Accurate coverage-dependence incorporated into first-principles kinetic models: Catalytic NO oxidation on Pt (1 1 1)

C. Wu, D. J. Schmidt, C. Wolverton, W. F. Schneider*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

127 Scopus citations

Abstract

The coverage of surface adsorbates influences both the number and types of sites available for catalytic reactions at a heterogeneous surface, but accounting for adsorbate-adsorbate interactions and understanding their implications on observed rates remain challenges for simulation. Here, we demonstrate the use of a density functional theory (DFT)-parameterized cluster expansion (CE) to incorporate accurate adsorbate-adsorbate interactions into a surface kinetic model. The distributions of adsorbates and reaction sites at a metal surface as a function of reaction conditions are obtained through Grand Canonical Monte Carlo simulations on the CE Hamiltonian. Reaction rates at those sites are obtained from the CE through a DFT-parameterized Brønsted- Evans-Polyani (BEP) relationship. The approach provides ready access both to steady-state rates and rate derivatives and further provides insight into the microscopic factors that influence observed rate behavior. We demonstrate the approach for steady-state O 2 dissociation at an O-covered Pt (1 1 1) surface - a model for catalytic NO oxidation at this surface - and recover apparent activation energies and rate orders consistent with experiment.

Original languageEnglish (US)
Pages (from-to)88-94
Number of pages7
JournalJournal of Catalysis
Volume286
DOIs
StatePublished - Feb 2012

Keywords

  • Adsorbate-adsorbate interactions
  • Cluster expansion
  • DFT
  • NO oxidation kinetics
  • O dissociation
  • Pt (1 1 1)
  • Rate laws

ASJC Scopus subject areas

  • Catalysis
  • Physical and Theoretical Chemistry

Fingerprint

Dive into the research topics of 'Accurate coverage-dependence incorporated into first-principles kinetic models: Catalytic NO oxidation on Pt (1 1 1)'. Together they form a unique fingerprint.

Cite this