(* = corresponding author, † = equal contributions)
T. Morawietz* and N. Artrith*,
“Machine Learning-Accelerated Quantum Mechanics-Based Atomistic Simulations for Industrial Applications”, Submitted (2020).
A.M. Cooper, J. Kästner, A. Urban, N. Artrith*,
“Efficient training of ANN potentials by including atomic forces via Taylor expansion and application to water and a transition-metal oxide”, npj Comput Mater 6 (2020) 54. Open Access .
The database can be obtained from the Materials Cloud repository .
N. Artrith*, Zhexi Lin, Jingguang G. Chen,
“Predicting the Activity and Selectivity of Bimetallic Metal Catalysts for Ethanol Reforming using Machine Learning”, ACS Catal. 10 (2020) 9438–9444 (Letter) . (preprint)
“The Impact of Surface Structure Transformations on the Performance of Li-Excess Cation-Disordered Rocksalt Cathodes”, Cell Reports Physical Science XX (2020) Accepted. Open Access .
“Effect of Fluorination on Lithium Transport and Short‐Range Order in Disordered‐Rocksalt‐Type Lithium‐Ion Battery Cathodes”, Adv. Energy Mater. 10 (2020) 1903240 .
2019 and before