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

Abstract EN

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 (R2) 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.