| A fourth-generation high-dimensional neural network potential with accurate electrostatics including non-local charge transfer TW Ko, JA Finkler, S Goedecker, J Behler Nature communications 12 (1), 398, 2021 | 314 | 2021 |
| General-purpose machine learning potentials capturing nonlocal charge transfer TW Ko, JA Finkler, S Goedecker, J Behler Accounts of Chemical Research 54 (4), 808-817, 2021 | 86 | 2021 |
| Fingerprint-based detection of non-local effects in the electronic structure of a simple single component covalent system B Parsaeifard, DS De, JA Finkler, S Goedecker Condensed Matter 6 (1), 9, 2021 | 15* | 2021 |
| Accurate fourth-generation machine learning potentials by electrostatic embedding TW Ko, JA Finkler, S Goedecker, J Behler Journal of Chemical Theory and Computation 19 (12), 3567-3579, 2023 | 13 | 2023 |
| CENT2: Improved charge equilibration via neural network technique ER Khajehpasha, JA Finkler, TD Kühne, SA Ghasemi Physical Review B 105 (14), 144106, 2022 | 12 | 2022 |
| Funnel hopping Monte Carlo: An efficient method to overcome broken ergodicity JA Finkler, S Goedecker The Journal of chemical physics 152 (16), 2020 | 8 | 2020 |
| The ternary phase diagram of nitrogen doped lutetium hydrides can not explain its claimed high TC superconductivity M Gubler, M Krummenacher, JA Finkler, JA Flores-Livas, S Goedecker New Journal of Physics 25 (12), 123008, 2023 | 5* | 2023 |
| Experimental absence of the non-perovskite ground state phases of MaPbI 3 explained by a funnel hopping Monte Carlo study based on a neural network potential JA Finkler, S Goedecker Materials Advances 4 (1), 184-194, 2023 | 5 | 2023 |
| Performing highly efficient Minima Hopping structure predictions using the Atomic Simulation Environment (ASE) M Krummenacher, M Gubler, JA Finkler, H Huber, M Sommer-Jörgensen, ... SoftwareX 25, 101632, 2024 | 1 | 2024 |
| Principles of isomer stability in small clusters G Fisicaro, B Schaefer, JA Finkler, S Goedecker Materials Advances 4 (7), 1746-1768, 2023 | 1 | 2023 |
| Accelerating fourth-generation machine learning potentials by quasi-linear scaling particle mesh charge equilibration M Gubler, JA Finkler, MR Schäfer, J Behler, S Goedecker arXiv preprint arXiv:2403.02155, 2024 | | 2024 |
| Corrigendum to performing highly efficient minima hopping structure predictions using the Atomic Simulation Environment (ASE)[SoftwareX 25 (2024) 101632] M Krummenacher, M Gubler, JA Finkler, H Huber, M Sommer-Jörgensen, ... SoftwareX, 101645, 2024 | | 2024 |
| Machine Learning in Atomistic Simulations: Enabling the Description of Charge Transfer Effects and Sampling Multi Funnel Systems with Global Monte Carlo Moves JA Finkler University of Basel, 2023 | | 2023 |
| Funnel Hopping Monte Carlo: Efficient Monte Carlo simulations for multi-funnel systems J Finkler, SA Goedecker APS March Meeting Abstracts 2022, Z49. 011, 2022 | | 2022 |
| A Fourth-Generation High-Dimensional Neural Network Potential with Accurate Electrostatics Including Non-local Charge Transfer J Finkler, T Ko, SA Goedecker, J Behler APS March Meeting Abstracts 2021, B22. 006, 2021 | | 2021 |
| Investigation of global charge distributions for constructing non-local machine learning potentials TW Ko, J Finkler, SA Goedecker, J Behler APS March Meeting Abstracts 2021, P22. 010, 2021 | | 2021 |
Stefan GoedeckerUniversity of Basel, SwitzerlandBestätigte E-Mail-Adresse bei unibas.ch
