| Modeling Gas Adsorption in Flexible Metal–Organic Frameworks via Hybrid Monte Carlo/Molecular Dynamics Schemes SMJ Rogge, R Goeminne, R Demuynck, JJ Gutiérrez‐Sevillano, ... Advanced Theory and Simulations 2 (4), 1800177, 2019 | 47 | 2019 |
| Charting the complete thermodynamic landscape of gas adsorption for a responsive metal–organic framework R Goeminne, S Krause, S Kaskel, T Verstraelen, JD Evans Journal of the American Chemical Society 143 (11), 4143-4147, 2021 | 24 | 2021 |
| Nuclear quantum effects on zeolite proton hopping kinetics explored with machine learning potentials and path integral molecular dynamics M Bocus, R Goeminne, A Lamaire, M Cools-Ceuppens, T Verstraelen, ... Nature Communications 14 (1), 1008, 2023 | 18 | 2023 |
| Accurately Determining the Phase Transition Temperature of CsPbI3 via Random-Phase Approximation Calculations and Phase-Transferable Machine Learning … T Braeckevelt, R Goeminne, S Vandenhaute, S Borgmans, T Verstraelen, ... Chemistry of Materials 34 (19), 8561-8576, 2022 | 11 | 2022 |
| DFT-Quality adsorption simulations in metal–organic frameworks enabled by machine learning Potentials R Goeminne, L Vanduyfhuys, V Van Speybroeck, T Verstraelen Journal of Chemical Theory and Computation 19 (18), 6313-6325, 2023 | 8 | 2023 |
| Development of Accurate and Reliable Methods for In Silico Modeling of Adsorption in Nanoporous Materials R Goeminne Ghent University, 2023 | | 2023 |
| On the impact of nuclear quantum effects on zeolite proton hopping kinetics through machine learning potentials and path integral molecular dynamics simulations M Bocus, R Goeminne, A Lamaire, M Cools-Ceuppens, T Verstraelen, ... | | 2022 |
| Accurate transferable polarization model derived from the monomer electron density R Goeminne, T Verstraelen arXiv preprint arXiv:2006.05224, 2020 | | 2020 |
