Journal
JOURNAL OF PHYSICAL CHEMISTRY LETTERS
Volume 10, Issue 6, Pages 1185-1191Publisher
AMER CHEMICAL SOC
DOI: 10.1021/acs.jpclett.9b00085
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Funding
- National Key R&D Program of China [2017YFA0303500]
- National Natural Science Foundation of China [21573203, 91645202, 21722306]
- Anhui Initiative in Quantum Information Technologies
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Direct dynamics simulations become increasingly popular in studying reaction dynamics for complex systems where analytical potential energy surfaces (PESs) are unavailable. Yet, the number and/or the propagation time of trajectories are often limited by high computational costs, and numerous energies and forces generated on-the-fly become wasted after simulations. We demonstrate here an example of reusing only a very small portion of existing direct dynamics data to reconstruct a 90-dimensional globally accurate reactive PES describing the interaction of CO2 with a movable Ni(100) surface based on a machine learning approach. In addition to reproducing previous results with much better statistics, we predict scattering probabilities of CO2 at the state-tostate level, which is extremely demanding for direct dynamics. We propose this unified way to investigate gaseous and gas-surface reactions of medium size, initiating with hundreds of preliminary direct dynamics trajectories, followed by low-cost and high-quality simulations on full-dimensional analytical PESs.
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