Surface molecular degradation of 3D glass polymer composite under low earth orbit simulated space environment

Epoxy resin reinforced with 3D parabeam glass fibre was subjected to low earth orbit (LEO) simulation conditions comprising ultra high vacuum, temperature cycling (TC), and ultraviolet (UV) radiation and atomic oxygen (AO) bombardment. Inspection of the same composite using only a selection of these hazardous conditions provided comparison measures to identify the effect of each condition on the surface degradation of the resin composite. Each of the individually selected conditions showed a different degradation mechanism that is accelerated by the presence of other conditions. X-ray photoelectron spectroscopy (XPS), time-of-flight secondary ion mass spectrometry (ToF-SIMS) and scanning electron microscopy (SEM) were used to provide surface information. The resin composite samples suffered surface oxidation that increased the oxygen content to 17.24% in comparison with the untreated sample (only 14.2%). The samples that were treated with AO showed higher C-O and CO functional groups on the surface in comparison with the rest of the samples (as indicated by XPS). Molecular information (from ToF-SIMS) showed that surface oxidation differs with different conditions and in comparison with the use of all conditions. All treated samples were shown to suffer significant chain scission and loss of volatiles as a result of the LEO conditions. The extent of the chain scission reaction for each condition can be indicated by the extent of the reduction of the relative concentration of the aliphatic hydrocarbon ions. The relative intensity of the C₄H₁₁N₄O₂⁺ ion showed that AO bombardment accelerated the oxidation of the surface. The AO effect is doubled when UV and TC are also present. SEM results indicated that sample surfaces were eroded and roughened upon exposure to LEO conditions. Presence of AO and UV in the LEO conditions introduced white deposits onto the surface, believed to be crosslinked formations.     

Characterization of branched polysaccharides using multiple-detection size separation techniques

The structure of branched polysaccharides involves a hierarchy of levels, from the constituent sugars, then the branching pattern, up to the macromolecular architecture, and then supramolecular organization. Finding causal relations between this complex structure/architecture and both (bio)synthetic mechanisms and final properties is needed for understanding the functionality of branched polysaccharides, which is important in fields ranging from improved nutrition and health through to papermaking and pharmaceuticals. The structural complexity makes this task especially challenging. This review focuses on the best current means to obtain reliable branch chain and size distributions using size-separation technologies coupled with number-, mass- and molecular-weight-sensitive detectors. Problems with current technologies are also critically appraised.     

Evaluation of different machines used to quantify genetic modification by real-time PCR

Quantification of genetic modification (GM) is often undertaken to test for compliance with the European Union GM labeling threshold in food. Different control laboratories will often use common validated methods, but with different models of real-time PCR machines. We performed two separate ring trials to evaluate the relative precision and accuracy of different types of real-time PCR machines used to quantify the concentration of GM maize. Both trials used dual-labeled fluorogenic probes for quantification. The first ring trial used separate GM and reference assays (a single fluorescence channel), and the second used a combined duplex assay (two simultaneous fluorescence channels). Five manufacturers and seven models--including a 96-well microtiter-plate, rotary, and portable machines--were examined. In one trial, the machine used had a significant effect on precision, but in the other it did not. Overall, the degree of variation due to the machine model was lower than other factors. No significant repeatable difference in accuracy was observed between machine models. It was not possible to use sufficient replication of machine type in each laboratory to examine all sources of variation in this study, but the results strongly indicate that factors other than machine type or manufacturer (e.g., method or laboratory) contribute more to variation in a GM quantification result.     

Motion and mixing for multiple ferromagnetic microswimmers

This paper concerns the interaction of several ferromagnetic microswimmers, their motion and the resulting fluid mixing. Each swimmer consists of two ferromagnetic beads joined by an elastic link, and is driven by an external, time-dependent magnetic field. The external field provides a torque on a swimmer and, together with the varying attraction between the magnetic beads, generates a time-irreversible motion leading to persistent swimming in a low Reynolds number environment. The aim of the present paper is to consider the interactions between several swimmers. A regime is considered in which identical swimmers move in the same overall direction, and their motion is synchronised because of driving by the external field. It is found that two swimmers tend to encircle one another while three undergo more complicated motion that may involve the braiding of swimmer trajectories. By means of approximations it is established that the interaction between pairs of swimmers gives circulatory motion which falls off with an inverse square law and is linked to their overall speed of motion through the fluid. As groups of two or more swimmers move through the fluid they process fluid, leaving behind a trail of fluid that has undergone mixing: this is investigated by following streak lines numerically.     

Nonlinear interference in a mean-field quantum model

Using similar nonlinear stationary mean-field models for both a 2D axisymmetricalBose-Einstein Condensate and an electron pair in a parabolic trap, we propose to describethe original many-particle ground state as a one-particle mixed state (in contrast to apure state), i.e. as a statistical ensemble of several one-particle quantum states. Thesequantum states are the eigenfunctions of the corresponding stationary nonlinearSchrödinger equation (hence called “nonlinear eigenstates”). Due to their nonlinearity,they are not orthogonal. Therefore, taking the simple example of a two-level system, weshow that each of these two nonlinear eigenstates |i? and|j? occurs with a probability (or statistical weight) that isdefined by their non-orthogonality ?i|j? 0. We givethe corresponding density matrix. We search for physical grounds in the interpretation ofour two main results, namely, a quantum-classical nonlinear transition and theinterference between two “nonlinear eigenstates”.     

The oxidation of Fe(111)

The oxidation of Fe(111) was studied using Auger electron spectroscopy (AES), low energy electron diffraction (LEED), X-ray photoelectron spectroscopy (XPS), ion scattering spectroscopy (ISS) and scanning tunnelling microscopy (STM). Oxidation of the crystal was found to be a very fast process, even at 200 K, and the Auger O signal saturation level is reached within ~ 50 × 10^? 6 mbar s. Annealing the oxidised surface at 773 K causes a significant decline in apparent surface oxygen concentration and produces a clear (6 × 6) LEED pattern, whereas after oxidation at ambient temperature no pattern was observed. STM results indicate that the oxygen signal was reduced due to the nucleation of large, but sparsely distributed oxide islands, leaving mainly the smooth (6 × 6) structure between the islands. The reactivity of the (6 × 6) layer towards methanol was investigated using temperature programmed desorption (TPD), which showed mainly decomposition to CO and CO₂, due to the production of formate intermediates on the surface. Interestingly, this removes the (6 × 6) structure by reduction, but it can be reformed from the sink of oxygen present in the large oxide islands simply by annealing at 773 K for a few minutes. The (6 × 6) appears to be a relatively stable, pseudo-oxide phase, that may be useful as a model oxide surface.     

Locating replenishment stations for electric vehicles: application to Danish traffic data

Environment-friendly electric vehicles have gained popularity and increased attention in recent years. The deployment of a network of recharging stations is essential given their limited travel range. This paper considers the problem of locating electronic replenishment stations for electric vehicles on a traffic network with flow-based demand. The objective is to optimize the network performance, for example to maximize the flow covered by a prefixed number of stations or to minimize the number of stations needed to cover traffic flows. Two integer linear programming formulations are proposed to model the problem. These models are tested on real-life traffic data collected in Denmark.     

Power generation using an activated carbon and metal mesh cathode in a microbial fuel cell

An inexpensive activated carbon (AC) air cathode was developed as an alternative to a platinum-catalyzed electrode for oxygen reduction in a microbial fuel cell (MFC). AC was cold-pressed with a polytetrafluoroethylene (PTFE) binder to form the cathode around a Ni mesh current collector. This cathode construction avoided the need for carbon cloth or a metal catalyst, and produced a cathode with high activity for oxygen reduction at typical MFC current densities. Tests with the AC cathode produced a maximum power density of 1220 mW/m² (normalized to cathode projected surface area; 36 W/m³ based on liquid volume) compared to 1060 mW/m² obtained by Pt catalyzed carbon cloth cathode. The Coulombic efficiency ranged from 15% to 55%. These findings show that AC is a cost-effective material for achieving useful rates of oxygen reduction in air cathode MFCs.     

Genetic programming as an analytical tool for non-linear dielectric spectroscopy.

By modelling the non-linear effects of membranous enzymes on an applied oscillating electromagnetic field using supervised multivariate analysis methods, Non-Linear Dielectric Spectroscopy (NLDS) has previously been shown to produce quantitative information that is indicative of the metabolic state of various organisms. The use of Genetic Programming (GP) for the multivariate analysis of NLDS data recorded from yeast fermentations is discussed, and GPs are compared with previous results using Partial Least Squares (PLS) and Artificial Neural Nets (NN). GP considerably outperforms these methods, both in terms of the precision of the predictions and their interpretability.