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Entropy in catalyst dynamics under confinement.

Qi-Yuan Fan1,2, Yun-Pei Liu1, Hao-Xuan Zhu1

  • 1State 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 Chengjun@xmu.edu.cn.

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Confinement in carbon nanotubes enhances catalyst dynamics and lowers melting points, facilitating reactions. This study reveals crucial insights into entropy

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Area of Science:

  • Catalysis
  • Materials Science
  • Physical Chemistry

Background:

  • Catalyst structural dynamics and entropy influence chemical reaction outcomes.
  • Confinement effects on catalyst dynamics are not fully understood.
  • Understanding these factors is key for designing efficient catalysts.

Purpose of the Study:

  • Investigate catalyst dynamics under confinement using machine learning.
  • Compute reaction free energies and entropies for O2 dissociation on confined Pt clusters.
  • Clarify the role of entropy in dynamic catalysis.

Main Methods:

  • Active learning scheme to train machine learning potentials.
  • Ab initio accuracy calculations.
  • Simulations of Pt clusters confined within carbon nanotubes (CNTs).

Main Results:

  • Observed entropic effects due to liquid-to-solid phase transitions of Pt clusters.
  • Confinement enhanced structural dynamics and lowered the melting temperature of Pt clusters.
  • Facilitated O2 dissociation at lower temperatures and prevented oxide formation.

Conclusions:

  • Confinement significantly impacts catalyst structural dynamics and entropy.
  • Dynamic structural evolution is crucial for catalytic efficiency.
  • Provides insights into entropy-driven dynamic catalysis.