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Porous boron nitride is gaining significant attention for applications in molecular separations, photocatalysis, and drug delivery. All these areas call for a high degree of stability (or a controlled stability) over a range of chemical environments, and particularly under humid conditions. The hydrolytic stability of the various forms of boron nitride, including porous boron nitride, has been sparingly addressed in the literature. Here, we map the physical-chemical properties of the material to its hydrolytic stability for a range of conditions. Using analytical, imaging and spectroscopic techniques, we identify the links between the hydrolytic instability of porous boron nitride and its limited crystallinity, high porosity as well as the presence of oxygen atoms. To address this instability issue, we demonstrate that subjecting the material to a thermal treatment leads to the formation of crystalline domains of h-BN exhibiting a hydrophobic character. The heat-treated sample exhibits enhanced hydrolytic stability, while maintaining a high porosity. This work provides an effective and simple approach to producing stable porous boron nitride structures, and will progress the implementation of the material in applications involving interfacial phenomena.

A combination of electrochemical measurement and interface analysis have been applied to characterise the interaction of OMID, an exemplar imidazoline-based corrosion inhibitor, with carbon steel in 1 M hydrochloric acid. Corrosion inhibition efficiency data indicate that excellent performance is achieved well below the critical micelle concentration. High resolution X-ray photoelectron spectra demonstrate that, as the corrosion rate decreases, the interface evolves towards one comprising OMID bound to film-free carbon steel. This latter result provides key input for those researchers attempting to predict corrosion inhibitor functionality through atomic scale interfacial modelling, and so identify next generation chemistries.

The dynamics of ligaments retracting under the action of surface tension occurs in a multitude of natural and industrial applications, such as inkjet printing and atomisation. We perform fully three-dimensional, two-phase direct numerical simulations of the retraction dynamics with soluble surfactants. A full parametric study is performed using a hybrid interface-tracking/level-set method, which is utilised to treat the interface; this method is capable of capturing faithfully the topological transitions that are a feature of the flow over a certain range of ligament aspect ratios and Ohnesorge numbers. Our results demonstrate the delicate interplay between capillarity, modulated by the presence of surfactants, surfactant-induced Marangoni stresses, inertial and viscous effects. Particular attention is paid to the formation of vortices, which accompany the retraction process, and the influence of surfactant on the vortex dynamics., Comment: 19 pages, 14 figures

Reverse osmosis membranes are used within the oil and gas industry for sea water desalination on off-shore oilrigs. The membranes consist of three layers of material – a polyester backing layer, a polysulfone support and a polyamide (PA) thin film separating layer. It is generally thought that the PA layer controls ion selectivity within the membrane, but little is understood about its structure or chemistry at the molecular scale. This active polyamide layer is synthesized by interfacial polymerisation at an organic/aqueous interface between m-phenylenediamine (MPD) and trimesoyl chloride (TMC), producing a highly cross-linked polyamide (PA) polymer. It has been speculated that the distribution of functional chemistry within this layer could play a role in solute filtration. The only technique potentially capable of probing the distribution of functional chemistry within the active PA layer with sufficient spatial and energy resolution is scanning transmission electron microscopy combined with electron energy-loss spectroscopy (STEM-EELS). Its use is a challenge because organic materials suffer beam-induced damage at relatively modest electron doses. Here we show that it is possible to use the N K-edge to map the active layer of a PA film using monochromated EELS spectrum imaging. The active PA layer is 12 nm thick, which supports previous neutron reflectivity data. Clear changes in the fine structure of the C K-edge across the PA films are measured and we use machine learning to assign fine structure at this edge. Using this method, we map highly heterogeneous intensity variations in functional chemistry attributed to N-C=C bonds within the PA. Similarities are found with previous molecular dynamics simulations of PA showing regions with a higher density of amide bonding as a result of the aggregation process at similar length scales. The chemical pathways that can be deduced may offer a clearer understanding of the transport mechanisms through the membrane.

Interactions between iron surfaces and hydrocarbons are the basis for a wide range of materials synthesis processes and novel applications, including sensing. However, in diesel engines these interactions can lead to deposit formation that reduces performance, lowers efficiency, and increases emissions. Here, we present a global study to understand deposition at iron-hexadecane interfaces. We use a combination of spectroscopy, microscopy, and mass spectrometry to investigate surface reactions, bulk chemistry, and deposition processes. A dynamic equilibrium between the oxidation products, both at the surface and in solution, determines the deposition at the surface. Considering the solution and the surface in parallel, we find that the iron speciation affects the morphology, composition, and quantity of the deposit at the surface, as well as the oxidation of hexadecane. Fe(II) and Fe(III) both promote the decomposition of peroxides-intermediates in the oxidation of hexadecane-but through noncatalytic and catalytic mechanisms, respectively. In contrast, Fe(0) is proposed to initiate hexadecane autoxidation during its oxidation to Fe(III). We find that in all cases, the surfaces exclusively contain Fe(III) following heat treatment with hexadecane. Upon subsequent exposure at room temperature, Fe(III) species are found to promote oxidation; this finding is particularly concerning for hybrid vehicles where longer time periods are expected between engine operation. Our work provides a foundation for the development of strategies that disrupt the role of iron in the degradation of hexadecane to ultimately reduce oxidation and deposition in diesel engines.

In this work, we investigate the effect of varying the concentration of sodium chloride up to 70 g.L−1 - equivalent to a recovery of approximately 50% in seawater desalination-on the transport properties of different reverse osmosis membranes. The study was performed using five commercial thin film composite (TFC) membranes and an analogue TFC membrane fabricated via the interfacial reaction of m-phenylenediamine and trimesoyl chloride. The surface properties of the membranes as measured by atomic force microscopy (AFM), zeta potential, and X-ray photoelectron spectroscopy (XPS) are presented. The solution diffusion model coupled with film theory was used to calculate the permeance of water and salt through the membranes, to account for the effect of concentration polarisation. The mass transfer coefficient in the test cells was estimated independently using the dissolution rate of benzoic acid; and was found to be approximately 1 × 10 − 4 m . s − 1 . A linear reduction in salt permeance was observed in some of the RO membranes, while it remained constant for other membranes, including the analogue membrane. All the tested membranes maintained constant water permeance below 45 g.L−1 NaCl. However, when the salt concentration at the membrane surface exceeded 45 g.L−1, water permeance either increased, remained constant or decreased. The results demonstrate the dependence of water and salt transport on the concentration of sodium chloride at the membrane surface.

Porous boron nitride (BN) is structurally analogous to activated carbon. This material is gaining increasing attention for its potential in a range of adsorption and chemical separation applications, with a number of recent proof-of-concept studies on the removal of organics from water. Today though, the properties of porous BN – i.e. surface area, pore network, chemistry – that dictate adsorption of specific organics remain vastly unknown. Yet, they will need to be optimized to realise the full potential of the material in the envisioned applications. Here, a selection of porous BN materials with varied pore structures and chemistries were studied for the adsorption of different organic molecules, either directly, through vapour sorption analyses or as part of a water/organic mixture in the liquid phase. These separations are relevant to the industrial and environmental sectors and are envisioned to take advantage of the hydrophobic character of the BN sheets. The materials were tested and regenerated and their physical and chemical features were characterized before and after testing. This study allowed identifying the adsorption mechanisms, assessing the performance of porous BN compared to benchmarks in the field and outlining ways to improve the adsorption performance further.

Distributed dataflow systems such as Apache Spark and Apache Flink are used to derive new insights from large datasets. While they efficiently execute concrete data processing workflows, expressed as dataflow graphs, they lack generic support for exploratory work- flows : if a user is uncertain about the correct processing pipeline, e.g. in terms of data cleaning strategy or choice of model parame- ters, they must repeatedly submit modified jobs to the system. This, however, misses out on optimisation opportunities for exploratory workflows, both in terms of scheduling and memory allocation. We describe meta-dataflows (MDFs), a new model to effectively express exploratory workflows and efficiently execute them on compute clusters. With MDFs, users specify a family of dataflows using two primitives: (a) an explore operator automatically con- siders choices in a dataflow; and (b) a choose operator assesses the result quality of explored dataflow branches and selects a subset of the results. We propose optimisations to execute MDFs: a system can (i) avoid redundant computation when exploring branches by reusing intermediate results and discarding results from underper- forming branches; and (ii) consider future data access patterns in the MDF when allocating cluster memory. Our evaluation shows that MDFs improve the runtime of exploratory workflows by up to 90% compared to sequential execution.

A model for ionic and electronic grain boundary transport through thin films, scales or membranes with columnar grain structure is introduced. The grain structure is idealized as a lattice of identical hexagonal cells – a honeycomb pattern. Reactions with the environment constitute the boundary conditions and drive the transport between the surfaces. Time-dependent simulations solving the Poisson equation self-consistently with the Nernst-Planck flux equations for the mobile species are performed. In the resulting Poisson-Nernst-Planck system of equations, the electrostatic potential is obtained from the Poisson equation in its integral form by summation. The model is used to interpret alumina membrane oxygen permeation experiments, in which different oxygen gas pressures are applied at opposite membrane surfaces and the resulting flux of oxygen molecules through the membrane is measured. Simulation results involving four mobile species, charged aluminum and oxygen vacancies, electrons, and holes, provide a complete description of the measurements and insight into the microscopic processes underpinning the oxygen permeation of the membrane. Most notably, the hypothesized transition between p-type and n-type ionic conductivity of the alumina grain boundaries as a function of the applied oxygen gas pressure is observed in the simulations. The range of validity of a simple analytic model for the oxygen permeation rate, similar to the Wagner theory of metal oxidation, is quantified by comparison to the numeric simulations. The three-dimensional model we develop here is readily adaptable to problems such as transport in a solid state electrode, or corrosion scale growth.