Kinetics for Catalytic Pyrolysis of Organic Solid Wastes

Catalytic pyrolysis has emerged as a pivotal technology for converting renewable diverse feedstocks (i.e., lignocellulosic biomass, algal biomass, and plastic wastes) into biofuels and chemicals. This review comprehensively examines the reaction kinetics in catalytic pyrolysis, addressing the fundamental gap between lab-scale research and industrial applications. The mechanisms of conventional (i.e., electrical heating) and microwave-assisted catalytic pyrolysis are detailed, highlighting the role of catalysts in altering reaction rates, reaction pathways, and decreasing activation energies. This paper delves into kinetic analysis techniques by comparing the model-free and model-fitting approaches and exploring the emerging role of machine learning in predicting kinetic parameters. In addition, it extensively explores the feedstock specific kinetic models, highlighting the behavior of pseudo-components of lignocellulosic feedstocks, plastic wastes, and their mixtures with a specific focus on synergistic effect during co-pyrolysis. Further, an essential framework to integrate molecular-scale phenomena with reactor-scale process performance was presented by exploring the advanced modelling techniques such as microkinetic modelling using density functional theory (DFT), lumped system analysis using process simulations, and catalyst deactivation kinetics. Despite its promise, challenges such as catalyst deactivation, heat and mass transfer limitations, and feedstock variability remain critical hurdles. This review concludes by identifying future research directions, emphasizing the in-situ characterization, integration of machine learning and artificial intelligence for process optimization, and kinetics of emerging catalyst systems to facilitate the commercial deployment of predictive models for catalytic pyrolysis technologies.