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Computer simulations of glasses: the potential energy landscape

Overview of attention for article published in Journal of Physics: Condensed Matter, July 2015
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Title
Computer simulations of glasses: the potential energy landscape
Published in
Journal of Physics: Condensed Matter, July 2015
DOI 10.1088/0953-8984/27/29/293201
Pubmed ID
Authors

Zamaan Raza, Björn Alling, Igor A Abrikosov

Abstract

We review the current state of research on glasses, discussing the theoretical background and computational models employed to describe them. This article focuses on the use of the potential energy landscape (PEL) paradigm to account for the phenomenology of glassy systems, and the way in which it can be applied in simulations and the interpretation of their results. This article provides a broad overview of the rich phenomenology of glasses, followed by a summary of the theoretical frameworks developed to describe this phenomonology. We discuss the background of the PEL in detail, the onerous task of how to generate computer models of glasses, various methods of analysing numerical simulations, and the literature on the most commonly used model systems. Finally, we tackle the problem of how to distinguish a good glass former from a good crystal former from an analysis of the PEL. In summarising the state of the potential energy landscape picture, we develop the foundations for new theoretical methods that allow the ab initio prediction of the glass-forming ability of new materials by analysis of the PEL.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 88 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 4 5%
Sweden 1 1%
Unknown 83 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 28 32%
Researcher 15 17%
Professor > Associate Professor 10 11%
Student > Master 9 10%
Student > Doctoral Student 4 5%
Other 11 13%
Unknown 11 13%
Readers by discipline Count As %
Physics and Astronomy 31 35%
Materials Science 21 24%
Chemistry 11 13%
Engineering 5 6%
Chemical Engineering 3 3%
Other 4 5%
Unknown 13 15%