522 citations · 1.7k across the 18 of their papers we have counts for
3 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 electrostatics in atomistic machine learning: a physical perspective
Federico Grasselli, Kevin Rossi, Stefano de Gironcoli +1
The inclusion of long-range electrostatics in atomistic machine learning (ML) is receiving increasing attention for achieving quantum-mechanical accuracy in predicting a wide range…
Exact Electrostatic Theory of Fermi-Energy Response at Metallic Interfaces
Théophane Bernhard, Andrea Grisafi
The response of the Fermi energy to external perturbations governs key physical observables at metallic interfaces. Although this response admits a local formulation in terms of th…