Fred O. Libnau

Spectra of water in the near- and mid-infrared region

Abstract Spectra of water have been acquired in the mid-infrared (MIR) and the near-infrared (NIR) region in the temperature range 2–96°C and 4–52°C, respectively. Loading plots from partial-least-squares regression were used to locate isosbestic points in the spectra bands of water. By means of least-squares, the original spectral profiles have been resolved into two spectra, one increasing and the other decreasing with temperature. Concentration profiles of the two structurally different water associations, for the investigated temperature range, were obtained by use of evolutionary curve resolution and first-order differentiation of the MIR spectra. Utilising information from the concentration profiles obtained in the MIR, the NIR spectra were resolved. Relative concentrations were obtained using spectral intensities from the isosbestic points. The complexity in both the fundamental and overtone region of the spectra shows that both structures of water are involved in H-bonding. This result indicates a pseudo-first-order reaction in water, either between an open and a more dense state, or between a rigid, strongly H-bonded state and a more loosely H-bonded state. The cross-correlation pattern between the two regions can be ascribed to the temperature-induced variation in the concentration of the two associations.

Self-Association of Medium-Chain Alcohols in n -Decane Solutions

Self-association of medium-chain alcohols in n-decane solutions has been studied by infrared absorption of the fundamental OH stretching vibration. The alcohols investigated were 1-propanol, 2-methyl-1-propanol, 2-methyl-2-propanol, 1-butanol, 1-pentanol, and 1-hexanol. Infrared spectra were acquired for varying alcohol molalities, the highest concentration being 0.2 mol/kg. The spectra for each alcohol were collected in a data matrix. The bilinear multicomponent data were successfully resolved into spectra and concentration profiles by a multivariate method. The result indicates that monomers dominate the spectral variance in the low-molality region, while cyclic oligomers dominate in the upper concentration range. It further indicates that minor amounts of open-chain aggregates may be present. The monomer and cyclic tetramer appear to be the dominant species, while the amount of open-chain aggregates was negligible even in the low-molality region. The equilibrium constants for the monomer–tetramer association reactions (K1–4) were calculated by a least-squares method. The calculated values for the equilibrium constants, based on the molality, range from 138 to 106 for the linear alcohol molecules. The result shows that 1-butanol, 1-pentanol, and 1-hexanol have similar constants, while 1-propanol displays a markedly higher value. The equilibrium constants obtained for 2-methyl-1-propanol and 2-methyl-2-propanol were 77 and 39, respectively. The considerably lower values for the branched alcohol molecules indicate that steric interaction between the chain prevents self-association into larger aggregates.

Determination of the Equilibrium Constant and Resolution of the HOD Spectrum by Alternating Least-Squares and Infrared Analysis

The equilibrium between H2O, D2O, and HOD in the liquid phase has been analyzed for different concentrations of the reactants by using the attenuated total internal reflectance (ATR) technique. The infrared spectroscopic profiles of the equilibrium mixtures were broken down into the contributing components by the alternating least-squares (ALS) curve resolution technique. Furthermore, the concentration profiles of H2O, D2O, and HOD were determined together with the equilibrium constant. Band assignment of the resolved HOD spectrum was further carried out. The equilibrium constant determined in this work agrees excellently with values determined by both theoretical calculations and experiments.

Interpretation of chemical structural changes by target-projection analysis of infrared profiles

Abstract Infrared profiles are used as structural descriptors for a range of chemical systems, embracing samples from process analysis, geochemistry and physical chemistry. Structural mapping by infrared profiling accompanied by target-projection analysis is shown to be a powerful tool for interpretation of the variation pattern in chemical systems. In most of the applications the interpretation complies with the understanding of the chemical changes taking place in the system discussed. For some applications, the target-projection analysis brings new insight by highlighting the changes in the multivariate infrared descriptors.

Resolution of infrared spectra and kinetic analysis of mutarotation of d-glucose in water by sequential rank analysis

Abstract Mutarotation of d -glucose in water has been studied by attenuated total internal reflectance Fourier-transform infrared spectrometry. Infrared spectra of solutions of both α- d -glucose and β- d -glucose in water were acquired at regular time intervals. The spectral profiles of the evolving mixtures were first-order differentiated and sequential rank analysis was used to obtain the concentration profiles of the anomers. The concentration profiles were subsequently used to obtain resolved infrared spectra of the two anomers. A crucial assumption for the resolution procedure used in this work is that the spectral peaks of the pure anomers are symmetric in the proximity of local maxima or minima. Rate constants for the conversion of α- to β-glucose and for the conversion of β- to α-glucose have been calculated from the concentration profiles. The calculated rate constants as well as equilibrium concentrations derived from them agree well with previously reported values.

Influence and correction of peak shift and band broadening observed by rank analysis on vibrational bands from variable-temperature measurements

Abstract Variable-temperature infrared (IR) spectra of cyclohexane and IR and Raman spectra of chlorocyclohexane have been investigated by graphic eigenvalue analysis. Thermal effects known as peak shift and band broadening combined with heteroscedastic noise in vibrational bands are found to have severe influence on the interpretation of the outcome of rank analysis. Methods for correction of frequency shifts and band broadening in the spectral profiles due to temperature variation are developed and tested.

A comparison of techniques for modelling data with non-linear structure

Partial least squares (PLS) is a powerful tool for multivariate linear regression. But what if the data show a non-linear structure? Near infrared spectra from a pharmaceutical process were used as a case study. An ANOVA test revealed that the data are well described by a 2nd order polynomial. This work investigates the application of regression techniques that account for slightly non-linear data. The regression techniques investigated are: linearising data by applying transformations, local PLS, i.e. splitting of data, and quadratic PLS. These models were compared with ordinary PLS and principal component regression (PCR). The predictive ability of the models was tested on an independent data set acquired a year later. Using the knowledge of non-linear pattern and important spectral regions, simpler models with better predictive ability can be obtained.

Projective ordination by SIMCA: A dynamic strategy for cost-efficient environmental monitoring around offshore installations

A method for environmental monitoring using benthic species profiles as input is developed in this work. The method, referred to as projective ordination, utilises local principal component modelling (SIMCA) to obtain a cross-validated model which spans the natural variation in a region around offshore oil-producing installations. The borderline between regions with disturbed and non-disturbed species communities is subsequently decided from the residual distribution. This distribution is used to design an approximate F-test for assessing whether a community at a particular sampling location is disturbed or not. If so, the nature of the disturbance is determined by projecting the data on the PC model.Projective ordination utilises information from previous surveys to define the permissible variation in species communities, i.e. the limit of the natural variation. In addition, the method is dynamic, in a sense that the sampling locations may vary from survey to survey.Furthermore, our analysis shows that the customary number of replicate samples per station can be reduced. Modelling with only four randomly chosen replicates out of the complete set of five for each sampling location, does not affect the model significantly. On the other hand, taking only 3 replicates into account leads to significant divergences.A model based on the 1990 and 1993 surveys at the Statfjord field is presented as an example of the technique.

Quantitative determination of stabiliser in a single base propellant by chemometric analysis of Fourier transform infrared spectra

Abstract The main constituent in a propellant is nitrocellulose, which by nature is unstable, and consequently it has to be stabilised with, e.g., diphenylamine. In order to determine the remaining shelflife of the propellant, the amount of stabiliser is determined. The method mostly used for this purpose, high-performance liquid chromatography (HPLC), is however complex and time consuming. Partial least squares calibration of the infrared spectroscopic profiles of the stabiliser and its derivatives in the propellant against their respective quantities (determined by HPLC) was tested to find out whether the quantitative determination of the above was possible. The initial results show that the cross-validated calibration model yields quantitative determination of the stabiliser and its derivatives within an error limit of 10% in predicted values. The correlation between the measured and predicted values was better than 0.94 for the stabiliser and its three first derivatives.

Non-linear curve fitting of bilinear data using orthogonal projections for rank analysis. Applications to gas chromatography / infrared spectrometry and variable temperature infrared studies

Abstract Non-linear curve fitting of bilinear data structures is demonstrated and used on one simulated and two real analytical infrared (IR) systems. Information regarding the number of peaks and their relative positions is revealed by orthogonal projection techniques. The systems have been studied without using any a priori information. The bilinearities of the analytical model systems are used to resolve corresponding IR spectra from fitted elution profiles based upon Gaussian curves in a gas chromatography / infrared spectrometry (GC/IR) study, and similarly to resolve concentration profiles from Gaussian and Lorentzian curves fitted to IR bands in a variable-temperature IR study. A GC/IR system (m- and p-xylene) was investigated revealing both the elution profiles, the IR spectra (887-702 cm−1, aromatic CH deformation) and the relative concentrations of the analytes. The OH deformation band (∼ 1640 cm−1) from a temperature study of water was resolved into a broad and a narrow peak, the narrow peak being located within the broad one. This indicates that water can be regarded as a two-structure system composed of a fully hydrogen-bonded and a partially hydrogen-bonded structure. The result from Gaussian and Lorentzian curve fitting leads to different interpretations regarding relative peak positions and widths of the two structures. Results obtained using latent projective graphs suggest that the OH deformation band consists of two Gaussian peaks.