Complete quality analysis of commercial surface-active products by Fourier-transform near infrared spectroscopy

Using proper calibration data Fourier-transform near infrared spectroscopy is used for developing multivariate calibrations for different analytical determinations routinely used in the surfactants industry. Four products were studied: oleyl-cetyl alcohol polyethoxylated, cocamidopropyl betaine (CAPB), sodium lauryl sulfate (SLS) and nonylphenol polyethoxylated (NPEO). Calibrations for major as well as very low concentrated compounds were achieved and every model was validated through linearity, bias, accuracy and precision tests, showing good results and the viability of NIR spectroscopy as a full quality control method for this products. Duplicate and complete analysis on a single sample takes at most 3 min, requiring neither sample preparation nor the use of reagents. The analytical reference procedures involved in this work represent the typical ones used in the industry and the NIR method shows good results in the analysis of components with weight concentrations less than 1%.     

A novel storage method for near infrared spectroscopy chemometric models

Chemometric Modeling Markup Language (CMML) is developed by us for containing chemometrics models within one document through converting binary data into strings by base64 encode/decode algorithms to solve the interoperability issue in sharing chemometrics models. It provides a base functionality for storage of sampling, variable selection, pretreating, outlier and modeling parameters and data. With the help of base64 algorithm, the usability of CMML is in equilibrium with size by transforming the binary data into base64 encoded string. Due to the advantages of Extensible Markup Language (XML), models stored in CMML can be easily reused in various other software and programming languages as long as the programming language has XML parsing library. One can also use the XML Path Language (XPath) query language to select desired data from the CMML file effectively. The application of this language in near infrared spectroscopy model storage is implemented as a class in C++ language and available as open source software (http://code.google.com/p/cmml), and the implementations in other languages, such as MATLAB and R are in progress.     

Micro-thermal field-flow fractionation: new high-performance method for particle size distribution analysis

Micro-thermal field-flow fractionation (mu-TFFF) was applied to the separation of polystyrene latices. This new high-resolution technique allows determination of the particle size distribution (PSD) if carried out under optimized experimental conditions. The optimum temperature of the accumulation wall, which influences the relaxation processes and, consequently, the zone broadening, was chosen on the basis of our prior work. The flow rate was chosen as a compromise between the theoretical optimum value, which is very low because the diffusion coefficients of the colloidal particles are very small, and a value allowing performance of the PSD analysis in a reasonable time. These experimental conditions can be manipulated easily due to the high versatility of mu-TFFF, which follows from a large decrease of the heat energy flux across the channel with its reduced dimensions in comparison with standard TFFF. The PSDs obtained from mu-TFFF data are compared with results from quasi-elastic laser light scattering (QELS) and transmission electron microscopy (TEM). It has been found that a baseline resolution of a model mixture of two samples of close average particle diameters can be achieved by an appropriate choice of the temperature drop in mu-TFFF, whereas only a broad, unresolved PSD of the mixed sample was obtained from the QELS measurement. The TEM of the mixed sample revealed the presence of two particle size populations. However, the number of particles which are practically counted on a TEM picture is several orders of magnitude lower than the number of particles taken into account in mu-TFFF or QELS. Consequently, the PSD obtained from the TEM did not represent the whole sample. Comparison of mu-TFFF with modern hydrodynamic chromatography (HC) has shown that the methods exhibit roughly the same resolution and time of analysis. Nevertheless, mu-TFFF is a more universal technique because the separation of the colloidal particles or of the macromolecules within a broad range of molar masses is carried out on the same channel, as demonstrated previously.     

Role of emulsifier on the particle size and polymer particle size distribution using multiwavelength spectroscopy measurements

Latex emulsions depend strongly on the polymer composition, and particle size distribution, which in turn, is a function of the preparation of the latex and on the formulation and composition variables. This study reports measurements of particle size and particle size distribution of latex emulsions as function of the reaction time and the type and concentration of emulsifier by using the multiwavelength spectroscopy technique. Results show changes in the particle size of latex emulsions with the reaction time, obtaining larger particles and broader distributions with increasing of Tween 80 ratio. The steric stabilization provides the sole nonionic emulsifier is not enough to protect the polymer particle, causing the flocculation among the interactive particles, resulting in unstable latex. However, latex emulsions prepared with Tween 80 ratio <70 wt.% can stabilize efficiently the nucleated particles, probably due to the effects provided by both, the electrostatic and steric stabilization mechanisms. The same effect is shown in the curves of conversion (%) as a function of reaction time, resulting in slower polymerization rate for Tween 80 ratio >70 wt.%. On the other hand, smaller polymer particles, in all range of emulsifier mixture, have been obtained to higher emulsifier concentration.     

Comparing near infrared and Raman spectroscopy for on-line monitoring of emulsion copolymerization reactions

In this work, Raman and Near InfraRed (NIR) spectroscopies are evaluated for the monitoring of different semicontinuous emulsion homo- and co-polymerization reactions. Important process variables, namely monomer concentrations and average particle sizes, were monitored by both techniques under realistic conditions that would be found in an industrial environment (e.g. low signal/noise ratio, probe placed in the reaction medium). Results suggest that Raman and NIR are suitable for on-line monitoring of emulsion polymerization reactions and that the success of their application is mainly related to representative calibration models used for the estimation of the properties of interest.     

Feasibility study on qualitative and quantitative analysis in tea by near infrared spectroscopy with multivariate calibration

This study attempted the feasibility to use near infrared (NIR) spectroscopy as a rapid analysis method to qualitative and quantitative assessment of the tea quality. NIR spectroscopy with soft independent modeling of class analogy (SIMCA) method was proposed to identify rapidly tea varieties in this paper. In the experiment, four tea varieties from Longjing, Biluochun, Qihong and Tieguanyin were studied. The better results were achieved following as: the identification rate equals to 90% only for Longjing in training set; 80% only for Biluochun in test set; while, the remaining equal to 100%. A partial least squares (PLS) algorithm is used to predict the content of caffeine and total polyphenols in tea. The models are calibrated by cross-validation and the best number of PLS factors was achieved according to the lowest root mean square error of cross-validation (RMSECV). The correlation coefficients and the root mean square error of prediction (RMSEP) in the test set were used as the evaluation parameters for the models as follows: R = 0.9688, RMSEP = 0.0836% for the caffeine; R = 0.9299, RMSEP = 1.1138% for total polyphenols. The overall results demonstrate that NIR spectroscopy with multivariate calibration could be successfully applied as a rapid method not only to identify the tea varieties but also to determine simultaneously some chemical compositions contents in tea.     

Prediction of phenolic compounds in red wine fermentations by visible and near infrared spectroscopy

Near infrared (NIR) spectroscopy was used to simultaneously predict the concentrations of malvidin-3-glucoside (M3G), pigmented polymers (PP) and tannins (T) in red wine. A total of 495 samples from 32 commercial scale red wine fermentations over two vintages using two grape varieties (Cabernet Sauvignon and Shiraz), and also including as additional variables two types of fermenters, two different yeasts, and three fermentation temperatures were used. Samples were scanned in transmission mode (400-2500 nm) using a monochromator instrument (NIRSystems6500). Calibration equations were developed from high performance liquid chromatography (HPLC) and NIR data using partial least squares (PLS) regression with internal cross validation. Using PLS regression, very good calibration statistics (R_cal²>0.80) were obtained for the prediction of M3G, PP and T with standard deviation (S.D.)/standard error in cross validation (SECV) ratio (residual predictive deviation, RPD)) ranging from 1.8 to 5.8. It was concluded that near infrared spectroscopy could be used as rapid alternative method for the prediction of the concentration of phenolic compounds in red wine fermentations.     

Simultaneous measurement of glucose and glutamine in aqueous solutions by near infrared spectroscopy

A method is described for measuring the concentrations of both glucose and glutamine in binary mixtures from near infrared (NIR) absorption spectra. Spectra are collected over the range from 5000–4000/cm (2.0–2.5μm) with a 1-mm optical path length. Glucose absorbance features at 4710, 4400, and 4300/cm and glutamine features at 4700, 4580, and 4390/cm provide the analytical information required for the measurement. Multivariate calibration models are generated by using partial least squares (PLS) regression alone and PLS regression combined with a preprocessing digital Fourier filtering step. The ideal number of PLS factors and spectral range are identified separately for each analyte. In addition, the optimum Fourier filter parameters are established for both compounds. The best overall analytical performance is obtained by combining Fourier filtering and PLS regression. Glucose measurements are established over the concentration range from 1.66–59.91 mM, with a standard error of prediction (SEP) of 0.32 mM and a mean percent error of 1.84%. Glutamine can be measured over the concentration range from 1.10–30.65 mM with a SEP of 0.75 mM and a mean percent error of 6.67%. These results demonstrate the analytical utility of NIR spectroscopy for monitoring glucose and glutamine levels in mammalian and insect cell cultures.     

A particle size distribution analysis of stressed HPLC column packing material

Summary A particle size distribution analysis has been completed on three different HPLC column packing materials including silica gel (Si60) and two bonded phases (RP8 and RP18). The stationary phases were subjected to 18 hours stress with 1 N or 3 N KOH and found to have quantitatively different distribution patterns initially, at 13 hours and finally at 18 hours although the average particle diameters for the Si60 and RP8 were the same or higher at 18 hours as initially. Thirteen hoursstress with sodium octanesulfonate, tetrabutylammonium phosphate and ammonium acetate at exaggerated conditions also resulted in distributional changes with the Si60 and RP8 decreasing in average particle diameter when exposed to ammonium acetate and tetrabutylammonium stressing respectively.     

Relationship between the particle size distribution of commercial fully porous and superficially porous high-performance liquid chromatography column packings and their chromatographic performance

The separation efficiency and kinetics of several commercial HPLC particle types (both fully porous and superficially porous) have been investigated using a pharmaceutical weakly basic N-containing compound as a test molecule. A strong trend between the particle size distribution (PSD) of the particles and the typically employed “goodness of packing”-parameters was observed. The relative standard deviation of the PSD of the tested particles ranged between 0.05 and 0.2, and in this range, a near linear relationship between the A-term constant, the h_min-value and the minimal separation impedance was found. The experimental findings hence confirm the recent observations regarding the relationship between the narrow PSD of the recently commercialized porous-shell particles and their superior efficiency and kinetic performance. The outcome also suggests that the performance of the current generation of fully porous particle columns could be significantly improved if the PSD of these particles could be reduced.     

Analytical applications of photon correlation spectroscopy for size distribution measurements of natural colloidal suspensions: capabilities and limitations

Particles are ubiquitous in all natural systems and play an important role in the control and fate of nutrients and pollutants. Currently, only limited information is available concerning particle number and size distributions, owing to the problems involved in their experimental determination. In the present paper, limitations and optimal conditions for particle size determinations of environmental samples using photon correlation spectroscopy are studied. The detection limit, the effects of polydispersity of the sample and the refractive index value are discussed based on results obtained with synthetic colloids. The photon correlation spectroscopic determination of particle size distributions in real aquatic systems is also presented in the second part of the paper.     

Determination of oleic acid in sunflower seeds by infrared spectroscopy and multivariate calibration method

A method for the determination of oleic acid in sunflower seeds is proposed. One hundred samples of sunflower seeds were analyzed by near-infrared diffuse reflectance spectroscopy (NIRDRS). The direct measures were realized in ground and sifted seeds. The PLS multivariate calibration model was obtained using first derivate absorbance values as response matrix, while the oleic acid concentration matrix was obtained analyzing the seed samples by gas chromatography with a flame ionization detector (GC-FID). The NIRDRS-PLS model was validated externally using unknown samples of sunflower seeds. The accuracy and precision of the method was evaluated using GC as reference method. The following figures of merit (FOM) were obtained: LOD = 3.4% (w/w); LOQ = 11.3% (w/w); SEN = 8 × 10⁻⁵; SEL = 0.15; analytical sensibility (γ) = 1.5 and linear range (LR) = 18.1-89.2% (w/w). This method is useful for the fast determination of oleic acid in sunflower seeds and for quality control of raw materials.     

Determination of particle size distribution by gravitational field-flow fractionation: Dimensional characterization of silica particles

Summary Gravitational field-flow fractionation (GFFF) is the simplest and cheapest of field-flow fractionation (FFF) techniques, although it is still at an early development stage. The application of GFFF to the determination of particle size distribution (PSD) of silica particles used as chromatographic supports is described. The accuracy of the method is evaluated by comparing PSDs obtained by GFFF with those obtained by laser diffraction, a non-separative technique widely applied to particle characterization. It is ultimately demonstrated that a low-cost GFFF channel can simply replace the column of a standard HPLC system, allowing laboratories that are not specialized in size analysis to perform accurate PSD studies with standard HPLC expertise.     

Feasibility study for the use of near infrared spectroscopy in the qualitative and quantitative analysis of green tea, Camellia sinensis (L.)

This paper indicates the possibility to use near infrared spectroscopy (NIR) combined with PLS as a rapid method to estimate the quality of green tea. NIR is used to build calibration models to predict the content of caffeine, epigallocatechin gallate (EGCG) and epicatechin (EC) and for the prediction of the total antioxidant capacity of green tea. For the determination of the total antioxidant capacity, the trolox equivalent antioxidant capacity (TEAC) method is used. Until now, the prediction of the antioxidant capacity as such by use of NIR has not been reported. For caffeine and TEAC, models are build for the whole green tea leaves and also for the ground leaves. For the polyphenols (EGCG and EC), only models for the whole leaves are investigated. A partial least squares (PLS) algorithm is used to perform the calibration. To decide upon the number of PLS factors included in the PLS model, the model with the lowest root mean square error of cross-validation (RMSECV) for the training set is chosen. The correlation coefficient (r) between the predicted and the reference results for the test set is used as an evaluation parameter for the models: for the TEAC results r=0.90 for the model with the whole leaves, r=0.86 for the model with the powdered leaves are obtained. The caffeine prediction model has a correlation coefficient r=0.96 for the whole leaves and r=0.93 for the ground leaves. The correlation coefficient for the EGCG and the EC content models are, respectively 0.83 and 0.44.     

Classification and quantitation of finishing oils by near infrared spectroscopy

One of the steps in the manufacturing of synthetic fibres involves using finishing oils to ensure proper lubricity and adherence between fibres, and also the absence of static electricity. Choosing an appropriate oil and dosage are essential with a view to ensuring effective subsequent processing and use. The aim of this work was to develop a fast method for determining the different finishing oil content in acrylic fibres by use of near infrared spectroscopy (NIRS) in conjunction with partial least-squares regression (PLSR). The high similarity between the NIR spectra of finishing oils led us to assume that a single calibration model might allow determine the oil content. However, the inability to quantify accurately different finishing oils by using a sole calibration model, constrain to the prior classification of the fibres coated with the different finishing oils. Two different pattern recognition methods were used: supervised independent modeling of class analogy (SIMCA) and artificial neural networks (ANNs). However, the low contribution of the finishing oil to the NIR spectrum for the fibre sample, the high similarity between the NIR spectra for the different oils and the substantial contribution of the linear density of the acrylic fibre to the spectrum precluded correct classification by SIMCA; on the other hand, ANNs provided good results. By constructing appropriate PLSR models for the different types of finishing oils, these can be accurately determined in acrylic fibres.     

A new method for determining droplet size distribution of an unstable dispersion

The droplet size distribution (DSD) of unstable water/oil dispersions has been studied with a new technique. The technique is based on a fast dilution of the dispersion injected into an analysis vessel where the DSD is analyzed with a video camera and a image analyzing tool. Dispersions generated with no pressure drop in the flow rig were compared to those generated with a pressure drop over a needle valve. The latter dispersion showed a much narrower DSD and a lower average droplet diameter. The results are from preliminary experiments in order to evaluate the method.     

A particle size distribution analysis of used HPLC column packing material

Summary Particle size distribution analysis and scanning electron microscopy (SEM) were carried out on eight used HPLC columns containing either irregular silica based, spherical silica based or spherical polymer based packing material. Particle size distributions of the used irregular silica based columns were at least bimodat at the outlet ends and either biomodal or log-normal at the inlet ends with regular progressions between the two extremes through the column. A new ODS-3 column showed log-normal size distributions from the inlet to the outlet ends. Spherical silica based column particle size distributions showed distinct shoulders on large central distribution peaks in most column sections with various degrees of shoulder erosion. The spherical resin based column showed a broader inlet particle size distribution progressing to a very narrow outlet distribution. SEMs of both irregular and spherical silica based columns revealed a larger number of undersized particles and debris at the outlet than inlet ends which could have resulted from stationary phase degradation, since this was not seen in the new ODS-3 column. While several SEMs of the spherical silica based columns revealed hollow spheres and twins, the spherical resin based column packing showed stress fractures or wrinkle lines resulting from use or dehydration.Presented in part as a poster at the HPLC '92, 16^th Symposium on CLC, Baltimore, MD, USA.     

High performance liquid chromatography column packings with deliberately broadened particle size distribution: relation between column performance and packing structure

The effect of the addition of 25%, 50% and 75% (weight percent, wt%) of larger particles (resp. 3 and 5 μm) to a commercial batch of 1.9 μm particles has been investigated as an academic exercise to study the effects of particle size distribution on the kinetic performance of packed bed columns in a magnified way. Comparing the performance of the different mixtures in a kinetic plot, it could be irrefutably shown that the addition of larger particles to a commercial batch of small particles cannot be expected to lead to an improved kinetic performance. Whereas the addition of 25 wt% of larger particles still only has a minor negative effect, a significantly deteriorated performance is obtained when 50 or 75 wt% of larger particles are added. In this case, separation impedance number increases up to 200% were observed. Studying the packing structure through computational packing simulations, together with the experimental determination of the external porosity, helped in understanding the obtained results. This showed that small particles tend to settle in the flow-through pores surrounding the larger particles, leading to very high packing densities (external porosities as low as 32% were observed) and also negatively influencing the column permeability as well as the band broadening (because of the broadened flow-through pore size range).     

Comparison and joint use of near infrared spectroscopy and Fourier transform mid infrared spectroscopy for the determination of wine parameters

A study of the statistic characteristics of the multidetermination of several enological parameters - namely, alcoholic degree, volumic mass, total acidity, glycerol, total polyphenol index, lactic acid and total sulphur dioxide - depending on the spectroscopic zone employed, was carried out. The two techniques used were near infrared spectroscopy (NIRS) and Fourier transform mid infrared spectroscopy (FT-MIRS). The combination of these two regions (sum of their spectra) was also studied. NIRS yielded better results, but the use of both zones improved the determination of glycerol and total sulphur dioxide. The training and validation sets used for developing general equations were built with samples from different apellation d’origine, different wine types, etc. Partial least squares regression was used for multivariate calibration, using systematic cross validation in the calibration stage and external validation in the testing stage. Sample preparation was not required.     

Rapid differentiation among bacteria that cause gastroenteritis by use of low-resolution Raman spectroscopy and PLS discriminant analysis

Use of classical microbiological methods to differentiate bacteria that cause gastroenteritis is cumbersome but usually very efficient. The high cost of reagents and the time required for such identifications, approximately four days, could have serious consequences, however, mainly when the patients are children, the elderly, or adults with low resistance. The search for new methods enabling rapid and reagentless differentiation of these microorganisms is, therefore, extremely relevant. In this work the main microorganisms responsible for gastroenteritis, Escherichia coli, Salmonella choleraesuis, and Shigella flexneri, were studied. For each microorganism sixty different dispersions were prepared in physiological solution. The Raman spectra of these dispersions were recorded using a diode laser operating in the near infrared region. Partial least-squares (PLS) discriminant analysis was used to differentiate among the bacteria by use of their respective Raman spectra. This approach enabled correct classification of 100% of the bacteria evaluated and unknown samples from the clinical environment, in less time (∼10 h), by use of a low-cost, portable Raman spectrometer, which can be easily used in intensive care units and clinical environments.