Application of kinetic plots in gas and liquid chromatography for the optimization of separation conditions

2015 ◽  
Vol 39 (1) ◽  
pp. 162-176 ◽  
Author(s):  
Alexander Kurganov ◽  
Anastasiia Kanateva ◽  
Elena Yakubenko
Keyword(s):  
Liquid Chromatography ◽  
Optimization Of Separation ◽  
Gas And Liquid Chromatography ◽  
Kinetic Plots ◽  
Separation Conditions

Multi-alkylated Polynuclear Aromatic Hydrocarbons of Tobacco Smoke: Separation and Identification

1978 ◽  
Vol 9 (4) ◽  
Author(s):  
M. E. Snook ◽  
R. F. Severson ◽  
R. F. Arrendale ◽  
H. C. Higman ◽  
O. T. Chortyk
Keyword(s):  
Liquid Chromatography ◽  
Cigarette Smoke ◽  
Aromatic Hydrocarbons ◽  
Ultra Violet ◽  
Polynuclear Aromatic Hydrocarbons ◽  
Gel Chromatography ◽  
Cigarette Smoke Condensate ◽  
Gas And Liquid Chromatography ◽  
Silicic Acid Chromatography ◽  
Derivatives Of

AbstractThe methyl, multi-methyl, and ethyl derivatives of the polynuclear aromatic hydrocarbons (PAH) of cigarette smoke condensate (CSC) were isolated from the neutrals by silicic acid chromatography, solvent partitioning and gel chromatography. The procedure yielded a relatively pure PAH isolate amenable to further identifications. The multi-alkylated PAH were concentrated in the early gel fractions with parent and higher ring PAH found in subsequent gel fractions. It was shown that CSC is very rich in alkylated PAH, and their successful identification required extensive use of gas and liquid chromatography and ultra-violet and GC - mass spectrometric techniques. High-pressure liquid chromatography (HPLC) separated individual isomers of the alkylated PAH in complex GC peaks. PAH from indene to pentamethylchrysene were found. This report concludes our identification studies on the PAH of CSC and complements our two previous reports in this journal. Collectively, our studies have identified approximately 1000 PAH of cigarette smoke condensate and have led to the development of methods for the routine quantitation of PAH in smalI quantities of cigarette smoke condensate.

Neural Network Based On the Improved Genetic Algorithm to Optimize Component Separation Conditions of Small Peptide

2011 ◽  
Vol 284-286 ◽  
pp. 261-264
Author(s):  
Jing Wen Tian ◽  
Feng Jun Wu ◽  
Hui Chen ◽  
Jing Di Ren
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Liquid Chromatography ◽  
Forecast Model ◽  
Optimization Methods ◽  
Reversed Phase ◽  
Improved Genetic Algorithm ◽  
Small Peptide ◽  
Neural Network Theory ◽  
Separation Conditions

Reference to traditional optimization methods, neural network based on improved genetic algorithm is used in optimization of reversed phase chromatography pluralistic isocratic mobile phase separation conditions. With detailing the combination of the improved genetic algorithm and neural network theory, the optimization process for the liquid chromatography conditions is introduced in details. Used this method to small peptide RP chromatography optimization, after searching operation, the establishment of an effective separation of forecast model receives satisfactory predictive value, which can prove that this method can be used in optimization of drug liquid chromatography conditions.

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