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.
- Research Organization:
- Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Oak Ridge Leadership Computing Facility (OLCF); Ames Lab., Ames, IA (United States)
- Sponsoring Organization:
- USDOE Office of Science (SC)
- DOE Contract Number:
- DE-AC02-07CH11358
- OSTI ID:
- 1157620
- Report Number(s):
- IS-J 8337
- Journal Information:
- Journal of Physical Chemistry. C, Vol. 118, Issue 18; ISSN 1932-7447
- Publisher:
- American Chemical Society
- Country of Publication:
- United States
- Language:
- English
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