Abstract
Heterogeneous catalysis is key for chemical transformations. Understanding how catalyst active sites dynamically evolve at the atomic scale under reaction conditions is a prerequisite for accurate determination of catalytic mechanisms and predictably developing catalysts. We combine in-situ time-dependent observation and machine learning-accelerated first-principle atomistic simulations to uncover the mechanism of restructuring of Pt catalysts under a pressure of carbon monoxide (CO). We show that a high CO coverage at a Pt step edge triggers the formation of atomic protrusions of low-coordination Pt atoms, which then detach from the step edge to create subnano-islands on the terraces, where undercoordinated sites are stabilized by the CO adsorbates. The fast and accurate machine learning potential is key to enable the exploration of ten of thousands of configurations for the CO covered restructuring catalyst. These studies open an avenue to achieve atom-scale understanding of structural dynamics of more complex metal nanoparticle catalysts under reaction.
Supplementary materials
Title
Supporting Materials for Atomic scale mechanism of Pt catalyst restructuring under a pressure of gas
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This PDF file includes:
Methods
Figs. S1 to S20
Tables S1 to S7
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Supplementary weblinks
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Computational Data
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All the structural data (trajectory files including the positions, energy, and force information) used for training & validation of HDNNP and the data generated from Basin Hopping simulations have been included.
Contains the files to utilize the n2p2-Neural Network Potential.
Contrains the NEB trajectories and python script used to generate Fig. 5 and S20.
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