Michael Patrick Allen

Active matter systems may be characterized by the conversion of energy into active motion, e.g., the self-propulsion of microorganisms. Artificial active colloids form models that exhibit essential properties of more complex biological systems but are amenable to laboratory experiments. While most experimental models consist of spheres, active particles of different shapes are less understood. Furthermore, interactions between these anisotropic active colloids are even less explored. Here, we investigate the motion of active colloidal clusters and the interactions between them. We focus on self-assembled dumbbells and trimers powered by an external dc electric field. For dumbbells, we observe an activity-dependent behavior of spinning, circular, and orbital motions. Moreover, collisions between dumbbells lead to the hierarchical self-assembly of tetramers and hexamers, both of which form rotational excited states. On the other hand, trimers exhibit flipping motion that leads to trajectories reminiscent of a honeycomb lattice.

This impressive book gives a comprehensive account of the science of liquid crystals, from the microscopic, molecular, viewpoint. As the author explains in the preface, there is a gap in the field ...

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This article reviews recent progress in the computer simulation of liquid crystals at the molecular level. It covers the use of simple rigid-body models of the constituent molecules, and more detailed modelling via atomistic force fields. Bulk mesophases, inhomogeneous systems, and interfaces are discussed. Recent progress in calculating elastic properties and dynamics is summarised. As well as presenting an overview, some specific topics of recent interest are highlighted: the biaxial nematic phase, chiral phases, ionic liquid crystals, and charge-transfer systems.

We present the results of an aggregation study on the intrinsically disordered biomineralisation peptide n16N, which selects the aragonite polymorph of calcium carbonate and is expected to have aggregation-dependent structure and function. The peptide is a sub-sequence of the in vivo protein n16, with putative framework and polymorph selection roles in the nacre layer of pearl oyster (Pinctada fucata). Employing the intermediate-resolution coarse-grained protein model PLUM*, which has previously been validated with respect to n16N, we simulate assemblies of these peptide units for system sizes inaccessible to atomistic models. We use extensive conformational sampling to show that the configurational ensemble explored by n16N aggregates contains a significant proportion of ordered -structure, within which arrangement of monomers is consistent with a previous hypothesis on functionally distinct subdomains of n16N. We also study an n16N mutant which fails to aggregate in experimental studies and obtain very similar behaviour, the consequences of which are discussed.

This chapter contains the essential statistical mechanics required to understand the inner workings of, and interpretation of results from, computer simulations. The microcanonical, canonical, isothermal–isobaric, semigrand and grand canonical ensembles are defined. Thermodynamic, structural, and dynamical properties of simple and complex liquids are related to appropriate functions of molecular positions and velocities. A number of important thermodynamic properties are defined in terms of fluctuations in these ensembles. The effect of the inclusion of hard constraints in the underlying potential model on the calculated properties is considered, and the addition of long-range and quantum corrections to classical simulations is presented. The extension of statistical mechanics to describe inhomogeneous systems such as the planar gas–liquid interface, fluid membranes, and liquid crystals, and its application in the simulation of these systems, are discussed.

Parallelization is essential for the effective use of modern high-performance computing facilities. This chapter summarizes some of the basic approaches that are commonly used in molecular simulation programs. The underlying shared-memory and distributed-memory architectures are explained. The concept of program threads and their use in parallelizing nested loops on a shared memory machine is described. Parallel tempering using message passing on a distributed memory machine is discussed and illustrated with an example code. Domain decomposition, and the implementation of constraints on parallel computers, are also explained.

This chapter describes the ways in which the Monte Carlo importance sampling method may be adapted to improve the calculation of ensemble averages, particularly those associated with free energy differences. These approaches include umbrella sampling, non-Boltzmann sampling, the Wang–Landau method, and nested sampling. In addition, a range of special techniques have been developed to accelerate the simulation of flexible molecules, such as polymers. These approaches are illustrated with scientific examples and program code. The chapter also explains the analysis of such simulations using techniques such as weighted histograms, and acceptance ratio calculations. Practical advice on selection of methods, parameters, and the direction in which to make comparisons, are given. Monte Carlo methods for modelling phase equilibria and chemical reactions at equilibrium are described.

This chapter explains some of the fundamental issues associated with applying perturbations to a molecular dynamics simulation, along with practical details of methods for studying systems out of equilibrium. The main emphasis is on fluid flow and viscosity measurements. Spatially homogeneous perturbations are described to study shear and extensional flow. Non-equilibrium methods are applied to the study of heat flow and the calculation of the thermal conductivity. Issues of thermostatting, and the modelling of surface-fluid interactions for inhomogeneous systems, are discussed. The measurement of free energy changes through non-equilibrium work expressions such as those of Jarzynski and Crooks is also explained.