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The adhesion energy, or strain energy release rate, G , between polydimethylsiloxane (PDMS) elastomers and flat silica surfaces modified by irreversible adsorption and end grafting of PDMS chains, has been characterised through peel tests and ‘JKR’ experiments. The 90° peel tests have been conducted down to very low velocity (5 nm s –1 ). In the ‘JKR’ experiment, a small spherical cap of elastomer is pushed against the surface, and the area of contact is monitored as a function of the applied load, allowing the determination of both G and the elastic modulus of the elastomer, E . Systematic measurements have been made, varying the molecular architecture of both the elastomer and the grafted layer (chain length and surface chain density). Our central result is that G , measured at the lowest possible accessible rates, passes through a maximum when the surface density of grafted chains increases. This can be rationalised in the framework of recent models of polymer–polymer junctions, provided that the ability of the grafted chains to penetrate into the network is accounted for. When the velocity of the advancing fracture is increased, the measured adhesion energy increases strongly and non-linearly, contrary to the predictions of molecular models based on the suction mechanism.

As a reactive oxygen species (ROS), hypochlorite (OCl ? ) plays a crucial role in oxidative stress and signal transduction, controlling a wide range of physiological functions. In addition, the wide use of OCl ? in the treatment of food and water might possibly threaten human health if the residual quantity was out of limits. Currently, sensitive methods employed to selectively monitor OCl ? in aqueous samples in situ are still scarce and badly needed. Boron esters or acids are considered to be suitable functional groups for the detection of hydrogen peroxide due to their reliable reactivity. In this work, we try to develop a highly sensitive and selective OCl ? probe ( TPE2B ) based on the mechanism of aggregation induced emission (AIE). Due to the distinct increase in water solubility of TPE2OH , which is generated from the reaction between TPE2B and OCl ? , the strong emission of TPE2B is quenched dramatically. The response speed was as fast as 30 seconds with a detection limit as low as 28 nM. Additionally, test papers were also fabricated and exhibited a highly sensitive response to 0.1 mM OCl ? .

Applications of biomethane as a source of renewable energy and transport fuel rely heavily on successful implementation of purification methods capable of removing undesirable impurities from biogas and increasing its calorific content. Metal–organic frameworks (MOFs) are competitive candidates for biogas upgrading due to a versatile range of attractive physical and chemical properties which can be utilised in membrane materials. In this work, we present a high-throughput computational screening methodology for efficient identification of MOF structures with promising gas separation performance. The proposed screening strategy is based on initial structural analysis and predictions of the single-component permeation of CO 2 , CH 4 and H 2 S from adsorption and diffusion calculations at infinite dilution. The identified top performing candidates are subject to further analysis of their gas separation performance at the operating conditions of 10 bar and 298 K, using grand canonical Monte Carlo and equilibrium molecular dynamics simulations on equimolar CO 2 /CH 4 and H 2 S/CH 4 mixtures. The Henry constant for the adsorption of H 2 O was also calculated to determine the hydrophobicity of MOF structures, as the presence of H 2 O often leads to membrane instability and performance limitations. For the considered gas mixtures, the top MOF candidates exhibit superior separation capabilities over polymer-, zeolite-, and mixed matrix-based membranes as indicated by the predicted values of selectivity and permeability. The proposed screening protocol offers a powerful tool for the rational design of novel MOFs for biogas upgrading.

We are engaged in a multidisciplinary study of fundamental aspects of the crystallization of organic molecular materials from solution, focusing on polymorphic systems under the recognition that such systems represent an ideal opportunity for obtaining a systematic understanding of competing pathways in crystallization processes. The range of techniques employed in this work are sensitive to structural properties on different length scales and are thus appropriate for mapping the changes that occur at different stages of the crystallization process, starting from the early aggregation events in solution (probed by solution-state NMR and molecular dynamics simulations, including studies of diffusion properties), leading to the growth of molecular aggregates (probed by small-angle neutron scattering), then the emergence of solid microcrystals dispersed in the crystallization solution (probed by small-angle neutron scattering and solid-state NMR ) and finally the formation of the bulk solid crystalline phase (probed by powder X-ray diffraction ). This paper reports preliminary results on the application of this multi-technique approach to study the crystallization of glycine (which has three known polymorphic forms under ambient conditions) from aqueous solution.

We have developed a corrosion model that can predict metal oxide growth and dissolution rates as a function of time for a range of solution conditions. Our model considers electrochemical reactions at the metal/oxide and oxide/solution interfaces, and the metal cation flux from the metal to the solution phase through a growing oxide layer, and formulates the key processes using classical chemical reaction rate or flux equations. The model imposes mass and charge balance and hence, is labeled as the Mass Charge Balance (MCB) model. Mass and charge balance dictate that at any given time the oxidation (or metal cation) flux must be equal to the sum of the oxide growth flux and the dissolution flux. For each redox reaction leading to the formation of a specific oxide, the metal oxidation flux is formulated using a modified Butler–Volmer equation with an oxide-thickness-dependent effective overpotential. The oxide growth and dissolution fluxes have a first-order dependence on the metal cation flux. The rate constant for oxide formation also follows an Arrhenius dependence on the potential drop across the oxide layer and hence decreases exponentially with oxide thickness. This model is able to predict the time-dependent potentiostatic corrosion behaviour of both pure iron, and Co–Cr and Fe–Ni–Cr alloys.

The heats of adsorption as a function of coverage have been determined for copper adsorption onto several well-defined oxide thin film surfaces at room temperature by microcalorimetric measurements. The heats of adsorption are accurately determined as a function of coverage with resolution of 2% of a monolayer. For all three oxide surfaces investigated, MgO(100), a p(2×1) molybdenum oxide film on Mo(100) and disordered W oxide, the initial heat of copper adsorption is much lower than the heat of sublimation for Cu (337.4 kJ mol -1 ). On MgO(100) the initial Cu heat of adsorption in the first 2–4% of a monolayer is 240 kJ mol -1 and increases rapidly to the heat of Cu sublimation. Auger spectroscopy shows that Cu grows on MgO(100) as two-dimensional (2-D) islands until ≈0.3 monolayers where it switches to the growth of 3-D islands, at which point the heat of adsorption of Cu reaches ≈92% of its heat of sublimation. The room temperature sticking probability of Cu on MgO was also investigated as a function of coverage and determined to be 0.99. On the ordered p(2×1) oxide of molybdenum on Mo(100), the initial Cu heat of adsorption is 287 kJ mol -1 . The heat of adsorption then decreases slightly to 278 kJ mol -1 in the first 15% of a monolayer, after which it rapidly increases to the heat of sublimation. Similarly, on the disorder W oxide surface the initial heat of Cu adsorption was 280 kJ mol -1 at 300 K. These results are compared to Pb adsorption on the same oxide thin films and are discussed in the context of important factors influencing metal island growth.

With advances in computational power, the rapidly growing role of computational/simulation methodologies in the physical sciences, and the development of new human–computer interaction technologies, the field of interactive molecular dynamics seems destined to expand. In this paper, we describe and benchmark the software algorithms and hardware setup for carrying out interactive molecular dynamics utilizing an array of consumer depth sensors. The system works by interpreting the human form as an energy landscape, and superimposing this landscape on a molecular dynamics simulation to chaperone the motion of the simulated atoms, affecting both graphics and sonified simulation data. GPU acceleration has been key to achieving our target of 60 frames per second (FPS), giving an extremely fluid interactive experience. GPU acceleration has also allowed us to scale the system for use in immersive 360° spaces with an array of up to ten depth sensors, allowing several users to simultaneously chaperone the dynamics. The flexibility of our platform for carrying out molecular dynamics simulations has been considerably enhanced by wrappers that facilitate fast communication with a portable selection of GPU-accelerated molecular force evaluation routines. In this paper, we describe a 360° atmospheric molecular dynamics simulation we have run in a chemistry/physics education context. We also describe initial tests in which users have been able to chaperone the dynamics of 10-alanine peptide embedded in an explicit water solvent. Using this system, both expert and novice users have been able to accelerate peptide rare event dynamics by 3–4 orders of magnitude.

Redox-active films are advantageous matrices for the immobilization of photosynthetic proteins, due to their ability to mediate electron transfer as well as to achieve high catalyst loading on an electrode for efficient generation of electricity or solar fuels. A general challenge arises from various charge recombination pathways along the light-induced electron transfer chain from the electrode to the charge carriers for electricity production or to the final electron acceptors for solar fuel formation. Experimental methods based on current measurement or product quantification are often unable to discern between the contributions from the photocatalytic process and the detrimental effect of the short-circuiting reactions. Here we report on a general electrochemical model of the reaction–diffusion processes to identify and quantify the “bottlenecks” present in the fuel or current generation. The model is able to predict photocurrent–time curves including deconvolution of the recombination contributions, and to visualize the corresponding time dependent concentration profiles of the product. Dimensionless groups are developed for straightforward identification of the limiting processes. The importance of the model for quantitative understanding of biophotoelectrochemical processes is highlighted with an example of simulation results predicting the effect of the diffusion coefficient of the charge carrier on photocurrent generation for different charge recombination kinetics.

Laboratory studies can provide important insights into the processes that occur at the scale of individual particles in ambient aerosol. We examine the accuracies of measurements of core physicochemical properties of aerosols that can be made in single particle studies and explore the impact of these properties on the microscopic processes that occur in ambient aerosol. Presenting new measurements, we examine here the refinements in our understanding of aerosol hygroscopicity, surface tension, viscosity and optical properties that can be gained from detailed laboratory measurements for complex mixtures through to surrogates for secondary organic atmospheric aerosols.