Automated calculation of thermal rate coefficients using ring polymer molecular dynamics and machine-learning interatomic potentials with active learning.

@article{Novikov2018AutomatedCO,
  title={Automated calculation of thermal rate coefficients using ring polymer molecular dynamics and machine-learning interatomic potentials with active learning.},
  author={Ivan S. Novikov and Yury V. Suleimanov and Alexander V. Shapeev},
  journal={Physical chemistry chemical physics : PCCP},
  year={2018},
  volume={20 46},
  pages={
          29503-29512
        }
}
We propose a methodology for the fully automated calculation of thermal rate coefficients of gas phase chemical reactions, which is based on combining ring polymer molecular dynamics (RPMD) and machine-learning interatomic potentials actively learning on-the-fly. Based on the original computational procedure implemented in the RPMDrate code, our methodology gradually and automatically constructs the potential energy surfaces (PESs) from scratch with the data set points being selected and… 

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