Théorique, numérique
In this project, we aim to establish a novel mechanistic framework that integrates experiments, theoretical analysis, and simulations to capture quantitatively the hydrodynamic interactions governing both individual and collective behaviors of microorganisms. Our proposed model captures active surface stresses of microorganisms that modulate spatiotemporally to mimic the forces exerted by their motile appendages. The stress distribution will be deduced via optimal control strategies and AI based on experimental data of fluid flows and surface movements around one or multiple cells subject to diverse stimuli and wall boundaries. We will integrate the deduced stress profiles into our computational tools to capture and obtain a full mechanistic understanding of the experimentally observed behaviors. These deduced stress profiles will subsequently be integrated into our computational tools, specifically adapted for large suspensions, to explore the captivating collective behaviors observed in our experiments.