7 citations · 9 across the 17 of their papers we have counts for
5 papers · 1 filter
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…