Ionic polymer-metal composite (IPMC) is a class of electroactive polymers with built-in actuation and sensing capabilities. In this dissertation, the modeling and several bio-inspired sensing applications of IPMC are investigated computationally and experimentally. First, physics-based modeling is studied for a tubular IPMC sensor under pure torsional stimulus. With inspiration from the fish lateral line system, IPMC is then explored for several flow-sensing applications, where modeling of fluid-structure interactions, sensor design, and experimental validation are conducted. Specifically, the sensitivities of IPMC-based artificial superficial and canal neuromasts are examined in terms of their dimensions, shapes, and stiffness properties. A canal lateral line-inspired pressure sensor is further proposed and developed. Another novel flow velocity sensor is proposed, which exploits self-generated von Kármán vortices to produce vibrations that are correlated with the flow speed. Finally, inspired by the vestibular system, an angular acceleration sensor is proposed by integrating IPMC sensors with a fluid-filled circular channel. These contributions are further elaborated below. Firstly, the Poisson-Nernst-Planck (PNP) model is used to describe the fundamental physics within the tubular IPMC under torsional excitation, where it is hypothesized that the anion concentration is coupled to the sum of shear strains induced by the torsional stimulus. Finite element simulation is conducted to solve for the torsional sensing response, where some of the key parameters are identified based on experimental measurements using an artificial neural network. Additional experimental results suggest that the proposed model is able to capture the torsional sensing dynamics for different amplitudes and rates of the torsional stimulus.Secondly, Inspired by the fish lateral line system, the sensitivity of IPMC-based artificial superficial and canal neuromasts are examined in terms of their dimensions, shapes, and stiffness properties. The PNP model is again used to describe the fundamental physics within the IPMC, where the bending stimulus due to the cupula displacement is coupled to the PNP model through the cation convective flux term. Comparison of the numerically computed cupula displacement with an analytical approximation is conducted.Thirdly, a novel pressure difference sensor inspired by the canal lateral line is proposed. The sensor output is experimentally characterized as the fish-like body is rotated with respect to a dipole source, which confirms that the sensor is capable of capturing the pressure between the two pores. Finite element modeling that capture fluid-structure interactions and IPMC physics are conducted to shed light on the sensor behavior. Finally, the utility of the sensor in underwater robotics is illustrated via orientation of the fish-like body towards the dipole source using feedback from the proposed sensor.Fourthly, a novel IPMC flow sensor is proposed that exploits self-generated von Kármán vortices to produce vibrations, the frequency and amplitude of which are correlated with the stream flow. Experiments are conducted in a flow channel to measure the IPMC output and the free-end displacement of the sheath under different flow speeds. The results indicate that the proposed sensor structure can produce significant oscillatory signals for effectively decoding the flow speed. Finally, inspired by the vestibular system, an angular acceleration sensor by exploiting IPMC sensor is proposed. The sensor has one 3D-printed circular canal filled with a viscous fluid. Experimental results involving different angular acceleration stimuli show that the proposed sensor is able to capture the angular acceleration for different rates of rotational stimulus. Finite-element simulation is conducted to provide insight into the experimental~ observations.
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