期刊
JOURNAL OF PHYSICAL CHEMISTRY A
卷 112, 期 28, 页码 6257-6261出版社
AMER CHEMICAL SOC
DOI: 10.1021/jp802118j
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We propose a multiscale method to explore the energy landscape of water clusters. An asynchronous genetic algorithm is employed to explore the potential energy surface (PES) of OSS2 and TTM2.1-F models. Local minimum structures are collected on the fly, and the ultrafast shape recognition algorithm was used to remove duplicate structures. These structures are then refined at the B3LYP/6-31+G* level. The number of distinct local minima we found (21, 76, 369, 1443, and 3563 isomers for n = 4-8, respectively) reflects the complexity of the PES of water clusters.
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