Catalytic conversion reactions in nanoporous systems with concentration-dependent selectivity: Statistical mechanical modeling

Garcia, Andres; Wang, Jing; Windus, Theresa L.; Sadow, Aaron D.; Evans, James W.

doi:10.1103/PhysRevE.93.052137

Title: Catalytic conversion reactions in nanoporous systems with concentration-dependent selectivity: Statistical mechanical modeling

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Abstract

Statistical mechanical modeling is developed to describe a catalytic conversion reaction A → B^c or B^t with concentration-dependent selectivity of the products, B^c or B^t, where reaction occurs inside catalytic particles traversed by narrow linear nanopores. The associated restricted diffusive transport, which in the extreme case is described by single-file diffusion, naturally induces strong concentration gradients. Hence, by comparing kinetic Monte Carlo simulation results with analytic treatments, selectivity is shown to be impacted by strong spatial correlations induced by restricted diffusivity in the presence of reaction and also by a subtle clustering of reactants, A.

Authors:

Garcia, Andres ^[1]; Wang, Jing ^[1]; Windus, Theresa L. ^[1]; Sadow, Aaron D. ^[1]; Evans, James W. ^[1]

Ames Lab. and Iowa State Univ., Ames, IA (United States)

Publication Date:: Fri May 20 00:00:00 EDT 2016

Research Org.:: Ames Laboratory (AMES), Ames, IA (United States)

Sponsoring Org.:: USDOE Office of Science (SC), Basic Energy Sciences (BES)

OSTI Identifier:: 1278786

Alternate Identifier(s):: OSTI ID: 1254052

Report Number(s):: IS-J-9017
Journal ID: ISSN 2470-0045; PLEEE8

Grant/Contract Number:: AC02-07CH11358

Resource Type:: Accepted Manuscript

Journal Name:: Physical Review E

Additional Journal Information:: Journal Volume: 93; Journal Issue: 5; Journal ID: ISSN 2470-0045

Publisher:: American Physical Society (APS)

Country of Publication:: United States

Language:: English

Subject:: 36 MATERIALS SCIENCE

Citation Formats


                    Garcia, Andres, Wang, Jing, Windus, Theresa L., Sadow, Aaron D., and Evans, James W. Catalytic conversion reactions in nanoporous systems with concentration-dependent selectivity: Statistical mechanical modeling.  United States: N. p., 2016. 
Web.  doi:10.1103/PhysRevE.93.052137.

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                    Garcia, Andres, Wang, Jing, Windus, Theresa L., Sadow, Aaron D., & Evans, James W. Catalytic conversion reactions in nanoporous systems with concentration-dependent selectivity: Statistical mechanical modeling.  United States.  https://doi.org/10.1103/PhysRevE.93.052137

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                    Garcia, Andres, Wang, Jing, Windus, Theresa L., Sadow, Aaron D., and Evans, James W. Fri .  
"Catalytic conversion reactions in nanoporous systems with concentration-dependent selectivity: Statistical mechanical modeling".  United States.  https://doi.org/10.1103/PhysRevE.93.052137.  https://www.osti.gov/servlets/purl/1278786.

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@article{osti_1278786,

  title        = {Catalytic conversion reactions in nanoporous systems with concentration-dependent selectivity: Statistical mechanical modeling},

  author       = {Garcia, Andres and Wang, Jing and Windus, Theresa L. and Sadow, Aaron D. and Evans, James W.},

  abstractNote = {Statistical mechanical modeling is developed to describe a catalytic conversion reaction A → Bc or Bt with concentration-dependent selectivity of the products, Bc or Bt, where reaction occurs inside catalytic particles traversed by narrow linear nanopores. The associated restricted diffusive transport, which in the extreme case is described by single-file diffusion, naturally induces strong concentration gradients. Hence, by comparing kinetic Monte Carlo simulation results with analytic treatments, selectivity is shown to be impacted by strong spatial correlations induced by restricted diffusivity in the presence of reaction and also by a subtle clustering of reactants, A.},

  doi          = {10.1103/PhysRevE.93.052137},

  journal      = {Physical Review E},

  number       = 5,

  volume       = 93,

  place        = {United States},

  year         = {Fri May 20 00:00:00 EDT 2016},

  month        = {Fri May 20 00:00:00 EDT 2016}

}

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