Engineering thermochemical reactors using residence time distribution ( RTD ): Methods, models, and modern approaches

Abstract Residence time distribution (RTD) analysis is fundamental in understanding and optimizing reactor behaviour, particularly in thermochemical conversion processes. This review explores the theoretical foundations of RTD, discussing key models such as the dispersion model, tanks‐in‐series model (TIS), compartment models, and bypassing and dead‐zone models, which characterize flow patterns and deviations from ideal reactor behaviour. The study further examines experimental RTD analysis methods, including tracer injection techniques (pulse, step, and impulse‐response) and detection methods (conductivity, UV–vis spectroscopy, and radiotracer analysis), emphasizing their role in accurate RTD measurement and interpretation. Computational advancements, particularly computational fluid dynamics (CFD) simulations, are reviewed as essential tools for predicting RTD curves and diagnosing flow non‐idealities such as dead zones, bypassing, and back‐mixing. The integration of AI and machine learning algorithms is also explored, demonstrating their potential in RTD parameter estimation, optimizing reactor performance, and enabling real‐time adjustments through predictive modelling. The review further highlights the impact of RTD on reactor fouling and catalyst deactivation, identifying key strategies for minimizing fouling through RTD‐based reactor modifications. Despite the significant progress in RTD analysis, challenges persist in measurement accuracy, data interpretation, and real‐time implementation. Future research directions emphasize high‐resolution RTD monitoring, hybrid AI‐RTD models, and advanced process control strategies to improve reactor efficiency and sustainability. By leveraging RTD‐driven reactor optimization, the next generation of thermochemical reactors can achieve enhanced energy efficiency, reduced environmental impact, and improved scalability. This review is a resource for researchers and engineers, outlining current advancements and future opportunities in RTD‐based reactor design and process optimization.