Probing the structural, electronic and magnetic properties of AgnSc (n = 1-16) clusters

The structural, electronic and magnetic properties of Ag n Sc ( n = 1-16) clusters have been studied on the basis of density functional theory and the CALYPSO structure prediction method. The optimized geometry exhibits that the growth process of Sc-doped silver clusters have a periodic structural c...

Full description

Saved in:
Bibliographic Details
Published inPhysical chemistry chemical physics : PCCP Vol. 2; no. 23; pp. 15824 - 15834
Main Authors Xiong, Ran, Die, Dong, Xu, Yong-Gen, Zheng, Ben-Xia, Fu, Yao-Chun
Format Journal Article
LanguageEnglish
Published Cambridge Royal Society of Chemistry 01.01.2018
Subjects
Online AccessGet full text

Cover

Loading…
More Information
Summary:The structural, electronic and magnetic properties of Ag n Sc ( n = 1-16) clusters have been studied on the basis of density functional theory and the CALYPSO structure prediction method. The optimized geometry exhibits that the growth process of Sc-doped silver clusters have a periodic structural change. The Ag atom grows around a basically invariant cluster core in each growth cycle. The Sc atom has a tendency to occupy the most highly coordinated position in the ground state. The infrared spectra, Raman spectra and photoelectron spectra of Ag n Sc clusters are forecasted and can be used to identify the structures of these clusters from experiments. The global maxima of the dissociation energy, the averaged binding energy and the gap of the energy level occur at n = 15 for the most stable Ag n Sc clusters, implying that the Ag 15 Sc can be perceived as a superatom. The magnetism analysis indicates that the magnetic moment of the Sc atom in Ag n Sc clusters decreases with the increase of the cluster. The change of the magnetic moment is proportional to the charge transfer between the Sc and Ag atoms. The structural, electronic and magnetic properties of Ag n Sc ( n = 1-16) clusters have been studied on the basis of density functional theory and the CALYPSO structure prediction method.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:1463-9076
1463-9084
DOI:10.1039/c8cp02605j