Advancing bioethanol production with a new kinetic model based on structure-oriented lumping for cellulose conversion

Bioethanol, as a significant renewable energy source, plays a crucial role in alleviating the energy crisis and reducing greenhouse gas emissions. This research constructed a kinetic model for the hydrolysis of cellulose into bioethanol using the Structure-Oriented Lumping (SOL) method. Three vector units were defined to represent the structure of cellulose and its products, and five reaction rules were used to generate an 18-step reaction network. Reaction rate constants for these reactions were determined for various catalysts using genetic algorithms, and catalyst performance was analyzed based on these rate constants. Results demonstrated a high degree of agreement between experimental data and model predictions over time for the yield of cellulose and its products across four model applications using 16 different catalysts, effectively predicting yield variations with the maximum mean absolute error (MAE) not exceeding 6.3 % and the minimum being as low as 0.8 %. The predictive accuracy of the model provides a robust basis for analyzing catalyst performance through four distinct model applications: 1. In the catalyst hydrolysis of cellulose to ethanol by 5Ru-25 W/HZSM-5, the model identified the hydrogenolysis of EG (k13) as the rate-determining step (RDS). 2. The model explored the impact of Cu-WOx/SiO2 catalysts loaded with various metals (X = None, Pd, Au, Ru), demonstrating how different metal loadings influence the RDSs for the production of EG and ethanol from cellulose. Notably, catalysts loaded with Ru significantly enhanced the RDS (km) for EG, thereby increasing its yield. 3. The model highlighted subtle influences on the RDS for cellulose hydrolysis to EG under catalysts prepared using different methods and carriers. However, fundamentally, these changes did not alter the rate-limiting step (k7), but merely affected the magnitude of the RDS rate. 4. For multiple diols, the model revealed that different catalysts have distinct ratedetermining steps, yet the yields of these products consistently correlate with their respective RDS rates. In addition, distinct from traditional thermodynamic analyses that explain catalyst reactivity and efficiency, this study delved into the nuanced association between catalysts and key reaction steps from a kinetic perspective, offering a new dimension of understanding of the catalytic process.