Real-time monitoring of polyurethane production using near-infrared spectroscopy

A process near-infrared (NIR) spectrophotometer was interfaced directly to a reactor by using a fiber optic bundle interactance immersion probe. This remote sensor configuration enables the production of polyurethanes to be monitored in real-time. A Beer's Law model was derived for the quantitative determination of isocyanate in the urethane polymerization reaction. Statistical process control was used to observe trends in the polymerization reaction. The integration of NIR process analytical instrumentation directly into the process provides real-time chemical information that yields improvements in product quality and consistency, while minimizing reaction time.     

Feasibility of monitoring acetic acid process using near-infrared spectroscopy

Near-infrared (NIR) spectroscopy has been utilized to demonstrate its feasibility for the measurement of major components in the acetic acid process. In order to simulate the acetic acid process, synthetic mixtures were prepared from five different components: acetic acid, methyl acetate, methyl iodide, water, and potassium iodide. Partial least squares (PLS) regression was utilized to differentiate the spectral characteristics as well as to quantify each component for the mixtures. The spectral features of acetic acid, methyl acetate, methyl iodide, and water are noticeably different with each other over the entire NIR region. The quantity of iodide ion, which does not absorb NIR radiation, was determined using the wavelength shift and intensity change of water absorption band caused by the change of iodide ion concentration. The PLS calibration results of the five components show good correlation with reference data. They also demonstrate the technical feasibility of NIR spectroscopy for monitoring important components in the acetic acid process.     

Chemometrics in near-infrared spectroscopy

Spectroscopy methods of chemical analysis are excellent for the application of chemometric methods, because the measurements at many different wavelengths provide inherently multivariate data. The chemist generally requires three categories of information from specimens under investigation: quantitative data, qualitative data, and fundamental information on the properties of the material. Spectroscopy has long been used for all three purposes; the recent application of chemometric algorithms has assisted greatly in these endeavors. Although there is some overlap, three chemometric methods correspond to the three types of information: multiple regression, discriminant analysis, and principal components analysis. The basis of these chemometric methods and some of their strengths and limitations in application to near-infrared spectroscopy are discussed.     

Quantification of paracetamol in intact tablets using near-infrared transmittance spectroscopy.

Production batch samples of paracetamol tablets and specially prepared out-of-specification batches covering the range 90-110% of the stated amount (500 mg) were analysed by the BP official UV assay and by NIR transmittance spectroscopy. NIR measurements were made on 20 intact tablets from each batch, scanned five times each (10 min measurement time per batch) over the spectral range 6000-11,520 cm-1. An average spectrum was calculated for each batch. Partial least squares (PLS) regression models were set up using a calibration set (20 batches) between the NIR response and the reference tablet paracetamol content (UV). Various pre-treatments of the spectra were examined; the smallest relative standard error of prediction (0.73%) was obtained using the first derivative of the absorbance over the full spectrum. Only two principal components were required for the PLS model to give a good relationship between the spectral information and paracetamol content. Applying this model to the validation set (15 batches) gave a mean bias of -0.08% and a mean accuracy of 0.59% with relative standard deviations of 0.75 and 0.44%, respectively. The proposed method is non-destructive and therefore lends itself to on-line/at-line production control purposes. The method is easy to use and does not require a knowledge of the mass of the tablets.     

Theoretical analysis of tablet hardness prediction using chemoinformetric near-infrared spectroscopy.

In order to clarify the theoretical basis of the variability in the measurement of tablet hardness by compression pressure, NIR spectroscopic methods were used to predict tablet hardness of the formulations. Tablets (200 mg, 8 mm in diameter) consisting of berberine chloride, lactose, and potato starch were formed at various compression pressures (59, 78, 98, 127, 195 MPa). The hardness and the distribution of micropores were measured. The reflectance NIR spectra of various compressed tablets were used as a calibration set to establish a calibration model to predict tablet hardness by principal component regression (PCR) analysis. The distribution of micropores was shifted to a smaller pore size with increasing compression pressure. The total pore volume of tablets decreased as the compression pressure increased. The hardness increased as the compression pressure increased. The hardness could be predicted using a calibration model consisting of 7 principal components (PCs) obtained by PCR. The relationship between the predicted and the actual hardness values exhibited a straight line, an R(2) of 0.925. In order to understand the theoretical analysis (scientific background) of calibration models used to evaluate tablet hardness, the standard error of cross validation (SEV) values, the loading vectors of each PC and the regression vector were investigated. The result obtained with the calibration models for hardness suggested that the regression vector might involve physical and chemical factors. In contrast, the porosity could be predicted using a calibration model composed of 2 PCs. The relationship between the predicted and the actual total pore volume showed a straight line with R(2) = 0.801. The regression vector of the total pore volume might be due to physical factors.     

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.     

Structure analysis of aromatic medicines containing nitrogen using near-infrared spectroscopy and generalized two-dimensional correlation spectroscopy

Four aromatic medicines (acetaminophen; niacinamide; p-aminophenol; nicotinic acid) containing nitrogen were investigated by FT-NIR (Fourier transform near-infrared) spectroscopy and generalized two-dimensional (2D) correlation spectroscopy. The FT-NIR spectra were measured over a temperature range of 30-130 degrees C. By combining near-infrared spectroscopy, generalized 2D correlation spectroscopy and references, the molecular structures (especially the hydrogen bond related with nitrogen) were analyzed and the NIR band assignments were performed. The results will be helpful to the understanding of aromatic medicines containing nitrogen and the utility of these substances.     

Monitoring tumor response during photodynamic therapy using near-infrared photon-migration spectroscopy.

Benzoporphyrin-derivative (BPD)-monoacid-ring A photodynamic therapy (PDT) was performed on subcutaneous tumor implants in a rat ovarian cancer model. In order to assess PDT efficacy the tumor and normal tissue optical properties were measured noninvasively prior to and during PDT using frequency-domain photon migration (FDPM). FDPM data were used to quantify tissue absorption and reduced scattering properties (given by the parameters mu a and mu's, respectively) at four near-infrared (NIR) wavelengths (674, 811, 849 and 956 nm). Tissue physiologic properties, including the in vivo concentration of BPD, deoxy-hemoglobin (Hb), oxy-hemoglobin (HbO2), total hemoglobin (TotHb), water (H2O) and percent tissue hemoglobin oxygen saturation (%StO2), were calculated from optical property data. PDT efficacy was also determined from morphometric analysis of tumor necrosis in histologic specimens. All the measured tumor properties changed significantly during PDT. [Hb] increased by 9%, while [HbO2], [TotHb] and %StO2 decreased by 18, 7 and 12%, respectively. Using histologic data we show that long-term PDT efficacy is highly correlated to mean BPD concentration in tumor and PDT-induced acute changes in [HbO2], [TotHb] and %StO2 (correlation coefficients of 0.829, 0.817 and 0.953, respectively). Overall, our results indicate that NIR FDPM spectroscopy is able to quantify noninvasively and dynamically the PDT-induced physiological effects in vivo that are highly correlated with therapeutic efficacy.     

Quantification of albumin in urine using preconcentration and near-infrared diffuse reflectance spectroscopy

Urinary albumin is an important diagnostic and prognostic marker for cardiorenal disease. Recent studies have shown that elevation of albumin excretion even in normal concentration range is associated with increased cardiorenal risk. Therefore, accurate measurement of urinary albumin in normal concentration range is necessary for clinical diagnosis. In this work, thiourea-functionalized silica nanoparticles are prepared and used for preconcentration of albumin in urine. The adsorbent with the analyte was then used for near-infrared diffuse reflectance spectroscopy measurement directly and partial least squares model was established for quantitative prediction. Forty samples were taken as calibration set for establishing PLS model and 17 samples were used for validation of the method. The correlation coefficient and the root mean squared error of cross validation is 0.9986 and 0.43, respectively. Residual predictive deviation value of the model is as high as 18.8. The recoveries of the 17 validation samples in the concentration range of 3.39-24.39 mg/L are between 95.9%-113.1%. Therefore, the method may provide a candidate method to quantify albumin excretion in urine.     

Identification of mixed states using electron spectroscopy

X-ray photoelectron spectroscopy (XPS) is a highly surface sensitive technique and is used in identification of oxidation states in catalysts at various stages. Copper, silver and platinum based catalysts are widely used in petrochemical industries. Our attempts at characterization have revealed that elements in these catalysts are normally present then one stae. It is terefore essential to identify their in more chemical as well as oxidation states. Such identification combined with quantitative analysis of data is helpful in correlating catalyst performance. Examples of mixed state identification are presented.IPCL Communication No. 266     

Identification of archaeological ivories using FT-Raman spectroscopy

FT-Raman spectroscopy has been used successfully for the non-destructive identification of modern ivories and is evaluated here for the identification of osseous materials from archaeological sites. Results on archaeological ivories are reported and the problems faced in matching FT-Raman spectra to standards for the validation of these materials are highlighted. Archaeological specimens of different dates, provenance and taphonomic history, including both conserved and unconserved items, have been analysed.     

Identification of synthetic precursors of amphetamine-like drugs using Raman spectroscopy and ab initio calculations: beta-Methyl-beta-nitrostyrene derivatives

The present work reports a vibrational spectroscopic study of several beta-methyl-beta-nitrostyrene derivatives, which are important intermediates in the synthesis of illicit amphetamine-like drugs, such as 3,4-methylenedioxymethamphetamine (MDMA), 3,4-methylenedioxyamphetamine (MDA), p-methoxyamphetamine (PMA) and 4-methylthioamphetamine (4-MTA). A complete conformational analysis of 3,4-methylenedioxy-beta-methyl-beta-nitrostyrene (3,4-MD-MeNS), 4-methoxy-beta-methyl-beta-nitrostyrene (4-MeO-MeNS), 4-methylthio-beta-methyl-beta-nitrostyrene (4-MeS-MeNS), was carried out by Raman spectroscopy coupled to ab initio MO calculations--both complete geometry optimisation and harmonic frequency calculation. The Raman spectra show characteristic features of these precursors, which allow their ready differentiation and identification. It was verified that the conformational behaviour of these systems is mainly determined by the stabilising effect of pi-electron delocalisation.     

Fire impact on forest soils evaluated using near-infrared spectroscopy and multivariate calibration

The assessment of physico-chemical properties in forest soils affected by fires was evaluated using near infrared reflectance (NIR) spectroscopy coupled with chemometric methods. In order to describe the soil properties, measurements were taken of the total organic carbon on solid phase, the total nitrogen content, the organic carbon and the specific absorbences at 254 and 280 nm of humic substances, organic carbon in humic and fulvic acids, concentrations of NH₄⁺, Ca²⁺, Mg²⁺, K⁺ and phosphorus in addition to NIR spectra. Then, a fire recurrence index was defined and calculated according to the different fires extents affecting soils. This calculation includes the occurrence of fires as well as the time elapsed since the last fire. This study shows that NIR spectroscopy could be considered as a tool for soil monitoring, particularly for the quantitative prediction of the total organic carbon, total nitrogen content, organic carbon in humic substances, concentrations of phosphorus, Mg²⁺, Ca²⁺ and NH₄⁺ and humic substances UVSA₂₅₄. Further validation in this field is necessary however, to try and make successful predictions of K⁺, organic carbon in humic and fulvic acids and the humic substances UVSA₂₈₀. Moreover, NIR coupled with PLS can also be useful to predict the fire recurrence index in order to determine the spatial variability. Also this method can be used to map more or less burned areas and possibly to apply adequate rehabilitation techniques, like soil litter reconstitution with organic enrichments (industrial composts) or reforestation. Finally, the proposed recurrence index can be considered representative of the state of the soils.     

Non-destructive dating of fiber-based gelatin silver prints using near-infrared spectroscopy and multivariate analysis

An innovative approach to date fiber-based gelatin silver prints using near-infrared spectroscopy (NIR) and multivariate analysis is presented. NIR spectra were acquired for 152 film stills printed in the USA between 1914 and 1986, and partial least square (PLS) analysis was used to correlate the spectra with the year the photographs were printed. Principal component analysis and spectral interpretation helped clarify the underlying correlation between the print date and the composition and ageing of the photographic papers. The method was successfully validated with an independent set of 66 film stills printed in the USA, and a prediction error (root mean square error of prediction) of 6 years was achieved. The method was also tested on films stills printed in Germany and Russia, as well as amateur prints and photographs in the collection of the Museum of Modern Art. The prediction error was significantly larger, with the exception of the amateur prints, due to differences in the composition and/or properties of the papers depending on their geographical origin and purpose as confirmed by discriminant analysis.     

Quantitative monitoring of an activated sludge reactor using on-line UV-visible and near-infrared spectroscopy

The performance of an activated sludge reactor can be significantly enhanced through use of continuous and real-time process-state monitoring, which avoids the need to sample for off-line analysis and to use chemicals. Despite the complexity associated with wastewater treatment systems, spectroscopic methods coupled with chemometric tools have been shown to be powerful tools for bioprocess monitoring and control. Once implemented and optimized, these methods are fast, nondestructive, user friendly, and most importantly, they can be implemented in situ, permitting rapid inference of the process state at any moment. In this work, UV-visible and NIR spectroscopy were used to monitor an activated sludge reactor using in situ immersion probes connected to the respective analyzers by optical fibers. During the monitoring period, disturbances to the biological system were induced to test the ability of each spectroscopic method to detect the changes in the system. Calibration models based on partial least squares (PLS) regression were developed for three key process parameters, namely chemical oxygen demand (COD), nitrate concentration (N-NO₃⁻), and total suspended solids (TSS). For NIR, the best results were achieved for TSS, with a relative error of 14.1% and a correlation coefficient of 0.91. The UV-visible technique gave similar results for the three parameters: an error of ~25% and correlation coefficients of ~0.82 for COD and TSS and 0.87 for N-NO₃⁻. The results obtained demonstrate that both techniques are suitable for consideration as alternative methods for monitoring and controlling wastewater treatment processes, presenting clear advantages when compared with the reference methods for wastewater treatment process qualification.     

近红外光谱法应用于奥美拉唑含量分析

基于近红外光谱分析技术建立奥美拉唑定量分析方法.以高效液相色谱法作为参考方法,采用偏最小二乘法(PLS)对同一厂家不同批号的奥美拉唑肠溶胶囊建立校正模型,所建模型相关系数(R)为0.978,校正均方差(RMSEC)为0.0899,交叉验证均方差(RMSECV)为0.182,校正模型的预测均方差(RMSEP)为0.161...     

Characterisation of heavy oils using near-infrared spectroscopy: optimisation of pre-processing methods and variable selection

In this study, chemometric predictive models were developed from near infrared (NIR) spectra for the quantitative determination of saturates, aromatics, resins and asphaltens (SARA) in heavy petroleum products. Model optimisation was based on adequate pre-processing and/or variable selection. In addition to classical methods, the potential of a genetic algorithm (GA) optimisation, which allows the co-optimisation of pre-processing methods and variable selection, was evaluated. The prediction results obtained with the different models were compared and decision regarding their statistical significance was taken applying a randomization t-test. Finally, the results obtained for the root mean square errors of prediction (and the corresponding concentration range) expressed in %(w/w), are 1.51 (14.1-99.1) for saturates, 1.59 (0.7-61.1) for aromatics, 0.77 (0-34.5) for resins and 1.26 (0-14.7) for asphaltens. In addition, the usefulness of the proposed optimisation method for global interpretation is shown, in accordance with the known chemical composition of SARA fractions.     

Quantitative aspects of near-infrared Fourier transform Raman spectroscopy

Three fundamental behaviors of vibrational spectroscopy data manipulation routinely associated with Fourier transform infrared (FTIR) spectroscopy are evaluated for near-infrared (NIR) Fourier transform Raman spectroscopy. Spectral reproducibility, spectral subtraction and sensitivity are examined relative to the NIR FT-Raman experiment. Quantitative predictive ability is compared for identical sets of samples containing mixtures of the three xylene isomers. Partial least-squares analysis is used to compare predictive ability. IR performance is found to be better than Raman, though the potential for method development using NIR FT-Raman is shown to be quite promising.