Simulation of reconstructions of the polar ZnO (0001) surfaces

Surface reconstructions on the polar ZnO(0001) surface are investigated using empirical potential models. Several possible reconstructions based around triangular motifs are investigated. The quenching of the dipole moment in the material dominates the energetics of the surface patterns so that no one particular size of surface triangular island or pit is strongly favoured. We employ Monte Carlo simulations to explore which patterns emerge from a high temperature quench and during deposition of additional ZnO monolayers. The simulations show that a range of triangular islands and pits evolve in competition with one another. The surface patterns we discover are qualitatively similar to those observed experimentally

Characterising submonolayer deposition via visibility graphs

We use visibility graphs as a tool to analyse the results of kinetic Monte Carlo (kMC) simulations of submonolayer deposition in a one-dimensional point island model. We introduce an efficient algorithm for the computation of the visibility graph resulting from a kMC simulation and show that from the properties of the visibility graph one can determine the critical island size, thus demonstrating that the visibility graph approach, which implicitly combines size and spatial data, can provide insights into island nucleation and growth processes

Fibronectin module FNIII9 adsorption at contrasting solid model surfaces studied by atomistic molecular dynamics

The mechanism of human fibronectin adhesion synergy region (known as integrin binding region) in repeat 9 (FNIII9) domain adsorption at pH 7 onto various and contrasting model surfaces has been studied using atomistic molecular dynamics simulations. We use an ionic model to mimic mica surface charge density but without a long-range electric field above the surface, a silica model with a long-range electric field similar to that found experimentally, and an Au {111} model with no partial charges or electric field. A detailed description of the adsorption processes and the contrasts between the various model surfaces is provided. In the case of our model silica surface with a long-range electrostatic field, the adsorption is rapid and primarily driven by electrostatics. Because it is negatively charged (?1e), FN III9 readily adsorbs to a positively charged surface. However, due to its partial charge distribution, FNIII9 can also adsorb to the negatively charged mica model because of the absence of a long-range repulsive electric field. The protein dipole moment dictates its contrasting orientation at these surfaces, and the anchoring residues have opposite charges to the surface. Adsorption on the model Au {111} surface is possible, but less specific, and various protein regions might be involved in the interactions with the surface. Despite strongly influencing the protein mobility, adsorption at these model surfaces does not require wholesale FNIII9 conformational changes, which suggests that the biological activity of the adsorbed protein might be preserved

Multi-scale chemistry modelling for spacecraft atmospheric re-entry

We aim to develop a model capable of simulating the surface chemistry and material erosion involved when a re-entry vehicle descends through the atmosphere. Our starting point is to simulate the erosion of a fcc crystal slab due to cluster bombardment, using the model Lennard-Jones potential. From this, we plan to scale up towards Direct Monte Carlo Simulation approaches for the gas dynamics above the surface

How negatively charged proteins adsorb to negatively charged surfaces - a molecular dynamics study of BSA adsorption on silica

How proteins adsorb to inorganic material surfaces is critically important for the development of new biotechnologies, since the orientation and structure of the adsorbed proteins impacts their functionality. Whilst it is known that many negatively charged proteins readily adsorb to negatively charged oxide surfaces, a detailed understanding of how this process occurs is lacking. In this work we study the adsorption of BSA, an important transport protein that is negatively charged at physiological conditions, to a model silica surface that is also negatively charged. We use fully atomistic Molecular Dynamics to provide detailed understanding of the non-covalent interactions that bind the BSA to the silica surface. Our results provide new insight into the competing roles of long-range electrostatics and short-range forces, and the consequences this has for the orientation and structure of the adsorbed proteins

Modelling organic gel growth in three-dimensions : textural and fractal properties of resorcinol-formaldehyde gels

Tailoring the properties of porous organic materials, such as resorcinol–formaldehyde gels, for use in various applications has been a central focus for many studies in recent years. In order to achieve effective optimisation for each application, this work aims to assess the impact of the various synthesis parameters on the final textural properties of the gel. Here, the formation of porous organic gels is modelled using a three-dimensional lattice-based Monte Carlo simulation. We model growth from monomer species into the interconnected primary clusters of a gel, and account for varying catalyst concentration and solids content, two parameters proven to control gel properties in experimental work. In addition to analysing the textural properties of the simulated materials, we also explore their fractal properties through correlation dimension and Hurst exponent calculations. The correlation dimension shows that while fractal properties are not typically observed in scattering experiments, they are possible to achieve with sufficiently low solids content and catalyst concentration. Furthermore, fractal properties are also apparent from the analysis of the diffusion path of guest species through the gel’s porous network. This model, therefore, provides insight into how porous organic gels can be manufactured with their textural and fractal properties computationally tailored according to the intended application

Steering protein adsorption at charged surfaces : electric fields and ionic screening

Protein adsorption at charged surfaces is a common process in the development of functional technological devices. Accurately reproducing the environment above the surface in simulations is essential for understanding how the adsorption process can be influenced and utilised. Here we present a simulation strategy that includes the electric field above the charged surface as well as the screening ions in solution, using standard molecular dynamics tools. With this approach we investigate the adsorption of Hen Egg White Lysozyme (HEWL) onto a model charged silica surface. We find that the screening effects of the ions slow down the adsorption process, giving the protein more time to find its optimal orientation as it adsorbs. Furthermore, we find that the concentrated ionic region directly above the surface helps to stabilise the protein structure in its adsorbed state. Together these effects imply that the adsorbed HEWL might retain its biological activity, with its active site exposed to solution rather than to the surface. Furthermore, this work shows how the steering effects of the electric field, coupled to the ionic screening, might be used to develop general strategies for surface functionalization through protein adsorption for technological applications

On linear growth in COVID-19 cases

We present an elementary model of COVID-19 propagation that makes explicit the connection between testing strategies and rates of transmission and the linear growth in new cases observed in many parts of the world

Scaling of glycine nucleation kinetics with shear rate and glass-liquid interfacial area

The scaling of the nucleation kinetics of glycine was investigated in supersaturated aqueous solutions under isothermal conditions. Induction times were measured in a Couette cell with a wide range of average shear rates γ_avg (25-250 s^-1) and a range of glass-liquid interfacial areas A (2.5-10 cm^2 per ml solution). The probability distributions of induction times were found to scale with shear rate and glass-liquid interfacial area, with the characteristic timescale (γ_avg.A)^-1. Primary nucleation rates and growth times to reach detection (estimated from the probability distributions) were both dependent on this timescale. In-situ dynamic light scattering revealed mesoscale clusters in the solutions that increased in size over time at rates which also depended on this timescale. The increase in size was thought to be due to the shear-enhanced aggregation or coalescence of mesoscale clusters leading to a higher number of larger mesoscale clusters, resulting in higher rates of primary nucleation

Vaccination, asymptomatics and public health information in COVID-19

The dynamics of the COVID-19 pandemic are greatly influenced by vaccine quality, as well as by vaccination rates and the behaviour of infected individuals, both of which reflect public policy. We develop a model for the dynamics of relevant cohorts within a fixed population, taking extreme care to model the reduced social contact of infected individuals in a rigorous self-consistent manner. The basic reproduction number R0is then derived in terms of the parameters of the model. Analysis of R0 reveals two interesting possibilities, both of which are plausible based on known characteristics of COVID-19. Firstly, if the population in general moderates social contact, while infected individuals who display clinical symptoms tend not to isolate, then increased vaccination can drive the epidemic towards a disease-free equilibrium (DFE). However, if the reverse is true, then increased vaccination can destabilise the DFE and yield an endemic state. This surprising result is due to the fact that the vaccines are leaky, and can lead to an increase in asymptomatic individuals who unknowingly spread the disease. Therefore, this work shows that public policy regarding the monitoring and release of health information should be combined judiciously with vaccination policy to control COVID-19