Recent Publications

A full publication list can be found on Google Scholar. Some selected recent publications are listed below:

Kernel Charge Equilibration: Efficient and Accurate Prediction of Molecular Dipole Moments with a Machine-Learning Enhanced Electron Density Model
C Staacke, S Wengert, C Kunkel, G Csányi, K Reuter; JT Margraf, MLST 2022, 3, 015032.

Heterogeneous Catalysis in Grammar School
JT Margraf, Z Ulissi, Y Jung, K Reuter J. Phys. Chem. C 2022, 126, 2931−2936.

Regularized second-order correlation methods for extended systems
E Keller, T Tsatsoulis, K Reuter, JT Margraf J Chem. Phys. 2022, 156, 024106.

On the role of long-range electrostatics in machine-learned interatomic potentials for complex battery materials
CG Staacke, HH Heenen, C Scheurer, G Csányi, K Reuter, JT Margraf ACS Appl. Energy Mater. 2021, 4, 11, 12562–12569.

Data-Efficient Machine Learning for Molecular Crystal Structure Prediction
S Wengert, G Csányi, K Reuter, JT Margraf Chem. Sci., 2021, 12, 4536-4546.

Pure non-local machine-learned density functional theory for electron correlation
JT Margraf, K Reuter Nat. Commun., 2021, 12, 344.

Machine learning in chemical reaction space
S Stocker, G Csányi, K Reuter, JT Margraf Nat. Commun., 2020, 11, 5505.

Size-Extensive Molecular Machine Learning with Global Representations
H Jung, S Stocker, C Kunkel, H Oberhofer, B Han, K Reuter, JT Margraf ChemSystemsChem, 2020, 2,  e190005.

Systematic Enumeration of Elementary Reaction Steps in Surface Catalysis
JT Margraf, K Reuter ACS Omega, 2019, 4, 3370–3379.

Making the Coupled Cluster Correlation Energy Machine-Learnable
JT Margraf, K Reuter J. Phys. Chem. A, 2018, 122, 6343.