8 citations · 8 across the 1 of their papers we have counts for
4 papers
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…
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 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…
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…