Firefly Algorithm for Structural Search

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• 作者：Guillermo Avendaño-Franco ; Aldo H. Romero
• 刊名：Journal of Chemical Theory and Computation
• 出版年：2016
• 出版时间：July 12, 2016
• 年：2016
• 卷：12
• 期：7
• 页码：3416-3428
• 全文大小：740K
• 年卷期：0
• ISSN：1549-9626

文摘

The problem of computational structure prediction of materials is approached using the firefly (FF) algorithm. Starting from the chemical composition and optionally using prior knowledge of similar structures, the FF method is able to predict not only known stable structures but also a variety of novel competitive metastable structures. This article focuses on the strengths and limitations of the algorithm as a multimodal global searcher. The algorithm has been implemented in software package PyChemia (href="https://github.com/MaterialsDiscovery/PyChemia" class="extLink">https://github.com/MaterialsDiscovery/PyChemia), an open source python library for materials analysis. We present applications of the method to van der Waals clusters and crystal structures. The FF method is shown to be competitive when compared to other population-based global searchers.