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Charge State Dependence of Phase Transition Catalysis of Dynamic Cu Clusters in CO2 Dissociation
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    C: Chemical and Catalytic Reactivity at Interfaces

    Charge State Dependence of Phase Transition Catalysis of Dynamic Cu Clusters in CO2 Dissociation
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    • Qi-Yuan Fan
      Qi-Yuan Fan
      State Key Laboratory of Physical Chemistry of Solid Surface, Collaborative Innovation Center of Chemistry for Energy Materials (iChEM), College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, China
      More by Qi-Yuan Fan
    • Zhong-Hao Shi
      Zhong-Hao Shi
      State Key Laboratory of Physical Chemistry of Solid Surface, Collaborative Innovation Center of Chemistry for Energy Materials (iChEM), College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, China
    • Ye Wang
      Ye Wang
      State Key Laboratory of Physical Chemistry of Solid Surface, Collaborative Innovation Center of Chemistry for Energy Materials (iChEM), College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, China
      More by Ye Wang
    • Jun Cheng*
      Jun Cheng
      State Key Laboratory of Physical Chemistry of Solid Surface, Collaborative Innovation Center of Chemistry for Energy Materials (iChEM), College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, China
      *E-mail: [email protected]
      More by Jun Cheng
    Other Access OptionsSupporting Information (1)

    The Journal of Physical Chemistry C

    Cite this: J. Phys. Chem. C 2021, 125, 50, 27615–27623
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    https://doi.org/10.1021/acs.jpcc.1c08970
    Published December 14, 2021
    Copyright © 2021 American Chemical Society

    Abstract

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    The reactivity of subnanometer cluster catalysts depends on their charge state and dynamical evolutions of configurations under reaction environments. There have been some studies on how the dynamic configurational evolutions of neutral clusters influence their catalytic performances. However, there is little work on the charge state sensitivity of dynamic effects of metal clusters. In the present work, we investigate the dynamic process of CO2 dissociation on negatively and positively charged Cu13 clusters and calculate the reaction free energy profiles using ab initio molecular dynamics. It is interesting to find that the reaction entropies are charge sensitive and show a different temperature dependence as compared to their neutral counterpart. In contrast to the single peaked shape shown in the neutral Cu13 cluster, the entropy curves of the charged clusters exhibit an abnormal pulse shape. Further analysis indicates that such nontrivial entropy curves can be attributable to the adsorption-induced solid-to-liquid phase transitions of the charged clusters under finite temperature conditions. Our work reveals a complex temperature dependence of the chemical reaction on the charge state of the metal cluster.

    Copyright © 2021 American Chemical Society

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    Supporting Information

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    The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acs.jpcc.1c08970.

    • Accumulative averages of the forces against time on Cu13 cluster; accumulative averages of the forces against time on Cu13+ cluster; hysteretic behaviors of mean forces on Cu13 cluster; PMF with error bars curves of Cu13 cluster at different temperatures; convergence of time averages of total energies of the IS, TS, and FS for CO2 dissociation on Cu13 at different temperatures; root-mean-squared Cu–Cu bond length fluctuations; PMF with error bars curves of Cu13+ cluster at different temperatures; convergence of time averages of total energies of the IS, TS, and FS for CO2 dissociation on Cu13+ at different temperatures; and Bader charge analysis (PDF)

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    This article is cited by 6 publications.

    1. Yun-Pei Liu, Qi-Yuan Fan, Fu-Qiang Gong, Jun Cheng. CatFlow: An Automated Workflow for Training Machine Learning Potentials to Compute Free Energies in Dynamic Catalysis. The Journal of Physical Chemistry C 2025, 129 (2) , 1089-1102. https://doi.org/10.1021/acs.jpcc.4c05568
    2. Qi-Yuan Fan, Fu-Qiang Gong, Yun-Pei Liu, Hao-Xuan Zhu, Jun Cheng. Modeling Dynamic Catalysis at ab Initio Accuracy: The Need for Free-Energy Calculation. ACS Catalysis 2024, 14 (21) , 16086-16097. https://doi.org/10.1021/acscatal.4c05372
    3. Jian-Feng Li, Jinlong Yang, Qiang Fu. The Journal of Physical Chemistry C Virtual Special Issue on “Energy and Catalysis in China”. The Journal of Physical Chemistry C 2022, 126 (5) , 2301-2306. https://doi.org/10.1021/acs.jpcc.2c00111
    4. Fu‐Qiang Gong, Yun‐Pei Liu, Ye Wang, Weinan E, Zhong‐Qun Tian, Jun Cheng. Machine Learning Molecular Dynamics Shows Anomalous Entropic Effect on Catalysis through Surface Pre‐melting of Nanoclusters. Angewandte Chemie 2024, 136 (27) https://doi.org/10.1002/ange.202405379
    5. Fu‐Qiang Gong, Yun‐Pei Liu, Ye Wang, Weinan E, Zhong‐Qun Tian, Jun Cheng. Machine Learning Molecular Dynamics Shows Anomalous Entropic Effect on Catalysis through Surface Pre‐melting of Nanoclusters. Angewandte Chemie International Edition 2024, 63 (27) https://doi.org/10.1002/anie.202405379
    6. Juan-Juan Sun, Qi-Yuan Fan, Xin Jin, Jing-Li Liu, Tong-Tong Liu, Bin Ren, Jun Cheng. Size-dependent phase transitions boost catalytic activity of sub-nanometer gold clusters. The Journal of Chemical Physics 2022, 156 (14) https://doi.org/10.1063/5.0084165

    The Journal of Physical Chemistry C

    Cite this: J. Phys. Chem. C 2021, 125, 50, 27615–27623
    Click to copy citationCitation copied!
    https://doi.org/10.1021/acs.jpcc.1c08970
    Published December 14, 2021
    Copyright © 2021 American Chemical Society

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