A diffusion model and optimal cell loading for immobilized cell biocatalysts.

Area of Science:

• Biocatalysis
• Chemical Engineering
• Biochemical Engineering

Background:

• Immobilized cell biocatalysts are crucial for industrial processes.
• Understanding diffusion limitations within these biocatalysts is key to optimizing reaction rates.
• Existing models may not fully capture the complex interplay of diffusion and cell loading.

Purpose of the Study:

• To develop a novel diffusion model for immobilized cell biocatalysts based on the random pore model.
• To predict the effective diffusivity and its dependence on cell loading.
• To determine optimal cell loadings for maximizing biocatalyst reaction rates.

Main Methods:

• Derivation of a diffusion model incorporating the random pore model.
• Validation using 19 experimental diffusion datasets.
• Analysis of the relationship between effective diffusivity, cell loading, intracellular diffusivity, and partitioning coefficient.

Main Results:

• The model shows effective diffusivity depends quadratically on cell loading.
• A single parameter captures intracellular diffusivity and partitioning effects.
• A general rule of thumb suggests a minimum cell loading of 1/3 for single reactions.
• Methods for calculating improved lower bounds for cell loading are provided.

Conclusions:

• The developed diffusion model accurately predicts behavior in immobilized cell biocatalysts.
• Optimal cell loadings can be determined to maximize biocatalyst performance.
• The findings provide practical guidelines for designing and operating immobilized cell systems.