Studies of phase transformations in the gelatine-water system using near-IR spectroscopy

Near-IR spectroscopy studies of gel formation mechanism are reported for gelatin-water systems. Relative absorbance in 1.4-μm and 1.9-μm bands was shown to be sensitive to the helix to coil phase transition in the pre-melting region. The formation mechanism of a metastable “coil” phase is in agreement with DSC and TGA data obtained in parallel experiments on the 10% gelatin gel. Received: 12 April 2000 Accepted: 4 October 2000     

NIR spectroscopy of jarosites

Near-infrared (NIR) spectroscopy has been used to analyse a suite of synthesised jarosites of formula Mn(Fe3+)6(SO4)4(OH)12 where M is K, Na, Ag, Pb, NH4+ and H3O+. Whilst the spectra of the jarosites show a common pattern, differences in the spectra are observed which enable the minerals to be distinguished. The NIR bands in the 6300-7000 cm-1 region are attributed to the first fundamental overtone of the infrared and Raman hydroxyl stretching vibrations. The NIR spectrum of the ammonium-jarosite shows additional bands at 6460 and 6143 cm-1, attributed to the first fundamental overtones of NH stretching vibrations. A set of bands are observed in the 4700-5500 cm-1 region which are assigned to combination bands of the hydroxyl stretching and deformation vibrations. The ammonium-jarosite shows additional bands at 4730 and 4621 cm-1, attributed to the combination of NH stretching and bending vibrations. NIR spectroscopy has the ability to distinguish between the jarosite minerals even when the formula of the minerals is closely related. The NIR spectroscopic technique has great potential as a mineral exploratory tool on planets and in particular Mars.     

Application of two-dimensional near-infrared correlation spectroscopy to protein research

The purpose of the present paper is to demonstrate the potential of generalized two-dimensional (2D) near-infrared (NIR) correlation spectroscopy in studies of hydration and structure of proteins. We describe here two examples. The first example is concerned with heat denaturation process of ovalbumin in aqueous solutions and the second one deals with isomerizations with varying pH of serum albumin. New insight has been obtained into the hydration and unfolding process of secondary structures of ovalbumin and serum albumin by studying temperature- or pH-dependent correlation patterns in 2D synchronous and asynchronous spectra. Generalized 2D NIR correlation spectroscopy emphasizes spectral features not readily observable in conventional one-dimensional spectra, enabling to extract subtle but valuable structural changes concerning with the protein denaturation.     

Tip-enhanced Raman spectroscopy for nanoscale strain characterization

Tip-enhanced Raman spectroscopy (TERS), which utilizes the strong localized optical field generated at the apex of a metallic tip when illuminated, has been shown to successfully probe the vibrational spectrum of today’s and tomorrow’s state-of-the-art silicon and next-generation semiconductor devices, such as quantum dots. Collecting and analyzing the vibrational spectrum not only aids in material identification but also provides insight into strain distributions in semiconductors. Here, the potential of TERS for nanoscale characterization of strain in silicon devices is reviewed. Emphasis will be placed on the key challenges of obtaining spectroscopic images of strain in actual strained silicon devices. Figure Figure Concept of Tip Enhanced Raman Spectroscopy (TERS), which utilizes the strong localized optical field generated at the apex of a metallic tip when illuminated. TERS has been demonstrated to successfully probe the vibrational spectrum of today’s and tomorrow’s state-of-the-art silicon and next generation semiconductor devices     

Application of near-infrared spectroscopy in the sugar industry for the detection of betaine

One problem in industrial molasses desugarization is the lack of a fast analytical method for process control. At the moment, control of the chromatographic production process is achieved by detecting refractive index and conductivity. However, since elution of some components takes place only in a narrowly defined time frame, the data gained are insufficient for effective online product quantification. Near-infrared (NIR) spectroscopy was applied to this process by development of a simple method for detection of betaine. Compared to chemometric models currently used, the developed method demonstrates the advantage of requiring only a small calibration set. Additionally, it can easily be transferred to other processes without further re-calibration. Based on the NIR spectrum of betaine, a characteristic peak in the spectrum could be assigned to the molasses compound betaine. A calibration was developed by using dissolved betaine in pure water. Afterwards, the calibration was tested for samples from a molasses desugarization process. The method was than successfully transferred to a complete chromatographic cycle of the industrial molasses desugarization process.     

Determination of organic additives in mortars by near-IR spectroscopy. A novel approach to designing a sample set with high-variability components

Industrial mortars consist primarily of a mixture of cement and an aggregate plus a small amount of additives that are used to modify specific properties. Using too high or too low additive rates usually results in the loss of desirable properties in the end product. This entails carefully controlling the amounts of additives added to mortar in order to ensure correct dosing and/or adequate homogeneity in the final mixture. Near-IR (NIR) spectroscopy has proved effective for this purpose as it requires no sample pretreatment and affords expeditious analyses. The purpose of this work was to determine two organic additives (viz. Ad1 and Ad2) in mortars by using partial least squares regression multivariate calibration models constructed from NIR spectroscopic data. The additives are used to expedite setting and increase cohesion between particles in the mortar. In order to ensure that the sample set contained natural variability in the samples, we used a methodology based on experimental design to construct a representative set of samples. This novel design is based on a hexagonal antiprism that encompasses the concentration ranges spanned by the analytes and the variability inherent in each additive. The D-optimality criterion was used to obtain various combinations between Ad1 and Ad2 additive classes. The partial least squares calibration models thus constructed for each additive provided accurate predictions: the intercept and the slope of the plots of predicted values versus reference values for each additive were close to 0 and 1, respectively, and their confidence ranges included the respective value. The ensuing analytical methods were validated by using an external sample set.     

Comparison of chemometric methods for brand classification of cigarettes by near-infrared spectroscopy

The combinations of NIR spectroscopy and three classification algorithms, i.e., multi-class support vector machine (BSVM), k-nearest neighbor (KNN) and soft independent modeling of class analogies (SIMCA), for discriminating different brands of cigarettes, were explored. The influence of the training set size on the relative performance of each algorithm was also investigated. A NIR spectral dataset involving the classification of cigarettes of three brands was used for illustration. Three performance criteria based on “correctly classified rate (CCR)”, i.e., “Average CCR”, “95 percentile of CCR” and “S.D. of CCR”, were defined to compare different algorithms. It was revealed that BSVM is significantly better than KNN or SIMCA in the statistical sense, especially in cases where the training set is relatively small. The results suggest that NIR spectroscopy together with BSVM could be an alternative to traditional methods for discriminating different brands of cigarettes.     

Recent applications of near-infrared spectroscopy in cancer diagnosis and therapy

In recent years, near-infrared spectroscopy (NIRS) has gained importance for non-invasive or minimally invasive diagnostic applications in cancer. This technology is based on differences of endogenous chromophores between cancer and normal tissues using either oxy-haemoglobin or deoxy-haemoglobin, lipid or water bands, or a combination of two or more of these as diagnostic markers. These marker bands provide a basis for the diagnosis and therapy monitoring of several cancers. Various applications also use advances in NIR fluorescence spectroscopy which is based on exogenous contrast-enhancing agents. In this review the literature published during the last seven years has been assessed. It will provide an overview on the importance of the NIRS tools in cancer pathology, and in the near future it is envisaged to play a crucial role in cancer diagnosis, treatment decisions, and defining therapeutic drug levels.     

ASTM clustering for improving coal analysis by near-infrared spectroscopy

Multivariate analysis techniques have been applied to near-infrared (NIR) spectra coals to investigate the relationship between nine coal properties (moisture (%), ash (%), volatile matter (%), fixed carbon (%), heating value (kcal/kg), carbon (%), hydrogen (%), nitrogen (%) and sulphur (%)) and the corresponding predictor variables. In this work, a whole set of coal samples was grouped into six more homogeneous clusters following the ASTM reference method for classification prior to the application of calibration methods to each coal set. The results obtained showed a considerable improvement of the error determination compared with the calibration for the whole sample set. For some groups, the established calibrations approached the quality required by the ASTM/ISO norms for laboratory analysis. To predict property values for a new coal sample it is necessary the assignation of that sample to its respective group. Thus, the discrimination and classification ability of coal samples by Diffuse Reflectance Infrared Fourier Transform Spectroscopy (DRIFTS) in the NIR range was also studied by applying Soft Independent Modelling of Class Analogy (SIMCA) and Linear Discriminant Analysis (LDA) techniques. Modelling of the groups by SIMCA led to overlapping models that cannot discriminate for unique classification. On the other hand, the application of Linear Discriminant Analysis improved the classification of the samples but not enough to be satisfactory for every group considered.     

The formation of intercalation compounds of MoS2 with cations of alkali metals and alkylammonium from monolayer dispersion of molybdenum disulfide

Ion-exchange interaction of the monolayer aqueous dispersion obtained by hydration of crystalline LiMoS₂ with Li, Na, K salts and alkyiammoniiim halides is studied. Intercalation compounds of MoS₂ with hydrated inorganic cations as well as hitherto unattainable intercalation compounds of MoS₂ with alkylammonium cations are shown to be formed under these conditions. The composition and structure of these compounds are investigated.Translated fromIzvestiya Akademii Nauk. Seriya Khimicheskaya, No. 4, pp. 672–674, April, 1993.     

Comparison of near-infrared and mid-infrared spectroscopy for the determination of distillation property of kerosene

Near-infrared (NIR) and mid-infrared (MIR) spectroscopy have been compared and evaluated for the determination of the distillation property of kerosene with the use of partial least squares (PLS) regression. Since kerosene is a complex mixture of similar hydrocarbons, both spectroscopic methods will be best evaluated with this complex sample matrix. PLS calibration models for each percent recovery temperature have been developed by using both NIR and MIR spectra without spectral pretreatment. Both methods have shown good correlation with the corresponding reference method, however NIR provided better calibration performance over MIR. To rationalize the improved calibration performance of NIR, spectra of the same kerosene sample were continuously collected and the corresponding spectral reproducibility was evaluated. The greater spectral reproducibility including signal-to-noise ratio of NIR led to the improved calibration performance, even though MIR spectroscopy provided more qualitative spectral information. The reproducibility of measurement, signal-to-noise ratio, and richness of qualitative information should be simultaneously considered for proper selection of a spectroscopic method for quantitative analysis.     

Qualitative and quantitative analysis of oxytetracycline by near-infrared spectroscopy

Near-infrared (NIR) spectroscopy, in combination with chemometrics, enable the analysis of raw materials without time-consuming sample preparation methods. The aim of our work was to estimate critical parameters in the analytical specification of oxytetracycline, and consequently the development of a method for quantification and qualification of these parameters by NIR spectroscopy. A Karl Fischer (K.F.) titration to determine the water content, a colorimetric assay method, and Fourier transform-infrared (FT-IR) spectroscopy to identify the oxytetracycline base, were used as reference methods, respectively. Multivariate calibration was performed on NIR spectral data using principal component analysis (PCA), partial least-squares (PLS 1) and principal component regression (PCR) chemometric methods. Multivariate calibration models for NIR spectroscopy have been developed. Using PCA and the Soft Independent Modelling of Class Analogy (SIMCA) approach, we established the cluster model for the determination of sample identity. PLS 1 and PCR regression methods were applied to develop the calibration models for the determination of water content and the assay of the oxytetracycline base. Comparing the PLS and PCR regression methods we found out that the PLS is better established by NIR, especially as the spectroscopic data (NIR spectra) are highly collinear and there are many wavelengths due to non-selective wavelengths. The calibration models for NIR spectroscopy are convenient alternatives to the colorimetric method and to the K.F. method, as well as to FT-IR spectroscopy, in the routine control of incoming material.     

偏最小二乘-近红外漫反射光谱法测定西米替丁药片

研究了应用偏最小二乘法(PLS)同近红外漫反射光谱法结合,对西米替丁片剂药品进行无损非破坏定量分析,建立了最佳的数学校正模型。讨论了波长间隔和主成分数对PLS定量预测能力的影响,预测了未知样品。     

Construction of a universal model for non-invasive identification of penicillins for injection using near-infrared diffuse reflectance spectroscopy

A universal NIR model for identification of 24 types of penicillins for injection has been developed. A total of 194 batches of 24 products from 87 manufacturers in China were used in the study. The classification model is a principal component analysis (PCA) based model consisting of a primary identification library with four sub-libraries. The spectral frequency regions used were 6000–6400 cm⁻¹ and 8400–8900 cm⁻¹ in the main library, 6000–6800 cm⁻¹ in sub-library 1, 4100–12,000 cm⁻¹ in sub-libraries 2 and 3, and 6200–6400 cm⁻¹ and 4700–5000 cm⁻¹ in sub-library 4. The data preprocessing method is the first derivative with nine-point smoothing followed by vector normalization. The distances between spectra were calculated using factors 2–5 for the primary identification library, factors 4–7 for sub-library 1, and factor 2 for sub-libraries 2–4. The specificity of the model was validated, and it had a correct identification rate of approximately 99%. This study has not only confirmed, but also improved the strategy described in our early report (Chong et al. (2009) [11]) to build such a library for the identification of different medicines by NIR.     

Rapid analysis of Radix puerariae by near-infrared spectroscopy

A new, rapid analytical method using near-infrared spectroscopy (NIRS) was developed to differentiate two species of Radix puerariae (GG), Pueraria lobata (YG) and Pueraria thomsonii (FG), and to determine the contents of puerarin, daidzin and total isoflavonoid in the samples. Five isoflavonoids, puerarin, daidzin, daidzein, genistin and genistein were analyzed simultaneously by high-performance liquid chromatography-diode array detection (HPLC-DAD). The total isoflavonoid content was exploited as critical parameter for successful discrimination of the two species. Scattering effect and baseline shift in the NIR spectra were corrected and the spectral features were enhanced by several pre-processing methods. By using linear discriminant analysis (LDA) and soft independent modeling class analogy (SIMCA), samples were separated successfully into two different clusters corresponding to the two GG species. Furthermore, sensitivity and specificity of the classification models were determined to evaluate the performance. Finally, partial least squares (PLS) regression was used to build the correlation models. The results showed that the correlation coefficients of the prediction models are R = 0.970 for the puerarin, R = 0.939 for daidzin and R = 0.969 for total isoflavonoid. The outcome showed that NIRS can serve as routine screening in the quality control of Chinese herbal medicine (CHM).     

Comparison of near-infrared and Raman spectroscopy for the determination of the density of polyethylene pellets

In this study, we compare near-infrared (NIR) and Raman spectroscopy for the determination of the density of linear low density polyethylene (PE) (in a pellet form). As generally known, Raman spectral features are more selective than those of NIR for most chemical samples. NIR spectroscopy has been more extensively used for the quantitative analysis of polymers, but Raman spectroscopy is the better choice as long as the problem of reproducibility of Raman measurements (especially for solid samples), mostly resulting from insufficient sample representation due to probing only localized chemical information and the sensitivity of sample placement with regard to the focal plane, can be overcome. To improve sample representation and reproducibility of Raman measurements, we have employed the wide area illumination (WAI) Raman scheme, capable of illuminating a laser onto a large sample area (28.3 mm²) for Raman spectral collection (a 6-mm laser spot with a focal length of 248 mm). Diffuse reflectance NIR spectra of PE pellets were collected using a sample moving system which allowed for the scanning of large areas. The prediction error was 0.0008 g cm⁻³ for Raman spectroscopy and 0.0011 g cm⁻³ for NIR spectroscopy. The harmonization of inherently selective Raman features and a reproducible spectral collection with correct sample representations using the WAI scheme led to an accurate determination of the density of the PE pellets.     

Electrochemical behaviour of conducting polymers obtained into clay-catalyst layers. An in situ Raman spectroscopy study

In this paper we present the study of the electrochemical properties of the following conducting polymers: poly(o-anisidine), polyaniline and copolymers of aniline and o-anisidine obtained by a new synthetic method. The polymers are synthesized in free-of-acid conditions, using an activated montmorillonitic clay catalyst, known as Maghnite-H⁺ (Mag-H) as proton source. The electrochemical behaviour of poly(o-anisidine) created using Mag-H (PoANI-MagH) and their copolymers with aniline is quite different of those polymers created in HCl solution. In situ Raman data suggest that the structure of PoANI-MagH is a mixture of conducting (polyaniline-type) and redox (phenoxazine or phenazine-type) segments.     

A near-infrared spectroscopy method to determine aminoglycosides in pharmaceutical formulations

The analytical determination of aminoglycosides in pharmaceutical formulations is very difficult due to the lack of chromophores or fluorophores. Several analytical methods have been developed along the years mainly based on derivatization reactions. The European Pharmacopeia (EP) and the United States Pharmacopeia (USP) describe a microbiological assay to the quantification of aminoglycosides. Near infrared spectroscopy (NIRS) can be used alternatively to analyse aminoglycosides without the need of derivatization reactions or other type of sample processing. A new NIRS based method was developed for the analysis of the aminoglycoside antibiotic neomycin. The method was developed with samples based on a commercial formulation containing neomycin sulphate and three excipients: lactose, talc and magnesium stearate. Synthetic and doped samples were manufactured for this purpose. Three lots of a commercial solid formulation were also used to assess the validity of the method to quantify neomycin sulphate in the industrial pharmaceutical product. The method proposes measurements in reflectance mode using a Fourier-transform near infrared (FT-NIR) spectrometer. Partial least squares regression was the multivariate method adopted to calibrate the NIR spectra with the neomycin sulphate mass fraction. The concentration of neomycin sulphate present in the commercial samples was confirmed by HPLC with pre-column derivatization with phenylisocyanate. Results show that neomycin sulphate was determined successfully in the commercial samples using the method calibrated with the doped samples (mass fraction error of 6.6%). Moreover, the synthetic samples were found to be unqualified to develop the method, producing a biased calibration.     

Rapid detection of Rosa laevigata polysaccharide content by near-infrared spectroscopy

We have investigated surface-enhanced Raman spectroscopy (SERS) spectrum of Omethoate (O,O-dimethyl-S-methylcarbamoylmethylthiophosphate). It is found significant signals in the ordinary Raman spectrum for solid-state Omethoate as well as strong vibrational signals absorbed on the silver sol surface which is prepared by γ-irradiation technique at a very low concentration. Effects of pH and anions (Cl-, Br-, I-) on the adsorption orientation are investigated as well. Two different adsorption mechanisms are deduced, depending on the experimental conditions. The sulfur atom or the sulfur and two oxygen atoms are adsorbed onto the silver sol surface. Among halide ions, Br- and I- are more strongly adsorbed onto the silver sol surface. As a result, the adsorption of Omethoate is less effective due to their steric hindrance.     

Resonance Raman spectroscopy of red blood cells using near-infrared laser excitation

Resonance Raman spectra of oxygenated and deoxygenated functional erythrocytes recorded using 785 nm laser excitation are presented. The high-quality spectra show a mixture of enhanced A_1g, A_2g, B_1g, B_2g, E_u and vinyl modes. The high sensitivity of the Raman system enabled spectra from four oxygenation and deoxygenation cycles to be recorded with only 18 mW of power at the sample over a 60-minute period. This low power prevented photo-/thermal degradation and negated protein denaturation leading to heme aggregation. The large database consisting of 210 spectra from the four cycles was analyzed with principal components analysis (PCA). The PC1 loadings plot provided exquisite detail on bands associated with the oxygenated and deoxygenated states. The enhancement of a band at 567 cm⁻¹, observed in the spectra of oxygenated cells and the corresponding PC1 loadings plot, was assigned to the Fe–O₂ stretching mode, while a band appearing at 419 cm⁻¹ was assigned to the Fe–O–O bending mode based on previous studies. For deoxygenated cells, the enhancement of B_1g modes at 785 nm excitation is consistent with vibronic coupling between band III and the Soret transition. In the case of oxygenated cells, the enhancement of iron-axial out-of-plane modes and non-totally symmetric modes is consistent with enhancement into the y,z-polarized transition centered at 785 nm. The enhancement of non-totally symmetric B_1g modes in oxygenated cells suggests vibronic coupling between band IV and the Soret band. This study provides new insights into the vibrational dynamics, electronic structure and resonant enhancement of heme moieties within functional erythrocytes at near-IR excitation wavelengths. Part of this work was first presented at SPEC 2006, Shedding New Light on Disease: Optical Diagnosis for the New Millennium, held at Heidelberg, Germany, on 20–24 May 2006.