activity
20242026
most citedGraph-neural-network predictions of solid-state NMR parameters from spherical tensor decomposition

8 citations · 19 across the 6 of their papers we have counts for

collaborators

7 papers

cond-mat.mtrl-sci2026

A Defect-Free Model of Amorphous Silicon with Pristine Electronic Structure

Louise A. M. Rosset, Chinonso Ugwumadu, Stephen R. Elliott +2

Amorphous silicon (a-Si) is understood to be the canonical continuous random network material, ideally defined by fully fourfold coordination. Here, we show that a defect-free ('id…

cond-mat.mtrl-sci2025

Atomic cluster expansion potential for the Si-H system

Louise A. M. Rosset, Volker L. Deringer

The silicon-hydrogen system is of key interest for solar-cell devices, including both crystalline and amorphous modifications. Elemental amorphous Si is now well understood, but th…

cond-mat.mtrl-sci20251 cited

Autonomous interpretation of atomistic scattering data

Andy S. Anker, John L. A. Gardner, Louise A. M. Rosset +2

Materials with bespoke properties have long been identified by computational searches, and their experimental realisation is now coming within reach through autonomous laboratories…

physics.comp-ph20257 cited

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…

cond-mat.mtrl-sci20253 cited

The structure and topology of an amorphous metal-organic framework

Thomas C. Nicholas, Daniel F. Thomas du Toit, Louise A. M. Rosset +3

Amorphous metal-organic frameworks are an important emerging materials class that combine the attractive physical properties of the amorphous state with the versatility of metal-or…

cond-mat.mtrl-sci2024

Graph-neural-network predictions of solid-state NMR parameters from spherical tensor decomposition

Chiheb Ben Mahmoud, Louise A. M. Rosset, Jonathan R. Yates +1

Nuclear magnetic resonance (NMR) is a powerful spectroscopic technique that is sensitive to the local atomic structure of matter. Computational predictions of NMR parameters can he…