Abstract: Large river catchments with mixed land use capture pesticides from many sources, and degradable pesticides are converted during downstream transport. Unravelling the contribution of pesticide source and the effect of degradation processes is a challenge in such areas. However, insight and understanding of the sources is important for targeted managen-lent, especially when water is abstracted from the river for drinking water production. The river Meuse is such a case. A long-term monitoring data set was applied in a modelling approach for assessing the contribution of waste water treatment plants (WWTPs) and tributaries (sub-basins) to surface water contamination, and to evaluate the effect of decay on the downstream concentrations of glyphosate and AMPA at the point of drinking water abstraction. The results show that WWTPs are important contributors for glyphosate and AMPA in large river catchments with mixed land uses. In the studied area, the river Meuse in the Netherlands, the relative contribution of WWTP effluents is above 29% for glyphosate and around 12% for AMPA. Local industries are found to be potentially big contributors of AMPA. Glyphosate entering the river system is gradually converted to AMPA and other degradation-productions, which results in downstream loads that are considerably lower than the sum of all influxes. In summer when the travel time is longer due to lower discharge, the first order decay of glyphosate in the river Meuse is estimated to result in about 50% reduction of the downstream glyphosate concentrations over a river stretch of 250 km. The contribution of glyphosate decay to the observed AMPA concentrations ranges between 2% and 10%. Contributions are sensitive to seasonal variations in discharge that influence the concentrations through dilution and degradation. (C) 2016 Elsevier B.V. All rights reserved.

Abstract: It has often been stated that a holographic biprism represents a near perfect energy filter and only elastically scattered electrons can participate in the interference fringes. This is based on the assumption that the reference wave does not contain inelastically scattered electrons. In this letter we show that this is not exactly true because of the delocalised inelastic interaction of the reference wave with the sample. We experimentally and theoretically show that inelastic scattering plays a role in the fringe formation, but it is shown that this contribution is small and can usually be neglected in practice. (C) 2011 Elsevier B.V. All rights reserved.

Abstract: We present a computational model for simulating the dispersion of traffic emitted particulate matter inside a road tunnel, with an emphasis on the number concentration of ultrafine particles (UFP). The model primarily calculates the size distribution of the particle number concentration at each location inside the tunnel. The proposed model differs from existing models in the sense that it uses a continuous representation of the size distribution based upon the high-order finite element method and that it solves the governing equations using the state-of-the-art discontinuous Galerkin method. Next to the traditional transport processes, the model also implements the most important aerosol transformation processes such as coagulation, condensation and dry deposition. It is shown that based upon parametrisations found in literature, the process of condensation in a traffic tunnel cannot properly be modelled. Therefore, we present a correction factor that allows for a better parametrisation. The adequate performance of the model is demonstrated by both a verification study and a validation study. For the verification we show that the discretisation error converges consistently while for the validation we compare the modelled results with a suitable set of data from a UFP measurement campaign in a Taiwanese traffic tunnel. The model is shown to correctly simulate the observed behaviour and by applying a statistical model evaluation we demonstrate that the proposed model meets widely accepted air quality model acceptance criteria. (C) 2012 Elsevier Ltd. All rights reserved.

Abstract: The aged Ni-rich NiTi shape memory alloys (SMAs) exhibit the multi-stage martensitic transformation (MMT), which has important influences on functional properties and practical applications of the NiTi SMAs. A hidden single-stage martensitic transformation from B2 parent phase to B19' martensite phase is found in an aged Ni51Ti49 alloy, which happens concurrently with a commonly observed two-stage martensitic transformation B2-R-B19' (R: martensite phase) and actually composes one stage of a multi-stage martensitic transformation (MMT) together with the two-stage one. B2-B19' martensitic transformation occurs in the NiTi matrix containing Ni4Ti3 precipitates with relatively large inter-particle space, while B2-R-B19' transformation takes place in the NiTi matrix with Ni4Ti3 precipitates having relatively small inter-particle space. (C) 2019 Elsevier B.V. All rights reserved.

Abstract: In the present work, a novel graphene (GN) and gelatin (GTN) composite was prepared and used as an immobilization matrix for hemoglobin (Hb). Compared with Hb immobilized on a bare, GN or GTN modified glassy carbon electrode (GCE), a stable and pair of well-defined quasi redox couple was observed at an Hb modified GN/GTN composite GCE at a formal potential of −0.306 V versus Ag|AgCl. The direct electrochemical behavior of Hb was greatly enhanced by the presence of both GTN and GN. A heterogeneous electron transfer rate constant (Ks) was calculated as 3.82 s−1 for Hb immobilized at GN/GTN modified GCE, which indicates the fast direct electron transfer of Hb toward the electrode surface. The biosensor shows a stable and wide linear response for H2O2 in the linear response range from 0.1 μM to 786.6 μM with an analytical sensitivity and limit of detection of 0.48 μAμM−1 cm−2 and 0.04 μM, respectively. The fabricated biosensor holds its high selectivity in the presence of potentially active interfering species and metal ions. The biosensor shows its satisfactory practical ability in the commercial contact lens solution and human serum samples.

Abstract: A shift from batch processing towards continuous processing is of interest in the pharmaceutical industry. However, this transition requires detailed knowledge and process understanding of all consecutive unit operations in a continuous manufacturing line to design adequate control strategies. This can be facilitated by developing mechanistic models of the multi-phase systems in the process. Since modelling efforts only started recently in this field, uncertainties about the model predictions are generally neglected. However, model predictions have an inherent uncertainty (i.e. prediction uncertainty) originating from uncertainty in input data, model parameters, model structure, boundary conditions and software. In this paper, the model prediction uncertainty is evaluated for a model describing the continuous drying of single pharmaceutical wet granules in a six-segmented fluidized bed drying unit, which is part of the full continuous from-powder-to-tablet manufacturing line (Consigma (TM), GEA Pharma Systems). A validated model describing the drying behaviour of a single pharmaceutical granule in two consecutive phases is used. First of all, the effect of the assumptions at the particle level on the prediction uncertainty is assessed. Secondly, the paper focuses on the influence of the most sensitive parameters in the model. Finally, a combined analysis (particle level plus most sensitive parameters) is performed and discussed. To propagate the uncertainty originating from the parameter uncertainty to the model output, the Generalized Likelihood Uncertainty Estimation (GLUE) method is used. This method enables a modeller to incorporate the information obtained from the experimental data in the assessment of the uncertain model predictions and to find a balance between model performance and data precision. A detailed evaluation of the obtained uncertainty analysis results is made with respect to the model structure, interactions between parameters and uncertainty boundaries. (C) 2013 Elsevier B.V. All rights reserved.

Abstract: The goal of this study is to provide a rigorous tool to quantify the inequality of the leaf size distribution of an individual plant, thereby serving as a reference trait for quantifying plant adaptations to local environmental conditions. The tool to be presented and tested employs three components: (1) a performance equation (PE), which can produce flexible asymmetrical and symmetrical bell-shaped curves, (2) the Lorenz curve (i.e., the cumulative proportion of leaf size vs. the cumulative proportion of number of leaves), which is the basis for calculating, and (3) the Gini index, which measures the inequality of leaf size distribution. We sampled 12 individual plants of a dwarf bamboo and measured the area and dry mass of each leaf of each plant. We then developed a generalized performance equation (GPE) of which the PE is a special case and fitted the Lorenz curve to leaf size distribution using the GPE and PE. The GPE performed better than the PE in fitting the Lorenz curve. We compared the Gini index of leaf area distribution with that of leaf dry mass distribution and found that there was a significant difference between the two indices that might emerge from the scaling relationship between leaf dry mass and area. Nevertheless, there was a strong correlation between the two Gini indices (r2 = 0.9846). This study provides a promising tool based on the GPE for quantifying the inequality of leaf size distributions across individual plants and can be used to quantify plant adaptations to local environmental conditions.

Abstract: Plant leaves exhibit diverse shapes that enable them to utilize a light resource maximally. If there were a general parametric model that could be used to calculate leaf area for different leaf shapes, it would help to elucidate the adaptive evolutional link among plants with the same or similar leaf shapes. We propose a simplified version of the original Gielis equation (SGE), which was developed to describe a variety of object shapes ranging from a droplet to an arbitrary polygon. We used this equation to fit the leaf profiles of 53 species (among which, 48 bamboo plants, 5 woody plants, and 10 geographical populations of a woody plant), totaling 3310 leaves. A third parameter (namely, the floating ratio c in leaf length) was introduced to account for the case when the theoretical leaf length deviates from the observed leaf length. For most datasets, the estimates of c were greater than zero but less than 10%, indicating that the leaf length predicted by the SGE was usually smaller than the actual length. However, the predicted leaf areas approximated their actual values after considering the floating ratios in leaf length. For most datasets, the mean percent errors of leaf areas were lower than 6%, except for a pooled dataset with 42 bamboo species. For the elliptical, lanceolate, linear, obovate, and ovate shapes, although the SGE did not fit the leaf edge perfectly, after adjusting the parameter c, there were small deviations of the predicted leaf areas from the actual values. This illustrates that leaves with different shapes might have similar functional features for photosynthesis, since the leaf areas can be described by the same equation. The anisotropy expressed as a difference in leaf shape for some plants might be an adaptive response to enable them to adapt to different habitats.

Abstract: Using the first-principles calculations, we explore the structural and novel electronic/optical properties of the C2N nanosheet. To this goal, we systematically investigate the affect of layer thickness, electrical field and strain on the electronic properties of the C2N nanosheet. By increasing the thickness of C2N, we observed that the band gap decreases. Moreover, by applying an electrical field to bilayer C2N, the band gap decreases and a semiconductor-to-metal transition can occur. Our results also confirm that uniaxial and biaxial strain can effectively alter the band gap of C2N monolayer. Furthermore, we show that the electronic and magnetic properties of C2N can be modified by the adsorption and substitution of various atoms. Depending on the species of embedded atoms, they may induce semiconductor (O, C, Si and Be), metal (S, N, P, Na, K, Mg and Ca), dilute-magnetic semiconductor (H, F, B), or ferro-magnetic-metal (Cl, Li) character in C2N monolayer. It was also found that the inclusion of hydrogen or oxygen impurities and nitrogen vacancies, can induce magnetism in the C2N monolayer. These extensive calculations can be useful to guide future studies to modify the electronic/optical properties of two-dimensional materials. (C) 2019 Elsevier Ltd. All rights reserved.

Abstract: Using first-principles calculations we systematically investigate the atomic, electronic and magnetic properties of novel two-dimensional materials (2DM) with a stoichiometry C3N which has recently been synthesized. We investigate how the number of layers affect the electronic properties by considering monolayer, bilayer and trilayer structures, with different stacking of the layers. We find that a transition from semiconducting to metallic character occurs which could offer potential applications in future nanoelectronic devices. We also study the affect of width of C3N nanoribbons, as well as the radius and length of C3N nanotubes, on the atomic, electronic and magnetic properties. Our results show that these properties can be modified depending on these dimensions, and depend markedly on the nature of the edge states. Functionalization of the nanostructures by the adsorption of H adatoms is found induce metallic, half-metallic, semiconducting and ferromagnetic behavior, which offers an approach to tailor the properties, as can the application of strain. Our calculations give insight into this new family of C3N nanostructures, which reveal unusual electronic and magnetic properties, and may have great potential in applications such as sensors, electronics and optoelectronic at the nanoscale.

Abstract: Sacrificial anodes have become a standard practice for the protection of ballast tanks of merchant vessels against corrosive damage. A well protected tank should extend the life span of a ship and consequently enhances its economic value. An in situ survey comprising more than 100 merchant vessels provided the opportunity to measure the impact of these anodes on the life expectancy of these vessels. Contrary to the general belief of these anodes beneficial effect, no significant difference was found in our observations in terms of corrosion occurrence between ship populations with and without sacrificial anodes, across all ship ages. This may be explained by the highly variable conditions and the complex geometry in a ballast tank severely impede optimal and straightforward installation of these anodes in these tanks. Also, poorly placed anodes in it may harm the integrity of the coating of the tank. We therefore plead for uniform and clear rules on anode installation and inspection.

Abstract: Colloidal nanocrystals combine size- and facet-dependent properties with solution processing. They offer thus a compelling suite of materials for technological applications. Their size- and facet-tunable features are studied in synthesis; however, to exploit their features in optoelectronic devices, it will be essential to translate control over size and facets from the colloid all the way to the film. Larger-diameter colloidal quantum dots (CQDs) offer the attractive possibility of harvesting infrared (IR) solar energy beyond absorption of silicon photovoltaics. These CQDs exhibit facets (nonpolar (100)) undisplayed in small-diameter CQDs; and the materials chemistry of smaller nanocrystals fails consequently to translate to materials for the short-wavelength IR regime. A new colloidal management strategy targeting the passivation of both (100) and (111) facets is demonstrated using distinct choices of cations and anions. The approach leads to narrow-bandgap CQDs with impressive colloidal stability and photoluminescence quantum yield. Photophysical studies confirm a reduction both in Stokes shift (approximate to 47 meV) and Urbach tail (approximate to 29 meV). This approach provides a approximate to 50% increase in the power conversion efficiency of IR photovoltaics compared to controls, and a approximate to 70% external quantum efficiency at their excitonic peak.