S. Vandenhaute
Development of on-the-fly machine learning potentials to investigate phase transformation mechanisms in perovskites
Defect migration in metal halide perovskites using machine learning potentials
Accurate description of phase transitions in flexible materials using transferable machine learning potentials
Exploring the black-to-yellow phase transformation mechanism of metal halide perovskites via machine learning potentials
It's all about time: Understanding the impact of coarse graining on accelerated diffusion in nanoporous materials
Investigating adsorption-induced flexibility in metal-organic frameworks using machine learning potentials
Reliably modeling the mechanical stability of MOFs at increasing length scales to unleash their full industrial potential
ISBN/ISSN:
Talk
Conference / event / venue
MMC
Oxford, United Kingdom
Tuesday, 4 June, 2019
Reliably modeling the mechanical stability of MOFs at increasing length scales to unleash their full industrial potential
ISBN/ISSN:
Talk
Conference / event / venue
MOF2018
Auckland, New Zealand
Sunday, 9 December, 2018 to Thursday, 13 December, 2018
Towards modeling long-range disorder in MOFs: Development of a computational toolbox to extend the length scale in molecular simulations
ISBN/ISSN:
Invited talk
Conference / event / venue
CECAM workshop: Multi-scale modelling of flexible and disordered porous materials
Paris, France
Monday, 11 June, 2018 to Wednesday, 13 June, 2018