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Sander Vandenhaute
Sander Vandenhaute
Ghent University
Verified email at ugent.be - Homepage
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Year
Machine learning potentials for metal-organic frameworks using an incremental learning approach
S Vandenhaute, M Cools-Ceuppens, S DeKeyser, T Verstraelen, ...
npj Computational Materials 9 (1), 1-8, 2023
792023
Towards modeling spatiotemporal processes in metal–organic frameworks
V Van Speybroeck, S Vandenhaute, AEJ Hoffman, SMJ Rogge
Trends in Chemistry 3 (8), 605-619, 2021
362021
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
222022
Large-scale molecular dynamics simulations reveal new insights into the phase transition mechanisms in MIL-53 (Al)
S Vandenhaute, SMJ Rogge, V Van Speybroeck
Frontiers in Chemistry 9, 718920, 2021
222021
Unraveling the nature of adsorbed isobutene in H-SSZ-13 with operando simulations at the top of Jacob’s ladder
M Bocus, S Vandenhaute, V Van Speybroeck
22024
Water motifs in zirconium metal-organic frameworks induced by nanoconfinement and hydrophilic adsorption sites
A Lamaire, J Wieme, S Vandenhaute, R Goeminne, SMJ Rogge, ...
Nature Communications 15 (1), 9997, 2024
12024
Free Energy Calculations using Smooth Basin Classification
S Vandenhaute, T Braeckevelt, P Dobbelaere, M Bocus, ...
arXiv preprint arXiv:2404.03777, 2024
12024
The Operando Nature of Isobutene Adsorbed in Zeolite H− SSZ− 13 Unraveled by Machine Learning Potentials Beyond DFT Accuracy
M Bocus, S Vandenhaute, V Van Speybroeck
Angewandte Chemie International Edition 64 (1), e202413637, 2025
2025
Machine learning potentials to bridge the gap between theory and experiments in zeolite catalysis
M Bocus, S Vandenhaute, V Van Speybroeck
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