activity
20042026
most citedA Performance and Cost Assessment of Machine Learning Interatomic Potentials

976 citations · 5.6k across the 39 of their papers we have counts for

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Showing 2020Show all

9 papers · 1 filter

cond-mat.mtrl-sci2020★ 533 cited

A Fourth-Generation High-Dimensional Neural Network Potential with Accurate Electrostatics Including Non-local Charge Transfer

Tsz Wai Ko, Jonas A. Finkler, Stefan Goedecker +1

Machine learning potentials have become an important tool for atomistic simulations in many fields, from chemistry via molecular biology to materials science. Most of the establish…

physics.comp-ph2020

A Bin and Hash Method for Analyzing Reference Data and Descriptors in Machine Learning Potentials

Martín Leandro Paleico, Jörg Behler

In recent years the development of machine learning (ML) potentials (MLP) has become a very active field of research. Numerous approaches have been proposed, which allow to perform…

physics.comp-ph2020★ 24 cited

An experimentally validated neural-network potential energy surface for H atoms on free-standing graphene in full dimensionality

Sebastian Wille, Hongyan Jiang, Oliver Bünermann +3

We present a first principles-quality potential energy surface (PES) describing the inter-atomic forces for hydrogen atoms interacting with free-standing graphene. The PES is a hig…

physics.chem-ph2020

Global Optimization of Copper Clusters at the ZnO(10-10) Surface Using a DFT-based Neural Network Potential and Genetic Algorithms

Martín Leandro Paleico, Jörg Behler

The determination of the most stable structures of metal clusters supported at solid surfaces by computer simulations represents a formidable challenge due to the complexity of the…

cond-mat.mtrl-sci2020★ 4 cited

A criticial view on e occupancy as a descriptor for oxygen evolution catalytic activity in LiMnO nanoparticles

Florian Schönewald, Marco Eckhoff, Max Baumung +4

We investigate the effect of the surface electronic structure and composition of LiMnO nanoparticles on the electrocatalytic oxygen evolution reaction (OER). Scanning trans…

cond-mat.mtrl-sci2020★ 41 cited

Predicting Oxidation and Spin States by High-Dimensional Neural Networks: Applications to Lithium Manganese Oxide Spinels

Marco Eckhoff, Knut Nikolas Lausch, Peter E. Blöchl +1

Lithium ion batteries often contain transition metal oxides like LiMnO (). Depending on the Li content different ratios of Mn to Mn$^\text{…