Investigation on the co-pyrolysis of agricultural waste and high-density polyethylene using TG-FTIR and artificial neural network modelling

To realize utilization of agricultural and plastic waste to alleviate environmental pollution, the individual pyrolysis and co-pyrolysis characteristics of kidney beans stalk (KS) and high-density polyethylene (HDPE) were investigated. Thermogravimetry coupled with Fourier transform infrared spectroscopy (TG-FTIR) was used to investigate the pyrolysis behaviour, synergistic effect, kinetics and gaseous product evolution of different samples. In addition, an artificial neural network (ANN) model was established to predict the mass change with temperature during sample pyrolysis or co-pyrolysis. The results showed that the decomposition of HDPE was easier than that of KS, and synergistic and inhibitive effects occurred during co-pyrolysis. The synergistic or inhibitive effect was most significant from 470 to 510 ℃. The FTIR analysis results showed that gaseous products of KS pyrolysis were mainly oxygen-containing compounds including CO2, CO, ketones, aldehydes, esters, etc., while those of HDPE pyrolysis were mainly hydrocarbons including alkanes, alkenes, aromatic rings, etc. The co-pyrolysis of samples with different proportions promoted or inhibited the production of some gaseous products to different degrees. Moreover, the activation energy of the two stages during co-pyrolysis was lower than that of the pure sample. The established ANN model can effectively predict the mass loss of a sample with temperature.