Combining synchronous fluorescence spectroscopy with multivariate methods for the analysis of petrol-kerosene mixtures

被引:34
作者
Divya, O. [1 ]
Mishra, Ashok K. [1 ]
机构
[1] Indian Inst Technol, Dept Chem, Madras 36, Tamil Nadu, India
关键词
SFS; synchronous fluorescence; principal component regression; partial least squares regression; POLYCYCLIC AROMATIC-HYDROCARBONS; CALIBRATION; ADULTERATION; SPECTRA;
D O I
10.1016/j.talanta.2006.09.032
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
Synchronous fluorescence spectroscopy (SFS) is a rapid, sensitive and nondestructive method suitable for the analysis of multifluorophoric mixtures. The present study demonstrates the use of SFS and multivariate methods for the analysis of petroleum products which is a complex mixture of multiple fluorophores. Two multivariate techniques principal component regression (PCR) and partial least square regression (PLSR) have been successfully applied for the classification of petrol-kerosene mixtures. Calibration models were constructed using 35 samples and their validation was carried out with varying composition of petrol and kerosene in the calibration range. The results showed that the method could be used for the estimation of kerosene in kerosene-mixed petrol. The model was found to be sensitive, detecting even 1 % contamination of kerosene in petrol. (C) 2006 Elsevier B.V. All rights reserved.
引用
收藏
页码:43 / 48
页数:6
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