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Molecular-Level Characterization of Heterogeneous Catalytic Systems by Algorithmic Time Dependent Monte Carlo

Abstract

Monte Carlo algorithms and codes, used to study heterogeneous catalytic systems in the frame of the computational section of the NANOCAT project, are presented along with some exemplifying applications and results. In particular, time dependent Monte Carlo methods supported by high level quantum chemical information employed in the field of heterogeneous catalysis are focused. Technical details of the present algorithmic Monte Carlo development as well as possible evolution aimed at a deeper interrelationship of quantum and stochastic methods are discussed, pointing to two different aspects: the thermal-effect involvement and the three-dimensional catalytic matrix simulation. As topical applications, (i) the isothermal and isobaric adsorption of CO on Group 10 metal surfaces, (ii) the hydrogenation on metal supported catalysts of organic substrates in two-phase and three-phase reactors, and (iii) the isomerization of but-2-ene species in three-dimensional supported and unsupported zeolite models are presented.

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Acknowledgements

This work was supported by the NANOCAT Project, funded in the frame of the 6th Framework Programme of the European Community—Contract No. NMP3-CT-2005-506621, by the University of Palermo and by the Italian Ministero dell’Università e della Ricerca.

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Correspondence to D. Duca.

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Armata, N., Baldissin, G., Barone, G. et al. Molecular-Level Characterization of Heterogeneous Catalytic Systems by Algorithmic Time Dependent Monte Carlo. Top Catal 52, 431–443 (2009). https://doi.org/10.1007/s11244-008-9178-9

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Keywords

  • Algorithmic Monte Carlo
  • tdMC
  • Surface processes
  • Heterogeneous catalysis
  • Catalytic reaction modelling