Thermal decomposition kinetics of plastic mixtures (PE/PVC and PE/PP) based on chemical reaction neural networks

Polyethylene (PE), polypropylene (PP), polyvinyl chloride (PVC), and their mixtures are widely used in packaging, electrical, and construction fields. Thermal decomposition is one of the primary methods for their recycling. In this study, the thermal decomposition kinetics of three plastics: PE, PP and PVC, along with two mixtures, e.g., PE/PVC and PE/PP, were investigated using a chemical reaction neural network (CRNN). Three models with four species and two reactions (4-2 model) are developed for PE, PP, and PVC decomposition. The experimental thermogravimetric (TG) curves can be well reproduced. The corresponding kinetic models for plastic mixtures are also proposed by integrating the kinetic models of single components. The results indicate that the predicted TG curves of PE/PVC mixtures align closely with the experimental data, confirming the absence of coupling effects between PE and PVC decomposition. However, the model for PE/PP mixtures fails to accurately predict the thermal decomposition process with a noticeable underprediction of the initial decomposition temperature. A careful analysis highlights the strong coupling effect between PE and PP decomposition upon heating, and a simple combination of kinetic models for single components cannot fully reveal the thermal decomposition mechanisms of the PE/PP mixtures. This work opens up a new modelling approach to build the kinetic models for plastics and evaluate the potential coupling effect in the practical decomposition of plastic mixtures.