Literature DB >> 28607184

A kinetic Monte Carlo approach to diffusion-controlled thermal desorption spectroscopy.

T Schablitzki1, J Rogal2, R Drautz1.   

Abstract

Atomistic simulations of thermal desorption spectra for effusion from bulk materials to characterize binding or trapping sites are a challenging task as large system sizes as well as extended time scales are required. Here, we introduce an approach where we combine kinetic Monte Carlo with an analytic approximation of the superbasins within the framework of absorbing Markov chains. We apply our approach to the effusion of hydrogen from BCC iron, where the diffusion within bulk grains is coarse grained using absorbing Markov chains, which provide an exact solution of the dynamics within a superbasin. Our analytic approximation to the superbasin is transferable with respect to grain size and elliptical shapes and can be applied in simulations with constant temperature as well as constant heating rate. The resulting thermal desorption spectra are in close agreement with direct kinetic Monte Carlo simulations, but the calculations are computationally much more efficient. Our approach is thus applicable to much larger system sizes and provides a first step towards an atomistic understanding of the influence of structural features on the position and shape of peaks in thermal desorption spectra.This article is part of the themed issue 'The challenges of hydrogen and metals'.
© 2017 The Author(s).

Entities:  

Keywords:  diffusion; hydrogen trapping; kinetic Monte Carlo; thermal desorption spectroscopy

Year:  2017        PMID: 28607184      PMCID: PMC5468722          DOI: 10.1098/rsta.2016.0404

Source DB:  PubMed          Journal:  Philos Trans A Math Phys Eng Sci        ISSN: 1364-503X            Impact factor:   4.226


  3 in total

1.  Monte Carlo algorithms with absorbing Markov chains: Fast local algorithms for slow dynamics.

Authors: 
Journal:  Phys Rev Lett       Date:  1995-01-02       Impact factor: 9.161

2.  Effect of surface nanostructure on temperature programmed reaction spectroscopy: first-principles kinetic monte Carlo simulations of CO oxidation at RuO2(110).

Authors:  Michael Rieger; Jutta Rogal; Karsten Reuter
Journal:  Phys Rev Lett       Date:  2008-01-11       Impact factor: 9.161

3.  A local superbasin kinetic Monte Carlo method.

Authors:  Kristen A Fichthorn; Yangzheng Lin
Journal:  J Chem Phys       Date:  2013-04-28       Impact factor: 3.488

  3 in total

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