Substantial gradient mitigation in simulated large-scale bioreactors by optimally placed multiple feed points

Area of Science:

• Biochemical Engineering
• Process Engineering
• Industrial Biotechnology

Background:

• Large-scale bioreactors (stirred tank, bubble column) face performance issues due to poor feed mixing.
• Insufficient macromixing causes heterogeneities in pH, substrate, and oxygen, complicating scale-up.
• Optimal feed strategies are crucial for efficient bioprocessing.

Purpose of the Study:

• To theoretically determine optimal feed point placement in large bioreactors.
• To evaluate the impact of multipoint feeding on mixing and process homogeneity.
• To restore ideal bioreactor performance and mitigate scale-up challenges.

Main Methods:

• One-dimensional diffusion equations used to derive theoretically optimal feed point locations.
• Three-dimensional compartment models simulated mixing, pH control, and bioreaction.
• Simulations conducted on four industrial bioreactors (8–237 m³).

Main Results:

• Symmetrical multipoint feeding in axially divided compartments substantially reduced mixing time (>1 minute).
• Significant mitigation of pH, substrate, and oxygen gradients observed.
• Bioreactor performance recovered to ideal homogeneous levels, improving oxygen consumption and biomass yield.

Conclusions:

• Optimal multipoint feed placement is a highly effective strategy for enhancing large-scale bioreactor performance.
• This approach mitigates critical process heterogeneities, enabling efficient scale-up.
• Biomass population heterogeneity was diminished, leading to more consistent biological outcomes.