Monte Carlo methods for the study of cation ordering in minerals

Warren, M. C.; Dove, Martin T.; Myers, Eva R.; Bosenick, Anne; Palin, Erika J.; Sainz‐Díaz, C. Ignacio; Guiton, Beth S.; Redfern, Simon A. T.

doi:10.1180/002646101550235

Cited by 68 publications

(48 citation statements)

References 27 publications

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“…[27] This review is concerned with developing models of the energetics of ordering, and using Monte Carlo (MC) methods to study the variation of equilibrium ordered states (both long-and shortrange) with temperature. These methods have been successfully applied to a wide range of minerals, as reviewed by Bosenick et al [28] and Warren et al, [29] and more recently to a range of examples within the family of 2:1 phyllosilicate minerals. The rationale behind using computer simulations to study cation ordering in phyllosilicates is that, due to their inhomogeneous structures, cation ordering can be strongly inhibited by kinetics.…”

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confidence: 99%

Computer simulations of cations order‐disorder in 2:1 dioctahedral phyllosilicates using cation‐exchange potentials and monte carlo methods

Palin

Dove

Redfern

et al. 2014

Int J of Quantum Chemistry

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This article reviews the use of Monte Carlo methods with cation-exchange potentials and effective Hamiltonians, based on empirical potentials and quantum-mechanical calculations, for the study of cation ordering in phyllosilicates. The basic methodology is described, and the application of the methods is illustrated with a number of key example case studies. These include Al-Si ordering in muscovite, Al-Fe-Mg ordering (both binary and ternary compositions) in the octahedral illite/smectite sheet, examination of the ordering behavior of phengite, in which the octahedral sites are occupied by Al and Mg and the tetrahedral sites by Al and Si, and Al-Si ordering in the tetrahedral phyllosilicate sheet with variable Al:Si ratio. In several cases, complex ordering processes were found. The essential conclusion from this work is that computer simulation studies of this nature can be a valuable tool in ordering studies of many nanomaterials.

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confidence: 99%

Computer simulations of cations order‐disorder in 2:1 dioctahedral phyllosilicates using cation‐exchange potentials and monte carlo methods

Palin

Dove

Redfern

et al. 2014

Int J of Quantum Chemistry

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“…The example is of simulations of cation ordering in a layer silicate such as muscovite, formula MgSi 3 AlO 8 (OH) [17]. The various steps in a complete study might be [18,19] 1. Obtain a trial structure from a crystallographic database.…”

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confidence: 99%

Collaborative grid infrastructure for molecular simulations: TheeMinerals minigrid as a prototype integrated compute and data grid

Calleja

Bruin

Tucker

et al. 2005

Molecular Simulation

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This paper describes a prototype grid infrastructure, called the "eMinerals minigrid", for molecular simulation scientists. which is based on an integration of shared compute and data resources. We describe the key components, namely the use of Condor pools, Linux/Unix clusters with PBS and IBM's LoadLeveller job handling tools, the use of Globus for security handling, the use of Condor-G tools for wrapping globus job submit commands, Condor's DAGman tool for handling workflow, the Storage Resource Broker for handling data, and the CCLRC dataportal and associated tools for both archiving data with metadata and making data available to other workers.

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“…To measure the latter one needs to take into account a small entropic contribution, which can be done using the method of thermodynamic integration [11]. This requires many runs at different temperatures, starting with the model T = 0 K system up to the required temperature.…”

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Calculating Activation Energies in Diffusion Processes Using a Monte Carlo Approach in a Grid Environment

Calleja

Dove

2004

Computational Science - ICCS 2004

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Abstract.A Monte Carlo based method due to Mishin [1] for obtaining activation energies for ionic transport processes has been implemented for empirical-potential models and used in conjunction with Condor and Globus tools. Results are shown for Na + migrating in quartz, and O 2−vacancy hopping in CaTiO3. We also describe the extensions at the Condor/Globus interface we found necessary to implement in order to facilitate transparent file transfer with Condor-G job submission.

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Monte Carlo methods for the study of cation ordering in minerals

Cited by 68 publications

References 27 publications

Computer simulations of cations order‐disorder in 2:1 dioctahedral phyllosilicates using cation‐exchange potentials and monte carlo methods

Computer simulations of cations order‐disorder in 2:1 dioctahedral phyllosilicates using cation‐exchange potentials and monte carlo methods

Collaborative grid infrastructure for molecular simulations: TheeMinerals minigrid as a prototype integrated compute and data grid

Calculating Activation Energies in Diffusion Processes Using a Monte Carlo Approach in a Grid Environment

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