A workflow for modeling radiolysis in chemically, physically, and geometrically complex scenarios

Radiation-based techniques contribute significantly to characterizing nanoscale samples across materials research but are frequently hampered by radiation-induced damage, particularly radiolysis in liquid media. The deep understanding and accurate modeling of radiation chemistry are crucial for interpreting experimental observations but are rarely sufficiently addressed in practice. We introduce a comprehensive workflow for numerically modeling radiolysis reaction kinetics in chemically, physically, and geometrically complex scenarios. The workflow streamlines the automatic composition of validated reaction networks from database files in a Python-based environment (AuRaCh tool) and their transfer to finite element computation environments (COMSOL Multiphysics software) for geometric and physical expansion. Its applicability is demonstrated in the context of liquid-phase electron microscopy but extends to other fields involving complex reaction networks. Model complexity is scrutinized, and potential simplifications are explored using characteristic numbers in experimentally relevant parameter regimes. The reported approach improves computational modeling and correlative experimental methods by promoting cross-community approaches.