7 citations · 9 across the 17 of their papers we have counts for
17 papers
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…
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…
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…
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…
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…
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…
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…
Medium-range structural order in amorphous arsenic
Yuanbin Liu, Yuxing Zhou, Richard Ademuwagun +4
Medium-range order (MRO) is a key structural feature of amorphous materials, but its origin and nature remain elusive. Here, we reveal the MRO in amorphous arsenic (a-As) using adv…
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…
Assessing zero-shot generalisation behaviour in graph-neural-network interatomic potentials
Chiheb Ben Mahmoud, Zakariya El-Machachi, Krystian A. Gierczak +2
With the rapidly growing availability of machine-learned interatomic potential (MLIP) models for chemistry, much current research focuses on the development of generally applicable…
Full-cycle device-scale simulations of memory materials with a tailored atomic-cluster-expansion potential
Yuxing Zhou, Daniel F. Thomas du Toit, Stephen R. Elliott +2
Computer simulations have long been key to understanding and designing phase-change materials (PCMs) for memory technologies. Machine learning is now increasingly being used to acc…
An automated framework for exploring and learning potential-energy surfaces
Yuanbin Liu, Joe D. Morrow, Christina Ertural +6
Machine learning has become ubiquitous in materials modelling and now routinely enables large-scale atomistic simulations with quantum-mechanical accuracy. However, developing mach…
The pathway to chirality in elemental tellurium
Yuxing Zhou, Stephen R. Elliott, Daniel F. Thomas du Toit +2
Chiral crystals, like chiral molecules, cannot be superimposed onto their mirror images -- a fundamental property that has been linked to interesting physical behavior and exploite…
Hyperparameter Optimization for Atomic Cluster Expansion Potentials
Daniel F. Thomas du Toit, Yuxing Zhou, Volker L. Deringer
Machine-learning-based interatomic potentials enable accurate materials simulations on extended time- and lengthscales. ML potentials based on the Atomic Cluster Expansion (ACE) fr…
Accelerated First-Principles Exploration of Structure and Reactivity in Graphene Oxide
Zakariya El-Machachi, Damyan Frantzov, A. Nijamudheen +3
Graphene oxide (GO) materials are widely studied, and yet their atomic-scale structures remain to be fully understood. Here we show that the chemical and configurational space of G…
Homopolar Chemical Bonds Induce In-Plane Anisotropy in Layered Semiconductors
Jieling Tan, Jiang-Jing Wang, Hang-Ming Zhang +6
Main-group layered binary semiconductors, in particular, the III-VI alloys in the binary Ga-Te system are attracting increasing interest for a range of practical applications. The…
High-dimensional order parameters and neural network classifiers applied to amorphous ices
Zoé Faure Beaulieu, Volker L. Deringer, Fausto Martelli
Amorphous ice phases are key constituents of water's complex structural landscape. This study investigates the polyamorphic nature of water, focusing on the complexities within low…