A database-integrated cheminformatics framework for mechanistic elucidation of secondary organic aerosol formation...

The formation mechanisms of secondary organic aerosol (SOA) from volatile organic compound (VOC) precursors are typically interpreted manually using traditional frameworks such as the Master Chemical Mechanism (MCM), a process that is time-intensive and constrained by the vast chemical space and complexity of atmospheric reaction networks. Here, we present a database-integrated cheminformatics framework that enables automated and scalable simulation of SOA formation from both anthropogenic and biogenic VOCs. The framework systematically compiles complete reaction networks from the MCM and literature-derived mechanisms into an initial chemical space and reaction history for each precursor, which is subsequently expanded using a set of generalized reaction rules representing key atmospheric processes. By combining curated reaction networks with an expanded rule set and an improved simulation workflow, the framework is designed to (i) improve predictive agreement with high-resolution mass spectrometry data, (ii) enable automated exploration of complex reaction networks without labor-intensive manual navigation of mechanisms such as the MCM, and (iii) generate chemically consistent and mechanistically explicit formation pathways for SOA products. The approach successfully assigns molecular structures to experimentally observed molecular formulas and explicitly preserves multistep oxidation sequences while reducing dependence on simulation depth, enabling efficient reconstruction of chemically meaningful pathways. By integrating heterogeneous reaction knowledge into a unified and extensible simulation platform, this work provides a robust computational tool for the mechanistic interpretation of SOA formation and demonstrates strong potential for predictive modeling of complex atmospheric chemical systems.