Development and optimization of a laboratory-scale bubble column bioreactor for bioethanol fermentation: a computational approach

This study presents the design and optimization of a laboratory-scale bubble column bioreactor (BCB) for bioethanol fermentation. Python-based simulations in Google Colab were employed to analyze mass transfer dynamics, hydrodynamic behavior, and reactor scale-up strategies under varying aeration rates. Although ethanol production is an anaerobic process, oxygen transfer analysis was conducted to characterize reactor performance and establish oxygen-limited conditions suitable for Saccharomyces cerevisiae fermentation, incorporating mass transfer modeling, reaction kinetics, process control, and sparger design to enhance fermentation efficiency. To further enhance fermentation efficiency, Response Surface Methodology (RSM) was applied following a two-stage optimization approach. A working volume of 500 mL was defined using fermentation kinetics, including an oxygen uptake rate of 1.1 g O₂/g cells, biomass yield of 0.5 g/g glucose, and kLa of 50 h⁻¹. A perforated plate sparger with six 1.2 mm orifices achieved a gas velocity of 90.3 m/s and 2.68 mm bubble size. Aeration was dynamically controlled to maintain 0.002 g/L dissolved oxygen, while pH was regulated at 5.0–5.5 using NaOH dosing. These conditions yielded 44.3% ethanol. A full factorial design identified Time, Air Flow Rate, Cell Loading, and Bead Mass as significant factors. RSM with Central Composite Design confirmed a significant quadratic model (F = 14.14, p < 0.0001; R² = 0.9601, Adjusted R² = 0.9201). Cell Loading (F = 48.48) and Bead Mass (F = 26.53) had the strongest effects. Optimal conditions yielded 47.9% ethanol at 52.70 h, 1.55 L/min air, 1.51 g/L cells, and 47.20 g beads, with 0.84% prediction error.