activity
20232026
most citedDistillation of atomistic foundation models across architectures and chemical domains

7 citations · 9 across the 17 of their papers we have counts for

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7 papers · 1 filter

cond-mat.mtrl-sci2026

Amorphous materials as a frontier challenge for universal interatomic potentials

Natascia L. Fragapane, Volker L. Deringer

Pre-trained or 'foundational' machine-learned interatomic potentials (MLIPs) are now widely used in materials modelling. However, early pre-trained models and benchmarks have large…

cond-mat.mtrl-sci2026

Atomistic Mechanisms of Hard Carbon Formation from Polyvinylidene Chloride

Litong Wu, Zitong Wu, Zakariya El-Machachi +1

Hard carbons are a class of disordered materials with widespread application in energy storage. Despite decades of research, their atomistic formation mechanisms have remained elus…

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-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.chem-ph2026

Regularity Priors for the Linear Atomic Cluster Expansion

James P. Darby, Joe D. Morrow, Albert P. Bartók +3

Machine-learned interatomic potentials enable large systems to be simulated for long time scales at near ab-initio accuracy. This accuracy is achieved by fitting extremely flexible…

cond-mat.soft2026

Topological origin of peak splitting in the structure factor of liquid water

Zoé Faure Beaulieu, Volker L. Deringer, Fausto Martelli

The splitting of the principal peak in the structure factor of liquid water is commonly interpreted as evidence of a competition between two distinct local environments. Here, we s…