Determining in situ phases of a nanoparticle catalyst via grand canonical Monte Carlo simulations with the ReaxFF potential

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Abstract

Catalyst design requires a detailed understanding of the structure of the catalyst surface as a function of varying reaction conditions. Here we demonstrate the capability of a grand canonical Monte Carlo/molecular dynamics (GC-MC/MD) method utilizing the ReaxFF potential to predict nanoparticle structure and phase stability as a function of temperature and pressure. This is demonstrated for Pd nanoparticles, which readily form oxide, hydride, and carbide phases under reaction environments, impacting catalytic behavior. The approach presented here can be extended to other catalytic systems, providing a new tool for exploring the effects of reaction conditions on catalyst activity, selectivity, and stability.

Original languageEnglish (US)
Pages (from-to)72-77
Number of pages6
JournalCatalysis Communications
Volume52
DOIs
StatePublished - Jul 5 2014

All Science Journal Classification (ASJC) codes

  • Catalysis
  • Chemistry(all)
  • Process Chemistry and Technology

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