and mathematical models for deconvolution of overlapping peaks and integration in noisy and complex systems 16 16 Marco, V.
Therefore, various peak recognition methods 10 10 Zhang, J. This issue becomes more critical with increasing demand for faster analysis and narrower peaks, which mobilizes the developers of algorithms for chromatographic data treatment. the errors associated with these procedures may propagate up to the final result of an analysis. Since the allocation (even if automated) of peak boundaries as well as the subsequent peak integration are not necessarily accurate and precise due to the presence of noise, for instance, 9 9 Dyson, N. typical responses such as efficiency, resolution, signal-to-noise ratio, analysis time, and symmetry, among others, are completely dependent on accurate measurements made on that peak, during optimization 5 5 Mostafa, A. Since the presence of an analyte is observed through appearance of a chromatographic/electrophoretic peak, whose height and area are sensitive to concentration, 4 4 Li, J.
#Agilent chemstation general purpose software download registration
However, the dispersion of the analyte molecules during their continuous and differential motion along the separation system is one of the main unavoidable separation characteristics, so that the analyte registration should be as representative as possible. Several advantages such as sensitivity of detection modes, selectivity and efficiency of separation columns and short analysis times, have led the chromatographic and electromigration techniques to this high level. Separation science clearly occupies a prominent position in analytical chemistry.
Peak recognition peak integration chromatography capillary electrophoresis Excel macros Statistically similar results were obtained, when compared with other commercial software, showing it to be a simple, practical and reliable tool for general use in the separation area. Data from liquid and gas chromatography, capillary electrophoresis and electrochromatography techniques with refractive index, flame ionization, capacitively coupled contactless conductivity (lab-made) and ultraviolet absorbance detections, respectively, were treated, illustrating the broad applicability of the proposed program for standard and sample analysis. The effect of peak shape (heights and symmetries) and baseline slope over accuracy was evaluated and the precision of recognition/integration was investigated under several simulated conditions, with varied signal-to-noise levels, smoothing modes and smoothing window sizes. A chromatogram/electropherogram is plotted along with the found baselines.
During integration, retention/migration time, area, height, half-height width, plate numbers, asymmetry factor, US Pharmacopeia tailing factor, resolution and statistical moments are determined. The proposed recognition is made according to parameters adjustable by the analyst, such as time range, noise smoothing window size and slope/curvature sensitivity. This paper describes the development, evaluation, features and applications of Chromophoreasy, an alternative Excel-based program for recognition and integration of chromatographic and electrophoretic peaks.