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Chemistry - Theoretical and Computational Chemistry | Computational Characterisation of Gold Nanocluster Structures

Computational Characterisation of Gold Nanocluster Structures

Series: Springer Theses

Logsdail, Andrew James

2013, XVI, 209 p. 99 illus., 84 illus. in color.

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  • Nominated as an Outstanding Ph.D. thesis by the University of Birmingham, UK
  • Presents a detailed analysis of structural preferences in monometallic and bimetallic gold nanoclusters
  • Characterises the optical properties of gold-based bimetallic nanoparticles with varying morphologies
In this thesis, Andrew Logsdail demonstrates that computational chemistry is a powerful tool in contemporary nanoscience, complementing experimental observations and helping guide future experiments. The aim of this particular PhD is to further our understanding of structural and compositional preferences in gold nanoparticles, as well as the compositional and chemical ordering preferences in bimetallic nanoalloys formed with other noble metals, such as palladium and platinum. Highlights include: calculations of the structural preferences and optical-response of gold nanoparticles and gold-containing nanoalloys; the design and implementation of novel numerical algorithms for the structural characterisation of gold nanoparticles from electron microscopy images; and electronic structure calculations investigating the interaction of gold nanoparticles with graphene and graphite substrates.The results presented here have significant implications for future research on the chemical and physical properties of gold-based nanoparticles and are of interest to many researchers working on experimental and theoretical aspects of nanoscience.

Content Level » Research

Keywords » Carbon Graphite Supported Gold - Genetic Algorithm - Gold Clusters - Gold Nanoclusters - Gold Nanoparticles - Nanoclusters - Optical Properties of Gold Nanoparticles - Search Algorithm - Structural Properties of Gold Nanoclusters

Related subjects » Catalysis - Chemistry - Theoretical and Computational Chemistry

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