263-2273, 2023
2 2023 D2 machine learning for reaction property prediction Q Zhao, DM Anstine, O Isayev, BM Savoie
1 2023