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Chemometrics to chemical modeling: Structural coding in hydrocarbons and retention indices of gas chromatography
Author(s) -
Yin Chunsheng,
Liu Wei,
Li Zhiliang,
Pan Zhongxiao,
Lin Teng,
Zhang Maosen
Publication year - 2001
Publication title -
journal of separation science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.72
H-Index - 102
eISSN - 1615-9314
pISSN - 1615-9306
DOI - 10.1002/1615-9314(20010301)24:3<213::aid-jssc213>3.0.co;2-4
Subject(s) - chemometrics , kovats retention index , chemistry , gas chromatography , chromatography , linear regression , correlation coefficient , analytical chemistry (journal) , mathematics , statistics
Systematic studies were performed on an application of chemometrics to molecular modeling and the regularity of the retention index ( RI ) of gas chromatography (GC). Molecular structures of hydrocarbons in straight‐run gasoline were numerically coded. A set of structural parameters was accordingly obtained for the hydrocarbons and found correlate to their GC retention indices. A quantitative structure‐retention relationship (QSRR) model (M1), with a correlation coefficient of R = 0.9901 and a standard deviation ( SD ) error of SD = 20.24, between the numeric structural codes and GC retention indices of 150 hydrocarbons was developed using multiple linear regression (MLR). If a “leave‐one‐out” cross‐validation procedure was employed to construct a QSRR model for all samples, a second model (M2) with R = 0.9874 and SD = 22.87 was generated. The structural codes of hydrocarbons were tested with MLR for estimation and prediction of the GC RI by models M1 and M2, and the results obtained proved to be satisfactory.