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International Journal of Analytical Chemistry
Volume 2015, Article ID 145315, 7 pages
Research Article

Online NIR Analysis and Prediction Model for Synthesis Process of Ethyl 2-Chloropropionate

School of Chemical Engineering, Sichuan University, Chengdu 610065, China

Received 13 May 2015; Accepted 15 July 2015

Academic Editor: Richard G. Brereton

Copyright © 2015 Wei Zhang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Online near-infrared spectroscopy was used as a process analysis technique in the synthesis of 2-chloropropionate for the first time. Then, the partial least squares regression (PLSR) quantitative model of the product solution concentration was established and optimized. Correlation coefficient () of partial least squares regression (PLSR) calibration model was 0.9944, and the root mean square error of correction (RMSEC) was 0.018105 mol/L. These values of PLSR and RMSEC could prove that the quantitative calibration model had good performance. Moreover, the root mean square error of prediction (RMSEP) of validation set was 0.036429 mol/L. The results were very similar to those of offline gas chromatographic analysis, which could prove the method was valid.