ML for gas-surface dynamics

Instructions and scripts for growing machine learning interatomic potentials (MLIPs) databases through adaptive sampling for gas-surface dynamics.

• High-error structure search using NQCDynamics.jl.
• Structure selection (clustering) for database reduction.

>>> Instructions are available here <<<

References

If you found the scripts and/or tutorial helpful, please cite the following references:

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]

@misc{stark_machine_2023,
	title = {Machine learning interatomic potentials for reactive hydrogen dynamics at metal surfaces based on iterative refinement of reaction probabilities},
	author = {Stark, Wojciech G. and Westermayr, Julia and Douglas-Gallardo, Oscar A. and Gardner, James and Habershon, Scott and Maurer, Reinhard J.},
	volume = {127},
	number = {50},
	pages = {24168–24182},
	year = {2023},
	publisher = {J. Phys. Chem. C},
	doi = {10.1021/acs.jpcc.3c06648}, 
	url = {https://doi.org/10.1021/acs.jpcc.3c06648}
}

J. Gardner, O. A. Douglas-Gallardo, W. G. Stark, J. Westermayr, S. M. Janke, S. Habershon, R. J. Maurer, NQCDynamics.jl: A Julia package for nonadiabatic quantum classical molecular dynamics in the condensed phase, J. Chem. Phys. 156, 174801 (2022) [arXiv] [journal]

@article{gardner_nqcdynamicsjl_2022,
	title = {{NQCDynamics}.jl: {A} {Julia} package for nonadiabatic quantum classical molecular dynamics in the condensed phase},
	author = {Gardner, James and Douglas-Gallardo, Oscar A. and Stark, Wojciech G. and Westermayr, Julia and Janke, Svenja M. and Habershon, Scott and Maurer, Reinhard J.},
	journal = {J. Chem. Phys.},
	volume = {156},
	number = {17},
	pages = {174801},
	year = {2022},
	issn = {0021-9606, 1089-7690},
	doi = {10.1063/5.0089436},
	url = {https://aip.scitation.org/doi/10.1063/5.0089436}
}