7 citations · 7 across the 3 of their papers we have counts for
3 papers
Data-driven atomistic modelling of hybrid halide perovskite passivation
Laura-Bianca Paşca, Henry J. Snaith, Volker L. Deringer
Molecular passivation of surface defects is key to improving the optoelectronic performance of hybrid halide perovskite materials, but the underlying atomistic mechanisms are incom…
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…
Machine-learning-driven modelling of amorphous and polycrystalline BaZrS
Laura-Bianca Paşca, Yuanbin Liu, Andy S. Anker +2
The chalcogenide perovskite material BaZrS is of growing interest for emerging thin-film photovoltaics. Here we show how machine-learning-driven modelling can be used to desc…