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Title: Optimising the design of building blocks for self-assembly of discrete clusters
Author: Madge, Jim
ISNI:       0000 0004 6497 1922
Awarding Body: Durham University
Current Institution: Durham University
Date of Award: 2017
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Self-assembly is the spontaneous organisation of matter into an ordered state. Significant progress has been made in the fabrication of synthetic components for self-assembly, opening up routes to building blocks for the production of functional materials and nanomachines. The information required to assemble a target structure can be encoded into the building blocks. For assembly of an equilibrium state, the target must be thermodynamically stable and the pathway must avoid kinetic traps. The design of building blocks must address both these requirements. In this work a generic model is introduced which, through an explicit representation of interactions, is able to express many approaches to self-assembly. The model consists of hard cubic particles, whose faces are patterned with attractive patches. A hybrid, dynamical Monte Carlo protocol is developed to simulate self-assembly of such inhomogeneous systems efficiently, accounting for both internal rearrangements and relative diffusion rates of aggregates. Using this single model, different self-assembly strategies are assessed, ranging from simple approaches with only one type of building block, to more complex strategies using multiple components and hierarchical paths. The important case of fully addressable targets, where all components of the structure are unique and have a specific location, is then examined in more detail. Firstly, a new metric is introduced to quantify the problem of competition between partly assembled fragments, which is a prominent source of kinetic traps in addressable clusters. Principles are established for minimising this problem. Secondly, a scheme for globally optimising the interactions amongst a set of particles is developed to maximise the performance of building blocks of a given complexity. This also makes it possible to determine the level of complexity required for a given target to assemble reliably. The computational tools and general principles established in this work should be applicable in a wide range of self-assembly problems.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available