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On the problem of cluster structure diversity and the value of data mining


Reference:

Sokol, A. A., Catlow, C. R. A., Miskufova, M., Shevlin, S. A., Al-Sunaidi, A. A., Walsh, A. and Woodley, S. M., 2010. On the problem of cluster structure diversity and the value of data mining. Physical Chemistry Chemical Physics, 12 (30), pp. 8438-8445.

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Official URL:

http://dx.doi.org/10.1039/c0cp00068j

Abstract

Data mining, involving cross examination of cluster structure pools collected for ZnO, GaN, LiF and AgI, has been applied to predict plausible cluster structures of related binary materials. We consider the energy landscapes of (MX) 12 clusters for materials that possess tetrahedral bulk phases, wurtzite or sphalerite, including LiF, BeO, BN, AlN, SiC, CuF, ZnO, GaN, GeC and AgI. The energy is evaluated using the hybrid PBEsol0 density functional for structures optimised at the PBEsol level. We report a novel encapsulated iodide structure for AgI and a series of new CuF structures, where significant differences are found between the results for the two functionals.

Details

Item Type Articles
CreatorsSokol, A. A., Catlow, C. R. A., Miskufova, M., Shevlin, S. A., Al-Sunaidi, A. A., Walsh, A. and Woodley, S. M.
DOI10.1039/c0cp00068j
Uncontrolled Keywordssolids, crystal-structure, evolutionary algorithms, oxide, genetic algorithm, carbon, structure prediction, cage, nanoparticles, geometry optimization
DepartmentsFaculty of Science > Chemistry
RefereedYes
StatusPublished
ID Code23985

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