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Project

Towards accurate structure-property relationships in metal-organic frameworks based on advanced multiscale simulations of spatially disordered finite crystals

Information

Project Team

Organisations

Outputs and Outcomes

Publications

The operando nature of isobutene adsorbed in Zeolite H‐SSZ‐13 unraveled by machine learning potentials beyond DFT accuracy

Massimo BocusSander VandenhauteVeronique Van Speybroeck

A1 Journal Article in ANGEWANDTE CHEMIE-INTERNATIONAL EDITION

2024

Machine learning potentials for metal-organic frameworks using an incremental learning approach

Sander VandenhauteMaarten Cools-CeuppensSimon DeKeyserToon VerstraelenVeronique Van Speybroeck

A1 Journal Article in NPJ COMPUTATIONAL MATERIALS

2023

Accurately determining the phase transition temperature of CsPbI3 via random-phase approximation calculations and phase-transferable machine learning potentials

Tom BraeckeveltRuben GoeminneSander VandenhauteSander BorgmansToon VerstraelenJulian A. SteeleMaarten B. J. RoeffaersJohan HofkensSven RoggeVeronique Van Speybroeck

A1 Journal Article in CHEMISTRY OF MATERIALS

2022