Artificial intelligence in combustion reaction kinetics: Methods and applications

Combustion is a complex process involving fluid dynamics, heat transfer and chemical kinetics, with significant environmental impacts due to greenhouse gas and pollutant emissions. The development of combustion reaction kinetics is crucial for understanding and subsequently regulating combustion processes. Combustion kinetic models face challenges in balancing accuracy and computational efficiency. The rapid development of artificial intelligence (AI) offers new momentum into the advancement of combustion reaction kinetics. This article presents a comprehensive review of AI applications in the development of combustion reaction kinetics. Specifically, this article systematically examines current AI implementations across five core task scenarios in combustion reaction kinetics modeling, including surrogate model construction, model parameter optimization and prediction, experimental design, reaction pathway inference and model reduction. This article emphasizes how AI advances combustion reaction kinetics by fully extracting information from data and integrating physical knowledge into data-driven approaches. Finally, this article provides predictions and recommendations on future directions where AI is expected to play a critical role in advancing combustion reaction kinetics. • Commonly used AI methods in combustion reaction kinetics. • AI applications in combustion reaction kinetics development to date. • Recommendations for future AI-powered combustion kinetic modeling.