249 citations · 260 across the 10 of their papers we have counts for
7 papers · 1 filter
A fast summation method for the DFT-D3 dispersion correction
Victoria Valeeva, Cheuk Hin Ho, Mario Geiger +4
The DFT-D3 dispersion correction is routinely added to machine learning force fields (MLFFs) trained on dispersion-deficient functionals such as PBE. Its environment-dependent pair…
An Atomic Cluster Expansion Potential for Twisted Multilayer Graphene
Yangshuai Wang, Drake Clark, Sambit Das +5
Twisted multilayer graphene, characterized by its moiré patterns arising from inter-layer rotational misalignment, serves as a rich platform for exploring quantum phenomena. Machin…
Many-Body Coarse-Grained Molecular Dynamics with the Atomic Cluster Expansion
Yangshuai Wang, Gabor Csanyi, Christoph Ortner
Molecular dynamics (MD) simulations provide detailed insight into atomic-scale mechanisms but are inherently restricted to small spatio-temporal scales. Coarse-grained molecular dy…
Self-consistent Coulomb interactions for machine learning interatomic potentials
Jack Thomas, William J. Baldwin, Gábor Csányi +1
A ubiquitous approach to obtain transferable machine learning-based models of potential energy surfaces for atomistic systems is to decompose the total energy into a sum of local a…
Surrogate models for vibrational entropy based on a spatial decomposition
Tina Torabi, Yangshuai Wang, Christoph Ortner
The temperature-dependent behavior of defect densities within a crystalline structure is intricately linked to the phenomenon of vibrational entropy. Traditional methods for evalua…
A Theoretical Case Study of the Generalisation of Machine-learned Potentials
Yangshuai Wang, Shashwat Patel, Christoph Ortner
Machine-learned interatomic potentials (MLIPs) are typically trained on datasets that encompass a restricted subset of possible input structures, which presents a potential challen…
ACEpotentials.jl: A Julia Implementation of the Atomic Cluster Expansion
William C. Witt, Cas van der Oord, Elena Gelžinytė +10
We introduce ACEpotentials.jl, a Julia-language software package that constructs interatomic potentials from quantum mechanical reference data using the Atomic Cluster Expansion (D…