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Structural exploration of Au(x)M(−) (M = Si, Ge, Sn; x = 9–12) clusters with a revised genetic algorithm
We used a revised genetic algorithm (GA) to explore the potential energy surface (PES) of Au(x)M(−) (x = 9–12; M = Si, Ge, Sn) clusters. The most interesting finding in the structural study of Au(x)Si(−) (x = 9–12) is the 3D (Au(9)Si(−) and Au(10)Si(−)) → quasi-planar 2D (Au(11)Si(−) and Au(12)Si(−)...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Royal Society of Chemistry
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9061163/ https://www.ncbi.nlm.nih.gov/pubmed/35519983 http://dx.doi.org/10.1039/c9ra01019j |
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author | Huang, Ping Jiang, Yan Liang, Tianquan Wu, Enhui Li, Jun Hou, Jing |
author_facet | Huang, Ping Jiang, Yan Liang, Tianquan Wu, Enhui Li, Jun Hou, Jing |
author_sort | Huang, Ping |
collection | PubMed |
description | We used a revised genetic algorithm (GA) to explore the potential energy surface (PES) of Au(x)M(−) (x = 9–12; M = Si, Ge, Sn) clusters. The most interesting finding in the structural study of Au(x)Si(−) (x = 9–12) is the 3D (Au(9)Si(−) and Au(10)Si(−)) → quasi-planar 2D (Au(11)Si(−) and Au(12)Si(−)) structural evolution of the Si-doped clusters, which reflects the competition of Au–Au interactions (forming a 2D structure) and Au–Si interactions (forming a 3D structure). The Au(x)M(−) (x = 9–12; M = Ge, Sn) clusters have quasi-planar structures, which suggests a lower tendency of sp(3) hybridization and a similarity of electronic structure for the Ge or Sn atom. Au(9)Si(−) and Au(10)Si(−) have a 3D structure, which can be viewed as being built from Au(8)Si(−) and Au(9)Si(−) with an extra Au atom bonded to a terminal gold atom, respectively. In contrast, the quasi-planar structures of Au(x)M(−) (x = 9–12; M = Ge, Sn) reflect the domination of the Au–Au interactions. Including the spin–orbit (SO) effects is very important to calculate the simulated spectrum (structural fingerprint information) in order to obtain quantitative agreement between theoretical and future experimental PES spectra. |
format | Online Article Text |
id | pubmed-9061163 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | The Royal Society of Chemistry |
record_format | MEDLINE/PubMed |
spelling | pubmed-90611632022-05-04 Structural exploration of Au(x)M(−) (M = Si, Ge, Sn; x = 9–12) clusters with a revised genetic algorithm Huang, Ping Jiang, Yan Liang, Tianquan Wu, Enhui Li, Jun Hou, Jing RSC Adv Chemistry We used a revised genetic algorithm (GA) to explore the potential energy surface (PES) of Au(x)M(−) (x = 9–12; M = Si, Ge, Sn) clusters. The most interesting finding in the structural study of Au(x)Si(−) (x = 9–12) is the 3D (Au(9)Si(−) and Au(10)Si(−)) → quasi-planar 2D (Au(11)Si(−) and Au(12)Si(−)) structural evolution of the Si-doped clusters, which reflects the competition of Au–Au interactions (forming a 2D structure) and Au–Si interactions (forming a 3D structure). The Au(x)M(−) (x = 9–12; M = Ge, Sn) clusters have quasi-planar structures, which suggests a lower tendency of sp(3) hybridization and a similarity of electronic structure for the Ge or Sn atom. Au(9)Si(−) and Au(10)Si(−) have a 3D structure, which can be viewed as being built from Au(8)Si(−) and Au(9)Si(−) with an extra Au atom bonded to a terminal gold atom, respectively. In contrast, the quasi-planar structures of Au(x)M(−) (x = 9–12; M = Ge, Sn) reflect the domination of the Au–Au interactions. Including the spin–orbit (SO) effects is very important to calculate the simulated spectrum (structural fingerprint information) in order to obtain quantitative agreement between theoretical and future experimental PES spectra. The Royal Society of Chemistry 2019-03-06 /pmc/articles/PMC9061163/ /pubmed/35519983 http://dx.doi.org/10.1039/c9ra01019j Text en This journal is © The Royal Society of Chemistry https://creativecommons.org/licenses/by-nc/3.0/ |
spellingShingle | Chemistry Huang, Ping Jiang, Yan Liang, Tianquan Wu, Enhui Li, Jun Hou, Jing Structural exploration of Au(x)M(−) (M = Si, Ge, Sn; x = 9–12) clusters with a revised genetic algorithm |
title | Structural exploration of Au(x)M(−) (M = Si, Ge, Sn; x = 9–12) clusters with a revised genetic algorithm |
title_full | Structural exploration of Au(x)M(−) (M = Si, Ge, Sn; x = 9–12) clusters with a revised genetic algorithm |
title_fullStr | Structural exploration of Au(x)M(−) (M = Si, Ge, Sn; x = 9–12) clusters with a revised genetic algorithm |
title_full_unstemmed | Structural exploration of Au(x)M(−) (M = Si, Ge, Sn; x = 9–12) clusters with a revised genetic algorithm |
title_short | Structural exploration of Au(x)M(−) (M = Si, Ge, Sn; x = 9–12) clusters with a revised genetic algorithm |
title_sort | structural exploration of au(x)m(−) (m = si, ge, sn; x = 9–12) clusters with a revised genetic algorithm |
topic | Chemistry |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9061163/ https://www.ncbi.nlm.nih.gov/pubmed/35519983 http://dx.doi.org/10.1039/c9ra01019j |
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