Qualitative and quantitative aspects of time-, charge-, and mobility-based electropherograms.

The migration process in capillary electrophoresis is obtained by using a high-voltage power supply, and the basic idea is to keep the control on the migration velocity of the analytes by controlling either the applied voltage or current. The effectiveness of this control has impact on the resulting electropherogram and, thus, in the identification and quantification of the analytes. Although the usual electropherogram is the record of the detector signal as a function of time, other two domains should be considered: charge and mobility. Both mathematical modeling and experimental results were used to evaluate the two different approaches for controlling the electrophoretic migration and the resulting time-, charge-, and mobility-based electropherograms. The main conclusions are (1) the current-controlled mode is superior to the voltage-controlled mode; (2) when the first mode cannot be implemented, the electrophoretic current should be monitored to improve the identification and quantification procedures; and (3) the consistent monitoring of the electrophoretic current allows the implementation of the charge-based electropherogram and the mobility spectrum. The first one is advantageous because the peak position is more reproducible, and the peak area is more resistant to change than the ones from the time-based electropherogram. The mobility spectrum has the additional advantage of being more informative about the mobility of the analytes. Although peak area is less robust, the spectrum may also be used for quantitation when the number of plates is greater than 103 .

Determining the probability of locating peaks using computerized peak-location methods in gamma-ray spectra as a function of the relative peak-area uncertainty.

The probabilities of locating peaks with a high relative peak-area uncertainty were determined empirically with nine types of peak-location software used in laboratories engaged in gamma-ray spectrometry measurements. It was found that it is not possible to locate peaks with a probability of 0.95, when they have a relative peak-area uncertainty in excess of 50%. Locating peaks at these relatively high peak-area uncertainties with a probability greater than 0.95 is only possible in the library-driven mode, where the peak positions are supposed a-priori. The deficiencies of the library-driven mode and the possibilities to improve the probabilities of locating peaks are briefly discussed.