Development of a method for the identification of organic contaminants in vinyl chloride monomer (VCM) by TD-GC-MS and multivariate analysis

• Published in: Analytical methods 2014-01, Vol.6 (22), p.8946-8955
• Main Authors: dos Santos, Fábio Neves, Horiuchi, Lucas Nao, Pereira, Pedro Afonso P.
• Format: Article
• Language: English
• Subjects: Contaminants; Inhibitors; Multivariate analysis; Polymerization; Polyvinyl chlorides; Samples; Statistical analysis; Statistical methods
• ISSN: 1759-9660; 1759-9679
• DOI: 10.1039/C4AY01508H

The main raw material used in the production of polyvinyl chloride (PVC) is vinyl chloride monomer (VCM). Controlling the purity of VCM is essential to control the parameters of the polymerization reaction and the properties of PVC resins, such as the molecular weight, porosity, particle size and thermal stability, since some organic contaminants react as co-monomers and are undesirable. Two methods of concentration by adsorption and thermal desorption were developed using the adsorbents Tenax-TA and Tenax-TA/Carboxen 1000/Carbosieve SIII, applying full and fractional factorial design to optimize the variables. Organic contaminants were identified in the various stages of production, storage and recovery at four distinct points in the process, leading to the identification of nineteen substances in all the samples, including aliphatic and aromatic hydrocarbons, organochlorines, alcohols, phenols and phenones. The contaminants that showed the highest relative abundances were styrene, benzene, toluene, naphthalene, 1,2-dichloroethane, 1-octanol and 1,3-butadiene. Among these contaminants, 1,3-butadiene and styrene have been reported in the literature as potent inhibitors of VCM polymerization. Using PCA multivariate analysis, it was possible to confirm that there are statistically significant differences in the characteristics of the VCM. Samples from four different points in the process were successfully classified into three different groups, in each of which the main contaminants responsible for the differentiation of the samples were identified. This work is innovative in the application of a TD-GC-MS-based system, for the identification of organic contaminants in VCM produced industrially, and in the investigation of its process by multivariate analysis.