Optimal Feed Control for Bioethanol Production by Extractive Fermentation

• Grant number: 25/12302-9
• Support Opportunities: Scholarships abroad - Research Internship - Doctorate
• Start date: January 01, 2026
• End date: September 30, 2026
• Field of knowledge: Engineering - Chemical Engineering - Chemical Process Industries
• Principal Investigator: Felipe Fernando Furlan
• Grantee: Gabriel Baioni e Silva
• Supervisor: Luis Ricardez-Sandoval
• Host Institution: Centro de Ciências Exatas e de Tecnologia (CCET). Universidade Federal de São Carlos (UFSCAR). São Carlos , SP, Brazil
• Institution abroad: University of Waterloo, Canada
• Associated to the scholarship: 24/02416-4 - Integration of flux balance analysis and techno-economic-environmental analyses to optimize bioethanol production by extractive fermentation, BP.DR

Abstract

Over the past decades, ethanol production has been established as a sustainable alternative to fossil fuels, contributing significantly to the reduction of greenhouse gas emissions and the enhancement of energy security. However, despite the advances achieved, certain challenges persist in the alcoholic fermentation process, such as ethanol-induced inhibition, which decreases the substrate conversion rate and maximum final ethanol concentration, leading to increased purification costs. Extractive fermentation emerges as a promising solution, as it enables the continuous removal of ethanol from the fermentation medium, reducing its toxicity and enhancing productivity. Additionally, dynamic control strategies for substrate feeding allow for the regulation of cell growth kinetics, optimizing fermentation time, controlling temperature, and improving process efficiency. Nevertheless, the integration of these approaches with real-time monitoring still presents limitations, offering opportunities for technological innovations. This study aims to develop optimal control strategies for substrate feeding in extractive fermentation processes, incorporating process modeling, as well as economic and environmental parameters as objective functions. The supervision of Professor Luis Ricardez-Sandoval is fundamental to this project, as his group's pioneering contributions in dynamic optimization are essential for developing the proposed advanced control strategies. Following these advanced methodologies, simulations will be conducted to correlate operational conditions with techno-economic and environmental indicators through surrogate modeling. Expected outcomes include increased efficiency in extractive fermentation, reduced energy consumption in ethanol purification, and decreased generation of effluents such as vinasse.