T. Verstraelen

The eMLP: a novel machine learning potential to model electronic properties with explicit-electrons

M. Cools-Ceuppens, J. Dambre, T. Verstraelen

ISBN/ISSN:

Talk

Conference / event / venue

AutoCheMo International Reactive Force Field Workshop

Ghent, Belgium

Wednesday, 8 December, 2021 to Thursday, 9 December, 2021

Nanoscale simulations of lubricants and lubricant additives

Simulation of lubricant properties in gear and bearing contacts

Training a reactive (ReaxFF) force field for the simulation of zeolite nucleation in a hydrated silicate ionic liquid

The Fe-Si phase diagram: from electrical steel to the planet Mercury

Ranking molecular crystals with a many-body expansion

Machine learning of the ground state density of molecules for force field development

Inverse design of energy materials using atomistic deep learning

Improved force-field approximations of symmetry-adapted perturbation theory

Developing a Hybrid Monte Carlo Algorithm for Peptides through Kernel Machine Learning

Pages