KINETIC MONTE CARLO SIMULATION OF THE GROWTH OF GOLD NANOSTRUCTURES ON A GRAPHITE SUBSTRATE

Nanotechnology has, without a doubt, ushered in a new era of technological convergence and holds the promise of making a profound impact on the way research in physics, chemistry, materials science, biotechnology etc. are conducted. The novel properties of materials at the nanoscale (or nanostructur...

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Bibliographic Details
Main Author: Claassens, Christina Hester
Other Authors: Dr MJH Hoffman
Format: Others
Language:en-uk
Published: University of the Free State 2007
Subjects:
Online Access:http://etd.uovs.ac.za//theses/available/etd-09252007-132432/restricted/
Description
Summary:Nanotechnology has, without a doubt, ushered in a new era of technological convergence and holds the promise of making a profound impact on the way research in physics, chemistry, materials science, biotechnology etc. are conducted. The novel properties of materials at the nanoscale (or nanostructures) make them useful in a variety of applications, from catalysis to the medical field and electronics industry. However, to exploit these properties at the nanoscale, precise control over the morphology and size of nanostructures is required. One strategy that may be explored to tailor nanostructure morphology and size is vapour deposition. A lot of further insight can be gained from computer simulations of the processes governing the growth of nanostructures during vapour deposition. A method that shows promise in simulating thin film growth through vapour deposition is kinetic Monte Carlo (KMC). Therefore, in this study, a KMC model was developed to describe growth through vapour deposition. A gold on graphite system was simulated to test the model. In this KMC model, substantial effort was devoted to developing the model in different stages, each stage being more robust than the previous one. The assumptions made at each stage and possible artefacts (unphysical consequences) arising from them are discussed in order to distinguish real physical effects from artificial ones. In the model, data structures, search algorithms and a random number generator were developed and employed in an object-orientated code to simulate the growth. Several simulations were performed at different growth conditions for each of the stages. The results are interpreted based on the kinetic constraints imposed during the growth.