The concept of reversed phase column and normal phase column in liquid chromatography

"Reversed phase" and "normal phase" are concepts proposed in the early stages of liquid chromatography.

From the above introduction, we know that the specific chromatographic method and whether the column is normal phase or reverse phase depends not only on the polarity of the stationary phase, but also on the polarity of the mobile phase

The inner diameter of the chromatographic column determines the sample load, and the sample load is proportional to the square of the inner diameter

How can the resolution be improved in liquid chromatography?

The separation degree calculation formula can be used to understand the factors that affect the separation degree.

Rs=1/4(N0.

N stands for Efficiency, which reflects the performance of the chromatographic column

a represents selectivity, which reflects the ability of the column-mobile phase system to separate two compounds

k means that as the capacity factor k increases, the degree of separation also increases, and this effect is very obvious when the value of k is low

What is gradient elution? When to use gradient elution?

In order to improve the analysis results, some operations need to continuously change the ratio of the solvent components in the mobile phase to continuously change the polarity of the mobile phase, so that each analytical component has an appropriate capacity factor k, and all the components in the sample The components can be separated optimally in the shortest time.

Gradient elution can play an important role in the following situations:

(1) Analysis of a variety of samples with a wide k value under isocratic conditions

(2) Analysis of macromolecule samples

(3) The sample contains strongly retained interferences.

(4) When the analytical method was established, the elution situation was not known, so gradient elution was used to find out the better elution conditions

Related links: How to qualitatively and quantitatively analyze chromatographic analysis and how to avoid false positive results when analyzing complex samples