Movement of microswimmers is key to targeted drug delivery

The research is being carried out by Ebru Demir, an assistant professor of mechanical engineering and mechanics in Lehigh University’s P.C. Rossin College of Engineering and Applied Science.

“We know that whenever a swimmer has a neighbour, it swims differently,” Demir said in a statement. “Birds fly in a V formation because it’s more efficient and it saves them energy. But for a group of microswimmers, we don’t know what the best formation looks like.”

Demir recently received funding through the US National Science Foundation’s Faculty Early Career Development (CAREER) Program for her research combining artificial microswimmers with machine learning to build Smart Artificial Microswimmers (SAMs).

By embedding AI into centimetre-scale robotic swimmers and comparing their behaviour with predictions from simulations, her project aims to uncover the underlying physics that governs their movement in complex fluid environments. 

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To study how the swimmers move in Newtonian and non-Newtonian fluids, Demir will insert microcontrollers that run reinforcement learning algorithms into 3D-printed autonomous robots that are 10-20cm in size.