Identification and quantification of overlapped peaks in liquid chromatography with UV diode array detection using an adaptive Kalman filter

Abstract A method for the identification and quantification of overlapped peaks in liquid chromatography with UV diode array detection is reported. The adaptive Kalman filter, which is optimized using simplex optimization, can detect low levels of isomeric impurities. The filter optimization is based on the maximum information yield from the filtering procedure, and is capable of compensating the model errors. This approach is combined with the commercially available software to result in a complete method for chromatographic peak analysis. A mixture of two isomers, chrysene and benz(a)anthracene, has been evaluated. This method can detect as low as 1 μM benz(a)anthracene in a 121 μM chrysene solution, and 1 μM chrysene in a 106 μM benz(a)anthracene solution. Both, identification and quantification of the major and minor components have been achieved. For the overall method, the prediction errors are within 2% for the major components and within 10% for the minor components. If the reference spectrum of the minor component is unavailable, this filter can also predict the concentration of the major component within an error of 7%. The reliability of this method has been tested by the second isomeric system, a mixture of benzo(k)fluoranthene and benzo(b)fluoranthene. This method is valid for highly overlapped peaks even when the chromatographic resolution is zero, but an overlap-free region is required in the spectra.

[1]  Joe M. Davis,et al.  Experimental verification of parameters calculated with the statistical model of overlap from chromatograms of a synthetic multicomponent mixture , 1990 .

[2]  H. R. Keller,et al.  Peak purity control in liquid chromatography with photodiode-array detection by a fixed size moving window evolving factor analysis , 1991 .

[3]  Desire L. Massart,et al.  Application of SIMPLISMA for the assessment of peak purity in liquid chromatography with diode array detection , 1994 .

[4]  W. Windig,et al.  Interactive self-modeling mixture analysis , 1991 .

[5]  Gerrit Kateman,et al.  Evaluation of peak-recognition techniques in liquid chromatography with photodiode array detection , 1987 .

[6]  Faster quantitative evaluation of high-performance liquid chromatography-ultraviolet diode-array data by multicomponent analysis , 1993 .

[7]  Joe M. Davis,et al.  Statistical theory of component overlap in multicomponent chromatograms , 1983 .

[8]  M. Maeder,et al.  The resolution of overlapping chromatographic peaks by evolving factor analysis , 1986 .

[9]  A. Fell,et al.  Novel techniques for peak recognition and deconvolution by computer-aided photodiode array detection in high-performance liquid chromatography , 1983 .

[10]  A. Fell,et al.  Computer-aided time domain differentiation in high-performance liquid chromatography , 1989 .

[11]  A comparison of the heuristic evoling latent projections and evolving factor analysis methods for peak purity control in liquid chromatography with photodiode array detection , 1992 .

[12]  Y. Hayashi,et al.  A one-dimensional kalman filter for peak resolution , 1988 .

[13]  Gerrit Kateman,et al.  Generalized rank annihilation factor analysis, iterative target transformation factor analysis, and residual bilinearization for the quantitative analysis of data from liquid chromatography with photodiode array detection , 1992 .

[14]  D. Massart,et al.  Orthogonal projection approach applied to peak purity assessment. , 1996, Analytical chemistry.

[15]  A. Fell,et al.  Multiple absorbance ratio correlation — a new approach for assessing peak purity in liquid chromatography , 1990 .

[16]  Peter D. Wentzell,et al.  Real-Time Principal Component Analysis Using Parallel Kalman Filter Networks for Peak Purity Analysis , 1991 .

[17]  D. Desilets,et al.  Quantitation and identification of polynuclear aromatic hydrocarbons by liquid chromatography and multiwavelength absorption spectrometry , 1984 .

[18]  R. D. Conlon,et al.  Numerical spectroscopy: Absorbance index technique and algorithm for qualitative analysis in liquid chromatography , 1981 .

[19]  Andrew W. Sulya,et al.  Ratio of sequential chromatograms for quantitative analysis and peak deconvolution: application to standard addition method and process monitoring , 1990 .

[20]  Sarah C. Rutan,et al.  Optimization of an adaptive kalman filter based on information theory , 1994 .

[21]  Gerrit Kateman,et al.  Evaluation of curve resolution and iterative target transformation factor analysis in quantitative analysis by liquid chromatography , 1987 .

[22]  H. R. Keller,et al.  Heuristic evolving latent projections: resolving two-way multicomponent data. 2. Detection and resolution of minor constituents , 1992 .

[23]  Marcel Maeder,et al.  Evolving factor analysis, a new multivariate technique in chromatography , 1988 .

[24]  G. Kateman,et al.  Multicomponent self-modelling curve resolution in high-performance liquid chromatography by iterative target transformation analysis , 1985 .

[25]  Steven D. Brown,et al.  Resolution of a coeluting chromatographic pair using kalman filtering , 1989 .

[26]  Yizeng Liang,et al.  Heuristic evolving latent projections: resolving two-way multicomponent data. 1. Selectivity, latent-projective graph, datascope, local rank, and unique resolution , 1992 .

[27]  Desire L. Massart,et al.  Algorithm for the assessment of peak purity in liquid chromatography with photodiode-array detection , 1994 .

[28]  A. Drouen,et al.  Dual-wavelength absorbance ratio for solute recognition in liquid chromatography , 1984 .