Optimization of Deep Eutectic Solvents (DES) Pretreatment for Enhanced Cellulose Yield from Lignocellulosic Biomass: A Case Study in Zambia

Deep Eutectic Solvents (DES) ratio when used in the corn stover pretreatment can enhance cellulose yield. It is an acknowledgement of Zambia’s rich biomass resources, such as agricultural residues, which can be converted into bioethanol. The study employs DES (specifically Choline Chloride and Lactic Acid synthesis) to remove lignin and hemicellulose from cellulose-rich CS fibers. To optimize the pretreatment process, predictive models such as Central Composite Design (CCD), Artificial Neural Network (ANN), Gradient Boosted Regression Trees (BRT), Random Forest (RF), and Support Vector Machine (SVM) were used. Among these, the BRT model showed the best performance, highlighting the complexity of modeling biochemical reactions and the need for diverse models to capture the full range of interactions in biomass conversion. Optimal pretreatment conditions were identified, emphasizing the significance of temperature, solvent ratio, and residence time in breaking down lignin, enhancing cellulose hydrolysis, and improving biofuel production efficiency. The study explores the influence between residence time, reaction temperature, and biomass-to-deep findings have implications for scaling up biofuel production, addressing energy security, and promoting economic stability in Zambia by reducing dependency on imported fossil fuels and stimulating economic growth through locally produced biofuels.