Adaptive Microfluidic Networks for Optimal Transport

• Applicant: Professorin Dr. Karen Alim
• Subject Area: Statistical Physics, Nonlinear Dynamics, Complex Systems, Soft and Fluid Matter, Biological Physics
• Term: since 2021
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 490727199

Flow transport in complex networks is abundant in biology and engineering, from the vasculature of animals, to the hyphal networks of fungi, to the random porous media making up batteries. It has long been thought that biological network morphologies were optimised to minimise the energetic cost associated to viscous flow dissipation in their branches. However, another possibility, raised recently is for these networks to be optimal for mass exchange, or perfusion. We then need not only to have a network that covers space efficiently, but also whose morphology leads to an even flow of chemicals (catalysts, nutrients, oxygen,...) throughout all its tubes, so that all parts of the network receive the same amount of chemical. Living systems continuously adapt their network morphology in response to stimuli; local feedback coupled to the presence of global flows leads to self-organised structures optimal for perfusion. In contrast, fluid velocities in engineered networks of random media differ from tube to tube, and follow an overall exponential distribution. Transport through these porous media is inefficient, being limited to a few fast lanes. The current strategy to optimize flow in porous media is to build, branch by branch, an optimized network morphology. The aim of our project is to combine theory, simulations and experiments to generate adaptive microfluidic networks whose morphology self-organises in response to signals, leading to network morphologies optimal for perfusion. In addition to its fundamental interest, the outcome of this project has a wide range of applications, from the design and cooling of efficient batteries, to the production of enhanced chemical reactors having high transport efficiency and a large reaction surface, contributing to having a cleaner, more affordable energy.

• DFG Programme: Research Grants
• International Connection: France
• Cooperation Partner: Dr. Gabriel Amselem