Interface Structure Prediction from First-Principles
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- 作者：Xin Zhao ; Qiang Shu ; Manh Cuong Nguyen ; Yangang Wang ; Min Ji ; Hongjun Xiang ; Kai-Ming Ho ; Xingao Gong ; Cai-Zhuang Wang
- 刊名：Journal of Physical Chemistry C
- 出版年：2014
- 出版时间：May 8, 2014
- 年：2014
- 卷：118
- 期：18
- 页码：9524-9530
- 全文大小：421K
- 年卷期：v.118,no.18(May 8, 2014)
- ISSN：1932-7455
文摘
Information about the atomic structures at solid鈥搒olid 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 危3(112)[1̅10] 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.