Literature DB >> 20614093

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

Alexey A Sokol1, C Richard A Catlow, Martina Miskufova, Stephen A Shevlin, Abdullah A Al-Sunaidi, Aron Walsh, Scott M Woodley.   

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.

Entities:  

Year:  2010        PMID: 20614093     DOI: 10.1039/c0cp00068j

Source DB:  PubMed          Journal:  Phys Chem Chem Phys        ISSN: 1463-9076            Impact factor:   3.676


  1 in total

1.  Structure Prediction and Mechanical Properties of Silicon Hexaboride on Ab Initio Level.

Authors:  Tamara Škundrić; Branko Matović; Aleksandra Zarubica; Jelena Zagorac; Peter Tatarko; Dejan Zagorac
Journal:  Materials (Basel)       Date:  2021-12-20       Impact factor: 3.623

  1 in total

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