A novel approach to the quantification of industrial mixtures from the Vinyl Acetate Monomer (VAM) process using Near Infrared spectroscopic data and a Quantitative Self Modeling Curve Resolution (SMCR) methodology

Abstract This work demonstrates the application of a new Quantitative Self Modeling Curve Resolution (SMCR) approach for the simultaneous qualitative and quantitative recovery of reaction constituents; ethylene, acetic acid, water, vinyl acetate monomer and carbon dioxide from the BP Chemicals Vinyl Acetate Monomer (VAM) process. A cheaper, easier and faster method for the calibration of the VAM process was required because the current calibration procedure is time consuming and expensive. A quantitative SMCR strategy which uses a correlation constraint (regression constraint) during the Alternating Least Squares (ALS) procedure was used to quantify each reaction constituent. Starting estimates for ALS were determined using Quantitative Iterative target Factor analysis (QITTFA) and the NIR spectroscopic data. Vinyl acetate could not be vaporised, therefore QITTFA was selected to provide starting estimates approximating the true solution in the absence of selectivity and a priori knowledge. The results were compared to a well-established multivariate calibration method; Partial Least Squares (PLS) using a non-parametric statistical randomisation test for multivariate calibration models and the model reference error (relative error (RE)) for the prediction of each constituent. It was concluded that the quantitative SMCR procedure could be used to quantify ethylene 9.06% (RE), acetic acid 19.30% (RE), water 13.77% (RE) and carbon dioxide 30.46% (RE) within the defined relative error margin. The advantages of the new approach were a ∼ 90% reduction in the calibration time, ∼ 90% reduction in the number of training samples required for the calibration and the simultaneous recovery of the reaction constituent spectral profiles. Therefore this quantitative SMCR strategy could be used for reactions or processes for which it is not possible to prepare mixtures of known composition, due to the absence of isolated reference material, stability issues and where the preparation of such samples are time consuming and expensive.