Structural exploration of AuxM− (M = Si, Ge, Sn; x = 9–12) clusters with a revised genetic algorithm-Reference-Cited by-同舟云学术

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Structural exploration of AuxM− (M = Si, Ge, Sn; x = 9–12) clusters with a revised genetic algorithm

Published:2019 Issue:13 Volume:9 Page:7432-7439
ISSN:2046-2069
Container-title:RSC Advances
language:en
Short-container-title:RSC Adv.

Author:

Huang Ping¹²³⁴,Jiang Yan¹²³⁴^ORCID,Liang Tianquan⁵⁶⁷⁴,Wu Enhui¹²³⁴,Li Jun¹²³⁴,Hou Jing⁸²³⁴

Affiliation:

1. Panzhihua International Research Institute of Vanadium and Titanium

2. Panzhihua University

3. Panzhihua 617000

4. People's Republic of China

5. College of Environment and Planning

6. Liaocheng University

7. Liaocheng 252059

8. College of Vanadium and Titanium

Abstract

We used a revised genetic algorithm (GA) to explore the potential energy surface (PES) of Au_xM⁻ (x = 9–12; M = Si, Ge, Sn) clusters.

Funder

National Natural Science Foundation of China

Publisher

Royal Society of Chemistry (RSC)

Subject

General Chemical Engineering,General Chemistry

Link

http://pubs.rsc.org/en/content/articlepdf/2019/RA/C9RA01019J

Reference69 articles.

1. Size- and support-dependency in the catalysis of gold

2. Ultraviolet photoelectron spectra of coinage metal clusters

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4. Structure determination of gaseous metal and semi-metal cluster ions by ion mobility spectrometry

5. Structure Determination of Isolated Metal Clusters via Far-Infrared Spectroscopy

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3. Understanding the geometric structure, electronic and stability properties of anionic germanium-doped magnesium clusters: Gas-phase GeMgn− (n = 2–12) DFT study;Computational Materials Science;2022-07

4. A new active learning approach for global optimization of atomic clusters;Theoretical Chemistry Accounts;2021-05-17

5. Global optimization of copper clusters at the ZnO(101¯0) surface using a DFT-based neural network potential and genetic algorithms;The Journal of Chemical Physics;2020-08-07

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