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Monte Carlo methods for the study of cation ordering in minerals

Published online by Cambridge University Press:  05 July 2018


M. C. Warren
Affiliation:
Department of Earth Sciences, University of Cambridge, Downing Street, Cambridge CB2 3EQ, UK
M. T. Dove
Affiliation:
Department of Earth Sciences, University of Cambridge, Downing Street, Cambridge CB2 3EQ, UK
E. R. Myers
Affiliation:
Department of Earth Sciences, University of Cambridge, Downing Street, Cambridge CB2 3EQ, UK
A. Bosenick
Affiliation:
Department of Earth Sciences, University of Cambridge, Downing Street, Cambridge CB2 3EQ, UK
E. J. Palin
Affiliation:
Department of Earth Sciences, University of Cambridge, Downing Street, Cambridge CB2 3EQ, UK
C. I. Sainz-Diaz
Affiliation:
Estacion Experimental del Zaidin, CSIC, C/ Profesor Albareda, 1, 18008-Granada, Spain
B. S. Guiton
Affiliation:
Department of Earth Sciences, University of Cambridge, Downing Street, Cambridge CB2 3EQ, UK
S. A. T. Redfern
Affiliation:
Department of Earth Sciences, University of Cambridge, Downing Street, Cambridge CB2 3EQ, UK
Corresponding
E-mail address:

Abstract

This paper reviews recent applications of Monte Carlo methods for the study of cation ordering in minerals. We describe the program Ossia99, designed for the simulation of complex ordering processes and for use on parallel computers. A number of applications for the study of long-range and short-range order are described, including the use of the Monte Carlo methods to compute quantities measured in an NMR experiment. The method of thermodynamic integration for the determination of the free energy is described in some detail, and several applications of the method to determine the thermodynamics of disordered systems are outlined.


Type
Research Article
Copyright
Copyright © The Mineralogical Society of Great Britain and Ireland 2001

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Footnotes

2

Present address: Department of Earth Sciences, The University of Manchester, Manchester M13 9PL, UK

3

Present address: Department of Pure Mathematics and Mathematical Statistics, University of Cambridge, 16 Mill Lane, Cambridge CB2 1SB, UK

4

Present address: Martenshofweg 9, 24109 Kiel, Germany


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