High-resolution modeling of capillary zone electrophoresis and isotachophoresis

Abstract

content decreases. The reasons for this can be understood by examining correlation analysis in general. In the presence of noise, r0 becomes naturally depressed compared to what it is for less noisy versions of the same spectrum (9). This ultimately leads to failure in the PCA analysis. The autocorrelation of any spectrum gives rise to an r0 value of unity and a full correlation function that is symmetric. Thus, when two spectra are almost identical, their cross-correlation spectrum will also be almost symmetric. Even though the r0 value may be depressed in the presence of noise, the overall correlation function will maintain its symmetry if the spectra are indeed similar. Autoconvolution of the correlation spectrum to give rtym is an efficient method to quantify this symmetry. Thus, rsym utilizes all of the information in the correlation function whereas r0 only uses one point. This suggests that rsym would be an effective replacement for r" even when considering high S/N data. In practical terms, it is not very difficult to use both values and compare the results.

Calculation of the composition of sample zones in capillary zone electrophoresis IV. Weak acids and system characteristics

“…To date, all experimental data have been in accordance with calculated values and a comparison with other simulation programs is important to determine and compare their possibilities [12][13][14][15][16][17][18][19][20].…”

Behavior of peptides in capillary electrophoresis: Effect of peptide charge, mass and structure

“…For general use in CE, with simple ions, several programs of this type have been developed [56,60, 84,86-991. However, due to the complexity of peptide molecules only few of them have been applied to the study of the CE behavior of peptides [60, 83, 86, 87, 911. Of course, these programs also allow the optimization of CE separations, provided the input data are sufficiently accurate and precise.…”

Calculation of the composition of sample zones in capillary zone electrophoresis II. Simulated electropherograms

“…This is in contrast to many other simulation programs or mathematical models. Models based on the KRF [5,8,9] can predict all peak shapes, but generally cannot calculate, e.g., the pH and anomalies in peak shape and baseline disturbances [4]. Also, a recently presented instrument simulator [10,11] for fast graphic illustration of the effect of a large number of variables on the shape of the electropherogram includes many factors but assumes the presence of a BGE, constant in composition, and cannot calculate the various possible UV traces in UV detection.…”