Vitaly Panchuk

Three-point multivariate calibration models by correlation constrained MCR-ALS: A feasibility study for quantitative analysis of complex mixtures

When it comes to address quantitative analysis in complex mixtures, Partial Least Squares (PLS) is often referred to as a standard first-order multivariate calibration method. The set of samples used to build the PLS regression model should ideally be large and representative to produce reliable predictions. In practice, however, the large number of calibration samples is not always affordable and the choice of these samples should be handled with care as it can significantly affect the accuracy of the predictive model. Correlation constrained multivariate curve resolution (CC-MCR) is an alternative regression method for first-order datasets where, unlike PLS, calibration and prediction stages are performed iteratively and optimized under constraints until the decomposition meets the convergence criterion. Both calibration and test samples are fitted into a unique bilinear model so that the number of calibration samples is no longer a critical issue. In this paper we demonstrate that under certain conditions CC-MCR models can provide for reasonable predictions in quantitative analysis of complex mixtures even when only three calibration samples are employed. The latter are defined as samples having the minimum, the maximum and the average concentration, providing for a simple and rapid strategy to build reliable calibration model. The feasibility of three-point multivariate calibration approach was assessed with several case studies featuring mixtures of different analytes in presence of interfering species. Satisfactory predictions with relative errors in the range 3-15% were achieved and good agreement with classical PLS models built from a larger set of calibration samples was observed.

Methodological problems of quantitative analysis in Mössbauer spectroscopy

The results from research into the effect of different factors on errors in quantitative determination of the phase composition of studied substances by Mössbauer spectroscopy ion absorption are presented, and ways of using them are suggested. The effectiveness of the suggested methods is verified by an example of analyzing standard and unknown compositions.

Calibration transfer between different analytical methods

The procedure for transfer of calibration models between different analytical methods is suggested. It is based on the direct standardization (DS) algorithm earlier suggested for data conversion between physically different instruments of the same type. As a result, multivariate regression models obtained e.g. for NIR spectroscopic measurements in one wavelength range can be successfully applied for predictions from the data obtained with another NIR spectrometer in another wavelength range. The performance of the suggested method was tested with two simulated and two real datasets. In the latter case calibration models constructed for energy-dispersive X-ray fluorescence, UV-Vis spectrometry and NIR spectrometry were addressed. The observed performance of the method implies that it can have a broad range of possible applications in analytical chemistry; some of them are suggested in the paper.

Determination of the oxidation state of iron by X-ray fluorescence spectroscopy using chemometric approaches

A possibility of identification of the oxidation state of iron by wavelength dispersive X-ray fluorescence spectroscopy using both the position and intensity of Lα and Lβ spectral lines of iron and by principal component analysis score data obtained by the decomposition of the spectral region corresponding to spectral L-series lines of iron is demonstrated. The application of scores ensures a more reliable identification in comparison with line parameters (position and intensity). Two approaches based on projection on latent structures (PLS) regression for the determination of the concentration of iron in different oxidation states are proposed. The first approach consists in using reference models with compositions similar to those of analyzed samples. In the second approach, PLS regression was build using model spectra obtained from spectra of readily available iron compounds.

Application of resonant detectors in Mössbauer spectroscopy

The application of resonant detectors in Mössbauer spectroscopy allows us to increase resolution and sensitivity and thus to expand the information potential of this method. In this work, the particulars of applying resonance detection are described and its advantages are demonstrated experimentally in comparison with conventional methods of detection.

Topological Data Analysis of Potentiometric Multisensor Measurements in Treated Wastewater

In this study, a multisensor system consisting of 23 potentiometric sensors was applied for long-term online measurements in outlet flow of the water treatment plant. Within 1 month of continuous measurements, the data set of more than 295,000 observations was acquired. The processing of this dataset with conventional chemometric tools was cumbersome and not very informative. Topological data analysis (TDA) was recently suggested in chemometric literature to deal with large spectroscopic datasets. In this research, we explore the opportunities of TDA with respect to multisensor data with only 23 variables. It is shown that TDA allows for convenient data visualization, studying the evolution of water quality during the measurements and tracking the periodical structure in the data related to the water quality depending on the time of the day and the day of the week. TDA appears to be a valuable tool for multisensor data exploration.

Signal Smoothing with PLS Regression

Smoothing of instrumental signals is an important prerequisite in data processing. Various smoothing methods were suggested through the last decades each having their own benefits and drawbacks. Most of the filtering methods are based on averaging in a certain window (e.g., Savitzky-Golay) or on frequency-domain representation (e.g., Fourier filtering). The present study introduces novel approach to signal filtering based on signal variance through PLS (projections on latent structures) regression. The influence of filtering parameters on the smoothed spectrum is explained and real world examples are shown.

Application of chemometric methods to XRF-data – A tutorial review

X-ray fluorescence (XRF) spectrometry is a modern method of element analysis, widely applied in forensic science, archeology, geochemistry and other fields. Chemometric data processing tools and approaches may help XRF to become even more informative. These tools allow for convenient data visualization, exploration of hidden relations in the data, classification of samples and quantitative treatment of noisy and overlapped spectra. This review describes the most popular chemometric techniques employed in XRF studies and provides typical examples of such applications.

Sample-in-waveguide geometry for TXRF sensitivity improvement

Total reflection X-ray fluorescence (TXRF) is a rapidly developing trace analysis method due to a number of advantages. It is a fast and multielemental method and does not require complex sample pretreatment. Nevertheless, there are certain drawbacks (especially in the environmental analysis) where TXRF sensitivity is not sufficient and employment of various preconcentration methods is required. The present study suggests a very simple procedure based on a planar waveguide technique, where the sample to be analyzed is placed directly into the waveguide. Waveguide construction is also simple and can be produced in any lab using two standard glass reflectors. Such an approach permits considerable improvement of the signal-to-noise ratio in a spectrum and allows for achievement of detection limits for e.g. Cd and Hg at 0.12 μg L−1 and 0.13 μg L−1 respectively.

Features of the Quantitative Analysis in Mössbauer Spectroscopy

The results describing the effect of different factors on errors in quantitative determination of the phase composition of studied substances by Mossbauer spectroscopy absorption are presented, and the ways of using them are suggested. The effectiveness of the suggested methods is verified by an example of analyzing standard and unknown compositions.