450 resultados para Surface Texture


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In recent years, the beauty leaf plant (Calophyllum Inophyllum) is being considered as a potential 2nd generation biodiesel source due to high seed oil content, high fruit production rate, simple cultivation and ability to grow in a wide range of climate conditions. However, however, due to the high free fatty acid (FFA) content in this oil, the potential of this biodiesel feedstock is still unrealized, and little research has been undertaken on it. In this study, transesterification of beauty leaf oil to produce biodiesel has been investigated. A two-step biodiesel conversion method consisting of acid catalysed pre-esterification and alkali catalysed transesterification has been utilized. The three main factors that drive the biodiesel (fatty acid methyl ester (FAME)) conversion from vegetable oil (triglycerides) were studied using response surface methodology (RSM) based on a Box-Behnken experimental design. The factors considered in this study were catalyst concentration, methanol to oil molar ratio and reaction temperature. Linear and full quadratic regression models were developed to predict FFA and FAME concentration and to optimize the reaction conditions. The significance of these factors and their interaction in both stages was determined using analysis of variance (ANOVA). The reaction conditions for the largest reduction in FFA concentration for acid catalysed pre-esterification was 30:1 methanol to oil molar ratio, 10% (w/w) sulfuric acid catalyst loading and 75 °C reaction temperature. In the alkali catalysed transesterification process 7.5:1 methanol to oil molar ratio, 1% (w/w) sodium methoxide catalyst loading and 55 °C reaction temperature were found to result in the highest FAME conversion. The good agreement between model outputs and experimental results demonstrated that this methodology may be useful for industrial process optimization for biodiesel production from beauty leaf oil and possibly other industrial processes as well.

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Realistic virtual models of leaf surfaces are important for a number of applications in the plant sciences, such as modelling agrichemical spray droplet movement and spreading on the surface. In this context, the virtual surfaces are required to be sufficiently smooth to facilitate the use of the mathematical equations that govern the motion of the droplet. While an effective approach is to apply discrete smoothing D2-spline algorithms to reconstruct the leaf surfaces from three-dimensional scanned data, difficulties arise when dealing with wheat leaves that tend to twist and bend. To overcome this topological difficulty, we develop a parameterisation technique that rotates and translates the original data, allowing the surface to be fitted using the discrete smoothing D2-spline methods in the new parameter space. Our algorithm uses finite element methods to represent the surface as a linear combination of compactly supported shape functions. Numerical results confirm that the parameterisation, along with the use of discrete smoothing D2-spline techniques, produces realistic virtual representations of wheat leaves.

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The surface of cubic silicon carbide (3C-SiC) hetero-epitaxial films grown on the (111) surface of silicon is a promising template for the subsequent epitaxial growth of III-V semiconductor layers and graphene. We investigate growth and post-growth approaches for controlling the surface roughness of epitaxial SiC to produce an optimal template. We first explore 3C-SiC growth on various degrees of offcut Si(111) substrates, although we observe that the SiC roughness tends to worsen as the degree of offcut increases. Hence we focus on post-growth approaches available on full wafers, comparing chemical mechanical polishing (CMP) and a novel plasma smoothening process. The CMP leads to a dramatic improvement, bringing the SiC surface roughness down to sub-nanometer level, though removing about 200 nm of the SiC layer. On the other hand, our proposed HCl plasma process appears very effective in smoothening selectively the sharpest surface topography, leading up to 30% improvement in SiC roughness with only about 50 nm thickness loss. We propose a simple physical model explaining the action of the plasma smoothening.

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Enhanced catalytic performance of zeoltes via the plasmonic effect of gold nanoparticles has been discovered to be closely correlated with the molecular polarity of reactants. The intensified polarised electrostatic field of Na+ in NaY plays a critical role in stretching the C=O bond of aldehydes to improve the reaction rate.

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Abstract: Nanostructured titanium dioxide (TiO2) electrodes, prepared by anodization of titanium, are employed to probe the electron-transfer process of cytochrome b5 (cyt b5) by surface-enhanced resonance Raman (SERR) spectroscopy. Concomitant with the increased nanoscopic surface roughness of TiO2, achieved by raising the anodization voltage from 10 to 20 V, the enhancement factor increases from 2.4 to 8.6, which is rationalized by calculations of the electric field enhancement. Cyt b 5 is immobilized on TiO2 under preservation of its native structure but it displays a non-ideal redox behavior due to the limited conductivity of the electrode material. The electron-transfer efficiency which depends on the crystalline phase of TiO2 has to be improved by appropriate doping for applications in bioelectrochemistry. Nanostructured TiO2 electrodes are employed to probe the electron-transfer process of cytochrome b5 by surface-enhanced resonance Raman spectroscopy. Concomitant with the increased nanoscopic surface roughness of TiO2, the enhancement factor increases, which can be attributed to the electric field enhancement. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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Silver nanoparticles with identical plasmonic properties but different surface functionalities are synthesized and tested as chemically selective surface-enhanced resonance Raman (SERR) amplifiers in a two-component protein solution. The surface plasmon resonances of the particles are tuned to 413 nm to match the molecular resonance of protein heme cofactors. Biocompatible functionalization of the nanoparticles with a thin film of chitosan yields selective SERR enhancement of the anionic protein cytochrome b5, whereas functionalization with SiO2 amplifies only the spectra of the cationic protein cytochrome c. As a result, subsequent addition of the two differently functionalized particles yields complementary information on the same mixed protein sample solution. Finally, the applicability of chitosan-coated Ag nanoparticles for protein separation was tested by in situ resonance Raman spectroscopy.

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Silica coated Ag nanoparticles with defined surface plasmon resonances are used to selectively detect and analyze protein cofactors in solution and on interfaces via surface enhanced resonance Raman spectroscopy. The silica coating has a surprisingly small effect on optical amplification but minimizes unwanted interactions between the protein and the nanoparticle.

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Spontaneous adsorption of 1,8,15,22-tetraaminophthalocyanatocobalt(II) (4α-CoIITAPc) on glassy carbon (GC) electrode leads to the formation of a stable self-assembled monolayer (SAM). Since the SAM of 4α-CoIITAPc is redox active, its adsorption on GC electrode was followed by cyclic voltammetry. SAM of 4α-CoIITAPc on GC electrode shows two pairs of well-defined redox peaks corresponding to CoIII/CoII and CoIIIPc−1/CoIIIPc−2. The surface coverage (Γ) value, calculated by integrating the charge under CoII oxidation, was used to study the adsorption thermodynamics and kinetics of 4α-CoIITAPc on GC surface. Cyclic voltammetric studies show that the adsorption of 4α-CoIITAPc on GC electrode has reached the saturation coverage (Γs) within 3 h. The Γs value for the SAM of 4α-CoIITAPc on GC electrode was found to be 2.37 × 10−10 mol cm−2. Gibbs free energy (ΔGads) and adsorption rate constant (kad) for the adsorption of 4α-CoIITAPc on GC surface were found to be −16.76 kJ mol−1 and 7.1 M−1 s−1, respectively. The possible mechanism for the self-assembly of 4α-CoIITAPc on GC surface is through the addition of nucleophilic amines to the olefinic bond on the GC surface in addition to a meager contribution from π stacking. The contribution of π stacking was confirmed from the adsorption of unsubstituted phthalocyanatocobalt(II) (CoPc) on GC electrode. Raman spectra for the SAM of 4α-CoIITAPc on carbon surface shows strong stretching and breathing bands of Pc macrocycle, pyrrole ring and isoindole ring. Raman and CV studies suggest that 4α-CoIITAPc is adopting nearly a flat orientation or little bit tilted orientation.

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Self-assembled monolayer (SAM) of 1,8,15,22-tetraaminophthalocyanatocobalt(II) (4α-CoIITAPc) was prepared on indium tin oxide (ITO) electrode by spontaneous adsorption from dimethylformamide (DMF) solution containing 4α-CoIITAPc. The SAM of 4α-CoIITAPc formed on ITO electrode was characterized by cyclic voltammetry, Raman and UV–visible spectroscopic techniques. The cyclic voltammogram (CV) of 4α-CoIITAPc SAM shows two pairs of well-defined redox peaks corresponding to CoIII/CoII and CoIIIPc−1/CoIIIPc−2. The surface coverage (Γ) was calculated by integrating the charge under the anodic wave corresponding to CoII oxidation and it was found to be 2.25 × 10−10 mol cm−2. Raman spectrum obtained for the SAM of 4α-CoIITAPc on ITO surface shows strong stretching and breathing bands of Pc macrocycle, pyrrole ring and isoindole ring. Further, the –NH2 bending mode of vibration was absent for the SAM of 4α-CoIITAPc on ITO surface which indirectly confirmed that all the amino groups of 4α-CoIITAPc are involved in bonding with ITO surface. UV–visible spectrum for the SAM of 4α-CoIITAPc on ITO surface shows an intense B-band, Q-band and n–π∗ transition with slight broadening when compared to that of 4α-CoIITAPc in DMF.

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This paper demonstrates a renewed procedure for the quantification of surface-enhanced Raman scattering (SERS) enhancement factors with improved precision. The principle of this method relies on deducting the resonance Raman scattering (RRS) contribution from surface-enhanced resonance Raman scattering (SERRS) to end up with the surface enhancement (SERS) effect alone. We employed 1,8,15,22-tetraaminophthalocyanato-cobalt(II) (4α-CoIITAPc), a resonance Raman- and electrochemically redox-active chromophore, as a probe molecule for RRS and SERRS experiments. The number of 4α-CoIITAPc molecules contributing to RRS and SERRS phenomena on plasmon inactive glassy carbon (GC) and plasmon active GC/Au surfaces, respectively, has been precisely estimated by cyclic voltammetry experiments. Furthermore, the SERS substrate enhancement factor (SSEF) quantified by our approach is compared with the traditionally employed methods. We also demonstrate that the present approach of SSEF quantification can be applied for any kind of different SERS substrates by choosing an appropriate laser line and probe molecule.

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This article describes the detection of DNA mutations using novel Au-Ag coated GaN substrate as SERS (surface-enhanced Raman spectroscopy) diagnostic platform. Oligonucleotide sequences corresponding to the BCR-ABL (breakpoint cluster region-Abelson) gene responsible for development of chronic myelogenous leukemia were used as a model system to demonstrate the discrimination between the wild type and Met244Val mutations. The thiolated ssDNA (single-strand DNA) was immobilized on the SERS-active surface and then hybridized to a labeled target sequence from solution. An intense SERS signal of the reporter molecule MGITC was detected from the complementary target due to formation of double helix. The SERS signal was either not observed, or decreased dramatically for a negative control sample consisting of labeled DNA that was not complementary to the DNA probe. The results indicate that our SERS substrate offers an opportunity for the development of novel diagnostic assays.

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Texture enhancement is an important component of image processing that finds extensive application in science and engineering. The quality of medical images, quantified using the imaging texture, plays a significant role in the routine diagnosis performed by medical practitioners. Most image texture enhancement is performed using classical integral order differential mask operators. Recently, first order fractional differential operators were used to enhance images. Experimentation with these methods led to the conclusion that fractional differential operators not only maintain the low frequency contour features in the smooth areas of the image, but they also nonlinearly enhance edges and textures corresponding to high frequency image components. However, whilst these methods perform well in particular cases, they are not routinely useful across all applications. To this end, we apply the second order Riesz fractional differential operator to improve upon existing approaches of texture enhancement. Compared with the classical integral order differential mask operators and other first order fractional differential operators, we find that our new algorithms provide higher signal to noise values and superior image quality.