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Title: Interface Structure Prediction from First-Principles

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 Σ3(112)[1¯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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Publication Date:
OSTI Identifier:
Report Number(s):
IS-J 8337
Journal ID: ISSN 1932-7447
DOE Contract Number:
Resource Type:
Journal Article
Resource Relation:
Journal Name: Journal of Physical Chemistry. C; Journal Volume: 118; Journal Issue: 18
American Chemical Society
Research Org:
Ames Laboratory (AMES), Ames, IA (United States)
Sponsoring Org:
USDOE Office of Science (SC)
Country of Publication:
United States
36 MATERIALS SCIENCE Surface chemistry and colloids