Novel insights into co-pyrolysis: kinetic, thermodynamic, and AI perspectives

The concept of this article is the need for rational waste management and the use of thermal methods, including pyrolysis. The novelty of the paper results from a comprehensive comparison of pyrolysis of selected plastic waste, coal and biomass, and their co-pyrolysis, using thermal analysis methods: Thermogravimetry, Differential Scanning Calorimetry, Evolved gas analysis, with simultaneous calculation of the kinetic and thermodynamic parameters, using Kissinger-Akahira-Sunnose (KAS), Ozawa-Flynn-Wall (OFW), and Starink methods. It was demonstrated that the intensification of co-pyrolysis processes concerning coal and biomass alone (especially in the case of bituminous coal 80 %/high-density polyethylene 20 % and bituminous coal 80 %/polytetrafluoroethylene 20 %), except co-pyrolysis of biomass with polyetheretherketone. A lower content of volatile matter in relation to biomass characterizes polyetheretherketone. In contrast, high-density polyethylene, polyoxymethylene, polytetrafluoroethylene, and polyvinylchloride have a higher volatile matter content than coal and biomass. The results of the tests showed that the inclusion of coal or biomass in the mixture with plastic waste reduces the overall endothermic effect of the process compared to plastics within the considered temperature ranges. The innovative aspect of the article is an artificial intelligence-based model for predicting the peak maximum weight loss rate of waste fuel blends. The fuzzy logic with Multiple Input and Single Output (MISO) modeling approaches is applied to develop the model. This novel comparative analysis of the pyrolysis processes of coal, biomass, and plastic waste blends, enhanced by a dedicated mathematical model and a fuzzy logic-based approach, offers new insights into the utilization of waste-derived energy within net-zero emissions and sustainable energy frameworks.