Evaluation of the Mooney Viscosity of Natural Rubber by Near‐Infrared Spectroscopy

Abstract

The direct near‐infrared spectroscopic reflectance measurements of prevulcanized natural rubber (brown crepe) was employed for determination of its Mooney viscosity. NIR reflectance spectra were obtained for a total of 100 samples whose Mooney viscosity (VM in the range 68–95 units) have been determined by the standard reference procedure using a commercial computerized Mooney viscometer. These samples were employed as the raw material or were treated to achieve better homogenization. A Fourier transform near infrared (FT‐NIR) spectrophotometer was employed, and the reflectance spectra were obtained with resolution of 4 cm^?1 in the range 4000–10,000 cm^?1 as an average of 75 scans. The samples were split in a calibration set containing 70 samples and in an external validation set consisting of the remaining 30 samples. The calibration and validation spectra sets were treated to correct for baseline shift, further transformed by first derivative and finally modeled by partial least squares (PLS) employing four latent variables. The model was evaluated with the external sample test set, and a RMSEP of 3.6 and 3.9 units of Mooney viscosity were obtained for homogenized and nonhomogenized samples, respectively. The NIR method is capable of determining the Mooney viscosity in few minutes in the non‐pretreated sample with an error that is satisfactory for quality control of natural rubber destined for automobile tire manufacturing.     

Applications of Near‐Infrared Spectroscopy in Refineries and Important Issues to Address

Abstract

This review primarily concerns NIR (near‐infrared) applications in refineries. Initially, this article reviews the fundamental aspects for analysis of hydrocarbon mixture by NIR spectroscopy, such as spectral sensitivity in various spectral regions, signal‐to‐noise ratio, and spectral resolution. Though there are applications of NIR to diverse petroleum products, this review subsequently focuses only on applications to four major products: gasoline, diesel, naphtha, and crude oil, which are the most interesting from a refiner's viewpoint. In each application, discussion of important issues to consider for proper and optimal NIR measurement is included. Finally, the issue of calibration transfer is discussed.     

Fourier‐Transform Near‐Infrared Spectroscopy as a Tool for Olive Fruit Classification and Quantitative Analysis

Abstract

The potential of diffuse reflectance near‐infrared spectroscopy combined with pattern recognition to discriminate between olives (Olea europaea L.) of different qualities has been tested. The sample set was formed of sound olive fruits and those showing the most common alterations of olives, which lead to decreased oil quality, namely freeze damages, harvest after falling on the ground, fermentation due to prolonged storage time, and olive tree diseases. Near‐infrared (NIR) spectra were recorded between 9900 and 4100 cm^?1. Preliminary studies of the data set structure were performed using hierarchical cluster analysis and principal component analysis. Discriminant analysis provided prediction abilities of 100% for sound, 79% for frostbite, 96% for ground, and 92% for fermented olives using a leave‐a‐fourth‐out cross‐validation procedure. Quantification of oil and water content in the olives was also approached by using partial least squares (PLS) regression. Results, in terms of predictive ability using a leave‐one‐out cross‐validation, were compared for calibration using the whole sample set and calibrations for the sound and damaged samples separately. Relative errors of prediction using all samples were 7.2% and 3.4% for oil content and humidity, respectively. Using only sound samples, relative errors of prediction of 3.8% and 2.8% for oil and water content, respectively, were obtained. Thus, better accuracy could be achieved when classification of the olive samples prior to quantitative analysis was performed. These results demonstrate the utility of NIR spectroscopy to differentiate olives of different qualities. Using NIR, a fast selection of sound olives in a quality‐orientated production facility becomes feasible.     

Characterization of Mango Juice by High‐Resolution NMR,Hyphenated NMR,and Diffusion‐Ordered Spectroscopy

Abstract

The application of nuclear magnetic resonance (NMR) spectroscopy, hyphenated NMR, and diffusion‐ordered spectroscopy (DOSY) to the characterization of mango juice, as an example of a complex food mixture, is described. The compositional changes taking place as a function of ripening were followed, and selected metabolites were quantified by integration of the corresponding NMR peaks. In this way, an overall view of the metabolite changes is obtained, enabling the study of the biochemical mechanisms involved in the ripening process. More than 50 compounds were identified by 1D‐ and 2D‐NMR, but many ambiguous assignments remain due to spectral overlap or insufficient coupling information. The use of Liquid Chromatography (LC‐NMR) and LC‐NMR/Mass Spectrometry (MS) enables a fuller characterization of the soluble pectin fraction to be made; its dependence on ripening stage is discussed. Finally, DOSY adds information on the M_r of many metabolites, including the pectin fractions of ripe and unripe mango juices, and enables further peak assignments to be made.     

Using Short Wave Visible–Near Infrared Reflectance Spectroscopy to Predict Soil Properties and Content

In this study, short wave visible–near infrared reflectance spectroscopy was evaluated for prediction of diverse soil properties related to four different soil series of several regions in Jiangxi, China. A total of 240 soil samples were collected for the calibration (n = 168) and prediction (n = 72) sets. The used wavelength range of short wave visible–near infrared reflectance spectroscopy is 325–1075 nm. Partial least squares regression and back propagation neural network were used to develop models for soil properties such as organic matter and extractable forms of calcium, magnesium, and potassium. Performance of these models was also compared and analyzed. The input of back propagation neural network was the first six principal components resulted from the principal component analysis and the optimal number of latent variables obtained from partial least squares regression. The overall results showed that the performance of partial least squares regression model was inferior to all back propagation neural network models. The best prediction was obtained with latent variables as input of back propagation neural network model for organic matter (determination coefficient = 0.84 and relative predictive determinant = 2.38), which was classified as very good model predictions. The prediction of calcium, magnesium, and potassium was classified as fair (determination coefficient = 0.56–0.68 and relative predictive determinant = 1.51–1.61), where quantitative predictions were considered possible. It is recommended to adopt latent variables as input for back propagation neural network model predicting soil properties with short wave visible–near infrared reflectance spectroscopy. In conclusion, short wave visible–near infrared reflectance spectroscopy was variably successful in estimating soil properties and showed potential for substituting laboratory analyses.     

High‐Resolution Submillimeter Wave Spectroscopy of Hydrogen Sulphide with Heterodyne Spectrometer

A submillimeter heterodyne spectrometer using continuous wave optically pumped molecular laser as local oscillator and Schottky diode as mixer was developed at Physical Research Laboratory, Ahmedabad (India) for quantitative spectroscopy of polyatomic molecules in laboratory. The experimental details of spectrometer and its application to study of molecular line parameters are presented. In particular line strength, collision line width (self and foreign) of H₂S 5_5,05_4,1 transition¹(579.799 GHz) have been measured. Air molecules have been used as foreign (perturbing) molecules taking Earths atmosphere into consideration².     

Near Infrared Spectroscopy of the Cretaceous Red Beds in Inner Mongolia DongshengmiaoSCIEI北大核心CSCD

Take the cores and surface weathered soil from the Cretaceous red beds in the western of Dongshengmiao mine of Inner Mongolia and analysis with near-infrared spectroscopy. The result shows that near-infrared spectroscopy can identify mineral quickly through the characteristic absorption peaks of each group. The Cretaceous red beds in the western of Dongshengmiao mine is argillaceous cementation, it is mainly composed of quartz, feldspar, montmorillonite, illite, chlorite, muscovite etc, the mineral composition is mainly affected by the upstream source area. The clay mineral like montmorillonite water swelling and uneven drying shrinkage expands the original crack and creates new cracks, reduces its strength, which is the mainly reason of its disintegration. According to the composition of clay mineral, we speculate its weathering process is mainly physical weathering, the climate during the weathering is cold and dry. The results can not only improve the geological feature of the mining area, but also show that the near-infrared spectroscopy technology can analyze the mineral composition of soil and rock effectively on the basis of Mineral spectroscopy, which demonstrates the feasibility of the near-infrared spectroscopy can analyze minerals in soil and rock quickly, that shows the feasibility in geology study, provides new ideas for the future research of soil and rock.     

A New Approach to Analysis of Molecular Structure in Thin Films: Infrared Multiple‐Angle Incidence Resolution Spectrometry

Abstract

Multiple‐angle incidence resolution spectrometry (MAIRS) is a potentially useful spectroscopic technique for quantitative analysis of molecular orientation in thin films deposited on a solid substrate. Although the technique is based on a unique measurement concept and theory, it can easily be equipped on a commercial FT‐IR and the operation is user friendly. In this review, representative application studies of MAIRS are summarized as well as a recent new theoretical approach to get over a conventional experimental limitation that a high‐refractive‐index substrate is necessary for quantitatively reliable MAIRS analysis.     

Partial Least Squares Processing of Near‐Infrared Spectra for Discrimination and Quantification of Adulterated Olive Oils

Abstract

A new processing based on partial least squares (PLS) algorithm for the discrimination and determination of adulterants in pure olive oil using near‐infrared (NIR) spectroscopy has been introduced. The 280 adulterations of olive oil with corn oil (n=70), hazelnut oil (n=70), soya oil (n=70), and sunflower oil (n=70) were prepared, and their NIR spectra in the region 12,000–4550 cm^?1 were collected. The 70 spectra of each adulteration of olive oil were divided into two sets, 50 spectra for a calibration set and 20 spectra for a prediction set. The spectra of a total calibration set (n=200) were separated into individual adulterant calibration sets (n_i=50, i=corn, hazelnut, soya, sunflower) by using discriminant PLS (DPLS) analysis, and PLS calibration models for the quantification of adulterants with corn oil, hazelnut oil, soya oil, or sunflower oil were developed separately. A variety of wavelength ranges and data pretreatments were examined for obtaining optimal results for the discrimination and quantification objects. Four PLS models for differentiating the adulterant types were evaluated by classifying the NIR spectra of a total prediction set (n=80) into known adulterant types. Then, these known adulterant spectra were analyzed by the PLS calibration models developed for each type to determine the content of an adulterant in pure olive oil. The results of evaluation revealed that the processing reported in this article works excellently for the discrimination and quantification of the adulterations of olive oil.     

Quantitatively Determination of Available Phosphorus and Available Potassium in Soil by Near Infrared Spectroscopy Combining with Recursive Partial Least SquaresSCIEI北大核心CSCD

Soil available phosphorus (P) and available potassium (K) don't possess direct spectral response in the near infrared (NIR) region. They are predictable because of their correlation with spectrally active constituents (organic matter, carbonates, clays, water, etc.). Such correlation may of course differ between the soil sample sets. Therefore, the NIR calibration models with fixed structure are difficult to achieve good prediction performances for soil P and K. In this work, the method of recursive partial least squares (RPLS), which is able to update the model coefficients recursively during the prediction process, has been applied to improve the predictive abilities of calibration models. This work compared the performance of partial least squares regression (PLS), locally weighted PLS (LW-PLS), moving window LW-PLS (LW-PLS2) and RPLS for the measurement of soil P and K. The entire data set of 194 soil samples was split into calibration set and prediction set based on soil types. The calibration set was composed of 120 Anthrosols samples, while the prediction set included 29 Ferralsols samples, 23 Anthrosols samples and 22 Primarosols samples. The best prediction results were obtained by the RPLS model. The coefficient of determination (122) and residual prediction deviation (RPD) were respectively 0.61, 0.76 and 1.60, 2.05 for soil P and K. The results indicate that RPLS is able to learn the information from the latest modeling sample by recursively updating the model coefficients. The proposed method RPLS has the advantages of wider applicability and better performance for MR prediction of soil P and K compared with other methods in this work.     

Application of NMR Spectroscopy and Mass Spectrometry to the Structural Elucidation of Modified Flavan‐3‐ols and Their Coupling Reaction Products*

NMR and MS techniques were used for the unambiguous structural elucidation of synthesized modified monomeric and dimeric flavan‐3‐ols presenting different substituents on the A‐ring C8 position. The full characterization of the synthesized compounds was achieved by concerted use of NMR and ESI‐MS techniques. Assignments of proton and carbon atoms was achieved through analysis of the 1D ¹H and ¹³C NMR spectra combined with homo‐ and heteronuclear 2D NMR experiments. In each case, HMBC correlation between proton H2 and carbon C8a was observed allowing assignment of this carbon, which represents the key for attribution of the A‐ring carbon atoms. The synthesis and structural characterization of activated monomeric and dimeric flavanols were also achieved and used as precursors for preparation of natural and modified dimeric procyanidin derivatives. The preparation of various dimeric species involving modified flavanols was explored through different coupling reactions. The structures of the compounds formed were characterized on the basis of their MS and NMR spectral analysis. Dimeric species were characterized through proton–proton and proton–carbon correlations, which distinguished between the different flavanol moieties and established their sequences.     

The Use of Solid‐Phase Supports for Derivatization in Chromatography and Spectroscopy

Abstract

Derivatization, or chemical modification of analytes, is often required for species that are only weakly detectable by common spectroscopic methods. Derivatization is most commonly performed in homogeneous solution or using phase‐transfer catalyzed reactions. However, the use of solid phase supports for performing the same reactions has a number of advantages. The sample can be “cleaned up” on the same phase, eliminating interfering matrix components or excess reagent. The process naturally concentrates the analyte, providing higher sensitivity, but also, under favorable circumstances, provides for more efficient reactions relative to solutions of the same original concentration. This review explores the uses to which such supports have been put, primarily in fluorescence derivatization for chromatographic applications. Some of the considerations in applying these techniques are described, and they are shown to be an extremely useful format for derivatization.     

Identification of Urinary Stone Components by X‐Ray Photoelectron Spectroscopy

Abstract

X‐ray photoelectron spectroscopy (XPS) has been used for the first time to study the composition of calcium oxalate (CaOxa) stones and uric acid stones. This technique allows for the identification and location of various inorganic and organic species at the same time. In CaOxa stones, there were less than 10% of phosphates. Sectional analyses of these stones indicated that the content of phosphorus in the stone center is higher than that in stone crust. In uric acid stones, CaOxa was rarely found. XPS is able to detect differences in chemical functionality. In uric acid stones, the binding energy (E _b) for nitrogen atoms were about 399.5 ± 0.2 eV, which are largely characteristic of organic nitrogens N (?3). In comparison, the E _b values of N (+5) in inorganic compounds are about 401 eV.     

Characterization of Crystalline Phase‐Transformations in Theophylline by Time‐Domain Terahertz Spectroscopy

Time‐domain terahertz (THz) spectroscopy has been used to characterize polymorphic transformations in polycrystalline theophylline, a widely used pharmaceutical compound. On transformation, different intermolecular bonding arrangements arise owing to changes in the lattice structure of the molecular crystal, leading to distinct THz spectral signatures. Temperature‐dependent THz absorption measurements in anhydrous theophylline confirm that the observed vibrational modes originate from phonons within the crystal structure.     

Detection of Terahertz,Mid- and Near Infrared Radiation by a Multilayer Metal—Insulator Heterostructure

An analogy between the tunneling of quantum particles through a chain of barriers and the propagation of electromagnetic waves through a metamedium has allowed new methods for the fabrication of selective detectors of terahertz, mid-infrared, and near infrared radiation. The calculations have shown that a resonance metal-insulator heterostructure with one and two metal layers allows achieving nearly 100% absorption of radiation in a narrow frequency range. The use of a large number of metal layers makes it possible to detect ultrashort (including picosecond) field pulses with a broad spectrum.

     

Photodegradation Studies by Laser‐Induced Fluorescence of the Reaction Product of 1,2‐Indanedione And Glycine

Photodegradation of the reaction product of 1,2‐indanedione with glycine in methanol at room temperature has been studied using laser-induced fluorescence. Samples were liquid solution and developed fingerprints on papers. Continuous laser excitation of fresh solution of 1,2‐indanedione–glycine dissolved in methanol shows that the emission peak at 564 nm reached a quite stable low level after almost 1 hr of continuous excitation. For latent fingerprints on papers developed with 1,2‐indanedione dissolved in methanol solution, the luminescence peak decreases for the first week and reached a stable level for almost 2 weeks. A long‐term study is needed to reach a conclusion on the stability of the samples (liquid and developed fingerprints) at room temperature conditions.     

Trace Analysis of Al on Silicon Surfaces by Ultra‐soft X‐Ray Emission Spectroscopy

It is shown that near normal incidence, low‐energy electron excitation of Al on silicon surfaces by ultra‐soft X‐Ray emission spectroscopy yielded limits of detectibility (LD) in the picogram region. This result on L band emission via electron excitation is fully competitive with photon excitation using K‐α lines via grazing incidence total reflection techniques (TXRF). Surprisingly, it was also found that normal incidence synchrotron photon excitation on the same sample yielded much higher values of LD than low‐energy electron excitation, undoubtedly due to the use of a poor transmission grating used in the entrance optics.     

Application of Multivariate Curve Resolution–Alternate Least Square Technique on Extracting Pure Spectral Components from Multiple Emitting Systems: a Case Study

Multiple emitting components in a fluorophoric system often produce complicated emission spectra. Extracting the individual spectral information from the composite spectra is important in order to comprehend the photophysical processes occurring in the multifluorophoric systems. Although the combination of Principal Component Analysis and Multivariate Curve Resolution-Alternate Least Square (PCA/MCR-ALS) technique is a well-known approach for curve deconvolution, its applicability in the spectral deconvolution of vibronically and electronically mixed up emitting systems as well as systems merged up with multiple electronic bands without a priori knowledge of the individual emitting species, is not properly studied. The present work highlights the strength of PCA/MCR-ALS in retrieving pure spectral information from the set of complex spectra arising out of the regular variation of causative factors that result in the variation of spectral composition. The retrieval of the emission bands utilizing the PCA/MCR-ALS technique has been made without having a priori information of the emitting species present in the multifluorophoric systems and the resolved spectra correspond well with the fluorescence spectra of the individual chemical species. The common curve fitting methods such as Gaussian and Lorentzian techniques have been found to be unsuccessful in providing meaningful photophysical information through the retrieved spectra. A comparative study of the curve fitting techniques MCR-ALS, Gaussian and Lorentzian in a set of complicated emission spectra of (i) pyrene and its excimer, (ii) pyrene and its excimer in presence of benzo[a]pyrene, and (iii) fisetin in bile salt medium is presented herein in details.     

Determination of the Heat of Adsorption and Desorption of a Volatile Organic Compound Under Dynamic Conditions Using Fourier‐Transform Infrared Spectroscopy

Quantitative Fourier‐transform infrared spectroscopic analysis was used for the determination of adsorption capacity of a model volatile organic compound (VOC) under dynamic conditions. The analytical method used also offers the possibility of distinguishing between reversible and irreversible adsorption as well as further detection of adsorbed VOC transformation. The obtained adsorbed amounts have been used for the determination of the heat of adsorption and the activation energy of desorption using, respectively, isosteric and temperature programmed desorption methods. The approach has been applied to explore the potential use of local clay as an adsorbent material for VOC pollutants.