Extraction of important reaction pathways for complex reaction network based on community detection algorithm

The development of accurate mechanistic process models of processes at the molecular radical scale is an important direction in the development of “molecular refining” in the world. The complexity of molecular refining process systems is mainly due to the coupling and multiscale of chemical reaction networks, which poses a challenge to the in-depth understanding of chemical production processes. The key information mining and representation of the complex reaction network can help engineers to understand the process mechanism in depth and realize the transparency of the mechanism. Since the complex reaction networks of oil refining processes have modular and community-based characteristics centered on key reaction substances, this paper adopted the Leiden community detection algorithm to divide the reaction networks of steam cracking into reaction communities at mesoscale. The corresponding key reaction pathways were extracted from the reduced reaction communities at the molecular free radical scale. It provided an interpretable bridge from macroscopic reaction networks to microscopic substance interactions and helped to reveal the knowledge transfer mechanism of the substance transformation process. © 2023 Chemical Industry Press. All rights reserved.