Volker L. Deringer

activity

20162024

most citedMachine-learning based interatomic potential for amorphous carbon

684 citations · 2.5k across the 32 of their papers we have counts for

collaborators

Showing 2021Show all

3 papers · 1 filter

cond-mat.mtrl-sci2021★ 24 cited

Indirect Learning of Interatomic Potentials for Accelerated Materials Simulations

Joe D. Morrow, Volker L. Deringer

Machine learning (ML) based interatomic potentials are emerging tools for materials simulations but require a trade-off between accuracy and speed. Here we show how one can use one…

cond-mat.mtrl-sci2021

Cluster Fragments in Amorphous Phosphorus and their Evolution under Pressure

Yuxing Zhou, William Kirkpatrick, Volker L. Deringer

Amorphous phosphorus (a-P) has long attracted interest because of its complex atomic structure, and more recently as an anode material for batteries. However, accurately describing…

cond-mat.mtrl-sci2021★ 20 cited

Bonding nature and optical contrast of $T i T e_{2}$ / $S b_{2} T e_{3}$ phase-change heterostructure

Xudong Wang, Yue Wu, Yuxing Zhou +2

Chalcogenide phase-change materials (PCMs) are regarded as the leading candidate for storage-class non-volatile memory and neuro-inspired computing. Recently, using the $T i T e_{2}$ /$S…

Indirect Learning of Interatomic Potentials for Accelerated Materials Simulations

Cluster Fragments in Amorphous Phosphorus and their Evolution under Pressure

Bonding nature and optical contrast of TiTe2​/Sb2​Te3​ phase-change heterostructure

Bonding nature and optical contrast of $T i T e_{2}$ / $S b_{2} T e_{3}$ phase-change heterostructure