Litcius/Paper detail

Investigating the Eley–Rideal recombination of hydrogen atoms on Cu (111)<i>via</i>a high-dimensional neural network potential energy surface

Lingjun Zhu, Ce Hu, Jialu Chen, Bin Jiang

2023Physical Chemistry Chemical Physics12 citationsDOIOpen Access PDF

Abstract

molecular dynamics, preventing quantitative comparisons with experimental data. Herein, we report the first high-dimensional neural network potential (NNP) for this ER reaction based on first-principles calculations including all molecular and surface degrees of freedom. Thanks to the high efficiency of this NNP, we are able to perform extensive quasi-classical molecular dynamics simulations with the inclusion of the excitation of low-lying electron-hole pairs (EHPs), which generally yield good agreement with various experimental results. More importantly, the isotopic and/or EHP effects in total reaction cross-sections and distributions of the product energy, scattering angle, and individual ro-vibrational states have been more clearly shown and discussed. This study sheds valuable light on this important ER prototype and opens a new avenue for further investigations of ER reactions using various initial conditions, surface temperatures, and coverages in the future.

Topics & Concepts

RecombinationHydrogenSurface (topology)Chemical physicsPotential energy surfaceAtomic physicsChemistryMaterials sciencePhysicsMoleculeQuantum mechanicsGeometryBiochemistryMathematicsGeneAdvanced Chemical Physics StudiesMachine Learning in Materials ScienceCatalytic Processes in Materials Science