A catalyst-aware explainable machine learning framework for biodiesel yield prediction over metal-doped biochar and activated carbon catalysts
Biodiesel production over metal-doped biochar and activated carbon (AC) catalysts involves complex nonlinear interactions among feedstock characteristics, catalyst descriptors, and operating conditions, making accurate yield prediction a challenging task. While machine learning (ML) has shown potential in process model...