H.R. Keller

Peak purity control in liquid chromatography with photodiode-array detection by a fixed size moving window evolving factor analysis

Abstract A new method for peak purity control of liquid chromatography with photodiode array detection data is proposed, based on evolving factor analysis. In contrast to the original technique, which works on an increasing number of spectra, the new method performs factor analysis on a moving window with a fixed number of spectra. In simulation experiments, the new method proved to be better at detecting small amounts (less than 1%) of a spectrally similar impurity under a main peak than the original evolving factor analysis method. Since latent factors are used, no assumptions are made about peak shape or spectral similarity.

Evolving factor analysis

Abstract Evolving factor analysis (EFA) is a general method for the analysis of multivariate data having an intrinsic order. Examples are data produced by many hyphenated techniques, such as high-performance liquid chromatography with photodiode array detection (HPLC-DAD) and the study of complex equilibria by ultraviolet spectrometry as a function of pH. EFA relies on an intrinsic order of the data and relies on only a few assumptions, such as nonnegativity of concentrations and the validity of Beers law. The method can be applied to curve resolution and the assessment of peak purity in different disciplines of analytical chemistry. A didactic example from HPLC-DAD is used to illustrate the method. Possible limitations of EFA are also discussed.

Multicriteria decision making: A case study

Abstract Keller, H.R., Massart, D.L. and Brans, J.P., 1991. Multicriteria decision making: a case study. Chemometrics and Intelligent Laboratory Systems 11: 175–189. With the aim of optimizing a formulation for use with textiles, Chardon et al. published the results of 49 experiments measured on 5 criteria. Several methods for multicriteria decision making were compared with each other on the basis of this data set. The Pareto optimality concept turned out to be a useful method in simple bicriteria cases. To take more criteria into account, more advanced techniques are required, such as ELECTRE or PROMETHEE. The PROMETHEE method, in particular, coupled with the principal component approach of the GAIA visualization technique proved a good tool in multicriteria decision making.

Evolving factor analysis in the presence of heteroscedastic noise

Abstract Evolving factor analysis (EFA) is a promixing method for the analysis of multivariate data with an intrinsic order. When applying EFA for assessment of peak homogeneity in liquid chromatography, one has to be aware of instrumental and experimental difficulties. Heteroscedasticity is one of the most serious problems and leads to additional eigenvalues that may be misinterpreted as being due to an impurity. After appropriate data pretreatment, the fixed-size window EFA technique proved successful for peak purity control in liquid chromatography with photodiode-array detection. Less than 1% of a spectrally similar impurity could be detected for Rs values as low as 0.3.

Simultaneous optimization of pH and organic modifier content of the mobile phase for the separation of chlorophenols using a Doehlert design

Abstract By optimizing the pH and volume fraction of organic modifier, the complete resolution of an isocratic separation of a mixture of phenol and thirteen of the nineteen chlorophenol isomers and of a mixture of the three tetrachlorophenols and pentachlorophenol was achieved. The effectiveness of the Doehlert design in optimizing both experimental parameters was investigated. A quadratic model was applied. For mixtures of a small number of compounds, a retention boundary map is proposed to determine limits of the concentration of organic modifier so as to elute compounds within a reasonable analysis time. The resulting three-dimensional graph of the minimum resolution as a function of the experimental parameters allows the direct visual evaluation of the ruggedness of the optimum conditions that are attainable in the selected parameter space and with a given stationary phase.

Artefacts in evolving factor analysis-based methods for peak purity control in liquid chromatography with diode-array detection

Abstract Evolving factor analysis and related techniques are promising methods for peak purity control in liquid chromatography with photodiode-array detection (DAD). Practical application of these techniques, however, can be limited by instrumental and experimental non-idealities. Possible reasons include a non-zero or sloping baseline, the DAD scan time, calibration graph non-linearity and heteroscedasticity. Methods are presented for correction of the first two problems. As various instruments behave differently, it is likely that the relevant difficulties depend on the instrument used. Additionally, one has to take into account that mobile phase effects, leading to changes in the spectra, are a potential source of artefacts. The detection limit of an impurity as a function of chromatographic separation, relative concentration and amount of noise was also studied for simulated data.

Microwave digestion: an analysis of procedures

Abstract Principal component analysis (PCA) and the multicriteria decision making methods, PROMETHEE and GAIA, were used to select a suitable microwave digestion method for metal analysis of soil samples. When the residuals matrix derived from the Cu, Pb, Co, Mn and Zn analyses of 18 different digests of the NBS 2704 SRM, was subjected to PCA and PROMETHEE ranking, two prefered methods were isolated. This PROMETHEE ranking together with the microwave oven settings and digest acid composition were then used as variables. The corresponding data matrix was subjected to PROMETHEE analysis coupled with the visualisation technique, GAIA. This illustrated the relationship between the different practical variables and method perfromance leading to the selection of the most suitable digestion method.

A comparison of the heuristic evoling latent projections and evolving factor analysis methods for peak purity control in liquid chromatography with photodiode array detection

Abstract The performance of the heuristic evoling latent projections (HELP) method is investigated for peak purity control in liquid chromatography with photodiode array detection. HELP and evolving factor analysis performed equally well; both techniques could detect less than 1% of a spectrally similar impurity even for small chromatographic separations. In certain cases, the two techniques may be limited by instrumental and experimental difficulties.

Effect of the scan time on methods based on evolving factor analysis in liquid chromatography

Abstract In some instances, photodiode-array detectors may show a non-linear response, causing artefacts in the practical application of certain chemometric methods for data analysis, such as those based on principal component analysis. The phenomenon is explained theoretically and illustrated with results obtained from simulation experiments. A routine for correction of this problem is also presented.

Application of chemometrics for the selection of microwave digestion procedures

Abstract The application of four chemometrics procedures viz., principal components analysis, SIMCA, multicriteria decision-making routines PROMETHEE and GAIA, and fuzzy clustering, was investigated for the selection of a suitable microwave digestion method for sediment and rock samples. The NBS 2704 SRM and a secondary rock standard were acid digested by 15 different methods and the digests analysed for six metals, Cu, Pb, Ni, Cr, Co and Zn. The four chemometrics approaches produced consistent results and provided similar information about the data structure (outliers, groupings, trends). Only the PROMETHEE procedure gave the ranking information necessary for the selection of a suitable digestion method. This method was based on the HF-HNO3 acid composition of the digest mixture.