Jostein Toft

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.

Eigenstructure tracking analysis for revealing noise pattern and local rank in instrumental profiles: application to transmittance and absorbance IR spectroscopy

Abstract Toft, J. and Kvalheim, O.M., 1993. Eigenstructure tracking analysis for revealing noise pattern and local rank in instrumental profiles: application to transmittance and absorbance IR spectroscopy. Chemometrics and Intelligent Laboratory Systems , 19: 65–73. The heteroscedasticity in mixture-designed three-component absorbance IR spectra is revealed by means of eigenstructure tracking analysis (ETA). A moving window containing neighbouring spectral wavelengths for all samples defined submatrices that were decomposed by means of singular-value decomposition. Starting from window size two, the ETA procedure continues with window size three, four etc. until the window size exceeds the highest local chemical rank by one. The last evolving eigenvalue for this window provides the structure of the local noise. Due to closure, the maximum window size needed for the three-component spectra analysed in this work was three. Eigenstructure tracking analysis reveals that the amount of noise in absorbance IR spectra depends exponentially on signal variance, reflecting the transformation from transmittance to absorbance IR spectra. Transmittance IR spectroscopy is found to show almost homoscedastic noise behaviour.

Evolutionary rank analysis applied to multidetectional chromatographic structures

Abstract Methods for evolutionary rank analysis are presented and discussed. The different approaches of evolutionary rank analysis have in common that the bilinear data structure is analyzed piece wise to locally reveal the presence of the analytes. A background for evolutionary rank analysis is given. General aspects of multicomponent analysis are presented in addition to a more thorough discussion of rank analysis. As evolutionary rank analysis represents a valuable tool in multicomponent analysis both regarding detection and for resolution purposes, the link between evolutionary rank analysis and curve resolution techniques for multidetection chromatography is given.

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.

Analysis of Nontransparent Polymers: Mixture Design, Second-Derivative Attenuated Total Internal Reflectance FT-IR, and Multivariate Calibration

The composition of nontransparent polymers has been predicted from the fingerprint region in the mid-IR. The polymers were analyzed by the Horizontal Attenuated Total internal Reflection (HATR) FT-IR technique. The polymers were blends of three different master batches: (1) a polymer of ethylene with carbon black, (2) a co-polymer of ethylene and propylene monomers, and (3) an ethylene-propylene-diene elastomer. A calibration set was defined by use of mixture design. Partial least-squares (PIS) regression was used to calculate models for prediction of the relative concentrations of each master batch (one at a time). Second-derivated IR profiles normalized to 100% were used as predictive variables. Two alternative criteria were compared for optimizing the predictive ability of the calibration models: (1) squared prediction error of all the calibration samples, and (2) prediction error of replicated calibration samples of the centerpoint in the design only. The latter criterion turned out to be the more useful for the purpose of this study. This is because the centerpoint represents the target sample of the blending process. The one-component PLS models, suggested by the latter optimization criterion, gave predictions within 1% of the stated relative concentrations and with standard deviations from 0.5 to 1.3% for all three master batches.

Multi-array resolution parameter for multidetection chromatography. Performance of alternating regression, iterative target transformation factor analysis and heuristic evolving latent projections

Abstract The resolution of multicomponent chromatographic structures is quantified using a parameter (R2- D ), ratioing the amount of selective information with the overall information. The performance of the three curve resolution techniques, alternating regression (AR), iterative target transformation factor analysis (ITTFA) and heuristic evolving latent projections (HELP), is evaluated on simulated two- and three-analyte systems. The multi-array resolution parameter (R2- D ) showed to be a valuable tool for a three-analyte system in predicting concentration errors and quality of resolved spectra for the three methods. As for the curve resolution techniques, the multi-array resolution parameter itself showed to be vulnerable to heteroscedastic noise. Overall the HELP method performed best while AR performed poorest, both regarding prediction of concentrations and resolving spectra.

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.

Complexation between benzoic acid and fatty amines: an adsorption and chemometric study

Abstract Interactions between benzoic acid and octyl amine have been studied by means of chemometric methods, i.e. PCA score plot and rank analysis and by adsorption onto solid α-alumina without and with 0.1 M NaCl and with pH adjusted to 4.2 or 3.95. The chemometric study reveals that a benzoic acid/octyl amine complex exist at the pKa value of benzoic acid. The adsorption isotherms show that a decomplexation occurs when the complex is in contact with solid α-alumina. It is only the benzoate ion that adsorbs onto the solid surface. Without added electrolyte, the shape of the isotherm is of L type and benzoate ion is found to occupy about 0.59 nm2 on the surface. In the presence of NaCl, benzoate ion occupies 4.91 nm2 on alumina. In this case the adsorption isotherms can be classified as S isotherms. The reduction in adsorption capacity can be explained by the electrostatic shielding of the surface sites with the electrolyte.