Citation: 
G. Trimarchi. Crystal structure prediction in the context of inverse materials design[J]. Journal of Semiconductors, 2018, 39(7): 071004. doi: 10.1088/16744926/39/7/071004
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G Trimarchi, Crystal structure prediction in the context of inverse materials design[J]. J. Semicond., 2018, 39(7): 071004. doi: 10.1088/16744926/39/7/071004.

Crystal structure prediction in the context of inverse materials design
DOI: 10.1088/16744926/39/7/071004
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Abstract
Inverse materials design tackles the challenge of finding materials with desired properties, tailored to specific applications, by combining atomistic simulations and optimization methods. The search for optimal materials requires one to survey large spaces of candidate solids. These spaces of materials can encompass both known and hypothetical compounds. When hypothetical compounds are explored, it becomes crucial to determine which ones are stable (and can be synthesized) and which are not. Crystal structure prediction is a necessary step for assessing theoretically the stability of a hypothetical material and, therefore, is a crucial step in inverse materials design protocols. Here, we describe how biologicallyinspired global optimization methods can efficiently predict the stable crystal structure of solids. Specifically, we discuss the application of genetic algorithms to search for optimal atom configurations in systems in which the underlying lattice is given, and of evolutionary algorithms to address the general latticetype prediction problem. 
References
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