| Surface Complexions Identified through Machine Learning and Surface Investigations J Timmermann, F Kraushofer, N Resch, P Li, Y Wang, Z Mao, M Riva, ... Physical review letters 125 (20), 206101, 2020 | 41 | 2020 |
| Benchmarks and dielectric constants for reparametrized OPLS and polarizable force field models of chlorinated hydrocarbons Z Liu, J Timmermann, K Reuter, C Scheurer The Journal of Physical Chemistry B 122 (2), 770-779, 2018 | 25 | 2018 |
| Data-efficient iterative training of Gaussian approximation potentials: Application to surface structure determination of rutile IrO2 and RuO2 J Timmermann, Y Lee, CG Staacke, JT Margraf, C Scheurer, K Reuter The Journal of Chemical Physics 155 (24), 2021 | 22 | 2021 |
| Staged Training of Machine-Learning Potentials from Small to Large Surface Unit Cells: Efficient Global Structure Determination of the RuO2(100)-c(2 × 2 … Y Lee, J Timmermann, C Panosetti, C Scheurer, K Reuter The Journal of Physical Chemistry C 127 (35), 17599-17608, 2023 | 3 | 2023 |
| Iridiumoxid as catalyst in water electrolysis: identification of novel surface structures via machine learning J Timmermann Technische Universität München, 2022 | 1 | 2022 |
| Ab initio modelling of iridium dioxide nanoparticles as catalysts for proton exchange membrane water electrolysis cells J Timmermann, D Opalka, A Anic High Performance Computing, 60, 0 | | |
