CFD-based prediction of initial microalgal adhesion to solid surfaces using force balances

Area of Science:

• Biotechnology
• Chemical Engineering
• Fluid Dynamics

Background:

• Microalgal cell adhesion to photobioreactor surfaces leads to significant economic losses due to reduced productivity.
• Current understanding of biofouling in photobioreactors is limited, with no existing multiphysical models capable of prediction.
• Physico-chemical surface properties and fluid dynamics are known factors influencing microalgal adhesion.

Purpose of the Study:

• To develop and validate a predictive model for microalgal cell adhesion in photobioreactors.
• To investigate the forces governing microalgal adhesion using a computational approach.
• To enhance the economic viability of microalgal cultivation by mitigating biofouling.

Main Methods:

• A Computational Fluid Dynamics (CFD) simulation was employed using a Eulerian-Lagrangian particle-tracking model.
• The adhesion criterion was established based on the force and moment balance within the extended Derjaguin-Landau-Verwey-Overbeek (XDLVO) model.
• Experimental validation was performed using a marine microalga, *Nannochloropsis gaditana*, in a flow cell with poly-methyl-methacrylate coupons.

Main Results:

• The developed CFD-DPM model qualitatively predicted the initial distribution of adhered microalgal cells on the flow cell coupons.
• The simulation successfully integrated fluid dynamics with physico-chemical adhesion forces.
• The model demonstrated the potential for predicting biofouling patterns in photobioreactors.

Conclusions:

• The combined CFD-DPM approach offers a robust method for predicting microalgal cell adhesion in photobioreactors.
• This predictive capability can help mitigate biofouling and improve the overall productivity and economic efficiency of microalgal cultivation.
• The study provides a foundation for further development of advanced multiphysical models for photobioreactor design and operation.