activity
20202026
most citedHigh-Dimensional Neural Network Potentials for Magnetic Systems Using Spin-Dependent Atom-Centered Symmetry Functions

93 citations · 363 across the 16 of their papers we have counts for

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Showing 2020Show all

4 papers · 1 filter

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{…

cond-mat.mtrl-sci2020★ 44 cited

Closing the gap between theory and experiment for lithium manganese oxide spinels using a high-dimensional neural network potential

Marco Eckhoff, Florian Schönewald, Marcel Risch +3

Many positive electrode materials in lithium ion batteries include transition metals which are difficult to describe by electronic structure methods like density functional theory…

cond-mat.mtrl-sci2020★ 29 cited

A Hybrid Density Functional Theory Benchmark Study on Lithium Manganese Oxides

Marco Eckhoff, Peter E. Blöchl, Jörg Behler

The lithium manganese oxide spinel LiMnO, with , is an important example for cathode materials in lithium ion batteries. However, an accurate description…