| High-dimensional neural-network potentials for multicomponent systems: Applications to zinc oxide N Artrith, T Morawietz, J Behler Physical Review B 83 (15), 153101, 2011 | 322 | 2011 |
| How van der Waals interactions determine the unique properties of water T Morawietz, A Singraber, C Dellago, J Behler Proceedings of the National Academy of Sciences 113 (30), 8368-8373, 2016 | 320 | 2016 |
| A Density-Functional Theory-Based Neural Network Potential for Water Clusters Including van der Waals Corrections T Morawietz, J Behler The Journal of Physical Chemistry A 117 (32), 7356–7366, 2013 | 172 | 2013 |
| A neural network potential-energy surface for the water dimer based on environment-dependent atomic energies and charges T Morawietz, V Sharma, J Behler The Journal of chemical physics 136 (6), 064103, 2012 | 128 | 2012 |
| Parallel multistream training of high-dimensional neural network potentials A Singraber, T Morawietz, J Behler, C Dellago Journal of chemical theory and computation 15 (5), 3075-3092, 2019 | 117 | 2019 |
| The interplay of structure and dynamics in the Raman spectrum of liquid water over the full frequency and temperature range T Morawietz, O Marsalek, SR Pattenaude, LM Streacker, D Ben-Amotz, ... The journal of physical chemistry letters 9 (4), 851-857, 2018 | 81 | 2018 |
| Representing the potential-energy surface of protonated water clusters by high-dimensional neural network potentials SK Natarajan, T Morawietz, J Behler Physical Chemistry Chemical Physics 17 (13), 8356-8371, 2015 | 73 | 2015 |
| Machine learning-accelerated quantum mechanics-based atomistic simulations for industrial applications T Morawietz, N Artrith Journal of Computer-Aided Molecular Design 35 (4), 557-586, 2021 | 26 | 2021 |
| A Full-Dimensional Neural Network Potential-Energy Surface for Water Clusters up to the Hexamer T Morawietz, J Behler Zeitschrift für Physikalische Chemie 227 (11), 1559, 2013 | 25 | 2013 |
| Strategies for the construction of machine-learning potentials for accurate and efficient atomic-scale simulations AM Miksch, T Morawietz, J Kästner, A Urban, N Artrith Machine Learning: Science and Technology 2 (3), 031001, 2021 | 23 | 2021 |
| Hiding in the crowd: spectral signatures of overcoordinated hydrogen-bond environments T Morawietz, AS Urbina, PK Wise, X Wu, W Lu, D Ben-Amotz, ... The Journal of Physical Chemistry Letters 10 (20), 6067-6073, 2019 | 22 | 2019 |
| Exploiting machine learning to efficiently predict multidimensional optical spectra in complex environments MS Chen, TJ Zuehlsdorff, T Morawietz, CM Isborn, TE Markland The Journal of Physical Chemistry Letters 11 (18), 7559-7568, 2020 | 20 | 2020 |
| Density anomaly of water at negative pressures from first principles A Singraber, T Morawietz, J Behler, C Dellago Journal of Physics: Condensed Matter 30 (25), 254005, 2018 | 12 | 2018 |
| AENET–LAMMPS and AENET–TINKER: Interfaces for accurate and efficient molecular dynamics simulations with machine learning potentials MS Chen, T Morawietz, H Mori, TE Markland, N Artrith The Journal of Chemical Physics 155 (7), 074801, 2021 | 7 | 2021 |
| Don’t overweight weights: Evaluation of weighting strategies for multi-task bioactivity classification models L Humbeck, T Morawietz, N Sturm, A Zalewski, S Harnqvist, W Heyndrickx, ... Molecules 26 (22), 6959, 2021 | 4 | 2021 |
| Efficient simulations of water with ab initio accuracy T Morawietz Bochum, Ruhr-Universität Bochum, Diss., 2015, 2016 | 2 | 2016 |
| Entwicklung eines effizienten Potentials für das Wasser-Dimer basierend auf künstlichen neuronalen Netzen () T Morawietz PhD Thesis, 2010 | 2 | 2010 |
| MELLODDY: cross pharma federated learning at unprecedented scale unlocks benefits in QSAR without compromising proprietary information W Heyndrickx, L Mervin, T Morawietz, N Sturm, L Friedrich, A Zalewski, ... | 1 | 2022 |
| Optically induced anisotropy in time-resolved scattering: Imaging molecular scale structure and dynamics in disordered media with experiment and theory A Montoya-Castillo, MS Chen, SL Raj, KA Jung, KS Kjaer, T Morawietz, ... Physical Review Letters 129, 056001, 2022 | | 2022 |
| Efficient simulations of water with accuracy T Morawietz | | 2016 |
Nongnuch ArtrithAssistant Professor, Debye Institute for Nanomaterials Science, Utrecht UniversityVerified email at atomistic.net
