M.S. Larrechi

Multivariate curve resolution–alternating least squares (MCR-ALS) applied to spectroscopic data from monitoring chemical reactions processes

This paper overviews the application of multivariate curve resolution (optimized by alternating least squares) to spectroscopic data acquired by monitoring chemical reactions and other processes. The goals of the resolution methods and the principles for understanding their applications are described. Some of the problems arising from these evolving systems and the limitations of the multivariate curve resolution methods are also discussed. This article reviews most of the applications of multivariate curve resolution applied to reacting systems published between January 2000 and June 2007. Some basic papers dated before 2000 have also been included.

Multivariate detection limits with fixed probabilities of error

Abstract In this paper, a new approach to calculate multivariate detection limits (MDL) for the commonly used inverse calibration model is discussed. The derived estimator follows the latest recommendations of the International Union of Pure and Applied Chemistry (IUPAC) concerning the detection capabilities of analytical methods. Consequently, the new approach: (a) is based on the theory of hypothesis testing and takes into account the probabilities of false positive and false negative decisions, and (b) takes into account all the different sources of error, both in calibration and prediction steps, which affect the final result. The MDL is affected by the presence of other analytes in the sample to be analysed; therefore, it has a different value for each sample to be tested and so the proposed approach attempts to find whether the concentration derived from a given response can be detected or not at the fixed probabilities of error. The estimator has been validated with and applied to real samples analysed by NIR spectroscopy.

Monitoring ethylene content in heterophasic copolymers by near-infrared spectroscopy: Standardisation of the calibration model

Abstract The concentration of ethylene in samples of heterophasic copolymers was monitored for 3 months by NIR spectroscopy and partial least-squares (PLS) multivariate calibration in an attempt to assess the validity over time of the calibration model. Assuming that the model would cease to be valid, we selected and monitored sufficient samples so as to initiate a process of standardisation. The samples were selected with the Kennard–Stone algorithm and according to the representivity of their ethylene content. The monitoring techniques were univariate (Shewhart) and multivariate ( T 2 and Q ) control plots. The results show that the system was stable, until the point at which there was a cause in variation which gave rise to an erroneous prediction of the ethylene content. This change did not vary over time. We used two techniques to standardise the calibration model: slope bias correction (SBC) and piecewise direct standardisation (PDS). They both corrected the error detected.

Figures of merit in multivariate calibration. Determination of four pesticides in water by flow injection analysis and spectrophotometric detection

Abstract The accuracy, trueness and determination limit of a flow injection analysis (FIA) method are evaluated in the simultaneous determination of the pesticides Carbaryl (RYL), Carbofurane (CBF), Propoxur (PPX) and Isoprocarb (IPC) in water by multicomponent analysis. Calibration is based both on the spectra of artificially made samples according to the experimental design theory and the spectra of pure pesticides. Prediction errors in the range 0.1–1.4 evaluated as RMSEP are obtained. The absence of bias is evaluated from the joint confidence interval test for the regression line obtained from measured and predicted concentrations taking into account errors in both axes. Multivariate determination limits were found to be between 0.03 and 1.0 ppm.

Expert system for the voltammetric determination of trace metals: Part I. Determination of copper, zinc, cadmium, lead and indium

Abstract An expert system for the voltammetric determination of Cu, Zn, Cd, Pb and In was developed. The system guides the user in the choice of sample treatment, the most appropriate voltammetric procedure and the identification and determination of the trace metals. The techniques implemented are differential-pulse polarography and anodic stripping voltammetry, using mercury drop electrodes. Only well known methods are recommended, with particular attention to standard methods. For the identification and resolution of overlapping peaks (Cd and In), the system may call two external programs, written in turbo BASIC. Quantification is carried out by means of the multiple standard addition method, and the quality of the calibration graph is tested by several statistical validation tests. The tool kit for the development of the expert system KES (Knowledge Engineering System) is used. Only commercially available material was used. The system is easily portable if the shell for the development of the expert system is employed.

Expert system for the voltammetric determination of trace metals: Part IV. Methods for speciation of chromium and arsenic

Abstract A previously described expert system for the voltammetric determination of Cu, Zn, Cd, Pb, In, Ni, Co, Tl, Hg, V and Se (optionally also Te) is enlarged and improved by including methods for speciation of chromium and arsenic. Voltammetric procedures for the quantification of Cr(III), Cr(VI), As(III) and As(V) are considered, Cr(III) and As(V) being determined by the difference between total chromium and Cr(VI), and total arsenic and As(III) respectively. The techniques implemented are differential pulse polarography, differential pulse anodic stripping voltammetry, differential pulse cathodic stripping voltammetry and differential pulse adsorptive stripping voltammetry, using mercury drop electrodes and a rotating gold electrode. The expert system is developed using KES (knowledge engineering system).

Automatic simultaneous determination of Ca and Mg in natural waters with no interference separation

Abstract In this study a methodology is reported for the automatic, simultaneous determination of Ca and Mg in natural waters which is not affected by the presence of species that may interfere with other methods. A flow system based on the sinusoidal injection analysis (SIA) methodology with diode array spectrophotometric detection of the complex formed by both analytes with the Arsenazo III has been used. The technique of multivariate calibration used, PLS1, enables Ca to be determined in the concentration range 45–85 mg l−1 and Mg to be determined in the range 2–70 mg l−1, with no need for the samples to be previously diluted. The accuracy of the method has been tested by comparing the results obtained with the standard atomic absorption spectrometry method. With an analysis speed of 20–30 samples per hour, the RMSE in terms of standard deviation of the original variables was 6.1 for Mg and 6.4 for Ca.

New chemometric tools to study the origin of amphorae produced in the Roman Empire

Abstract Information about geographical and chronological origin is often required of archaeological samples. In order to obtain such information, pattern recognition techniques are now used as valid tools for processing series of data from morphological and chemical analyses. This article reviews the advantages and disadvantages of artificial neural networks (ANNs) methods and compares them with chemometric techniques such as the standard clustering method, principal component analysis, (PCA) and SIMCA. Kohonen, Back-propagation of errors, and counter-propagation learning strategies of ANNs are used to study 160 amphorae dating to the 5th century A.D. The majority (128) of the amphorae are of known and 32 of unknown geographical origin. Some predictions about the unknown samples are made, thus showing the potential of ANN techniques and their possible contribution to archaeological studies.

Expert system for the voltammetric determination of trace metals: Part II. Methods for determining nickel cobalt and thallium at different concentration ratios

Abstract An expert system for the voltammetric determination of Cu, Zn, Cd, Pb, In, Ni, Co and Tl was developed with special attention to methods for determining Ni, Co and Tl at different concentration ratios. The system guides the user in the choice of sample treatment, the most appropriate voltammetric procedure and the identification and determination of trace metals. The techniques implemented are differential-pulse polarography, anodic stripping voltammetry and adsorptive stripping voltammetry, using mercury drop electrodes. Only well known methods are recommended, with particular attention to standard methods. For the identification and resolution of overlapping peaks, the system may be used in conjunction with two external programs, written in turbo BASIC. Quantification is carried out by means of the multiple standard addition method, and the quality of the calibration graph is tested by several statistical tests performed by another external program. The expert system is developed using KES (Knowledge Engineering System).

On-line automated analytical signal diagnosis in sequential injection analysis systems using artificial neural networks

Abstract This paper describes an automated analytical system able to diagnose multivariate spectrophotometric responses, with the aim of detecting faulty responses and assigning causes to the symptoms detected. Not only does this system detect faulty spectra, but it is also capable of modifying, by means of a ‘feed-back response’, the entire analytical system, and, when it is necessary, to report the conditions of the sequential injection analysis system to give an on-line diagnosis signal. Artificial neural networks (ANNs), in particular counter-propagation neural networks, have been applied to detect faults and diagnose signals obtained in a sequential injection analysis system. This strategy has been used to analyse natural water samples and, in particular, to simultaneously determine calcium and magnesium by means of spectrophotometric detection of the complex which both cations form with the reagent Arsenazo(III).