Conceptual, self-assembling graphene nanocontainers

We show that graphene nano-sheets, when appropriately functionalised, can form self-assembling nanocontainers which may be opened or closed using a chemical trigger such as pH or polarity of solvent. Conceptual design rules are presented for different container structures, whose ability to form and encapsulate guest molecules is verified by molecular dynamics simulations. The structural simplicity of the graphene nanocontainers offers considerable scope for scaling the capacity, modulating the nature of the internal environment, and defining the trigger for encapsulation or release of the guest molecule(s). This design study will serve to provide additional impetus to developing synthetic approaches for selective functionalisation of graphene

Active Self-Assembly of Algorithmic Shapes and Patterns in Polylogarithmic Time

We describe a computational model for studying the complexity of self-assembled structures with active molecular components. Our model captures notions of growth and movement ubiquitous in biological systems. The model is inspired by biology's fantastic ability to assemble biomolecules that form systems with complicated structure and dynamics, from molecular motors that walk on rigid tracks and proteins that dynamically alter the structure of the cell during mitosis, to embryonic development where large-scale complicated organisms efficiently grow from a single cell. Using this active self-assembly model, we show how to efficiently self-assemble shapes and patterns from simple monomers. For example, we show how to grow a line of monomers in time and number of monomer states that is merely logarithmic in the length of the line. Our main results show how to grow arbitrary connected two-dimensional geometric shapes and patterns in expected time that is polylogarithmic in the size of the shape, plus roughly the time required to run a Turing machine deciding whether or not a given pixel is in the shape. We do this while keeping the number of monomer types logarithmic in shape size, plus those monomers required by the Kolmogorov complexity of the shape or pattern. This work thus highlights the efficiency advantages of active self-assembly over passive self-assembly and motivates experimental effort to construct general-purpose active molecular self-assembly systems

Self-assembling knots of controlled topology by designing the geometry of patchy templates

Self-assembling of complex molecular structures with a target topology is of importance to design and synthesize functional materials. Here, Polles et al. demonstrate the spontaneous formation of closed knotted structures from simple helical building blocks with sticky ends in simulations

Coarse-grained models for self-assembling systems

In the last years, a considerable deal of work has so far been spent to understand and hence harness the physical principles that underpin the general properties of self-assembling systems. In particular, theoretical and computational modelling have been extensively used to obtain a detailed description of the actual process. This thesis reports on computational work, focusing on two different self-assembling systems and from two distinct perspectives. In the first part, a computational study of the self-assembly of string-like rigid templates in solution aims to explore to what extent it is possible to direct the assembly of the templates into knotted or linked structures by suitably tuning geometrical parameters of the system. The second part is devoted to some of the smallest instances of molecular self-assembly in nature, that is viral capsids. We report on the development of a physics-based algorithm to subdivide the structure of a capsid in quasi-rigid units, helping to elucidate the pathway of assembly from the identification of its building blocks with a top-down approach