Coupling of sequential injection chromatography with multivariate curve resolution-alternating least-squares for enhancement of peak capacity

Flow-through low-pressure chromatographic separations capitalized on the sequential injection chromatographic (SIC) concept are for the first time coupled to second-order multivariate regression models based on multivariate curve resolution-alternating least-squares (MCR-ALS) for outperforming current chromatographic methods in terms of resolution efficiency. The proposed SIC-MCR-ALS method involving sequential injection separation on short monolithic columns along with isocratic elution fosters ultrafast reversed-phase separations of complex multicomponent mixtures regardless of peak overlapping and retention parameters. The ruggedness of SIC systems is enhanced by removing the solenoid valves from the flow network, thus diminishing the column back pressure effects. As a consequence, the flow setup admitted mobile-phase flow rates much higher than those traditionally enabled in SIC. To ascertain the improved peak capacity of the SIC-MCR-ALS procedure, five phenolic species commonly used in disinfectant products and featuring similar UV spectra and close retention times in short reversed-phase silica-based monolithic phases are selected as model compounds and determined in just 1 min using mobile-phase flow rates of >or=2 mL min(-1). Notwithstanding the fact that the five phenolic derivatives coelute in a single chromatographic band, thus rendering resolution values ranging from 0.05 to 1.11, the concentration profiles and the pure spectra of each individual phenol species could be concurrently obtained. Quantitative validation of the chromatographic-chemometric method demonstrated both the reliability of the results and the enhanced resolution of mixtures with regard to former SIC systems with no need for thorough optimization of the separation conditions.     

Application of Raman multivariate curve resolution to solvation-shell spectroscopy

Raman spectroscopy and multivariate curve resolution (Raman-MCR) are combined to yield a powerful spectroscopic method for identifying solute-induced perturbations of solvent molecules. The principles and applications of the resulting solvation-shell spectroscopy are described and illustrated using both numerical model spectra and experimental Raman spectra, including water in acetone and aqueous OH(-), as well as of both neutral and ionic acetic acid solutions. The results illustrate the quantitative capabilities of Raman-MCR as a solvation-shell spectroscopy, including fundamental limitations arising from "intensity" and "rotational" ambiguities.     

Noninvasive, quantitative analysis of drug mixtures in containers using spatially offset Raman spectroscopy (SORS) and multivariate statistical analysis

In this paper, spatially offset Raman spectroscopy (SORS) is demonstrated for noninvasively investigating the composition of drug mixtures inside an opaque plastic container. The mixtures consisted of three components including a target drug (acetaminophen or phenylephrine hydrochloride) and two diluents (glucose and caffeine). The target drug concentrations ranged from 5% to 100%. After conducting SORS analysis to ascertain the Raman spectra of the concealed mixtures, principal component analysis (PCA) was performed on the SORS spectra to reveal trends within the data. Partial least squares (PLS) regression was used to construct models that predicted the concentration of each target drug, in the presence of the other two diluents. The PLS models were able to predict the concentration of acetaminophen in the validation samples with a root-mean-square error of prediction (RMSEP) of 3.8% and the concentration of phenylephrine hydrochloride with an RMSEP of 4.6%. This work demonstrates the potential of SORS, used in conjunction with multivariate statistical techniques, to perform noninvasive, quantitative analysis on mixtures inside opaque containers. This has applications for pharmaceutical analysis, such as monitoring the degradation of pharmaceutical products on the shelf, in forensic investigations of counterfeit drugs, and for the analysis of illicit drug mixtures which may contain multiple components.     

Diffusion measurements in binary liquid mixtures by Raman spectroscopy

It is shown that Raman spectroscopy allows determination of the molar fractions in mixtures subjected to molecular diffusion. Spectra of three binary systems, benzene/n-hexane, benzene/cyclohexane, and benzene/acetone, were obtained during vertical (exchange) diffusion at several different heights (z) as a function of time. A procedure to determine time-dependent concentration profiles and diffusion coefficients is described in detail for one system, and results are given for the two other cases. For the system benzene/cyclohexane, much lower diffusion coefficients than reported in the literature were found, even in a thermostatically controlled diffusion cell, recording spectra through circulating water. For the system benzene/acetone, the determined diffusion coefficients were in good agreement with the literature data. The limitations of the Raman method are discussed, and it is concluded that many more systems ought to be studied. It is pointed out that diffusion profiles can be obtained in ternary and higher systems, where proper measurements are almost nonexistent.     

Exploring time-dependent structural changes during the cold crystallization process of isotactic polystyrene by infrared spectroscopy and multivariate curve resolution

The present study attempts an application of Fourier transform infrared (FT-IR) spectroscopy in conjunction with multivariate curve resolution (MCR) techniques to explore the structural evolution of isotactic polystyrene (iPS) during the cold crystallization process. The focus of the present study is placed on the performance of MCR techniques, e.g., orthogonal projection (OP), alternating least squares (ALS), and fixed-size moving window evolving factor analysis (FSMWEFA), and the interpretability of spectral changes in the investigated chemical process. As a result, valuable information and conclusions about the structural evolution of iPS during the crystallization process can be extracted: when the amorphous phase of iPS changes, the ordering of the phenyl rings takes place first, and then the polymer chains adjust their local conformations to form short 3(1) helix structures. Furthermore, according to intensity profiles of the spectral variations, the ordering of the phenyl rings proceeds more intensely than the formation of ordered local chains, and the structural evolution of iPS occurs even during the induction period. The spectral variations resulting from the conformational changes in the 3(1) helical structures depend on the sequence length of the helical chains: the longer the polymer chain is, the smaller the corresponding band variations are. It has been demonstrated that the combination of FTIR spectroscopy and chemometric MCR techniques is very promising for the analysis of the crystallization process of polymers. MCR is a powerful tool for analyzing and visualizing spectral data and integrating them with other information, making spectral intensity variations more amenable to interpretation in order to explore the molecular dynamics of polymers.     

Quantitative Raman spectroscopy of highly fluorescent samples using pseudosecond derivatives and multivariate analysis

Intense luminescence backgrounds cause significant problems in quantitative Raman spectroscopy, particularly in multivariate analysis where background suppression is essential. Taking second derivatives reduces the background, but differentiation increases the apparent noise that arises on spectra recorded with CCD detectors due to random, but fixed, variations in the pixel-to-pixel response. We have recently reported a very general method for correcting CCD fixed-pattern response in which spectra are taken at two or more slightly shifted spectrometer positions and are then subtracted to give a derivative-like shifted, subtracted Raman (SSR) spectrum. Here we show that differentiating SSR data (which has inherently higher S/N than the undifferenced data) yields spectra that are similar to those that are obtained from the normal two-step differentiation process and can be characterized as pseudo-second-derivative, PSD, spectra. The backgrounds are suppressed in the PSD spectra, which means they can be used directly in multivariate data analysis, but they have significantly higher S/N ratios than do simple second derivatives. To demonstrate the improvement brought about by using PSD spectra, we have analyzed known samples, consisting of simple binary mixtures of methanol and ethanol doped with laser dye. When the background levels of all samples included in the models were < or =10x greater than the intensity of the strongest Raman bands, partial least-squares calibration of the PSD data gave a standard error of prediction of 3.2%. Calibration using second derivatives gave a prediction error which was approximately twice as large, at 6.5%; however, when data with background levels . approximately 100x larger than the strongest Raman bands were included, the noise on the second-derivative spectra was so large as to prevent a meaningful calibration. Conversely, the PSD treatment of these samples gave a very satisfactory calibration with a standard error of prediction (3.3%) almost identical to that obtained when the most fluorescent samples were excluded. This method clearly has great potential for general purpose Raman analytical chemistry, because it does not depend on specialized equipment, is computationally undemanding, and gives stable and robust calibrations, even for samples in which the luminescence background level fluctuates between the extremes of being practically zero and completely dominating the Raman signal.     

Raman and infrared fingerprint spectroscopy of peroxide-based explosives

A comparative study of the vibrational spectroscopy of peroxide-based explosives is presented. Triacetone triperoxide (TATP) and hexamethyl-enetriperoxide-diamine (HMTD), now commonly used by terrorists, are examined as well as other peroxide-ring structures: DADP (diacetone diperoxide); TPTP [3,3,6,6,9,9-Hexaethyl-1,2,4,5,7,8-hexaoxo-nonane (tripentanone triperoxide)]; DCypDp {6,7,13,14-Tetraoxadispiro [4.2.4.2]tetradecane (dicyclopentanone diperoxide)}; TCypDp {6,7,15,16,22,23-Hexaoxatrispiro[4.2.4.2.4.2] henicosane (tricyclopentanone triperoxide)}; DCyhDp {7,8,15,16-tetraoxadispiro [5.2.5.2] hexadecane (dicyclohexanone diperoxide)}; and TCyhTp {7,8,14,15,21,22-hexaoxatrispiro [5.2.5.2.5.2] tetracosane (tricyclohexanone triperoxide)}. Both Raman and infrared (IR) spectra were measured and compared to theoretical calculations. The calculated spectra were obtained by calculation of the harmonic frequencies of the studied compounds, at the density functional theory (DFT) B3LYP/cc-pVDZ level of theory, and by the use of scaling factors. It is found that the vibrational features related to the peroxide bonds are strongly mixed. As a result, the spectrum is congested and highly sensitive to minor changes in the molecule.     

Study of the hydrolysis of a sulfonylurea herbicide using liquid chromatography with diode array detection and mass spectrometry by three-way multivariate curve resolution-alternating least squares

This research is focused on the development of a novel, automated chemometric method for obtaining relevant chemical information from time-course measurements of an evolving chemical system. This paper describes an investigation of the hydrolysis of Ally, which is a sulfonylurea herbicide. The hydrolysis of this compound is observed at different pHs and temperatures by reversed-phase liquid chromatography using a diode array detector. The data are analyzed using a three-way, multivariate curve resolution technique. Of special interest was the application of a closure constraint in the kinetic dimension followed by the determination of the rate constants for each step of the pathway by using a differential equation solver and nonlinear fitting of the data.     

Shear viscosity of methanol and methanol + water mixtures under pressure

Shear viscosities have been measured for methanol up to 400 MPa at 298, 313, and 323 K and for methanol-water mixtures (a) at 0.1 MPa and 278 K and (b) up to 300 MPa at 298 K. Where a comparison is possible the results are in good agreement with literature data. The data for the mixtures are discussed in terms of hydrogen bonding in methanol and water and by the use of excess viscosities.     

Equilibrium modeling of mixtures of methanol and water

An understanding of the species that form in mixtures of alcohol and water is important for their use in liquid chromatography applications. In reverse-phase liquid chromatography the retention of solutes on a chromatography column is influenced by the composition of the mobile phase, and in the case of alcohol and water mobile phases, the amount of free alcohol and water present. Previous and similar modeling studies of methanol (MeOH) and water mixtures by near-infrared (NIR) spectroscopy have found up to four species present including free MeOH and water and MeOH and water complexes formed by hydrogen bonding associations. In this work an equilibrium model has been applied to NIR measurements of MeOH and water mixtures. A high-performance liquid chromatography (HPLC) pump was coupled to an NIR flow cell to produce a gradual change in mixture composition. This resulted in a greater mixture resolution than has been achieved previously by manual mixture preparation. It was determined that five species contributed to the data. An equilibria model consisting of MeOH, H2O, MeOH(H2O) (log K(MeOH)H2O = 0.10+/-0.03), MeOH(H2O)4 (log K(MeOH)4H2O = -2.14+/-0.08), and MeOH(H2O)9 (log K(MeOH)9H2O = -8.6+/-0.1) was successfully fitted to the data. The model supports the results of previous work and highlights the progressive formation of MeOH and water complexes that occur with changing mixture composition. The model also supports that mixtures of MeOH and water are not simple binary mixtures and that this is responsible for observed deviations from expected elution behavior.     

Prediction of mutagenic activity of nitronaphthalene isomers by infrared and Raman spectroscopy

IR and Raman spectra of 1- and 2-nitronaphthalene isomers (1-NN and 2-NN) have been investigated to obtain more insight into the effect of the structure on mutagenic properties. To this purpose we have performed density functional theory calculations using B3LYP functional with cc-pVDZ basis set. The results have shown that IR and Raman spectra of nitronaphthalene isomers are somewhat similar to each other. A notable exception regards the symmetrical NO bonds stretching +CN bond stretching vibration (nusNO2+nuCN), which appears as very intense peak near 1350 cm(-1) in IR and Raman spectra of both isomers. Present calculations predict that for 2-NN isomer IR and Raman absorptions of this vibration are more intense by ca. 50 and 60%, respectively, than those of 1-NN isomer. The noticeably higher IR and Raman intensity values of the nusNO2+nuCN mode for 2-NN originate, respectively, from large dipole moment and polarizability changes with respect to the normal mode, suggesting that intermolecular interactions are especially favoured along this coordinate. These results are consistent with higher mutagenic activities of 2-NN in comparison to 1-NN isomer, supporting the binding to enzyme mechanism as a determining step in mutagenic pathways for this series of nitroaromatic compounds.     

Determination of water concentration in brain tissue by Raman spectroscopy

Brain edema is one of the most common morbidity factors in patients with intracranial neoplasms and cerebrovascular pathology. Monitoring of intracranial pressure gives only an indirect and global measure of brain swelling. We have made an assessment of the applicability of Raman spectroscopy as an alternative method for assessing brain edema, which measures the water concentration in the tissue directly. Partial least-squares models were developed on the basis of Raman spectra measured in the 2600-3800-cm(-1) region, which predict the water fraction of brain tissue in the 0.75-0.95 range, with an accuracy better than 0.01.     

Iterative least-squares fit procedures for the identification of organic vapor mixtures by Fourier transform infrared spectrophotometry

Least-squares fitting (LSF) was applied to the qualitative analysis of IR spectra based on comparing standard reference spectra with the sample mixture spectrum. Identification of compounds in the sample was made by judging the fit level of the spectrum of each compound with the sample spectrum. An iterative procedure was developed to eliminate compounds with the worst fit levels in order to approach an optimal fit for the sample spectrum. The qualitative analysis results obtained from the optimal fit were further used for quantitative analysis.     

Chemical compositions of hardwood and softwood pulps employing photoacoustic Fourier transform infrared spectroscopy in combination with partial least-squares analysis

In the present study, hardwood and softwood pulps were characterized by employing Fourier transform infrared photoacoustic spectroscopy (FT-IR-PAS). The pulp samples examined originated from Swedish sulfite and kraft pulp mills, which utilize different cooking processes and modern bleaching technologies. Partial least-squares (PLS) analysis was used to correlate the spectral data obtained with the kappa (K) numbers and carbohydrate compositions of the pulp samples determined by enzymatic hydrolysis and subsequent capillary zone electrophoresis. Using four principal components, the present PLS model based on photoacoustic FT-IR spectra could explain 85% of the variance in the X matrix and 81% of the variance in the Y matrix. The FT-IR-PAS technique in combination with PLS was found to accurately predict the contents of carbohydrates, i.e., xylose, glucose, mannose, arabinose, galactose, and hexenuronic acid residues, as well as the content of lignin measured in terms of K numbers and corrected K numbers of the pulps. From these predictions, the contents of xylan, glucomannan, and cellulose can also be predicted. The content of 4-O-methylglucuronic acid residues is, however, more difficult to predict accurately, using this approach.     

Study of a new resin-based composites containing hydroxyapatite filler using Raman and infrared spectroscopy

The degree of conversion of polymeric matrix in hydroxyapatite-containing dental fillings by Raman and infrared spectroscopy has been determined. Resin-based dental composites are one of the most popular filling materials used in dentistry. These light-cured materials are characterized by the value of the degree of conversion, which depends on curing time and influences the quality of obtained dental filling. Distribution of the filler into polymeric matrix, which has a significant impact on the properties of the final product, has been determined by Raman mapping. The applied procedure also has allowed to present the changes of the degree of conversion on the examined surfaces. The results of the study demonstrate the versatility of the Raman spectroscopy as the analytical spectroscopic technique for determining chemical properties of dental fillings and providing insight into their organization at the microstructural level. The obtained degree of conversion values have been compared with data for the commercially available dental fillings characterized by other authors.     

Identification and characterization of artists' red dyes and their mixtures by surface-enhanced Raman spectroscopy

Silver film over nanospheres (AgFONs) were successfully employed as surface-enhanced Raman spectroscopy (SERS) substrates to characterize several artists' red dyes including: alizarin, purpurin, carminic acid, cochineal, and lac dye. Spectra were collected on sample volumes (1 x 10(-6) M or 15 ng/microL) similar to those that would be found in a museum setting and were found to be higher in resolution and consistency than those collected on silver island films (AgIFs). In fact, to the best of the authors' knowledge, this work presents the highest resolution spectrum of the artists' material cochineal to date. In order to determine an optimized SERS system for dye identification, experiments were conducted in which laser excitation wavelengths were matched with correlating AgFON localized surface plasmon resonance (LSPR) maxima. Enhancements of approximately two orders of magnitude were seen when resonance SERS conditions were met in comparison to non-resonance SERS conditions. Finally, because most samples collected in a museum contain multiple dyestuffs, AgFONs were employed to simultaneously identify individual dyes within several dye mixtures. These results indicate that AgFONs have great potential to be used to identify not only real artwork samples containing a single dye but also samples containing dyes mixtures.     

Fourier transform infrared least-squares methods for the quantitative analysis of multicomponent mixtures of airborne vapors of industrial hygiene concern

Air monitoring methods suitable for use in the workplace, though accurate for monitoring individual compounds or classes of compounds, cannot be used to monitor several compounds or classes of compounds simultaneously. In the past few years, Fourier transform infrared (FT-IR) spectroscopy has been investigated for use as a method for multicomponent quantitative analysis. This work focuses on quantitative analysis of six mixtures in ambient air. The concentration ranges of the two- to six-component mixtures are from 50 ppm to 100 ppb. The optimal least-squares fit (LSF) method selected, background reference file chosen, and quantitative peak windows picked were evaluated in this effort. The quantitative results of six mixtures were accurate at the 50, 10, and 1 ppm levels. There were some components for which the analysis was also accurate at the 0.1 ppm level. The data indicate that the LSF program could be used to quantify strongly overlapping multicomponent mixtures. The results support the conclusion that the FT-IR spectrometer is appropriate for the direct quantification of multicomponent mixtures of many airborne gases and vapors of industrial hygiene concern.     

Accuracy of remote sensing of water temperature by Raman spectroscopy

We present an experimental study of the Raman spectrum of pure and synthetic seawater with respect to its salinity and temperature dependence. Experiments made in the laboratory with both cw and pulsed excitation yield information on the limits and applicability of the technique in actual experiments in the field. We have also performed an experimental analysis to determine the presence of stimulated Raman scattering and its influence on the temperature dependence of the spectrum.