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Title: Simulation studies of monodisperse self-assembly
Author: Wilber, Alex W.
ISNI:       0000 0004 2694 6398
Awarding Body: University of Oxford
Current Institution: University of Oxford
Date of Award: 2009
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The processes by which anisotropic colloidal and nanoscale particles may come together to form ordered monodisperse structures are not well understood. The canonical example of such a system is provided by the assembly of virus capsids, in which tens to thousands of particles of one or a few types assemble efficiently into ordered, highly symmetrical shells. Other examples include a wide variety of protein oligomers, and there is interest in producing analogous systems of synthetic particles. In this thesis I study the self-assembly of simple model particles, consisting of spheres decorated with attractive patches. I consider in detail the assembly of clusters of particles corresponding to the Platonic solids. For the majority of these structures assembly is found to be efficient over a wide range of parameter space. The optimal conditions represent a compromise between thermodynamic stability and kinetic accessibility. We consider two versions of the model, with and without constraints on the torsion angle of bound particles. In both cases the structures with triangular faces are found to assemble most easily. In the absence of torsional constraints dodecahedra will not assemble under any set of parameters as a result of the preferential formation of disordered aggregates. With torsional constraints included all of the Platonic solids assemble successfully and the behaviour of the model is considerably changed. In particular disordered aggregates become far less favourable. I explore possible methods of assembling larger structures, either via “hierarchical” assembly where small clusters are first assembled and then used as building blocks in another stage of assembly, or by a templating method in which an inner cluster acts as a template for a larger outer cluster. These approaches are studied using the “Virtual Move Monte Carlo” cluster move algorithm, the behaviour of which we examine in some detail.
Supervisor: Doye, Jonathan P. K. ; Louis, Ard A. Sponsor: Engineering and Physical Sciences Research Council
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: Computational chemistry ; Physical & theoretical chemistry ; Biophysics ; Disease (zoology) ; Self-assembly ; monodisperse ; virus ; simulation ; Monte Carlo