Sensing like aquatic organisms: using electroactive polymers (EAPs) in an artificial lateral line system

Abstract

The present study explores the development of an artificial lateral line system using electroactive polymer (EAP) sensors, specifically, ionic polymer-metal composites (IPMCs) and polymer gels. The proposed system aims to replicate the sensory capabilities of the natural lateral line found in aquatic organisms, offering structurally embedded flow sensing in the design of underwater vehicles. IPMCs have been extensively studied as bending-based sensors due to their inherent mechanoelectric transduction (MET) capabilities. In this study, the IPMC operates as a neuromast, emulating the cilium structure of the lateral line by converting external mechanical inputs, such as water flow, into a voltage response proportional to the stimulus magnitude. Polymer gels, a novel smart sensor material, are integrated as the lateral line canal material to complement the IPMC-based bending sensor. These pressure-sensitive polymer gels can detect changes in hydrodynamic pressure in the surrounding fluid environment. A TPU-based canal structure was modeled and 3D printed, embedding two surface TPU-DBA polymer gel sensors at the pore entrance. Additionally, a single IPMC sensor, enclosed within a PDMS cupula-like structure, was placed in the center of the canal. The results validate the efficacy of the proposed artificial lateral line model. The combined response of IPMCs and TPU-based polymer gels provides accurate and real-time feedback on hydrodynamic changes and flow patterns, mimicking the natural sensory capabilities of aquatic organisms. The development of this artificial lateral line system holds significant potential for various applications, including underwater robotics, hydrodynamic monitoring, and environmental surveillance, advancing biomimetic sensing systems in dynamic fluid environments.

Nazanin Minaian

Ph.D. Candidate | Graduate Research Assistant

My research interests include electroactive polymers, flow sensing, energy harvesting, and computer vision.