气相色谱柱温的智能最佳化 Ⅰ.理论基础

Intelligent Optimization of Column Temperatures in Gas Chromatography Ⅰ. Theory

本文提出了智能最佳化气相色谱柱温的理论基础,解决了最佳温度求解区间及控温方式的预测、最难分离物质对及交叉点的预测、围绕最难分离物质对及交叉点的最佳化分离温度的预测三个问题,为智能最佳化柱温程序设计奠定了基础.

This paper gives the theory on intelligent optimization of column temperatures in a given gas chromatographic column system. Based on the structure-retention relationship between solutes and solvents, and the dependence of retention values on temperatures, most difficult separating component pairs and temperature separability range can be predicted, ideal optimum temperature programming, in which every step is determined by a most difficult separating component pair, can be further obtained.