Prediction by multivariate data analysis of long-term properties of glassfiber reinforced polyester composites

摘要

The prediction of long-term properties of polymers has been analysed by identifiction of low molecular weight compounds in glassfibre-reinforced polyester composites which were subjected to accelerated ageing at 40 and 60℃ and 80 -RH for periods up to 6 years. Before the accelerated ageing the materials were stored for 20 years at ambient temperature. After different ageing times the low molecular weight products in the materials were identified with GC-MS and headspace-GC-MS. Several different alcohols, phthalates and other aromatic compounds were identified. Temperature had a large influence on the degradation of phthalates and the formation of alcohols. In the first step we used principal component analysis (PCA) and partial least square (PLS)to locate outliers and to identify the products that were not connected to degradation time or temperature. After that PCA and PLS were used to reveal if unsaturated polyesters have different degradation mechanisms at 40 and 60℃ by comparing the amounts and types of degradation products. The relative influence of each factor on the degradation rate was studied and groups were made among the degradation products to define which degradation products are correlated with ageing time and temperature. Finally the ageing time was predicted from the amounts of degradation products (in that case the amount of products are considered as X factors and the time of degradation as a Y response). PCA showed that it was not possible to find a pattern in the HS-GC-MS chromatograms, due to the different volatility of the compounds. The score plots