146 citations · 199 across the 6 of their papers we have counts for
3 papers · 1 filter
Synthetic pre-training of graph-network models for predicting solid-state NMR parameters
Chiheb Ben Mahmoud, Carlos Bornes, Christopher J. Heard +3
Nuclear magnetic resonance (NMR) is a powerful probe of atomic structure, but accurate quantum-mechanical predictions of tensorial NMR parameters are computationally demanding. Thi…
Predicting hot-electron free energies from ground-state data
Chiheb Ben Mahmoud, Federico Grasselli, Michele Ceriotti
Machine-learning potentials are usually trained on the ground-state, Born-Oppenheimer energy surface, which depends exclusively on the atomic positions and not on the simulation te…
Learning the electronic density of states in condensed matter
Chiheb Ben Mahmoud, Andrea Anelli, Gábor Csányi +1
The electronic density of states (DOS) quantifies the distribution of the energy levels that can be occupied by electrons in a quasiparticle picture, and is central to modern elect…