An Information-Based Computational Technique for Estimation of Chromatographic Peak Purity

Assessment of the purity of chromatographic peaks is an important step in developing and validating purification procedures for complex mixtures. While curve-fitting techniques can be useful for determining the retention times and relative concentrations of the components of a chromatographic peak, their utility is limited by the lack of unambiguous criteria for determining the number of such components. In this work, we present a computational technique for analyzing chromatograms to estimate the number of components, their retention times, and their relative concentrations. In contrast to Fourier-transform-based techniques, the technique we present does not require manual peak identification. It is based on curve-fitting and uses the Akaike information criterion to estimate the number of components. Application of the technique to chromatograms obtained from size-exclusion and reverse-phase chromatography of test mixtures indicates that it is useful for the characterization of complex mixtures.