980 resultados para Reflectance near infrared spectroscopy


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The resin phase of dental composites is mainly composed of combinations of dimethacrylate comonomers, with final polymeric network structure defined by monomer type/reactivity and degree of conversion. This fundamental study evaluates how increasing concentrations of the flexible triethylene glycol dimethacrylate (TEGDMA) influences void formation in bisphenol A diglycidyl dimethacrylate (BisGMA) co-polymerizations and correlates this aspect of network structure with reaction kinetic parameters and macroscopic volumetric shrinkage. Photopolymerization kinetics was followed in real-time by a near-infrared (NIR) spectroscopic technique, viscosity was assessed with a viscometer, volumetric shrinkage was followed with a linometer, free volume formation was determined by positron annihilation lifetime spectroscopy (PALS) and the sol-gel composition was determined by extraction with dichloromethane followed by (1)H NMR analysis. Results show that, as expected, volumetric shrinkage increases with TEGDMA concentration and monomer conversion. Extraction/(1)H NMR studies show increasing participation of the more flexible TEGDMA towards the limiting stages of conversion/crosslinking development. As the conversion progresses, either based on longer irradiation times or greater TEGDMA concentrations, the network becomes more dense, which is evidenced by the decrease in free volume and weight loss after extraction in these situations. For the same composition (BisGMA/TEGDMA 60-40 mol%) light-cured for increasing periods of time (from 10 to 600 s), free volume decreased and volumetric shrinkage increased, in a linear relationship with conversion. However, the correlation between free volume and macroscopic volumetric shrinkage was shown to be rather complex for variable compositions exposed for the same time (600 s). The addition of TEGDMA decreases free-volume up to 40 mol% (due to increased conversion), but above that concentration, in spite of the increase in conversion/crosslinking, free volume pore size increases due to the high concentration of the more flexible monomer. In those cases, the increase in volumetric shrinkage was due to higher functional group concentration, in spite of the greater free volume. Therefore, through the application of the PALS model, this study elucidates the network formation in dimethacrylates commonly used in dental materials. (C) 2010 Elsevier Ltd. All rights reserved.

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Free radical bulk copolymerization of methyl methacrylate (MMA) and allyl acetate (AAc) has been investigated using electron spin resonance (ESR) and FT-near infrared (FTNIR) spectroscopy. Data are used to evaluate the rate constants. The mole fraction of AAc plays an important role in the copolymerization of these two monomers. AAc not only delays the Trommsdorff effect but also increases the onset of percentage total conversion at which the Trommsdorff region begins. With AAc fraction 0.5 and higher, no Trommsdorff effect was observed. Inclusion of AAc into copolymer structure mainly occurs in the Trommsdorf region or when the AAc fraction in the comonomer feed is dominant. This is associated with a drop in the concentration of propagating radicals. However, ESR spectra indicate that the MMA propagating radical is predominant during the reaction. In the comonomer mixtures where a Trommsdorff region can be observed, the addition of AAc does not produce any significant change in k(p) and k(t) in the steady state region. Major changes in k(p) and k(t) are observed after the gel point and glassy state, respectively. (C) 2001 Society of Chemical Industry.

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The molecular orientation in a conventionally extruded PVC pipe, a uniaxially oriented PVC pipe and a biaxially oriented PVC pipe has been studied via Infrared dichroism. The degree of order or crystallinity has also been studied by Differential Scanning Calorimetry and also via Infrared Spectroscopy. The fundamental structural difference between the conventional and oriented pipes was that polymer chains were preferentially aligning in the hoop direction for oriented pipes whereas they were fairly isotropic in the conventional pipe with a slight preferential alignment in the axial direction. Analysis of the C-Cl stretching mode indicated that the uniaxially oriented pipe had much higher alignment of the C-Cl bond in the axial direction than the biaxial pipe, which correlates with higher fracture toughness for circumferential cracking in the biaxial pipe. Both DSC and Infrared spectroscopy detected little change in the crystallinity or order in the oriented pipes compared to the conventionally extruded pipes. (C) 2002 Kluwer Academic Publishers.

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The radio frequency (RF) plasma-modified surfaces of kaolinite were investigated by diffuse reflectance infrared Fourier transform spectroscopy (DRIFT) and deuteration techniques to determine the nature of RF plasma-induced surface functional groups, the altered sites in the lattice, and interaction mechanism between RF plasma and the surface of the kaolinite. It has been concluded that the RF plasma-induced infrared (IR) vibration absorption bands at 2805, 3010, and 3100 cm(-1) are attributable to the stretching vibration of hydrogen-bonded hydroxyl groups, and the band at 1407 cm(-1) is attributable to the bending vibration of (HO-)Al-O or (HO-)Si-O groupings with hydrogen-bonded hydroxyl groups. Structural alteration occurred on both the surface and subsurface region of the kaolinite during RF plasma treatment. Further structural alteration or adjustment was also observed on well-modified and well-deuterated kaolinite. There are two types of OD bands visible in the DRIFT spectra of this kaolinite, one type which decreased rapidly as a function of time in moist air, and the other which remained unchanged during the measurement. Furthermore, the appearance of broad IR bands at 3500-3100 cm(-1) as a result of deuteration is evidence of structural disturbance by RF plasma treatment lattice deuteration. An RF plasma-induced hydrogen bonding model on the surface of the kaolinite is proposed.

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Visible range to telecom band spectral translation is accomplished using an amorphous SiC pi'n/pin wavelength selector under appropriate front and back optical light bias. Results show that background intensity works as selectors in the infrared region, shifting the sensor sensitivity. Low intensities select the near-infrared range while high intensities select the visible part according to its wavelength. Here, the optical gain is very high in the infrared/red range, decreases in the green range, stays close to one in the blue region and strongly decreases in the near-UV range. The transfer characteristics effects due to changes in steady state light intensity and wavelength backgrounds are presented. The relationship between the optical inputs and the output signal is established. A capacitive optoelectronic model is presented and tested using the experimental results. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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A chromatographic separation of active ingredients of Combivir, Epivir, Kaletra, Norvir, Prezista, Retrovir, Trivizir, Valcyte, and Viramune is performed on thin layer chromatography. The spectra of these nine drugs were recorded using the Fourier transform infrared spectroscopy. This information is then analyzed by means of the cosine correlation. The comparison of the infrared spectra in the perspective of the adopted similarity measure is possible to visualize with present day computer tools, and the emerging clusters provide additional information about the similarities of the investigated set of complex drugs.

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Hyperspectral remote sensing exploits the electromagnetic scattering patterns of the different materials at specific wavelengths [2, 3]. Hyperspectral sensors have been developed to sample the scattered portion of the electromagnetic spectrum extending from the visible region through the near-infrared and mid-infrared, in hundreds of narrow contiguous bands [4, 5]. The number and variety of potential civilian and military applications of hyperspectral remote sensing is enormous [6, 7]. Very often, the resolution cell corresponding to a single pixel in an image contains several substances (endmembers) [4]. In this situation, the scattered energy is a mixing of the endmember spectra. A challenging task underlying many hyperspectral imagery applications is then decomposing a mixed pixel into a collection of reflectance spectra, called endmember signatures, and the corresponding abundance fractions [8–10]. Depending on the mixing scales at each pixel, the observed mixture is either linear or nonlinear [11, 12]. Linear mixing model holds approximately when the mixing scale is macroscopic [13] and there is negligible interaction among distinct endmembers [3, 14]. If, however, the mixing scale is microscopic (or intimate mixtures) [15, 16] and the incident solar radiation is scattered by the scene through multiple bounces involving several endmembers [17], the linear model is no longer accurate. Linear spectral unmixing has been intensively researched in the last years [9, 10, 12, 18–21]. It considers that a mixed pixel is a linear combination of endmember signatures weighted by the correspondent abundance fractions. Under this model, and assuming that the number of substances and their reflectance spectra are known, hyperspectral unmixing is a linear problem for which many solutions have been proposed (e.g., maximum likelihood estimation [8], spectral signature matching [22], spectral angle mapper [23], subspace projection methods [24,25], and constrained least squares [26]). In most cases, the number of substances and their reflectances are not known and, then, hyperspectral unmixing falls into the class of blind source separation problems [27]. Independent component analysis (ICA) has recently been proposed as a tool to blindly unmix hyperspectral data [28–31]. ICA is based on the assumption of mutually independent sources (abundance fractions), which is not the case of hyperspectral data, since the sum of abundance fractions is constant, implying statistical dependence among them. This dependence compromises ICA applicability to hyperspectral images as shown in Refs. [21, 32]. In fact, ICA finds the endmember signatures by multiplying the spectral vectors with an unmixing matrix, which minimizes the mutual information among sources. If sources are independent, ICA provides the correct unmixing, since the minimum of the mutual information is obtained only when sources are independent. This is no longer true for dependent abundance fractions. Nevertheless, some endmembers may be approximately unmixed. These aspects are addressed in Ref. [33]. Under the linear mixing model, the observations from a scene are in a simplex whose vertices correspond to the endmembers. Several approaches [34–36] have exploited this geometric feature of hyperspectral mixtures [35]. Minimum volume transform (MVT) algorithm [36] determines the simplex of minimum volume containing the data. The method presented in Ref. [37] is also of MVT type but, by introducing the notion of bundles, it takes into account the endmember variability usually present in hyperspectral mixtures. The MVT type approaches are complex from the computational point of view. Usually, these algorithms find in the first place the convex hull defined by the observed data and then fit a minimum volume simplex to it. For example, the gift wrapping algorithm [38] computes the convex hull of n data points in a d-dimensional space with a computational complexity of O(nbd=2cþ1), where bxc is the highest integer lower or equal than x and n is the number of samples. The complexity of the method presented in Ref. [37] is even higher, since the temperature of the simulated annealing algorithm used shall follow a log( ) law [39] to assure convergence (in probability) to the desired solution. Aiming at a lower computational complexity, some algorithms such as the pixel purity index (PPI) [35] and the N-FINDR [40] still find the minimum volume simplex containing the data cloud, but they assume the presence of at least one pure pixel of each endmember in the data. This is a strong requisite that may not hold in some data sets. In any case, these algorithms find the set of most pure pixels in the data. PPI algorithm uses the minimum noise fraction (MNF) [41] as a preprocessing step to reduce dimensionality and to improve the signal-to-noise ratio (SNR). The algorithm then projects every spectral vector onto skewers (large number of random vectors) [35, 42,43]. The points corresponding to extremes, for each skewer direction, are stored. A cumulative account records the number of times each pixel (i.e., a given spectral vector) is found to be an extreme. The pixels with the highest scores are the purest ones. N-FINDR algorithm [40] is based on the fact that in p spectral dimensions, the p-volume defined by a simplex formed by the purest pixels is larger than any other volume defined by any other combination of pixels. This algorithm finds the set of pixels defining the largest volume by inflating a simplex inside the data. ORA SIS [44, 45] is a hyperspectral framework developed by the U.S. Naval Research Laboratory consisting of several algorithms organized in six modules: exemplar selector, adaptative learner, demixer, knowledge base or spectral library, and spatial postrocessor. The first step consists in flat-fielding the spectra. Next, the exemplar selection module is used to select spectral vectors that best represent the smaller convex cone containing the data. The other pixels are rejected when the spectral angle distance (SAD) is less than a given thresh old. The procedure finds the basis for a subspace of a lower dimension using a modified Gram–Schmidt orthogonalizati on. The selected vectors are then projected onto this subspace and a simplex is found by an MV T pro cess. ORA SIS is oriented to real-time target detection from uncrewed air vehicles using hyperspectral data [46]. In this chapter we develop a new algorithm to unmix linear mixtures of endmember spectra. First, the algorithm determines the number of endmembers and the signal subspace using a newly developed concept [47, 48]. Second, the algorithm extracts the most pure pixels present in the data. Unlike other methods, this algorithm is completely automatic and unsupervised. To estimate the number of endmembers and the signal subspace in hyperspectral linear mixtures, the proposed scheme begins by estimating sign al and noise correlation matrices. The latter is based on multiple regression theory. The signal subspace is then identified by selectin g the set of signal eigenvalue s that best represents the data, in the least-square sense [48,49 ], we note, however, that VCA works with projected and with unprojected data. The extraction of the end members exploits two facts: (1) the endmembers are the vertices of a simplex and (2) the affine transformation of a simplex is also a simplex. As PPI and N-FIND R algorithms, VCA also assumes the presence of pure pixels in the data. The algorithm iteratively projects data on to a direction orthogonal to the subspace spanned by the endmembers already determined. The new end member signature corresponds to the extreme of the projection. The algorithm iterates until all end members are exhausted. VCA performs much better than PPI and better than or comparable to N-FI NDR; yet it has a computational complexity between on e and two orders of magnitude lower than N-FINDR. The chapter is structure d as follows. Section 19.2 describes the fundamentals of the proposed method. Section 19.3 and Section 19.4 evaluate the proposed algorithm using simulated and real data, respectively. Section 19.5 presents some concluding remarks.

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Este trabalho descreve o desenvolvimento de um material sensor para creatinina por impressão molecular em estrutura polimérica (MIP) e a sua aplicação no desenvolvimento de um dispositivo de natureza potenciométrica para a determinação da molécula alvo em fluidos biológicos. A creatinina é um dos biomarcadores mais utilizados no acompanhamento da doença renal, já que é um bom indicador da taxa de filtração glomerular (TFG). Os materiais biomiméticos desenhados para interação com a creatinina foram obtidos por polimerização radicalar, recorrendo a monómeros de ácido metacríclico ou de vinilpiridina e a um agente de reticulação apropriado. De modo a aferir o efeito da impressão da creatinina na resposta dos materiais MIP à sua presença, foram também preparados e avaliados materiais de controlo, obtidos sem impressão molecular (NIP). O controlo da constituição química destes materiais, incluindo a extração da molécula impressa, foi realizado por Espectroscopia de Raman e de Infravermelho com Transformada de Fourrier. A afinidade de ligação entre estes materiais e a creatinina foi também avaliada com base em estudos cinéticos. Todos os materiais descritos foram integrados em membranas selectivas de elétrodos seletivos de ião, preparadas sem ou com aditivo iónico lipófilo, de carga negativa ou positiva. A avaliação das características gerais de funcionamento destes elétrodos, em meios de composição e pH diferentes, indicaram que as membranas com materiais impressos e aditivo aniónico eram as únicas com utilidade analítica. Os melhores resultados foram obtidos em solução tampão Piperazine-N,N′-bis(2- ethanesulfonic acid), PIPES, de pH 2,8, condição que permitiu obter uma resposta quasi-Nernstiana, a partir de 1,6×10-5 mol L-1. Estes elétrodos demonstraram ainda uma boa selectividade ao apresentaram uma resposta preferencial para a creatinina quando na presença de ureia, carnitina, glucose, ácido ascórbico, albumina, cloreto de cálcio, cloreto de potássio, cloreto de sódio e sulfato de magnésio. Os elétrodos foram ainda aplicados com sucesso na análise de amostras sintéticas de urina, quando os materiais sensores eram baseados em ácido metacrilico, e soro, quando os materiais sensores utilizados eram baseados em vinilpiridina.

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The purpose of this study was to develop a bone substitute material capable of preventing or treating osteomyelitis through a sustainable release of vancomycin and simultaneously inducing bone regeneration. Porous heparinized nanohydroxyapatite (nanoHA)/collagen granules were characterized using scanning electron microscopy, micro-computed tomography and attenuated total reflectance Fourier transform infrared spectroscopy. After vancomycin adsorption onto the granules, its releasing profile was studied by UV molecular absorption spectroscopy. The heparinized granules presented a more sustainable release over time, in comparison with nonheparinized nanoHA and nanoHA/collagen granules. Vancomycin was released for 360 h and proved to be bioactive until 216 h. Staphylococcus aureus adhesion was higher on granules containing collagen, guiding the bacteria to the material with antibiotic, improving their eradication. Moreover, cytotoxicity of the released vancomycin was assessed using osteoblast cultures, and after 14 days of culture in the presence of vancomycin, cells were able to remain viable, increasing their metabolic activity and colonizing the granules, as observed by scanning electron microscopy and confocal laser scanning microscopy. These findings suggest that heparinized nanoHA/collagen granules are a promising material to improve the treatment of osteomyelitis, as they are capable of releasing vancomycin, eliminating the bacteria, and presented morphological and chemical characteristics to induce bone regeneration.

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CH, Chitosan; HPMC, (Hydroxypropyl)methyl cellulose; FT, Freeze-thaw; SC, Solvent casting; CH:HPMC (X:Y), pH Z, FT/SC, Chitosan and (hydroxypropyl)methyl cellulose hydrogel, at X and Y proportion (0-100), at Z pH (3.0-4.0) and prepared by freeze-thaw or solvent casting techniques; DSC, Differential scanning calorimetry; MDSC, Temperature modulated Differential scanning calorimetry; Tg, glass transition temperature; ΔH, enthalpy change; TGA, Thermogravimetric Analysis; TG, Thermogravimetry; DTG, Derivative or Differential thermogravimetry; σ, Tensile strength; ε, elongation at break; DMA, Dynamic mechanical analysis; X-Ray, X-radiation, FTIR-ATR, Attenuated total reflectance Fourier transform infrared spectroscopy; SEM, Scanning electron microscopy.

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CH, Chitosan; HPMC, (Hydroxypropyl)methyl cellulose; FT, Freeze-thaw; SC, Solvent casting; CH:HPMC (X:Y), pH Z, FT/SC, Chitosan and (hydroxypropyl)methyl cellulose hydrogel, at X and Y proportion (0-100), at Z pH (3.0-4.0) and prepared by freeze-thaw or solvent casting techniques; DSC, Differential scanning calorimetry; MDSC, Temperature modulated Differential scanning calorimetry; Tg, glass transition temperature; ΔH, enthalpy change; TGA, Thermogravimetric Analysis; TG, Thermogravimetry; DTG, Derivative or Differential thermogravimetry; σ, Tensile strength; ε, elongation at break; DMA, Dynamic mechanical analysis; X-Ray, X-radiation, FTIR-ATR, Attenuated total reflectance Fourier transform infrared spectroscopy; SEM, Scanning electron microscopy.

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Dissertação de mestrado integrado em Engenharia Civil