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Evolution of electronic and vibrational properties of M@Xn (M = Ag, Au, X = Ge, Si, n = 10, 12, 14) clusters: a density functional modeling

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dc.contributor.author Bandyopadhyay, Debashis
dc.date.accessioned 2024-02-08T11:00:26Z
dc.date.available 2024-02-08T11:00:26Z
dc.date.issued 2018-03
dc.identifier.uri https://link.springer.com/article/10.1007/s10853-018-2002-4
dc.identifier.uri http://dspace.bits-pilani.ac.in:8080/jspui/xmlui/handle/123456789/14128
dc.description.abstract Evolution of electronic and vibrational properties of M@Xn (M = Ag, Au, X = Ge, Si, n = 10, 12, 14) nanoclusters is investigated by using first-principle density functional theory (DFT)-based calculations with effective core potentials. To explain the thermodynamic and chemical stability of the ground state cluster in each size, variation of different thermodynamic and chemical parameters, like, binding energy (BE), HOMO–LUMO gap (ΔE), vertical ionization potential (VIP) and vertical electron affinity (VEA) was studied with the variation of the size of the clusters for emphasizing the differences and similarities in the clusters. It is found that Au doping in Ge and Si cages prefers endohedral position, whereas Ag prefers to take the position at the surface of the cages. In addition, IR and Raman spectra of the clusters are also studied to understand the vibrational nature of the stable clusters. At the end, present theoretical results are compared with existing experimental data. Theoretical knowledge of the thermodynamic, chemical and vibrational properties of these specific ground state structures is important for understanding its potential application in the field of optoelectronic science. en_US
dc.language.iso en en_US
dc.publisher Springer en_US
dc.subject Physics en_US
dc.subject Vertical ionization potential (VIP) en_US
dc.subject Vertical electron affinity (VEA) en_US
dc.subject Thermodynamics en_US
dc.title Evolution of electronic and vibrational properties of M@Xn (M = Ag, Au, X = Ge, Si, n = 10, 12, 14) clusters: a density functional modeling en_US
dc.type Article en_US


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