Fast and accurate molecular dynamics simulations using ML-based interatomic potentials and electronic friction models.
This repository accompanies the research on nonadiabatic reactive scattering of hydrogen on copper surfaces. It provides:
- Trained machine learning interatomic potentials (MLIPs)
- Scripts for high-throughput molecular dynamics (MD)
- Electronic friction models, including local density friction approximation (LDFA), and orbital-dependent friction (ODF) models.
- Tools for state-to-state scattering dynamics.
- Databases for model training and validation
- MLIP construction through adaptive sampling
- High-error structure search with NQCDynamics.jl
- Clustering-based structure selection
- Full MD pipelines for:
- Dissociative chemisorption dynamics for evaluation of sticking probabilities
- State-to-state scattering dynamics
📚 Full documentation and instructions:
👉 Project Website
If this code or data helped your work, please cite:
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H2/Cu Nonadiabatic dynamics, construction of electronic friction models:
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H2/Cu dissociative chemisorption, construction of MLIPs
- W. G. Stark, J. Westermayr, O. A. Douglas-Gallardo, J. Gardner, S. Habershon, R. J. Maurer, Machine learning interatomic potentials for reactive hydrogen dynamics at metal surfaces based on iterative refinement of reaction probabilities, J. Phys. Chem. C, 127, 50, 24168–24182, (2023) [arXiv] [journal]
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NQCDynamics code:
BibTeX
@article{stark_nonadiabatic_2025,
title = {Nonadiabatic reactive scattering of hydrogen on different surface facets of copper},
author = {Stark, Wojciech G. and Box, Connor L. and Sachs, Matthias and Hertl, Nils and Maurer, Reinhard J.},
publisher = {Phys. Rev. B},
volume = {112},
number = {3},
doi = {10.1103/h7vd-94pk},
year = {2025},
url = {https://link.aps.org/doi/10.1103/h7vd-94pk},
}
@article{stark_machine_2023,
title = {Machine learning interatomic potentials for reactive hydrogen dynamics at metal surfaces},
author = {Stark, Wojciech G. et al.},
journal = {J. Phys. Chem. C},
year = {2023},
volume = {127},
number = {50},
pages = {24168–24182},
doi = {10.1021/acs.jpcc.3c06648}
}
@article{gardner_nqcdynamicsjl_2022,
title = {{NQCDynamics}.jl: {A} Julia package for nonadiabatic quantum classical molecular dynamics},
author = {Gardner, James et al.},
journal = {J. Chem. Phys.},
volume = {156},
number = {17},
pages = {174801},
year = {2022},
doi = {10.1063/5.0089436}
}