904 resultados para liquid metal diffusion


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How can obstacles to innovation be overcome in road construction? Using a focus group methodology, and based on two prior rounds of empirical work, the analysis in this chapter generates a set of four key solutions to two main construction innovation obstacles: (1) restrictive tender assessment and (2) disagreement over who carries the risk of new product failure. The four key solutions uncovered were: 1) pre-project product certification; 2) past innovation performance assessment; 3) earlier involvement of product suppliers and road asset operators; and 4) performance-based specifications. Additional research is suggested in order to illicit deeper insights into possible solutions to construction innovation obstacles, and should emphasise furthering the theoretical interpretation of empirical phenomena.

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In this study, effects of concentrations of Cu(II), Zn(II) and Sn(II) ions in the electrolytic bath solution on the properties of electrochemically deposited CuZnSn (CZT) films were investigated. Study of the composition of a CZT film has shown that the metallic content (relative atomic ratio) in the film increased linearly with increase in the metal ion concentration. It is the first time that the relationship of the compositions of the alloy phases in the co-electrodeposited CZT film with the concentration of metal ions has been revealed. The results have confirmed that the formation and content of Cu6Sn5 and Cu5Zn8 alloy phases in the film were directly controlled by the concentration of Cu(II). SEM measurements have shown that Sn(II) has significant impact on film morphology, which became more porous as a result of the larger nucleation size of tin. The changes in the surface properties of the films was also confirmed by chronoamperometry characteristic (i–t) deposition curves. By optimization of metal ion concentrations in the electrolyte solution, a copper-poor and zinc-rich kesterite Cu2ZnSnS4 (CZTS) film was synthesized by the sulfurization of the deposited CZT film. The solar cell with the CZTS film showed an energy conversion efficiency of 2.15% under the illumination intensity of 100 mW cm 2.

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The numerical solution of fractional partial differential equations poses significant computational challenges in regard to efficiency as a result of the spatial nonlocality of the fractional differential operators. The dense coefficient matrices that arise from spatial discretisation of these operators mean that even one-dimensional problems can be difficult to solve using standard methods on grids comprising thousands of nodes or more. In this work we address this issue of efficiency for one-dimensional, nonlinear space-fractional reaction–diffusion equations with fractional Laplacian operators. We apply variable-order, variable-stepsize backward differentiation formulas in a Jacobian-free Newton–Krylov framework to advance the solution in time. A key advantage of this approach is the elimination of any requirement to form the dense matrix representation of the fractional Laplacian operator. We show how a banded approximation to this matrix, which can be formed and factorised efficiently, can be used as part of an effective preconditioner that accelerates convergence of the Krylov subspace iterative solver. Our approach also captures the full contribution from the nonlinear reaction term in the preconditioner, which is crucial for problems that exhibit stiff reactions. Numerical examples are presented to illustrate the overall effectiveness of the solver.

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Fractional differential equations are becoming increasingly used as a powerful modelling approach for understanding the many aspects of nonlocality and spatial heterogeneity. However, the numerical approximation of these models is demanding and imposes a number of computational constraints. In this paper, we introduce Fourier spectral methods as an attractive and easy-to-code alternative for the integration of fractional-in-space reaction-diffusion equations described by the fractional Laplacian in bounded rectangular domains ofRn. The main advantages of the proposed schemes is that they yield a fully diagonal representation of the fractional operator, with increased accuracy and efficiency when compared to low-order counterparts, and a completely straightforward extension to two and three spatial dimensions. Our approach is illustrated by solving several problems of practical interest, including the fractional Allen–Cahn, FitzHugh–Nagumo and Gray–Scott models, together with an analysis of the properties of these systems in terms of the fractional power of the underlying Laplacian operator.

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Flos Chrysanthemum is a generic name for a particular group of edible plants, which also have medicinal properties. There are, in fact, twenty to thirty different cultivars, which are commonly used in beverages and for medicinal purposes. In this work, four Flos Chrysanthemum cultivars, Hangju, Taiju, Gongju, and Boju, were collected and chromatographic fingerprints were used to distinguish and assess these cultivars for quality control purposes. Chromatography fingerprints contain chemical information but also often have baseline drifts and peak shifts, which complicate data processing, and adaptive iteratively reweighted, penalized least squares, and correlation optimized warping were applied to correct the fingerprint peaks. The adjusted data were submitted to unsupervised and supervised pattern recognition methods. Principal component analysis was used to qualitatively differentiate the Flos Chrysanthemum cultivars. Partial least squares, continuum power regression, and K-nearest neighbors were used to predict the unknown samples. Finally, the elliptic joint confidence region method was used to evaluate the prediction ability of these models. The partial least squares and continuum power regression methods were shown to best represent the experimental results.

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Impulse propagation in biological tissues is known to be modulated by structural heterogeneity. In cardiac muscle, improved understanding on how this heterogeneity influences electrical spread is key to advancing our interpretation of dispersion of repolarization. We propose fractional diffusion models as a novel mathematical description of structurally heterogeneous excitable media, as a means of representing the modulation of the total electric field by the secondary electrical sources associated with tissue inhomogeneities. Our results, analysed against in vivo human recordings and experimental data of different animal species, indicate that structural heterogeneity underlies relevant characteristics of cardiac electrical propagation at tissue level. These include conduction effects on action potential (AP) morphology, the shortening of AP duration along the activation pathway and the progressive modulation by premature beats of spatial patterns of dispersion of repolarization. The proposed approach may also have important implications in other research fields involving excitable complex media.

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Many protocols have been used for extraction of DNA from Thraustochytrids. These generally involve the use of CTAB, phenol/chloroform and ethanol. They also feature mechanical grinding, sonication, N2 freezing or bead beating. However, the resulting chemical and physical damage to extracted DNA reduces its quality. The methods are also unsuitable for large numbers of samples. Commercially-available DNA extraction kits give better quality and yields but are expensive. Therefore, an optimized DNA extraction protocol was developed which is suitable for Thraustochytrids to both minimise expensive and time-consuming steps prior to DNA extraction and also to improve the yield. The most effective method is a combination of single bead in TissueLyser (Qiagen) and Proteinase K. Results were conclusive: both the quality and the yield of extracted DNA were higher than with any other method giving an average yield of 8.5 µg/100 mg biomass.

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A combined data matrix consisting of high performance liquid chromatography–diode array detector (HPLC–DAD) and inductively coupled plasma-mass spectrometry (ICP-MS) measurements of samples from the plant roots of the Cortex moutan (CM), produced much better classification and prediction results in comparison with those obtained from either of the individual data sets. The HPLC peaks (organic components) of the CM samples, and the ICP-MS measurements (trace metal elements) were investigated with the use of principal component analysis (PCA) and the linear discriminant analysis (LDA) methods of data analysis; essentially, qualitative results suggested that discrimination of the CM samples from three different provinces was possible with the combined matrix producing best results. Another three methods, K-nearest neighbor (KNN), back-propagation artificial neural network (BP-ANN) and least squares support vector machines (LS-SVM) were applied for the classification and prediction of the samples. Again, the combined data matrix analyzed by the KNN method produced best results (100% correct; prediction set data). Additionally, multiple linear regression (MLR) was utilized to explore any relationship between the organic constituents and the metal elements of the CM samples; the extracted linear regression equations showed that the essential metals as well as some metallic pollutants were related to the organic compounds on the basis of their concentrations

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Recent advances in direct-use plasmonic-metal nanoparticles (NPs) as photocatalysts to drive organic synthesis reactions under visible-light irradiation have attracted great interest. Plasmonic-metal NPs are characterized by their strong interaction with visible light through excitation of the localized surface plasmon resonance (LSPR). Herein, we review recent developments in direct photocatalysis using plasmonic-metal NPs and their applications. We focus on the role played by the LSPR of the metal NPs in catalyzing organic transformations and, more broadly, the role that light irradiation plays in catalyzing the reactions. Through this, the reaction mechanisms that these light-excited energetic electrons promote will be highlighted. This review will be of particular interest to researchers who are designing and fabricating new plasmonic-metal NP photocatalysts by identifying important reaction mechanisms that occur through light irradiation.

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The orientational distribution of a set of stable nitroxide radicals in aligned liquid crystals 5CB (nematic) and 8CB (smectic A) was studied in detail by numerical simulation of EPR spectra. The order parameters up to the 10th rank were measured. The directions of the principal orientation axes of the radicals were determined. It was shown that the ordering of the probe molecules is controlled by their interaction with the matrix molecules more than the inherent geometry of the probes themselves. The rigid fused phenanthrene-based (A5) and 2-azaphenalene (A4) nitroxides as well as the rigid core elongated C11 and 5α-cholestane (CLS) nitroxides were found to be most sensitive to the orientation of the liquid crystal matrixes.

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Supported nanoparticles (NPs) of nonplasmonic transition metals (Pd, Pt, Rh, and Ir) are widely used as thermally activated catalysts for the synthesis of important organic compounds, but little is known about their photocatalytic capabilities. We discovered that irradiation with light can significantly enhance the intrinsic catalytic performance of these metal NPs at ambient temperatures for several types of reactions. These metal NPs strongly absorb the light mainly through interband electronic transitions. The excited electrons interact with the reactant molecules on the particles to accelerate these reactions. The rate of the catalyzed reaction depends on the concentration and energy of the excited electrons, which can be increased by increasing the light intensity or by reducing the irradiation wavelength. The metal NPs can also effectively couple thermal and light energy sources to more efficiently drive chemical transformations.

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A method for the determination of imidacloprid in paddy water and soil was developed using liquid chromatography electrospray ionization-tandem mass spectrometry (LC/ESI-MS/MS). Separation of imidacloprid was carried out on a Shimadzu C18 column (150 mm × 4.6 mm, 4.6 μm) with an acetonitrile?water (50 : 50, v/v) mobile phase containing 0.1% of acetic acid. The flow rate was 0.3 mL/min in isocratic mode. The product ion at 209 m/z was selected for quantification in multiple-reaction monitoring scan mode. Imidacloprid residues in soil were extracted by a solid-liquid extraction method with acetonitrile. Water samples were filtered and directly injected for analysis without extraction. Detection limits of 0.5 μg/kg and 0.3 μg/L were achieved for soil and water samples, respectively. The method had recoveries of 90 ± 2% (n = 4) for soil samples and 100 ± 2% (n = 4) for water samples. A linear relationship was observed throughout the investigated range of concentrations (1-200 μg/L), with the correlation coefficients ranging from 0.999 to 1.000. © Pleiades Publishing, Ltd., 2010.

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A method for determination of tricyclazole in water using solid phase extraction and high performance liquid chromatography (HPLC) with UV detection at 230nm and a mobile phase of acetonitrile:water (20:80, v/v) was developed. A performance comparison between two types of solid phase sorbents, the C18 sorbent of Supelclean ENVI-18 cartridge and the styrene-divinyl benzene copolymer sorbent of Sep-Pak PS2-Plus cartridge was conducted. The Sep-Pak PS2-Plus cartridges were found more suitable for extracting tricyclazole from water samples than the Supelclean ENVI-18 cartridges. For this cartridge, both methanol and ethyl acetate produced good results. The method was validated with good linearity and with a limit of detection of 0.008gL-1 for a 500-fold concentration through the SPE procedure. The recoveries of the method were stable at 80% and the precision was from 1.1-6.0% within the range of fortified concentrations. The validated method was also applied to measure the concentrations of tricyclazole in real paddy water.

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Introduction Decreased water displacement following increased neural activity has been observed using diffusion-weighted functional MRI (DfMRI) at high b-values. The physiological mechanisms underlying the diffusion signal change may be unique from the standard blood oxygenation level-dependent (BOLD) contrast and closer to the source of neural activity. Whether DfMRI reflects neural activity more directly than BOLD outside the primary cerebral regions remains unclear. Methods Colored and achromatic Mondrian visual stimuli were statistically contrasted to functionally localize the human color center Area V4 in neurologically intact adults. Spatial and temporal properties of DfMRI and BOLD activation were examined across regions of the visual cortex. Results At the individual level, DfMRI activation patterns showed greater spatial specificity to V4 than BOLD. The BOLD activation patterns were more prominent in the primary visual cortex than DfMRI, where activation was localized to the ventral temporal lobe. Temporally, the diffusion signal change in V4 and V1 both preceded the corresponding hemodynamic response, however the early diffusion signal change was more evident in V1. Conclusions DfMRI may be of use in imaging applications implementing cognitive subtraction paradigms, and where highly precise individual functional localization is required.

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Background Exposure to air pollutants, including diesel particulate matter, has been linked to adverse respiratory health effects. Inhaled diesel particulate matter contains adsorbed organic compounds. It is not clear whether the adsorbed organics or the residual components are more deleterious to airway cells. Using a physiologically relevant model, we investigated the role of diesel organic content on mediating cellular responses of primary human bronchial epithelial cells (HBECs) cultured at an air-liquid interface (ALI). Methods Primary HBECs were cultured and differentiated at ALI for at least 28 days. To determine which component is most harmful, we compared primary HBEC responses elicited by residual (with organics removed) diesel emissions (DE) to those elicited by neat (unmodified) DE for 30 and 60 minutes at ALI, with cigarette smoke condensate (CSC) as the positive control, and filtered air as negative control. Cell viability (WST-1 cell proliferation assay), inflammation (TNF-α, IL-6 and IL-8 ELISA) and changes in gene expression (qRT-PCR for HO-1, CYP1A1, TNF-α and IL-8 mRNA) were measured. Results Immunofluorescence and cytological staining confirmed the mucociliary phenotype of primary HBECs differentiated at ALI. Neat DE caused a comparable reduction in cell viability at 30 or 60 min exposures, whereas residual DE caused a greater reduction at 60 min. When corrected for cell viability, cytokine protein secretion for TNF-α, IL-6 and IL-8 were maximal with residual DE at 60 min. mRNA expression for HO-1, CYP1A1, TNF-α and IL-8 was not significantly different between exposures. Conclusion This study provides new insights into epithelial cell responses to diesel emissions using a physiologically relevant aerosol exposure model. Both the organic content and residual components of diesel emissions play an important role in determining bronchial epithelial cell response in vitro. Future studies should be directed at testing potentially useful interventions against the adverse health effects of air pollution exposure.