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TGMin: A global-minimum structure search program based on a constrained basin-hopping algorithm

delete2017-07-29
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Y
Ya‐Fan Zhao
X
Xin Chen
黎军 封面图
黎军 (Jun Li) *
DOI:10.1007/s12274-017-1553-zdelete
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摘要

摘要

En 中文
In this article, we introduce Tsinghua Global Minimum (TGMin) as a new program for the global minimum searching of geometric structures of gas-phase or surface-supported atomic clusters, and the constrained basin-hopping (BH) algorithm implemented in this program. To improve the efficiency of the BH algorithm, several types of constraints are introduced to reduce the vast search space, including constraints on the random displacement step size, displacement of low-coordination atoms, and geometrical structure adjustment after displacement. The ultrafast shape-recognition (USR) algorithm and its variants are implemented to identify duplicate structures during the global minimum search. In addition to the Metropolis acceptance criterion, we also implemented a morphology-based constraint that confines the global minimum search to a specific type of morphology, such as planar or non-planar structures, which offers a strict divide-and-conquer strategy for the BH algorithm. These improvements are implemented in the TGMin program, which was developed over the past decade and has been used in a number of publications. We tested our TGMin program on global minimum structural searches for a number of metal and main-group clusters including C-60, Au-20 and B-20 clusters. Over the past five years, the TGMin program has been used to determine the global minimum structures of a series of boron atomic clusters (such as [B-26](-), [B-28](-), [B-30](-), [B-35](-), [B-36](-), [B-39](-), [B-40](-), [MnB16](-), [CoB18](-), [RhB18](-), and [TaB20](-)), metal-containing clusters Li (n) (n = 3-20), Au-9(CO)(8) (+) and [Cr6O19](2-), and the oxide-supported metal catalyst Au-7/gamma-Al2O3, as well as other isolated and surface-supported atomic clusters. In this article we present the major features of TGMin program and show that it is highly efficient at searching for global-minimum structures of atomic clusters in the gas phase and on various surface supports.
Keyword:
basin hopping
ultrafast shape recognition
global minimum search
density functional theory
cluster
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Nano Research
IF:
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论文数:
7.4K
被引数:
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机构

T
tsinghua university
学者数:
11.9W
论文数: 10.0W
被引数: 137
C
chinese academy of sciences
学者数:
56.7W
论文数: 45.0W
被引数: 704
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