Gas chromatography
High performance liquid chromatography Theoretical basis of column chromatography in multicomponent separations Required value of peak resolution and accuracy of obtained, quantitative method Plate height of solute with capacity ratio equal to one or approaching to infinity Linearity between peak width and retention value High efficient GC columns HPLC small-bore column
Summary
The point of our published papers since 1957 is reviewed. The relations between the required value of peak resolution, K1 (or R), and peak separation, K3 (eqn 9); K1 and relative accuracy of a peak height quantitative method, Ph (eqn. 10); K1 and relative accuracy of a peak area method, Pa, (eqn. 12) at different concentration ratios, @, are derived. The final result in Table 2 shows a large influence of on the required value of KI.
The approximately linear relation between peak width and retention value (eqn. 18) exists not only in GC. but also in HPLC. Plate height values HI and H" for a solute with capacity ratio, k', equal to unity or approaching infinity, respectively, are used to evaluate the column efficiency (eqn. 20). The measuring methods (eqn. 21,22,23) and parameters effecting on Hi and H" are given for GC packed column (eqn. 24), GC open tubular column (eqn. 25) and HPLC (eqn. 26). In the light of this, columns of high efficiency were developed. Some typical chromatograms for high speed analysis and separation of complex mixtures are given.
Column chromatography, like gas chromatography and high performance liquid chromatography, is still one of the most active areas in analytical chemistry. The aim of any chromatography process is to separate a multicomponent mixture. For this purpose we have to develop a column of high efficiency column or column system of good selectivityand to select operating parameters, not only forasingle substance, but for the multicomponent mixtures as well. Hence the influences of various components on column efficiency and column selectivity have to be considered and the pair of substances most difficult to separate must be predicted in order to select the optimum parameters.