ATR-FTIR Spectroscopy Combined with Chemometric Methods for the Classification of Polyethylene Residues Containing Different Contaminants

Abstract

Low density polyethylene (LDPE) and high density polyethylene (HDPE) are the principal plastics present in solid plastic waste and are found out as the main components of microplastics in marine and terrestrial environments. Currently, efforts have been made to develop new and effective methods to ensure the identification and separation of plastics in waste, ensuring the necessary purity to obtain quality and economically competitive recycled products. In this contribution, we investigated the usage of Fourier-Transform Infrared Spectroscopy in Attenuated Total Reflection mode (ATR-FTIR) combined with Principal Component Analysis (PCA), Linear Partial Least Squares Regression by Intervals (iPLS-R) and Competitive Adaptive Weighted Sampling (CARS/PLS-R) as chemometric methods to classify and determine the compositional fraction of the pristine and recycled mixtures of HDPE and LDPE from plastic waste in São Paulo, Brazil. Here, the 3D PCA plots were not effective in classifying the different polyethylenes and their polymer blends using the three main Principal Components (PC), but 2D PCA diagrams using PC1 and PC3 presented promising performance for this purpose. The iPLS-R presents the best predictive ability than CARS/PLS-R to determine the LDPE content in HDPE/LDPE recycled blends. However, the presence of different contaminants (in 5 wt%), such as silicon dioxide (SiO2), calcium carbonate (CaCO3), recycled polypropylene (PP), and recycled poly(ethylene terephthalate) (PET), reduces the potential usage of the iPLS-R models as identification tools for LDPE and HDPE sorting in industrial recycling processes.