Anionic surfactant solutions under shear using dissipative particle dynamics.

We present a dissipative particle dynamics study of surfactant solutions under shear, which allows us to investigate their rheological properties. We consider a variety of concentrations and phase structures, including micellar solutions and liquid crystal phases. It is shown that the viscosity of micellar solutions increases as a function of concentration, in agreement with what is expected from experimental data.

Using Raman Spectroscopy and Molecular Dynamics to Study Conformation Changes of Sodium Lauryl Ether Sulfate Molecules.

A study using both Raman spectroscopy and molecular dynamics (MD) simulations was carried out for alkyl ethoxysulfate (AES) surfactants at various concentrations in solution. Direct comparison between experiment and simulation shows that the conformational changes observed in MD are in good agreement with those obtained via Raman spectroscopy. We show that there is an increase in the relative number of conformations with increasing concentration and illustrate the relationship between phase structure and molecular conformation, which is often speculated but difficult to confirm.

Studying the Structure of Sodium Lauryl Ether Sulfate Solutions Using Dissipative Particle Dynamics.

Sodium lauryl ether sulfate (SLES) is a common anionic surfactant used in a large number of personal care products. Commercial products typically contain a distribution in the number of ethoxy groups; despite this, there is limited existing work studying the effect of the ethoxy groups on the phase formation and structure. This is particularly important for the effect the structure has on the viscosity, an important consideration for commercial products.

Multi-objective optimisation of polymerase chain reaction continuous flow systems.

A surrogate-enabled multi-objective optimisation methodology for a continuous flow Polymerase Chain Reaction (CFPCR) systems is presented, which enables the effect of the applied PCR protocol and the channel width in the extension zone on four practical objectives of interest, to be explored. High fidelity, conjugate heat transfer (CHT) simulations are combined with Machine Learning to create accurate surrogate models of DNA amplification efficiency, total residence time, total substrate volume and pressure drop throughout the design space for a practical CFPCR device with sigmoid-shape microfluidic channels. A series of single objective optimisations are carried out which demonstrate that DNA concentration, pressure drop, total residence time and total substrate volume within a single unitcell can be improved by up to [Formula: see text]5.

A user-orientated approach to provenance capture and representation for in silico experiments, explored within the atmospheric chemistry community.

We present a novel user-orientated approach to provenance capture and representation for in silico experiments, contrasted against the more systems-orientated approaches that have been typical within the e-Science domain. In our approach, we seek to capture the scientist's reasoning in the form of annotations as an experiment evolves, while using the scientist's terminology in the representation of process provenance. Our user-orientated approach is applied in a case study within the atmospheric chemistry domain: we consider the design, development and evaluation of an electronic laboratory notebook, a provenance capture and storage tool, for iterative model development.

Semantically enhanced provenance capture for chamber model development with a master chemical mechanism.

The development and maintenance of benchmark databases within scientific communities is reliant on interactions with database users. We explore the role of semantically enhanced provenance for computational modelling processes that make use of one such database: the master chemical mechanism, a key resource within the atmospheric chemistry community.