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Design and application of genetic algorithms for structural optimization of nanoalloys

Roy L. Johnston 

School of Chemistry, University of Birmingham, Edgbaston, Birmingham B152TT, United Kingdom

Abstract

The desire to fabricate materials with well defined, controllable properties and structures, on the nanometre scale, coupled with the flexibility afforded by intermetallic materials, has generated interest in
bimetallic alloy clusters or "nanoalloys". One of the major reasons for interest in nanoalloy particles is the fact that their chemical and physical properties may be tuned by varying the composition and atomic ordering, as well as the size of the clusters. Their surface structures, compositions and segregation properties are of interest as they are important in determining chemical reactivity, and
especially catalytic activity. Nanoalloy clusters are also of interest as they may display structures and properties which are distinct from those of the pure elemental clusters. In this talk, I will start by introducing the field of nanoalloys and reasons for studying them. I will also summarise the important factors that determine the mixing or segregation properties of nanoalloy clusters. I will describe the model (the Gupta many-body potential) and the methodologies (genetic algorithms, Basin Hopping Monte Carlo and systematic optimisation studies of geometric shell clusters) that we have used to study the structures and segregation properties of a variety of nanoalloys - paying particular attention to the design of the genetic algorithm. The results of recent DFT calculations will also be presented.

 

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Related papers

Presentation: Invited at E-MRS Fall Meeting 2007, Symposium G, by Roy L. Johnston
See On-line Journal of E-MRS Fall Meeting 2007

Submitted: 2007-05-09 12:47
Revised:   2009-06-07 00:44