Simulation of Self-Assembly

The assembly of nanoscale materials and devices with useful structural, mechanical and electrical properties presents a great challenge for the future. A very promising approach is offered by self-assembly processes, in which nanoscopic or colloidal building blocks combine spontaneously to form ordered structures. While top-down approaches to assembly become increasingly challenging on small length scales, self-assembly offers a bottom-up approach which circumvents many of these difficulties.Biological systems display an astonishing variety of ordered and precise self-assembly processes. For example, the process of virus replication involves the assembly of hundreds of proteins to form highly symmetric shells called capsids. Such systems provide inspiring examples of the level of control possible in self-assembly. Future applications in nanotechnology are likely to require this level of sophisticated control in order to form precisely ordered structures, with specific chemical and physical properties of technological importance.To achieve such targets will require not only experimental advances in the synthesis of the building blocks for self-assembly, but also a deep theoretical understanding of the fundamental principles of self-assembly and the design rules for creating new self-assembling materials with useful structural, electronic, or optoelectronic properties. Computer simulation provides the tools for discovering these design principles, for example through direct visualization of the microscopic mechanisms of self-assembly. However, in many cases there is a large gap in length and time scales between the systems it is feasible to study computationally, and those of interest to experimentalists. The principal aim of the current project is to develop a variety of new computational tools that are required to overcome these obstacles to simulating self-assembly, and to apply them to understand the structures, thermodynamics and dynamics of both biological and synthetic self-assembling systems. To this end, we have assembled an experienced team with complementary research skills in the fields of structure analysis and optimisation, development of potential and free energy models, dynamics, thermodynamics, landscape analysis and visualisation.Our project involves several interdependent themes. One key aim is to understand and control size selection for self-assembling shells, helices and other interesting morphologies, including knotted topologies. Here we will employ direct simulation, and seek to explain the observed behaviour using a new method for visualising the complex landscape corresponding to favourable structures, kinetic traps, and the pathways that link them. We will combine two existing methods for studying rare events to exploit the best features of each one in a hybrid approach, where geometry optimisation is used to identify the pathways, and reaction rates are evaluated accurately using detailed dynamics. We also aim to simulate nucleation and crystallisation of bulk phases with interesting structures, which might exhibit novel properties of technological importance. Here we would predict the organisation of bulk phases along with the corresponding phase diagrams. A key objective of this project is to predict suitable building blocks for self-assembly of structures with specific properties at a coarse-grained level. By discovering the critical interparticle forces that determine the outcome of the self-assembly process we will guide new experiments. Here we need to define parameters such as the shape of the particles and the way they bind together. We will also investigate hierarchical self-assembly, where structures that form in the first step are used as the building blocks for subsequent steps in the creation of even larger and potentially more complex materials. This investigation will suggest experimental routes to multi-component nanoscale structures.