4 papers · 1 filter
SALTED: a symmetry-adapted machine-learning program for predicting electron-densities in molecules and materials
Zekun Lou, Alan M. Lewis, Théophane Bernhard +5
SALTED provides an open-source Python package for machine learning the quantum-mechanical electron density, , in molecular and condensed-phase systems based on input…
Long-Range Machine Learning of Electron Density for Twisted Bilayer Moiré Materials
Zekun Lou, Alan M. Lewis, Mariana Rossi
Moiré superlattices in two-dimensional (2D) materials exhibit rich quantum phenomena, but ab initio modelling of these systems remains computationally prohibitive. Existing machine…
Roadmap on Advancements of the FHI-aims Software Package
Joseph W. Abbott, Carlos Mera Acosta, Alaa Akkoush +203
Electronic-structure theory is the foundation of the description of materials including multiscale modeling of their properties and functions. Obviously, without sufficient accurac…
Learning the Electrostatic Response of the Electron Density through a Symmetry-Adapted Vector Field Model
Mariana Rossi, Kevin Rossi, Alan M. Lewis +2
A current challenge in atomistic machine learning is that of efficiently predicting the response of the electron density under electric fields. We address this challenge with symme…