3 papers
cond-mat.mtrl-sci2026
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…
physics.chem-ph2026
An Accurate Tensorial Model for Prediction of Full Zeolite NMR Spectra
Carlos Bornes, Chiheb Ben Mahmoud, Volker L. Deringer +2
Solid state nuclear magnetic resonance (ss-NMR) is one of the most sensitive and popular techniques for structure elucidation in geometrically complex crystalline materials, such a…
physics.comp-ph2025
Distillation of atomistic foundation models across architectures and chemical domains
John L. A. Gardner, Daniel F. Thomas du Toit, Chiheb Ben Mahmoud +8
Machine-learned interatomic potentials have transformed computational research in the physical sciences. Recent atomistic `foundation' models have changed the field yet again: trai…