Stoichiometry Driven cPINN Modeling of Phenol Synthesis: Application in Enzyme Mediated, Biosynthetic Pathways, Bioengineering and Pharmaceutical Sciences
This study proposes a causal physics-informed neural network for phenol synthesis through alkaline fusion and acidification. Physical laws and stoichiometric constraints are embedded in the loss function to learn concentration trajectories and kinetic parameters for a stiff nonlinear reaction system.