994 resultados para active infrared
Resumo:
Detailed investigation of an intermediate member of the reddingite–phosphoferrite series, using infrared and Raman spectroscopy, scanning electron microcopy and electron microprobe analysis, has been carried out on a homogeneous sample from a lithium-bearing pegmatite named Cigana mine, near Conselheiro Pena, Minas Gerais, Brazil. The determined formula is (Mn1.60Fe1.21Ca0.01Mg0.01)∑2.83(PO4)2.12⋅(H2O2.85F0.01)∑2.86 indicating predominance in the reddingite member. Raman spectroscopy coupled with infrared spectroscopy supports the concept of phosphate, hydrogen phosphate and dihydrogen phosphate units in the structure of reddingite-phosphoferrite. Infrared and Raman bands attributed to water and hydroxyl stretching modes are identified. Vibrational spectroscopy adds useful information to the molecular structure of reddingite–phosphoferrite.
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Determining the properties and integrity of subchondral bone in the developmental stages of osteoarthritis, especially in a form that can facilitate real-time characterization for diagnostic and decision-making purposes, is still a matter for research and development. This paper presents relationships between near infrared absorption spectra and properties of subchondral bone obtained from 3 models of osteoarthritic degeneration induced in laboratory rats via: (i) menisectomy (MSX); (ii) anterior cruciate ligament transaction (ACL); and (iii) intra-articular injection of mono-ido-acetate (1 mg) (MIA), in the right knee joint, with 12 rats per model group (N = 36). After 8 weeks, the animals were sacrificed and knee joints were collected. A custom-made diffuse reflectance NIR probe of diameter 5 mm was placed on the tibial surface and spectral data were acquired from each specimen in the wavenumber range 4000–12 500 cm− 1. After spectral acquisition, micro computed tomography (micro-CT) was performed on the samples and subchondral bone parameters namely: bone volume (BV) and bone mineral density (BMD) were extracted from the micro-CT data. Statistical correlation was then conducted between these parameters and regions of the near infrared spectra using multivariate techniques including principal component analysis (PCA), discriminant analysis (DA), and partial least squares (PLS) regression. Statistically significant linear correlations were found between the near infrared absorption spectra and subchondral bone BMD (R2 = 98.84%) and BV (R2 = 97.87%). In conclusion, near infrared spectroscopic probing can be used to detect, qualify and quantify changes in the composition of the subchondral bone, and could potentially assist in distinguishing healthy from OA bone as demonstrated with our laboratory rat models.
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Infrared spectroscopy has been used to characterize and compare four palygorskite mineral samples from China. The position of the main bands identified by infrared spectra is similar, but there are some differences in intensity, which are significant. In addition, several additional bands are observed in the spectra of palygorskite and their impurities. This variability is attributed to differences in the geological environment, such as the degree of weathering and the extent of transportation of the minerals during formation or deposition, and the impurity content in these palygorskites. The bands of water and hydroxyl groups in these spectra of palygorskite samples have been studied. The characteristic band of palygorskite is observed at 1195 cm�1. Another four bands observed at 3480, 3380, 3266 and 3190 cm�1 are attributed to the water molecules in the palygorskite structure. These results suggest that the infrared spectra of palygorskites mineral from different regions are decided not only by the main physicochemical properties of palygorskite, but also by the amount and kind of impurities.
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Current diagnostic methods for assessing the severity of articular cartilage degenerative conditions, such as osteoarthritis, are inadequate. There is also a lack of techniques that can be used for real-time evaluation of the tissue during surgery to inform treatment decision and eliminate subjectivity. This book, derived from Dr Afara’s doctoral research, presents a scientific framework that is based on near infrared (NIR) spectroscopy for facilitating the non-destructive evaluation of articular cartilage health relative to its structural, functional, and mechanical properties. This development is a component of the ongoing research on advanced endoscopic diagnostic techniques in the Articular Cartilage Biomechanics Research Laboratory of Professor Adekunle Oloyede at Queensland University of Technology (QUT), Brisbane Australia.
Resumo:
Several approaches have been introduced in the literature for active noise control (ANC) systems. Since the filtered-x least-mean-square (FxLMS) algorithm appears to be the best choice as a controller filter, researchers tend to improve performance of ANC systems by enhancing and modifying this algorithm. This paper proposes a new version of the FxLMS algorithm, as a first novelty. In many ANC applications, an on-line secondary path modeling method using white noise as a training signal is required to ensure convergence of the system. As a second novelty, this paper proposes a new approach for on-line secondary path modeling on the basis of a new variable-step-size (VSS) LMS algorithm in feed forward ANC systems. The proposed algorithm is designed so that the noise injection is stopped at the optimum point when the modeling accuracy is sufficient. In this approach, a sudden change in the secondary path during operation makes the algorithm reactivate injection of the white noise to re-adjust the secondary path estimate. Comparative simulation results shown in this paper indicate the effectiveness of the proposed approach in reducing both narrow-band and broad-band noise. In addition, the proposed ANC system is robust against sudden changes of the secondary path model.
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This paper proposes a self-tuning feedforward active noise control (ANC) system with online secondary path modeling. The step-size parameters of the controller and modeling filters have crucial rule on the system performance. In literature, these parameters are adjusted by trial-and-error. In other words, they are manually initialized before system starting, which require performing extensive experiments to ensure the convergence of the system. Hence there is no guarantee that the system could perform well under different situations. In the proposed method, the appropriate values for the step-sizes are obtained automatically. Computer simulation results indicate the effectiveness of the proposed method.
Resumo:
In practical cases for active noise control (ANC), the secondary path has usually a time varying behavior. For these cases, an online secondary path modeling method that uses a white noise as a training signal is required to ensure convergence of the system. The modeling accuracy and the convergence rate are increased when a white noise with a larger variance is used. However, the larger variance increases the residual noise, which decreases performance of the system and additionally causes instability problem to feedback structures. A sudden change in the secondary path leads to divergence of the online secondary path modeling filter. To overcome these problems, this paper proposes a new approach for online secondary path modeling in feedback ANC systems. The proposed algorithm uses the advantages of white noise with larger variance to model the secondary path, but the injection is stopped at the optimum point to increase performance of the algorithm and to prevent the instability effect of the white noise. In this approach, instead of continuous injection of the white noise, a sudden change in secondary path during the operation makes the algorithm to reactivate injection of the white noise to correct the secondary path estimation. In addition, the proposed method models the secondary path without the need of using off-line estimation of the secondary path. Considering the above features increases the convergence rate and modeling accuracy, which results in a high system performance. Computer simulation results shown in this paper indicate effectiveness of the proposed method.
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An analytical method for the detection of carbonaceous gases by a non-dispersive infrared sensor (NDIR) has been developed. The calibration plots of six carbonaceous gases including CO2, CH4, CO, C2H2, C2H4 and C2H6 were obtained and the reproducibility determined to verify the feasibility of this gas monitoring method. The results prove that squared correlation coefficients for the six gas measurements are greater than 0.999. The reproducibility is excellent, thus indicating that this analytical method is useful to determinate the concentrations of carbonaceous gases.
Resumo:
The mineral tooeleite Fe6(AsO3)4SO4(OH)4�4H2O is secondary ferric arsenite sulphate mineral which has environmental significance for arsenic remediation because of its high stability in the regolith. The mineral has been studied by X-ray diffraction (XRD), infrared (IR) and Raman spectroscopy. The XRD result indicates tooeleite can form more crystalline solids in an acid environment than in an alkaline environment. Infrared spectroscopy identifies moderately intense band at 773 cm�1 assigned to AsO3� 3 symmetric stretching vibration. Raman spectroscopy identifies three bands at 803, 758 and 661 cm�1 assigned to the symmetric and antisymmetric stretching vibrations of AsO3� 3 and As-OH stretching vibration respectively. In addition, the infrared bands observed at 1116, 1040, 1090, 981 and 616 cm�1, are assigned to the m3, m1 and m4 modes of SO2� 4 . The same bands are observed at 1287, 1085, 983 and 604 cm�1 in the Raman spectrum. As3d band at binding energy of 44.05 eV in XPS confirms arsenic valence of tooeleite is +3. These characteristic bands in the IR and Raman spectra provide useful basis for identifying the mineral tooeleite.
Resumo:
We have analyzed a frondelite mineral sample from the Cigana mine, located in the municipality of Conselheiro Pena, a well-known pegmatite in Brazil. In the Cigana pegmatite, secondary phosphates, namely eosphorite, fairfieldite, fluorapatite, frondelite, gormanite, hureaulite, lithiophilite, reddingite and vivianite are common minerals in miarolitic cavities and in massive blocks after triphylite. The chemical formula was determined as (Mn0.68, Fe0.32)(Fe3+)3,72(PO4)3.17(OH)4.99. The structure of the mineral was assessed using vibrational spectroscopy. Bands attributed to the stretching and bending modes of PO4 3- and HOPO3 3- units were identified. The observation of multiple bands supports the concept of symmetry reduction of the phosphate anion in the frondelite structure. Sharp Raman and infrared bands at 3581 cm−1 is assigned to the OH stretching vibration. Broad Raman bands at 3063, 3529 and 3365 cm−1 are attributed to water stretching vibrational modes.
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The mineral weloganite Na2Sr3Zr(CO3)6·3H2O has been studied by using vibrational spectroscopy and a comparison is made with the spectra of weloganite with other carbonate minerals. Weloganite is member of the mckelveyite group that includes donnayite-(Y) and mckelveyite-(Y). The Raman spectrum of weloganite is characterized by an intense band at 1082 cm−1 with shoulder bands at 1061 and 1073 cm−1, attributed to the View the MathML source symmetric stretching vibration. The observation of three symmetric stretching vibrations is very unusual. The position of View the MathML source symmetric stretching vibration varies with mineral composition. The Raman bands at 1350, 1371, 1385, 1417, 1526, 1546, and 1563 cm−1 are assigned to the ν3 (CO3)2− antisymmetric stretching mode. The observation of additional Raman bands for the ν3 modes for weloganite is significant in that it shows distortion of the carbonate anion in the mineral structure. The Raman band observed at 870 cm−1 is assigned to the (CO3)2− ν2 bending mode. Raman bands observed for weloganite at 679, 682, 696, 728, 736, 749, and 762 cm−1 are assigned to the (CO3)2− ν4 bending modes. A comparison of the vibrational spectra is made with that of the rare earth carbonates decrespignyite, bastnasite, hydroxybastnasite, parisite, and northupite.
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The mineral creedite is a fluorinated hydroxy hydrated sulphate of aluminium and calcium of formula Ca3Al2SO4(F,OH)·2H2O. The mineral has been studied by a combination of electron probe analysis to determine the molecular formula of the mineral and the structure assessed by vibrational spectroscopy. The spectroscopy of creedite may be compared with that of the alums. The Raman spectrum of creedite is characterised by an intense sharp band at 986 cm−1 assigned to the View the MathML source ν1 (Ag) symmetric stretching mode. Multiple bands of creedite in the antisymmetric stretching region support the concept of a reduction in symmetry of the sulphate anion. Multiple bands are also observed in the bending region with the three bands at 601, 629 and 663 cm−1 assigned to the View the MathML source ν4 (Ag) bending modes. The observation of multiple bands at 440, 457 and 483 cm−1 attributed to the View the MathML source ν2 (Bg) bending modes supports the concept that the symmetry of the sulphate is reduced by coordination to the water bonded to the Al3+ in the creedite structure. The splitting of the ν2, ν3 and ν4 modes is attributed to the reduction of symmetry of the SO4 and it is proposed that the sulphate coordinates to water in the hydrated aluminium in bidentate chelation.
Resumo:
The phosphate mineral leucophosphite K(Fe2)3þ(PO4)2(OH) · 2H2O has been characterized by SEM-EDS, Raman, and infrared spectro- scopic measurements. The mineral is predominantly a K and Fe phosphate with some minor substitution of Al in the Fe3þ site. Raman bands at 994 and 1058 cm-1 are assigned to the symmetric stretching modes of PO3- and HPO2- units. The Raman bands at 1104, 1135, and 1177 cm-1 are assigned to the PO3- and HPO2- antisymmetric stretching modes. Raman and infrared spectra in the 2600–3800 cm-1 region show a complex set of overlapping bands, which may be resolved into the component bands. The Raman bands observed at 3325, 3355, and 3456 cm-1 are attributed to water stretching vibrations, and in the infrared spectrum, bands at 3237, 3317, and 3453 cm-1 are assigned to water stretching bands.
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The conventional mechanical properties of articular cartilage, such as compressive stiffness, have been demonstrated to be limited in their capacity to distinguish intact (visually normal) from degraded cartilage samples. In this paper, we explore the correlation between a new mechanical parameter, namely the reswelling of articular cartilage following unloading from a given compressive load, and the near infrared (NIR) spectrum. The capacity to distinguish mechanically intact from proteoglycan-depleted tissue relative to the "reswelling" characteristic was first established, and the result was subsequently correlated with the NIR spectral data of the respective tissue samples. To achieve this, normal intact and enzymatically degraded samples were subjected to both NIR probing and mechanical compression based on a load-unload-reswelling protocol. The parameter δ(r), characteristic of the osmotic "reswelling" of the matrix after unloading to a constant small load in the order of the osmotic pressure of cartilage, was obtained for the different sample types. Multivariate statistics was employed to determine the degree of correlation between δ(r) and the NIR absorption spectrum of relevant specimens using Partial Least Squared (PLS) regression. The results show a strong relationship (R(2)=95.89%, p<0.0001) between the spectral data and δ(r). This correlation of δ(r) with NIR spectral data suggests the potential for determining the reswelling characteristics non-destructively. It was also observed that δ(r) values bear a significant relationship with the cartilage matrix integrity, indicated by its proteoglycan content, and can therefore differentiate between normal and artificially degraded proteoglycan-depleted cartilage samples. It is therefore argued that the reswelling of cartilage, which is both biochemical (osmotic) and mechanical (hydrostatic pressure) in origin, could be a strong candidate for characterizing the tissue, especially in regions surrounding focal cartilage defects in joints.
Resumo:
Abstract An assessment of the molecular structure of carletonite a rare phyllosilicate mineral with general chemical formula given as KNa4Ca4Si8O18(CO3)4(OH,F)·H2O has been undertaken using vibrational spectroscopy. Carletonite has a complex layered structure. Within one period of c, it contains a silicate layer of composition NaKSi8O18·H2O, a carbonate layer of composition NaCO3·0.5H2O and two carbonate layers of composition NaCa2CO3(F,OH)0.5. Raman bands are observed at 1066, 1075 and 1086 cm−1. Whether these bands are due to the CO32- ν1 symmetric stretching mode or to an SiO stretching vibration is open to question. Multiple bands are observed in the 300–800 cm−1 spectral region, making the attribution of these bands difficult. Multiple water stretching and bending modes are observed showing that there is much variation in hydrogen bonding between water and the silicate and carbonate surfaces.