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Interface Structure Prediction from First-Principles

TitleInterface Structure Prediction from First-Principles
Publication TypeJournal Article
Year of Publication2014
AuthorsZhao, X, Shu, Q, Nguyen, MC, Wang, YG, Ji, M, Xiang, HJ, Ho, KM, Gong, XG, Wang, CZ
JournalJournal of Physical Chemistry C
Date Published05
Type of ArticleArticle
ISBN Number1932-7447
Accession NumberWOS:000335878900025
Keywordsab-initio data, effective, Genetic algorithm, grain-boundaries, metals, oxides, potentials, systems, total-energy calculations, wave basis-set

Information about the atomic structures at solid-solid interfaces is crucial for understanding and predicting the performance of materials. Due to the complexity of the interfaces, it is very challenging to resolve their atomic structures using either experimental techniques or computer simulations. In this paper, we present an efficient first-principles computational method for interface structure prediction based on an adaptive genetic algorithm. This approach significantly reduces the computational cost, while retaining the accuracy of first-principles prediction. The method is applied to the investigation of both stoichiometric and nonstoichiometric SrTiO3 Sigma 3(112)[(1) over bar 10] grain boundaries with unit cell containing up to 200 atoms. Several novel low-energy structures are discovered, which provide fresh insights into the structure and stability of the grain boundaries.

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