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Journal articles on the topic 'Spectral mixtures'
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1
Lo, Su-Chin, and Chris W. Brown. "Infrared Spectral Search for Mixtures in Medium-Size Libraries." Applied Spectroscopy 45, no. 10 (December 1991): 1621–27. http://dx.doi.org/10.1366/0003702914335256.
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A new algorithm is presented for searching medium-size infrared spectral libraries for the components in spectra of mixtures. The algorithm treats the spectra in the library as an m-component quantitative analysis problem in which each of the library spectra represents a standard mixture having a concentration of 1.0 for that component. Principal component regression (PCR) is used to reduce the dimensionality of the problem and to provide the regression coefficients for determining pseudo-concentrations or composition indices (CI) in mixtures. The PCR analysis is followed by the application of an adaptive filter to remove all similarity of the first target component from the mixture and from a selected subgroup of the library. This is followed by a second PCR analysis on the modified spectral data to identify the next target compound. If the correct target components are selected with successive applications of the adaptive filter, the residuals will approach zero. All components in five two- and three-component mixtures were correctly identified by this new Mix-Match algorithm, whereas only two of the five mixtures were completely identified by a typical dot-product search routine.
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Ducasse, Etienne, Karine Adeline, Xavier Briottet, Audrey Hohmann, Anne Bourguignon, and Gilles Grandjean. "Montmorillonite Estimation in Clay–Quartz–Calcite Samples from Laboratory SWIR Imaging Spectroscopy: A Comparative Study of Spectral Preprocessings and Unmixing Methods." Remote Sensing 12, no. 11 (May 27, 2020): 1723. http://dx.doi.org/10.3390/rs12111723.
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Clay minerals play an important role in shrinking–swelling of soils and off–road vehicle mobility mainly due to the presence of smectites including montmorillonites. Since soils are composed of different minerals intimately mixed, an accurate estimation of its abundance is challenging. Imaging spectroscopy in the short wave infrared spectral region (SWIR) combined with unmixing methods is a good candidate to estimate clay mineral abundance. However, the performance of unmixing methods is mineral-dependent and may be enhanced by using appropriate spectral preprocessings. The objective of this paper is to carry out a comparative study in order to determine the best couple spectral preprocessing/unmixing method to quantify montmorillonite in intimate mixtures with clays, such as montmorillonite, kaolinite and illite, and no-clay minerals, such as calcite and quartz. To this end, a spectral database is built with laboratory hyperspectral imagery from 51 dry pure mineral samples and intimate mineral mixtures of controlled abundances. Six spectral preprocessings, standard normal variate (SNV), continuum removal (CR), continuous wavelet transform (CWT), Hapke model, first derivative (1st SGD) and pseudo–absorbance (Log(1/R)), are applied and compared with reflectance spectra. Two linear unmixing methods, fully constrained least square method (FCLS) and multiple endmember spectral mixture analysis (MESMA), and two non-linear unmixing methods, generalized bilinear method (GBM) and multi-linear model (MLM), are compared. Global results showed that the benefit of spectral preprocessings occurs when spectral absorption features of minerals overlap for SNV, CR, CWT and 1st SGD, whereas the use of reflectance spectra performs the best when no overlap is present. With one mineral having no spectral feature (quartz), montmorillonite abundance estimation is difficult and gives RMSE higher than 50%. For the other mixtures, performances of linear and non-linear unmixing methods are similar. Consequently, the recommended couple spectral preprocessing/unmixing method based on the trade-off between its simplicity and performance is 1st SGD/FCLS for clay binary and ternary mixtures (RMSE of 9.2% for montmorillonite–illite mixtures, 13.9% for montmorillonite–kaolinite mixtures and 10.8% for montmorillonite–illite–kaolinite mixtures) and reflectance/FCLS for binary mixtures with calcite (RMSE of 8.8% for montmorillonite–calcite mixtures). These performances open the way to improve the classification of expansive soils.
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Brown, Chris W., Anne E. Okafor, Steven M. Donahue, and Su-Chin Lo. "UV-Visible Spectral Library Search with Mixtures." Applied Spectroscopy 49, no. 7 (July 1995): 1022–27. http://dx.doi.org/10.1366/0003702953964723.
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A library mixture search method originally developed for infrared spectra has been successfully applied to UV-visible spectra. This novel approach for searching a spectral library performs a principal component analysis (PCA) on the entire library of spectra for pure compounds. The library spectra are represented by their PCA scores, and the concentrations (assumed to be unity) are regressed onto these scores. The scores for an unknown spectrum projected onto the PCA basis set are multiplied by the regression matrix to predict pseudo-concentrations or composition indices. After the first pass through the library, a subgroup of the top 20 hits (10% of the library) is selected and the PCR analysis is repeated on this set to improve the selection process. Spectra of each of the individual target components are adaptively filtered from the subgroup of library spectra and from the unknown spectrum prior to the repeat of the PCR analysis. The application of the adaptive filter greatly improves the success rate on hitting the second and third components by removing the first hit during each pass through the library. Computation times for training and applying the Mix-Match algorithm are greatly reduced by pre-processing with Fourier Transforms. A 200-compound library could be trained in 45 min and searched in 9 s; a 20-compound subgroup could be adaptively filtered and searched in 37 s. Both components in 12 two-component mixtures and one component in each of two two-component mixtures were correctly identified; the algorithm failed on both components in only one out of 15 two-component mixtures. All three components were correctly identified in one three-component mixture, and one component was correctly identified in another three-component mixture.
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Magazù, S., E. Calabrò, and M. T. Caccamo. "Experimental Study of Thermal Restraint in Bio-Protectant Disaccharides by FTIR Spectroscopy." Open Biotechnology Journal 12, no. 1 (July 31, 2018): 123–33. http://dx.doi.org/10.2174/1874070701812010123.
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Background: In the present paper, InfraRed (IR) spectra on water mixtures of two homologous disaccharides, i.e. sucrose and trehalose, as a function of temperature have been collected. Methods: In particular, IR spectra were registered, in the spectral range from 4000 cm-1 to 400 cm-1, to investigate the thermal response of the water mixtures of two homologous disaccharides, through positive thermal scans, i.e. by increasing the temperature from the value of 25°C to the value of 50°C. The OH-stretching region has been analyzed by means of two simple and straightforward procedures, i.e. by evaluating the shift of the intramolecular OH stretching center frequency and the Spectral Distance (SD). Result and Conclusion: Both the analyses indicate that trehalose water mixture have a higher thermal response than that of the sucrose-water mixture.
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Anastasiadis, Johannes, and Michael Heizmann. "GAN-regularized augmentation strategy for spectral datasets." tm - Technisches Messen 89, no. 4 (February 5, 2022): 278–88. http://dx.doi.org/10.1515/teme-2021-0109.
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Abstract Artificial neural networks are used in various fields including spectral unmixing, which is used to determine the proportions of substances involved in a mixture, and achieve promising results. This is especially true if there is a non-linear relationship between the spectra of mixtures and the spectra of the substances involved (pure spectra). To achieve sufficient results, neural networks need lots of representative training data. We present a method that extends existing training data for spectral unmixing consisting of spectra of mixtures by learning the mixing characteristic using an artificial neural network. Spectral variability is considered by random inputs. The network structure used is a generative adversarial net that takes the dependence on the abundances of pure substances into account by an additional term in its objective function, which is minimized during training. After training further data for abundance vectors for which there is no real measurement data in the original training dataset can be generated. A neural network trained with the augmented training dataset shows better performance in spectral unmixing compared to being trained with the original dataset. The presented network structure improves already existing results obtained with a generative convolutional neural network, which is superior to model-based approaches.
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Golyak, I. S., E. R. Kareva, I. L. Fufurin, D. R. Anfimov, A. V. Scherbakova, A. O. Nebritova, P. P. Demkin, and A. N. Morozov. "Numerical methods of spectral analysis of multicomponent gas mixtures and human exhaled breath." Computer Optics 46, no. 4 (August 2022): 650–58. http://dx.doi.org/10.18287/2412-6179-co-1058.
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In this paper, the application of machine learning and deep learning in the spectral analysis of multicomponent gas mixtures is considered. The experimental setup consists of a quantum cascade laser with a tuning range of 5.3–12.8 µm, a peak power of up to 150 mW, and an astigmatic Herriott gas cell with an optical path length of up to 76 m. Acetone, ethanol, methanol, and their mixtures are used as test substances. For the detection and clustering of substances, including molecular biomarkers, methods of machine learning, such as stochastic embedding of neighbors with a t-distribution, principal component analysis and classification methods, such as random forest, gradient boosting, and logistic regression, are proposed. A shallow convolutional neural network based on TensorFlow (Google) and Keras is used for the spectral analysis of gas mixtures. Model spectra of substances are used as a training sample, and model and experimental spectra are used as a test sample. It is shown that neural networks trained on model spectra (NIST database) can recognize substances in experimental gas mixtures. We propose using machine learning methods for clustering and classification of pure substances and gas mixtures and neural networks for the identification of gas mixture components. Using the experimental setup described, the experimentally obtained concentration limits are 80 ppb for acetone and 100–120 ppb for ethanol and methanol. The possibility of using the proposed methods for analyzing spectra of human exhaled air is shown, which is significant for biomedical applications.
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Lo, Su-Chin, and Chris W. Brown. "Infrared Spectral Search for Mixtures in Large-Size Libraries." Applied Spectroscopy 45, no. 10 (December 1991): 1628–32. http://dx.doi.org/10.1366/0003702914335111.
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A routine for searching large spectral libraries with spectra of mixtures is presented. The dimensionality of a 3169-compound library is reduced to 12% of its original size by using Fourier transform compression and principal component analysis. A principal component regression is performed and used as a prefilter in selecting spectra having features (and chemical groups) similar to those of the unknown mixture. A dot-product metric is then used to identify a target component from the subgroup formed by the prefilter. This is followed by the application of an adaptive filter to remove the similarity of the target component from the subgroup and from the unknown mixture; the search is repeated on the modified data. Successive applications of the adaptive filter will produce minimum residuals if the correct identifications are made. Once the residuals are minimized, a similarity index is calculated to determine the closeness of the unknown mixture spectrum to a spectrum reconstructed from the library spectra. Four out of five two- and three-component spectra were correctly identified. One of the two components in the fifth mixture was correctly identified, and the residual values flagged the improper identification of the second component. After the adaptive filter was applied to the entire library, the second component was correctly identified. Results for this new algorithm are compared to those from four more traditional search routines, which were only completely successful on one of the unknown mixtures.
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Nyden, Marc R., and Krishnan Chittur. "Component Spectrum Reconstruction from Partially Characterized Mixtures." Applied Spectroscopy 43, no. 1 (January 1989): 123–28. http://dx.doi.org/10.1366/0003702894201743.
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A mathematical analysis of some existing approaches to component spectrum reconstruction is presented. This analysis leads to the derivation of a generalization of the cross-correlation technique. The effectiveness of these methods is assessed from the quality of the reconstructions obtained with the use of synthetic mixture spectra. Reconstructions of the spectra of the components of aqueous mixtures of immunoglobulin G and albumin are compared to the corresponding spectral reconstructions of the pure proteins in buffer.
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Ciarniello, Mauro, Lyuba V. Moroz, Olivier Poch, Vassilissa Vinogradoff, Pierre Beck, Batiste Rousseau, Istiqomah Istiqomah, et al. "VIS-IR Spectroscopy of Mixtures of Water Ice, Organic Matter, and Opaque Mineral in Support of Small Body Remote Sensing Observations." Minerals 11, no. 11 (November 3, 2021): 1222. http://dx.doi.org/10.3390/min11111222.
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Visual-to-infrared (VIS-IR) remote sensing observations of different classes of outer solar system objects indicate the presence of water ice and organics. Here, we present laboratory reflectance spectra in the 0.5–4.2 μm spectral range of binary particulate mixtures of water ice, organics analogue (kerite), and an opaque iron sulphide phase (pyrrhotite) to investigate the spectral effects of varying mixing ratios, endmember grain size, and mixing modality. The laboratory spectra are also compared to different implementations of the Hapke reflectance model (Hapke, 2012). We find that minor amounts (≲1 wt%) of kerite (investigated grain sizes of 45–63 μm and <25 μm) can remain undetected when mixed in coarse-grained (67 ± 31 μm) water ice, suggesting that organics similar to meteoritic insoluble organic matter (IOM) might be characterized by larger detectability thresholds. Additionally, our measurements indicate that the VIS absolute reflectance of water ice-containing mixtures is not necessarily monotonically linked to water ice abundance. The latter is better constrained by spectral indicators such as the band depths of water ice VIS-IR diagnostic absorptions and spectral slopes. Simulation of laboratory spectra of intimate mixtures with a semi-empirical formulation of the Hapke model suggests that simplistic assumptions on the endmember grain size distribution and shape may lead to estimated mixing ratios considerably offset from the nominal values. Finally, laboratory spectra of water ice grains with fine-grained pyrrhotite inclusions (intraparticle mixture) have been positively compared with a modified version of the Hapke model from Lucey and Riner (2011).
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Kulko, Roman-David, Alexander Pletl, Andreas Hanus, and Benedikt Elser. "Detection of Plastic Granules and Their Mixtures." Sensors 23, no. 7 (March 24, 2023): 3441. http://dx.doi.org/10.3390/s23073441.
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Chemically pure plastic granulate is used as the starting material in the production of plastic parts. Extrusion machines rely on purity, otherwise resources are lost, and waste is produced. To avoid losses, the machines need to analyze the raw material. Spectroscopy in the visible and near-infrared range and machine learning can be used as analyzers. We present an approach using two spectrometers with a spectral range of 400–1700 nm and a fusion model comprising classification, regression, and validation to detect 25 materials and proportions of their binary mixtures. one dimensional convolutional neural network is used for classification and partial least squares regression for the estimation of proportions. The classification is validated by reconstructing the sample spectrum using the component spectra in linear least squares fitting. To save time and effort, the fusion model is trained on semi-empirical spectral data. The component spectra are acquired empirically and the binary mixture spectra are computed as linear combinations. The fusion model achieves very a high accuracy on visible and near-infrared spectral data. Even in a smaller spectral range from 400–1100 nm, the accuracy is high. The visible and near-infrared spectroscopy and the presented fusion model can be used as a concept for building an analyzer. Inexpensive silicon sensor-based spectrometers can be used.
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Sinha Roy, Aritro, and Madhur Srivastava. "Unsupervised Analysis of Small Molecule Mixtures by Wavelet-Based Super-Resolved NMR." Molecules 28, no. 2 (January 13, 2023): 792. http://dx.doi.org/10.3390/molecules28020792.
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Resolving small molecule mixtures by nuclear magnetic resonance (NMR) spectroscopy has been of great interest for a long time for its precision, reproducibility, and efficiency. However, spectral analyses for such mixtures are often highly challenging due to overlapping resonance lines and limited chemical shift windows. The existing experimental and theoretical methods to produce shift NMR spectra in dealing with the problem have limited applicability owing to sensitivity issues, inconsistency, and/or the requirement of prior knowledge. Recently, we resolved the problem by decoupling multiplet structures in NMR spectra by the wavelet packet transform (WPT) technique. In this work, we developed a scheme for deploying the method in generating highly resolved WPT NMR spectra and predicting the composition of the corresponding molecular mixtures from their 1H NMR spectra in an automated fashion. The four-step spectral analysis scheme consists of calculating the WPT spectrum, peak matching with a WPT shift NMR library, followed by two optimization steps in producing the predicted molecular composition of a mixture. The robustness of the method was tested on an augmented dataset of 1000 molecular mixtures, each containing 3 to 7 molecules. The method successfully predicted the constituent molecules with a median true positive rate of 1.0 against the varying compositions, while a median false positive rate of 0.04 was obtained. The approach can be scaled easily for much larger datasets.
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Boutonnat, M., D. A. Gilmore, K. A. Keilbach, N. Oliphant, and G. H. Atkinson. "Photoacoustic Detection of Formaldehyde as a Minority Component in Gas Mixtures." Applied Spectroscopy 42, no. 8 (November 1988): 1520–24. http://dx.doi.org/10.1366/0003702884429797.
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Concentrations of H2CO in the part-per-billion by volume (ppbv) range are determined in gaseous mixtures containing large excesses of NO2 CH3CHO, and N2 by the use of photoacoustic spectroscopy (PAS). Mixtures containing H2CO as a minority component are prepared by gas permeation methods and examined by pulsed laser PAS in the ultraviolet and visible spectral regions. The relative concentrations of the major components of each mixture are an order of magnitude or more larger than the H2CO component under study. PA spectra with 0.5-cm−1 resolution in the 302.5–303.8 nm region are presented in Fig. 3 and are used to identify spectral signatures needed for selective detection. The dependence of PA signals on concentration is determined separately for each of the three polyatomic components in samples with N2. An experimental protocol for quantitatively measuring H2CO concentrations near 50 ppbv in NO2, CH3CHO, and N2 mixtures is described.
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Thomas, O. E., O. A. Adegoke, F. G. Adenmosun, and O. J. Abiodun. "Preferential Solvation of 4-Carboxyl-2, 6-Dinitrophenylazohydroxynaphthalenes in Mixed Hydroxylic Solvents." Nigerian Journal of Pharmaceutical Research 17, no. 1 (August 12, 2021): 1–13. http://dx.doi.org/10.4314/njpr.v17i1.1.
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Background: The applications of a group of 4-carboxyl-2,6-dintrophenylazohydroxynaphathalenes, AZ-01 to 04, as colourants, chemosensors or synthetic intermediates have been limited by their solubility.Aim: To investigate the effect of solvent mixture composition on the solubility, solution thermodynamics and position of equilibrium processes of the dyes.Method: The UV-visible spectral patterns of the dyes in binary mixtures including Methanol:Water, Ethanol:Water, Methanol:Ethanol, Methanol:Propan-1-ol, Methanol:Propan-2-ol, Propan-1-ol:Water and Propan-2-ol:Water were acquired. The type and quantitative estimation of solute-solvent interactions at play were determined by fitting spectral patterns to solvent parameters using multilinear regression.Results: Preferential solvation was detected by the non-ideality of the plots of E12 as against the mole fractions of co-solvent in all binary mixtures. In pure solvents, the spectral shifts of AZ-01, 03 and 04, which exist predominantly in the hydrazone form, were affected by polarity of solvent milieu while solvent basicity and acidity, in that order, were the significant parameters for AZ-02. In aqueous alcoholic mixtures, solvent polarity was contributory, although to different degrees, to the observed spectral data of the four dyes. However, solvent acidity and basicity were the primary determinants of spectral shifts observed with AZ-04 and AZ-03 respectively. Spectra-structure relationships identified the formation of the charged hydrazone tautomer which requires stabilisation by polar solvent milieu as responsible for the observed trend. In addition, interactions between new aggregated solvent-solvent species and the propionic acid substituent present in AZ-03 contributed to its spectral shifts.Conclusion: The solvatochromic properties of the phenylazonaphthalene series in binary mixtures have been successfully studied.
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Blanco, M., J. Coello, H. Iturriaga, S. Maspoch, and M. Redon. "Principal Component Regression for Mixture Resolution in Control Analysis by UV-Visible Spectrophotometry." Applied Spectroscopy 48, no. 1 (January 1994): 37–43. http://dx.doi.org/10.1366/0003702944027633.
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The potential of principal component regression (PCR) for mixture resolution by UV-visible spectrophotometry was assessed. For this purpose, a set of binary mixtures with Gaussian bands was simulated, and the influence of spectral overlap on the precision of quantification was studied. Likewise, the results obtained in the resolution of a mixture of components with extensively overlapped spectra were investigated in terms of spectral noise and the criterion used to select the optimal number of principal components. The model was validated by cross-validation, and the number of significant principal components was determined on the basis of four different criteria. Three types of noise were considered: intrinsic instrumental noise, which was modeled from experimental data provided by an HP 8452A diode array spectrophotometer; constant baseline shifts; and baseline drift. Introducing artificial baseline alterations in some samples of the calibration matrix was found to increase the reliability of the proposed method in routine analysis. The method was applied to the analysis of mixtures of Ti, AI, and Fe by resolving the spectra of their 8-hydroxyquinoline complexes previously extracted into chloroform.
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Belyakov, M. V., E. A. Nikitin, and I. Yu Efremenkov. "Efficiency of the Photoluminescent Method for Monitoring the Homogeneity of Feed Mixtures in Animal Husbandry." Agricultural Machinery and Technologies 16, no. 3 (October 2, 2022): 55–61. http://dx.doi.org/10.22314/2073-7599-2022-16-3-55-61.
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The spectral evaluation systems for controlling the feed mixtures homogeneity were analyzed. (Research purpose) To study the optical luminescent properties of the feed mixtures main components in the ultraviolet and visible range and develop a method for their photoluminescent quality control. (Materials and methods) Two groups of feed mixture components were studied: granular compound feed and corn silage. The spectral characteristics were measured by Fluorat-02-Panorama spectrofluorimeter. The synchronous scanning helped to identify the excitation spectra and, on their basis, the photoluminescence spectra were determined according to a previously tested technique. (Results and discussion) The components excitation spectra revealed the main maxima of 362 nanometers and 424 nanometers. All the photoluminescence characteristics proved to be single-modal, for each excitation wavelength, the measured curves are qualitatively similar, but differ quantitatively: for example, the difference in the compound feed and light silage flows is 2.4 times at a length of 232 nanometers, 2.8 times at 424 nanometers and 3.8 times at 362 nanometers. It is advisable to use 362-nanometer wavelength radiation to excite the experimental sample of the feed mixture, and to record photoluminescence within the range of 390-540 nanometers. The method of express quality control of mixing includes the following stages: initial calibration by the compound feed luminescence, sample preparation, mixture luminescence excitation, the luminescence flux registration, photo signal amplifiation and processing according to diagnostic algorithms, followed by either feed distribution or sequel mixing with repeated express control. (Conclusions) The proposed method for assessing the quality of mixing the feed mixture components can be implemented using a compact spectral device. It was found that the use of the proposed method in the technological process of preparing the feed mixture will reduce the energy costs.
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Vacque, V., N. Dupuy, B. Sombret, J. P. Huvenne, and P. Legrand. "Self-Modeling Mixture Analysis Applied to FT-Raman Spectral Data of Hydrogen Peroxide Activation by Nitriles." Applied Spectroscopy 51, no. 3 (March 1997): 407–15. http://dx.doi.org/10.1366/0003702971940288.
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In the analytical environment, spectral data resulting from analysis of samples often represent mixtures of several components. Extraction of information about pure components of these kinds of mixtures is a major problem, especially when reference spectra are not available or when unstable intermediates are formed. Self-modeling multivariate mixture analysis has been developed for this type of problem. In this paper two examples will be used to show the potential of this technique coupled with FT-Raman spectroscopy to elucidate reaction mechanisms and to follow in situ the kinetics of chemical transformations.
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Wei, Weiwei, Yuxuan Liao, Yufei Wang, Shaoqi Wang, Wen Du, Hongmei Lu, Bo Kong, Huawu Yang, and Zhimin Zhang. "Deep Learning-Based Method for Compound Identification in NMR Spectra of Mixtures." Molecules 27, no. 12 (June 7, 2022): 3653. http://dx.doi.org/10.3390/molecules27123653.
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Nuclear magnetic resonance (NMR) spectroscopy is highly unbiased and reproducible, which provides us a powerful tool to analyze mixtures consisting of small molecules. However, the compound identification in NMR spectra of mixtures is highly challenging because of chemical shift variations of the same compound in different mixtures and peak overlapping among molecules. Here, we present a pseudo-Siamese convolutional neural network method (pSCNN) to identify compounds in mixtures for NMR spectroscopy. A data augmentation method was implemented for the superposition of several NMR spectra sampled from a spectral database with random noises. The augmented dataset was split and used to train, validate and test the pSCNN model. Two experimental NMR datasets (flavor mixtures and additional flavor mixture) were acquired to benchmark its performance in real applications. The results show that the proposed method can achieve good performances in the augmented test set (ACC = 99.80%, TPR = 99.70% and FPR = 0.10%), the flavor mixtures dataset (ACC = 97.62%, TPR = 96.44% and FPR = 2.29%) and the additional flavor mixture dataset (ACC = 91.67%, TPR = 100.00% and FPR = 10.53%). We have demonstrated that the translational invariance of convolutional neural networks can solve the chemical shift variation problem in NMR spectra. In summary, pSCNN is an off-the-shelf method to identify compounds in mixtures for NMR spectroscopy because of its accuracy in compound identification and robustness to chemical shift variation.
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Dagg, I. R., A. Anderson, S. Yan, W. Smith, C. G. Joslin, and L. A. A. Read. "The quadrupole moment of cyanogen: a comparative study of collision-induced absorption in gaseous C2N2, CO2, and mixtures with argon." Canadian Journal of Physics 64, no. 11 (November 1, 1986): 1475–81. http://dx.doi.org/10.1139/p86-261.
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The collision-induced spectra of C2N2 gas and a gaseous mixture of C2N2 and Ar at 298 K have been obtained in the spectral region below 120 cm−1 using far-infrared laser and microwave techniques as well as a Fourier-transform spectrometer. In addition, the collision-induced spectra of a gaseous mixture of CO2 and Ar are reported at temperatures of 233 and 298 K in the spectral region below 230 cm−1. The theoretical values for the spectral moments α1 and γ1 for CO2 are much smaller than the experimental values, as expected for a molecule with a relatively large quadrupole moment. However, for CO2–Ar mixtures, the agreement between the theoretically and experimentally determined spectral moments is relatively good, resulting in a value of 4.6 B for the quadrupole moment of CO2 instead of the generally accepted value of 4.3 B. The quadrupole moment of C2N2 is estimated to be 6.2 ± 0.4 B from our data and the theory for the spectral moments, if a correction is made for an overestimate of the quadrupole moment similar to that obtained for the CO2–Ar mixture. This value is considerably smaller than a previously reported calculated result of 9.0 B. Line-shape expressions based on information theory (IT6) do not yield good agreement with experiment, a result that is attributed to the large anisotropy of the molecules.
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Lo, Su-Chin, and Chris W. Brown. "Near-Infrared Mixture Identification by an Automated Library Searching Method: A Multivariate Approach." Applied Spectroscopy 46, no. 5 (May 1992): 790–96. http://dx.doi.org/10.1366/0003702924124646.
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A mathematical technique for the identification of components in the near-infrared spectra of liquid mixtures without any prior chemical information is demonstrated. Originally, the technique was developed for searching mid-infrared spectral libraries. It utilizes principal component analysis to generate an orthonormal reference library and to compute the projections or scores of a mixture spectrum onto the principal space spanned by the orthonormal set. Both library and mixture spectra are analyzed and processed in Fourier domain to enhance the searching performance. A calibration matrix is calculated from library scores and is used to predict the mixture composition. Five liquid mixtures were correctly identified with the use of the calibration algorithm, whereas only one mixture was correctly characterized with a straight dot-product metric. The predictions were verified with the use of an adaptive filter to remove each of the resulting components from the library and the mixture spectra. In addition, a similarity index between the original mixture spectrum and a regenerated mixture spectrum is used as a final confirmation of the predictions. The effects of random noise on the searching method were also examined, and further enhancements of searching performance are suggested for identifying poor-quality mixture spectra.
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Malinina, Antonina. "Spectroscopic diagnostics of a high-frequency dielectric barrier discharge of atmospheric pressure in mixtures of cadmium diiodide vapor with neon and small additions of xenon." Journal of Technological and Space Plasmas 1, no. 1 (November 16, 2020): 45–53. http://dx.doi.org/10.31281/jtsp.v1i1.14.
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Diagnostics of the emission spectra of a gas-discharge plasma of a barrier discharge of atmospheric pressure in mixtures of cadmium diiodide vapor with neon and small additions of xenon is carried out. A gas-discharge plasma was created and the components of the working mixture were excited by a high-frequency barrier discharge at a sinusoidal voltage pulse repetition rate of up to 140 kHz. Emission of exciplex molecules of cadmium monoiodide with a maximum emission at a wavelength of λ = 655 nm and xenon iodide with a maximum of radiation at wavelengths λ = 253 and λ = 320 nm, excimer molecules of iodine, lines of atoms of cadmium, iodine, neon and xenon was revealed. It was found that at temperatures of the mixtures under study above 150 0C, the predominance of radiation from exciplex molecules of cadmium monoiodide is observed. The reason for the increased brightness of the emission of exciplex molecules of cadmium monoiodide in mixtures of cadmium diiodide vapor with neon and xenon additive is established. The regularities in the spectral characteristics of radiation in the mixtures under study are discussed. A high-frequency barrier discharge of atmospheric pressure in mixtures of cadmium diiodide vapor with neon and xenon is of interest for creating a multi-wavelength excilamp in the UV and visible spectral ranges
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Hu, Xiaoyi, Te Jiang, Pei Ma, Hao Zhang, Paul Lucey, and Menghua Zhu. "A Spectral Library Study of Mixtures of Common Lunar Minerals and Glass." Remote Sensing 15, no. 8 (April 21, 2023): 2195. http://dx.doi.org/10.3390/rs15082195.
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Reflectance spectroscopy is a powerful tool to remotely identify the mineral and chemical compositions of the lunar regolith. The lunar soils contain silicate minerals with prominent absorption features and glasses with much less distinctive spectral features. The accuracy of mineral abundance retrieval may be affected by the presence of glasses. In this work, we construct a spectral library of mixtures of major lunar-type minerals and synthetic glasses with varying relative abundances and test their performance on mineral abundance retrievals. By matching the library spectra with the spectra of mineral mixtures with known abundances, we found that the accuracy of mineral abundance retrieval can be improved by including glass as an endmember. Although our method cannot identify the abundance of glasses quantitatively, the presence or absence of glasses in the mixtures can be decisively determined.
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Tzeng, W. B., K. Narayanan, and G. C. Chang. "Simultaneous Detection of C6H5NHD, C6H5ND2, C6D5NH2, C6D5NHD, and C6D5ND2 by Resonant Two-Photon Ionization Mass Spectrometry." Applied Spectroscopy 52, no. 6 (June 1998): 890–93. http://dx.doi.org/10.1366/0003702981944445.
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The resonant two-photon ionization (R2PI) spectra of jet-cooled C6H5NH2, C6H5NHD, C6H5ND2, C6D5NH2, C6D5NHD, and C6D5ND2 resulting from the S1← S0 electronic transition have been simultaneously recorded in three different sample mixtures. New data on C6H5NHD and C6D5NHD are presented for the first time. The observed R2PI spectral bands of these species are successfully assigned on the basis of observed frequency shifts in some vibrational modes of deuterated species and calculated ab initio values. On the basis of mass separation and optical spectral analyses, this method provides an unambiguous means for the simultaneous and selective detection of isotopically substituted anilines presented in the mixture.
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Erskine, Steven R., Brett M. Quencer, and Kenneth R. Beebe. "Rapid Optical Purity Determination Using Chiral Spectroscopy, Achiral Spectroscopy, and Multivariate Analysis." Applied Spectroscopy 49, no. 11 (November 1995): 1682–91. http://dx.doi.org/10.1366/0003702953965849.
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A chemometric approach for determining enantiomeric purity from chirally sensitive spectral measurements such as circular dichroism (CD) in combination with conventional absorbance spectra has been demonstrated. This approach can be used to monitor process streams to ensure enantiomeric purity of chiral products without the need for chromatographic separation. The approach taken in this paper is a combination of the information available from conventional absorbance spectra, such as UV-Vis or IR, with that obtained by less prominent measurements which are sensitive to optical activity, such as circular dichroism or optical rotatory dispersion (ORD). By coupling these methods, one can obtain information about the concentrations of the desired components in a mixture as well as their enantiomeric purity. This information can be extracted from a number of optically active or optically inactive components simultaneously with the use of readily available multivariate analysis tools such as partial least-squares (PLS) or principal components regression (PCR), a feature unavailable with previously demonstrated single-wavelength measurements. This paper will focus on data from a set of test mixtures to evaluate the accuracy of predictions and to assess the best approach to predict the enantiomeric purities of the test mixtures. Three different mathematical approaches were used, and the results were compared to determine the best method for evaluating this type of data. In addition, the efficiency of this method for predicting enantiomer concentrations in complex mixtures was tested. Partial least-squares was shown to yield the most accurate prediction of the concentrations of even a complex mixture containing similar compounds with nearly indistinguishable spectral features.
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Chung, Hoeil, Mark A. Arnold, Martin Rhiel, and David W. Murhammer. "Simultaneous Measurements of Glucose, Glutamine, Ammonia, Lactate, and Glutamate in Aqueous Solutions by Near-Infrared Spectroscopy." Applied Spectroscopy 50, no. 2 (February 1996): 270–76. http://dx.doi.org/10.1366/0003702963906447.
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Calibration models are generated and evaluated for the measurement of five different components in synthetic mixtures prepared in aqueous solutions. Mixtures of glucose, glutamine, ammonia, lactate, and glutamate were prepared to simulate concentration levels expected during routine bioreactor fermentation processes. Near-IR spectra were collected from these solutions over the spectral range from 5000 to 4000 cm−1. This spectral information was used to build individual multivariate calibration models for each analyte. Models were constructed on the basis of partial least-squares regression of raw and Fourier filtered absorbance spectra. Each analyte could be detected selectively with mean percent errors of prediction ranging from 4 to 8%.
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Генерал, А. А. "Оптическое излучение плазменных струй атмосферного давления, возбуждамых барьерным разрядом." Журнал технической физики 127, no. 11 (2019): 716. http://dx.doi.org/10.21883/os.2019.11.48504.41-19.
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In the spectral range 270–900 nm luminescence spectra experimentally investigated plasma jets formed a barrier discharge in atmospheric pressure in an argon-air mixtures, and helium-air. It is shown that the emission spectra generated by the plasma jets are mainly represented by electron-vibration transitions of the second positive system of neutral nitrogen molecules. The radiation powers of these mixtures are compared.
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Wetzler, Diana E., Carlos Chesta, Roberto Fernández-Prini, and Pedro F. Aramendía. "Dynamic solvatochromism in solvent mixtures." Pure and Applied Chemistry 73, no. 3 (January 1, 2001): 405–9. http://dx.doi.org/10.1351/pac200173030405.
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Solvatochromism and thermochromism of 4-aminophthalimide and 4-amino-N-methylphthalimide were studied by absorption and steady-state and time-resolved emission spectroscopy in solvent mixtures of tolueneethanol and tolueneacetonitrile at different temperatures. Emission spectra shift to the red upon addition of a polar solvent (PS) to toluene. Solvent mixtures show a much greater thermochromic shift to the blue in emission than the neat solvents. This is explained by the decrease in temperature of the exothermic association of the polar solvent to the excited state. Emission spectra are time dependent in solvent mixtures in the ns timescale. The time evolution of this emission is interpreted on the basis of the different solvation of the ground state and the emitting excited state. SternVolmer plots are obtained for the dependence of the spectral-shift characteristic time with [PS].
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Elaraby, Samar, Sherif M. Abuelenin, Adel Moussa, and Yasser M. Sabry. "Deep Learning on Synthesized Sensor Characteristics and Transmission Spectra Enabling MEMS-Based Spectroscopic Gas Analysis beyond the Fourier Transform Limit." Foundations 1, no. 2 (December 15, 2021): 304–17. http://dx.doi.org/10.3390/foundations1020022.
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Miniaturized Fourier transform infrared spectrometers serve emerging market needs in many applications such as gas analysis. The miniaturization comes at the cost of lower performance than bench-top instrumentation, especially for the spectral resolution. However, higher spectral resolution is needed for better identification of the composition of materials. This article presents a convolutional neural network (CNN) for 3X resolution enhancement of the measured infrared gas spectra using a Fourier transform infrared (FTIR) spectrometer beyond the transform limit. The proposed network extracts a set of high-dimensional features from the input spectra and constructs high-resolution outputs by nonlinear mapping. The network is trained using synthetic transmission spectra of complex gas mixtures and simulated sensor non-idealities such as baseline drifts and non-uniform signal-to-noise ratio. Ten gases that are relevant to the natural and bio gas industry are considered whose mixtures suffer from overlapped features in the mid-infrared spectral range of 2000–4000 cm−1. The network results are presented for both synthetic and experimentally measured spectra using both bench-top and miniaturized MEMS spectrometers, improving the resolution from 60 cm−1 to 20 cm−1 with a mean square error down to 2.4×10−3 in the transmission spectra. The technique supports selective spectral analysis based on miniaturized MEMS spectrometers.
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Heylen, Rob, and Paul Gader. "Nonlinear Spectral Unmixing With a Linear Mixture of Intimate Mixtures Model." IEEE Geoscience and Remote Sensing Letters 11, no. 7 (July 2014): 1195–99. http://dx.doi.org/10.1109/lgrs.2013.2288921.
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Wentzell, Peter D., Ji-Hong Wang, Leon F. Loucks, and Kelli M. Miller. "Article." Canadian Journal of Chemistry 76, no. 8 (August 1, 1998): 1144–55. http://dx.doi.org/10.1139/v98-128.
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A new procedure to extract spectral and concentration information for unknown components in a series of mixture spectra is described. The algorithm, a form of self-modeling curve resolution (SMCR), requires no assumptions about the mixture data except for linear additivity and non-negativity of component spectra, and non-negativity of concentrations. It provides permissible bands for the spectra and concentration profiles of individual components in the mixtures and is applicable to problems in chromatography, equilibrium studies, and kinetics, among others. The new method employs a nonlinear optimization procedure and is substantially more efficient than similar methods that have been previously reported. The SMCR algorithm is demonstrated by applying it to the autocatalytic oxidation of oxalic acid by permanganate in the presence of sulfuric acid. The reaction was monitored spectroscopically between 200 and 1000 nm under four different reaction conditions. Results verified the presence of two reaction intermediates previously proposed in the literature and confirmed their spectral properties. Concentration profiles for the intermediates are described.Key words: curve resolution, kinetics, chemometrics, permanganate, oxalic acid.
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Reeves, James B. "Solid-State Matrix Effects on Near-Infrared Spectra: Interactions of Glucose and Sucrose with Amylose, Amylopectin, Cellulose, and Starch—Implications for Near-Infrared Calibrations." Applied Spectroscopy 50, no. 2 (February 1996): 154–60. http://dx.doi.org/10.1366/0003702963906465.
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The objective of this work was to explore the question of how the interactions between carbohydrate monomers and polymers affect near-infrared spectra and to evaluate the implications of such effects with respect to the development of near-infrared calibrations. The effects of the presence of amylopectin, amylose, cellulose, and starch during the drying of glucose and sucrose on the resulting spectra were investigated. Sugars in various molar ratios with polymers were dried in a rotating mixer and then reground, and spectra from 10,000 to 4000 cm−1 were taken. In addition, spectra of identical mixtures prepared by mixing previously ground sugars and polymers were taken for comparison. Results on samples prepared either by simple mixing of sugars and carbohydrate polymers or by grinding mixtures produced by drying sugars in the presence of polymers indicated that interactions occur between the substances in question. Although simple mixtures of sugars with cellulose, amylose, amylopectin, or starch showed some spectral changes in the spectra of the sugars, in general, the spectra obtained by spectral subtraction were considerably more similar to those of the pure sugars than were those obtained for materials dried together.
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Garcı́a-Haro, F. J., M. A. Gilabert, and J. Meliá. "Extraction of Endmembers from Spectral Mixtures." Remote Sensing of Environment 68, no. 3 (June 1999): 237–53. http://dx.doi.org/10.1016/s0034-4257(98)00115-1.
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Tuncer, Enis. "Spectral density representation of dielectric mixtures." Applied Physics A 107, no. 3 (February 29, 2012): 575–82. http://dx.doi.org/10.1007/s00339-012-6832-7.
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Sharaf, Yasmine Ahmed, Adel Ehab Ibrahim, Sami El Deeb, and Rania Adel Sayed. "Green Chemometric Determination of Cefotaxime Sodium in the Presence of Its Degradation Impurities Using Different Multivariate Data Processing Tools; GAPI and AGREE Greenness Evaluation." Molecules 28, no. 5 (February 26, 2023): 2187. http://dx.doi.org/10.3390/molecules28052187.
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Four eco-friendly, cost-effective, and fast stability-indicating UV-VIS spectrophotometric methods were validated for cefotaxime sodium (CFX) determination either in the presence of its acidic or alkaline degradation products. The applied methods used multivariate chemometry, namely, classical least square (CLS), principal component regression (PCR), partial least square (PLS), and genetic algorithm-partial least square (GA-PLS), to resolve the analytes’ spectral overlap. The spectral zone for the studied mixtures was within the range from 220 to 320 nm at a 1 nm interval. The selected region showed severe overlap in the UV spectra of cefotaxime sodium and its acidic or alkaline degradation products. Seventeen mixtures were used for the models’ construction, and eight were used as an external validation set. For the PLS and GA-PLS models, a number of latent factors were determined as a pre-step before the modelsʹ construction and found to be three for the (CFX/acidic degradants) mixture and two for the (CFX/alkaline degradants) mixture. For GA-PLS, spectral points were minimized to around 45% of the PLS models. The root mean square errors of prediction were found to be (0.19, 0.29, 0.47, and 0.20) for the (CFX/acidic degradants) mixture and (0.21, 0.21, 0.21, and 0.22) for the (CFX/alkaline degradants) mixture for CLS, PCR, PLS, and GA-PLS, respectively, indicating the excellent accuracy and precision of the developed models. The linear concentration range was studied within 12–20 μg mL–1 for CFX in both mixtures. The validity of the developed models was also judged using other different calculated tools such as root mean square error of cross validation, percentage recoveries, standard deviations, and correlation coefficients, which indicated excellent results. The developed methods were also applied to the determination of cefotaxime sodium in marketed vials, with satisfactory results. The results were statistically compared to the reported method, revealing no significant differences. Furthermore, the greenness profiles of the proposed methods were assessed using the GAPI and AGREE metrics.
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Sun, Yan, Wensheng Cai, and Xueguang Shao. "Chemometrics: An Excavator in Temperature-Dependent Near-Infrared Spectroscopy." Molecules 27, no. 2 (January 11, 2022): 452. http://dx.doi.org/10.3390/molecules27020452.
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Temperature-dependent near-infrared (NIR) spectroscopy has been developed and taken as a powerful technique for analyzing the structure of water and the interactions in aqueous systems. Due to the overlapping of the peaks in NIR spectra, it is difficult to obtain the spectral features showing the structures and interactions. Chemometrics, therefore, is adopted to improve the spectral resolution and extract spectral information from the temperature-dependent NIR spectra for structural and quantitative analysis. In this review, works on chemometric studies for analyzing temperature-dependent NIR spectra were summarized. The temperature-induced spectral features of water structures can be extracted from the spectra with the help of chemometrics. Using the spectral variation of water with the temperature, the structural changes of small molecules, proteins, thermo-responsive polymers, and their interactions with water in aqueous solutions can be demonstrated. Furthermore, quantitative models between the spectra and the temperature or concentration can be established using the spectral variations of water and applied to determine the compositions in aqueous mixtures.
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Ronay, I., F. Kizel, and R. Lati. "THE EFFECT OF SPECTRAL MIXTURES ON WEED SPECIES CLASSIFICATION." ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences V-3-2022 (May 17, 2022): 477–84. http://dx.doi.org/10.5194/isprs-annals-v-3-2022-477-2022.
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Abstract. Site-specific weed management (SSWM) is a precise and resource-efficient approach that can result in more productive and sustainable agricultural practices. SSWM requires weed maps, in which the vegetation-related pixels are segmented from the soil and other substances and then classified into crops and different weed species. Such classification with a high spatial resolution is significant for SSWM since preventing economic losses due to weeds requires making management decisions at meter scales. In this regard, hyperspectral sensors can capture leaf anatomy and biochemistry variations, suggesting many advantages for weed classification. However, the typical tradeoff between spectral and spatial resolution poses a challenge for applying hyperspectral imaging in large scales and scenarios of high densities and tiny seedlings at early growth due to mixed pixels. Mixture analysis methods were previously demonstrated to offer opportunities for dealing with mixed pixels in vegetation ecology and agriculture. Nonetheless, they were not widely utilized for weed classification. This study aims to reveal the impact of the spectral mixture on classification results using supervised classification, spectral unmixing, and spatial analysis. We attempted to characterize how the spectral mixture of different weed species and soil at different growth stages affects classification results. Our results suggest that spectral mixtures are probably a significant factor driving misclassifications when classifying weed species. Their effect can be characterized by spatial analysis and fractions obtained by spectral unmixing. We assume that the subpixel information provided by the fraction maps may add information about the spectral mixture that can assist in interpreting misclassification pixels alongside the widely used confusion matrix. This contribution is highly relevant at coarser spatial resolutions.
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Groß, S., M. Esselborn, B. Weinzierl, M. Wirth, A. Fix, and A. Petzold. "Aerosol classification by airborne high spectral resolution lidar observations." Atmospheric Chemistry and Physics 13, no. 5 (March 5, 2013): 2487–505. http://dx.doi.org/10.5194/acp-13-2487-2013.
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Abstract. During four aircraft field experiments with the DLR research aircraft Falcon in 1998 (LACE), 2006 (SAMUM-1) and 2008 (SAMUM-2 and EUCAARI), airborne High Spectral Resolution Lidar (HSRL) and in situ measurements of aerosol microphysical and optical properties were performed. Altogether, the properties of six different aerosol types and aerosol mixtures – Saharan mineral dust, Saharan dust mixtures, Canadian biomass burning aerosol, African biomass burning mixture, anthropogenic pollution aerosol, and marine aerosol have been studied. On the basis of this extensive HSRL data set, we present an aerosol classification scheme which is also capable to identify mixtures of different aerosol types. We calculated mixing lines that allowed us to determine the contributing aerosol types. The aerosol classification scheme was supported by backward trajectory analysis and validated with in-situ measurements. Our results demonstrate that the developed aerosol mask is capable to identify complex stratifications with different aerosol types throughout the atmosphere.
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Holden, Carol A., Sally S. Hunnicutt, Raymundo Sánchez-Ponce, John M. Craig, and Sarah C. Rutan. "Study of Complexation in Methanol/Water Mixtures by Infrared and Raman Spectroscopy and Multivariate Curve Resolution—Alternating Least-Squares Analysis." Applied Spectroscopy 57, no. 5 (May 2003): 483–90. http://dx.doi.org/10.1366/000370203321666470.
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The structure of the mobile phase in liquid chromatography plays an important role in the determination of retention behavior on reversed-phase stationary materials. One of the most commonly employed mobile phases is a mixture of methanol and water. In this work, infrared and Raman spectroscopic methods were used to investigate the structure of species formed in methanol/water mixtures. Chemometric methods using multivariate curve resolution by alternating least-squares analysis were used to resolve the overlapped spectra and to determine concentration profiles as a function of composition. The results showed that the structure of these mixtures could be described by a mixture model consisting of four species, namely, methanol, water, and two complexes, methanol/water (1:1) and methanol/water (1:4). The spectral frequencies and concentration profiles found from the Raman and infrared measurements were consistent with one another and with theoretical calculations.
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Ilchenko, Oleksii O., Andrii M. Kutsyk, and Vyacheslav V. Obukhovsky. "Study of Complexation in Acetone-Chloroform Mixtures by Infrared Spectroscopy." Journal of Atomic and Molecular Physics 2014 (February 24, 2014): 1–6. http://dx.doi.org/10.1155/2014/106178.
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FTIR spectra of acetone-chloroform system with various component ratios were investigated within the spectral range 3950–4550 cm−1. Methods of multivariate curve resolution were applied to decompose the FTIR spectra into specific components of different composition. A method of decomposition based on structural model of solution which contains acetone, chloroform, and complex acetone/chloroform (1 : 1) was proposed. Results of both approaches are in good agreement within the range of measuring error.
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Rossi, T. M., and I. M. Warner. "Pattern Recognition of Two-Dimensional Fluorescence Data Using Cross-Correlation Analysis." Applied Spectroscopy 39, no. 6 (November 1985): 949–59. http://dx.doi.org/10.1366/0003702854249501.
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An algorithm for spectral matching of excitation-emission matrices (EEMs) is reported. The pattern-recognition method developed operates completely in the frequency domain after Fourier transformation of unknown and standard EEMs. Spectral matches are evaluated by correlation and intervector distances between Fourier spectra of EEMs. Application of this method to single-component EEMs demonstrates the utility of pattern recognition for the identification of spectrally similar anthracene derivatives. In a study of multicomponent EEMs, mixtures of polynuclear aromatics (PNAs) are identified by comparison to a standard set of mixtures, and eigenvector deconvolution is coupled with pattern recognition for the identification of individual components in two-component mixtures. In addition, the feasibility of applying automatic pattern recognition to the identification of bacteria based on their uptake of fluorescent dyes is explored.
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Guilment, Jean, Sharon Markel, and Willem Windig. "Infrared Chemical Micro-Imaging Assisted by Interactive Self-Modeling Multivariate Analysis." Applied Spectroscopy 48, no. 3 (March 1994): 320–26. http://dx.doi.org/10.1366/0003702944028308.
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In the analytical environment, spectral data resulting from analysis of samples often represent mixtures of several components. Extraction of information about pure components from that kind of mixture is a major problem, especially when reference spectra are not available. Self-modeling multivariate mixture analysis has been developed for this type of problem. In this paper, two examples will be used to show the potential of the technique for vibrational spectroscopy. Infrared microspectroscopic chemical imaging has been employed to improve spatial resolution for distinguishing differences between adjacent, nonidentical materials. The resolution of a 2- to 3- μm-thick inner layer, from a four-layer polymer laminate, has been achieved. The same approach has been utilized to extract pure component spectra out of a KBr pellet of a mixture of three compounds.
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Ustinovskii, N. N., A. O. Levchenko, and V. D. Zvorykin. "Transient absorption and laser gain in e-beam-excited Ar/Kr/NF3(F2 + N2) gas mixtures." Laser and Particle Beams 29, no. 1 (March 2011): 141–52. http://dx.doi.org/10.1017/s0263034611000012.
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AbstractNewly developed erosion-plasma-source probe technique has been applied for virtually single shot recording of absorption/fluorescence spectra in the 190–510 nm spectral range of e-beam-excited Ar/Kr/NF3(F2 + N2) mixtures. The e-beam excitation rate of about 1 MW/cm3 is typical of large-volume rare-gas halide lasers. It is experimentally observed that, in Kr/F2 and Ar/F2 mixtures, fluorescence and absorption spectra of Rg2F species are shifted with respect to each other in the opposite direction. Continuous absorption spectrum of Ar2F excimer is reported, as far as we know, for the first time in the refereed literature. Strong overlapping between the fluorescence and absorption spectra of Ar2F is responsible for absence of lasing on Ar2F molecule. Absorption spectrum of Kr2F excimer is recorded in pure form using the mixture (Ne/Kr/F2) with no alternative broadband absorber. Minor additive of nitrogen to Ar/Kr/F2 mixture or use of NF3 instead of F2 has been found to result in broadband optical amplification centered at λ ~ 460 nm. The maximum optical gain is estimated as about 0.1 ± 0.05 m−1.
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Betting, H., and M. Stockhausen. "Dielectric Relaxation Study of Some Solutions Containing β-Cyclodextrin and Dimethylsulfoxide." Zeitschrift für Naturforschung A 54, no. 6-7 (July 1, 1999): 382–86. http://dx.doi.org/10.1515/zna-1999-6-707.
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Abstract Dielectric spectra have been measured up to 72 GHz at 20°C for solutions of β-cyclodextrin (CD) in the following solvents over the whole solubility range of CD: dimethylsulfoxide (DMSO), DMSO/ 1,4-dioxane mixture (2:1 molar ratio), DMSO/water mixtures (2:1 and 1:2). The spectra are analyzed into a sum of Debye type spectral components. These are likely to be caused by different physical pro-cesses. The discussion shows (i) that there is a preferential CD-DMSO interaction, by far exceeding the CD-water interaction, and (») that, concerning CD-DMSO, a loose interaction can be distinguished from the formation of an inclusion complex.
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Chung, Hoeil, Joon-Sik Lee, and Min-Sik Ku. "Feasibility of Simultaneous Measurement of Xylene Isomers and other Hydrocarbons in p-Xylene Production Processes Using Near-Infrared Spectroscopy." Applied Spectroscopy 52, no. 6 (June 1998): 885–89. http://dx.doi.org/10.1366/0003702981944436.
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The feasibility of simultaneous measurement of important components such as o-xylene, m-xylene, p-xylene, ethylbenzene, toluene, aliphatic hydrocarbons, and total C9–C10 aromatic hydrocarbons in the p-xylene production process is investigated. Mixtures of those components were prepared to simulate concentration levels in actual p-xylene processes, and near-infrared (NIR) spectra were collected from mixtures over the spectral range of 1100 to 2500 nm. Even with the very similar spectral features of xylene isomers and other aromatic compounds, the concentrations of each of the components in the mixtures are accurately predicted by using a partial least-squares (PLS) algorithm and show excellent correlation with conventional gas chromatographic analysis. The results clearly demonstrate the possibility of using NIR spectroscopy for monitoring the major components in an actual p-xylene production process for process control and optimization.
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Sharma, Rakesh, Navdeep Gogna, Harpreet Singh, and Kavita Dorai. "Fast profiling of metabolite mixtures using chemometric analysis of a speeded-up 2D heteronuclear correlation NMR experiment." RSC Advances 7, no. 47 (2017): 29860–70. http://dx.doi.org/10.1039/c7ra04032f.
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One-dimensional (1D) NMR spectra of mixtures of metabolites suffer from severe overlap of spectral resonances and hence recent research in NMR-based metabolomics focuses on using two-dimensional (2D) NMR experiments for metabolite fingerprinting.
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Ariunbold, Gombojav O., Bryan Semon, Supriya Nagpal, and Yuri Rostovtsev. "Ultrafast dephasing in hydrogen-bonded pyridine–water mixtures." Open Physics 19, no. 1 (January 1, 2021): 234–40. http://dx.doi.org/10.1515/phys-2021-0027.
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Abstract Hydrogen-bonded mixtures with varying concentration are a complicated networked system that demands a detection technique with both time and frequency resolutions. Hydrogen-bonded pyridine–water mixtures are studied by a time-frequency resolved coherent Raman spectroscopic technique. Femtosecond broadband dual-pulse excitation and delayed picosecond probing provide sub-picosecond time resolution in the mixtures temporal evolution. For different pyridine concentrations in water, asymmetric blue versus red shifts (relative to pure pyridine spectral peaks) were observed by simultaneously recording both the coherent anti-Stokes and Stokes Raman spectra. Macroscopic coherence dephasing times for the perturbed pyridine ring modes were observed in ranges of 0.9–2.6 ps for both 18 and 10 cm − 1 10\hspace{0.33em}{{\rm{cm}}}^{-1} broad probe pulses. For high pyridine concentrations in water, an additional spectral broadening (or escalated dephasing) for a triangular ring vibrational mode was observed. This can be understood as a result of ultrafast collective emissions from coherently excited ensemble of pairs of pyridine molecules bound to water molecules.
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Trofimov, Vyacheslav A., and Svetlana A. Varentsova. "A Possible Way for the Detection and Identification of Dangerous Substances in Ternary Mixtures Using THz Pulsed Spectroscopy." Sensors 19, no. 10 (May 22, 2019): 2365. http://dx.doi.org/10.3390/s19102365.
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We discuss an effective tool for the detection and identification of substances in ternary mixtures with similar spectral properties using a broadband reflected THz signal. Nowadays, this is an urgent problem; its effective solution is still far off. Two ternary mixtures of the explosives (RDX+TNT+HMX and RDX+TNT+PETN) were used as the examples for demonstration of the efficiency of the method proposed. The identification is based on the pulsed THz spectroscopy. We follow the spectral intensities together with the use of integral correlation criteria. They use the spectral line dynamics of the THz pulse reflected from the substance under investigation and that of the standard THz signal from database. In order to increase the accuracy and reliability of the identification, we analyze the partial non-overlapping time intervals, containing the main pulse of the reflected THz signal and the sequential sub-pulses. The main pulse is shown to contain information about high absorption frequencies (ν > 2.6 THz) of the mixture components. In the sub-pulses, the absorption frequencies of the components are detected in the range of low (ν < 2.6 THz) and high (ν > 2.6 THz) frequencies. The opportunity of distinguishing the mixtures with similar spectral properties is also shown.
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Van Agthoven, Maria A., Go Fujisawa, Philip Rabbito, and Oliver C. Mullins. "Near-Infrared Spectral Analysis of Gas Mixtures." Applied Spectroscopy 56, no. 5 (May 2002): 593–98. http://dx.doi.org/10.1366/0003702021955376.
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The analysis by near-infrared spectroscopy (NIR) of a series of gas mixtures approximating natural gases is reported. Wide variations of gas pressure and temperature are used in accord with conditions found in various utilitarian gas flow streams. The NIR analysis of CH4 and CO2 composition is found to be straightforward and depends only on compound mass density, but not explicitly on temperature, pressure, or composition. Linearity of the spectra of more complex mixtures is maintained, but the NIR analysis is more complex. Principal component analysis is shown to resolve composition for those gas mixtures.
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Cloutis, Edward A., Michael J. Gaffey, Dorian G. W. Smith, and R. ST J. Lambert. "Reflectance spectra of glass-bearing mafic silicate mixtures and spectral deconvolution procedures." Icarus 86, no. 2 (August 1990): 383–401. http://dx.doi.org/10.1016/0019-1035(90)90226-y.
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Cloutis, Edward A., Juan A. Sanchez, Vishnu Reddy, Michael J. Gaffey, Richard P. Binzel, Thomas H. Burbine, Paul S. Hardersen, et al. "Olivine–metal mixtures: Spectral reflectance properties and application to asteroid reflectance spectra." Icarus 252 (May 2015): 39–82. http://dx.doi.org/10.1016/j.icarus.2014.10.003.
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Dagg, I. R., A. Anderson, S. Yan, W. Smith, C. G. Joslin, and L. A. A. Read. "Collision-induced absorption in gaseous mixtures of nitrogen and methane." Canadian Journal of Physics 64, no. 11 (November 1, 1986): 1467–74. http://dx.doi.org/10.1139/p86-260.
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The collision-induced absorption spectra of nitrogen–methane gas mixtures have been measured in the spectral region below 400 cm−1 at four temperatures, namely, 212, 179, 149, and 126 K. The measurements have involved the use of Fourier-transform infrared and microwave techniques as well as a far-infrared laser operating at 84.2 and at 15.1 cm−1. These are compared with a theoretical line shape obtained from a convolution of free rotational spectra and a translational component as determined from information theory. The calculated spectra show good agreement with the experimental results only in the lower frequency region. An important feature of the theoretical development is that no adjustable parameters need be introduced.