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  1. null (Ed.)
    Abstract In this paper, we examine the development of tailored 3D-structured (engineered) polymer-metal interfaces to create enhanced ionic polymer-metal composite (eIPMC) sensors towards soft, self-powered, high sensitivity strain sensor applications. First, a physics-based chemoelectromechanical model is developed to predict the sensor behavior of eIPMCs by incorporating structure microfeature effects in the mechanical response of the material. The model incorporates electrode surface properties, such as microscale feature thickness, size and spacing, to help define the mechanical response and transport characteristics of the polymer-electrode interface. Second, two novel approaches are described to create functional samples of eIPMC sensors using fused deposition manufacturing and inkjet printing technologies. Sample eIPMC sensors are fabricated for experimental characterization. Finally, experimental results are provided to show superior performance in the sensing capabilities compared to traditional sensors fabricated from sheet-form material. The results also validate important predictive aspects of the proposed minimal model. 
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  2. Engineered Ionic Polymer Metal Composites (eIPMCs) represent the next generation of IPMCs, soft electro-chemo-mechanically coupled smart materials used as actuators and sensors. Recent studies indicate that eIPMC sensors, featuring unique microstructures at the interface between the ionic polymer membrane and the electrode, exhibit enhanced electrochemical behavior and sensitivity under compression, as compared to traditional IPMCs. However, a complete and experimentally-validated model of how eIPMCs behave under dynamic compression loads is currently missing. In this paper, we develop an analytical model for eIPMC sensors, elucidating the role of the engineered interface, modeled as a separate material layer with unique mechanical and electrochemical properties. Theoretical predictions focus on the mechanical-to-electrochemical transduction response under dynamic compressive loads. Experimental verification is conducted on conventional IPMC and novel eIPMC samples fabricated using the polymer abrading technique. Electrochemical impedance spectroscopy is performed to study the effect of the engineered interface on the electrochemical properties. Open-circuit (OC) voltage and short-circuit (SC) current are measured under external compressive loads in different loading scenarios to demonstrate sensing performance. Results show good qualitative agreement between experimental trends and model predictions. Experiments over the frequency range 1-18 Hz demonstrate an increase of 220%-290% in open-circuit voltage and 17%-166% in SC current sensitivity for eIPMCs over IPMCs. 
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    Free, publicly-accessible full text available January 30, 2026
  3. The soft and compliant nature of ionic polymer-metal composite (IPMC) sensors has recently been investigated for various applications in soft robotic and mechatronic devices. Recent results of physics-based chemoelectromechanical modeling suggest that IPMC asymmetric surface roughening may enhance the sensitivity under compression. This paper presents initial experimental results on IPMC compression sensors fabricated with varying degrees of asymmetric surface roughness. The roughness is created through a simple mechanical sanding process on the base polymer material, referred to as "polymer abrading technique'", followed by traditional electroless plating to create electrodes. Sample sensors are characterized by measuring the voltage response under different compressive loads. The results show consistently increased sensor sensitivity of the asymmetrically roughened IPMCs versus a control sample. Sensitivity increases non-monotonically with rougher electrode surfaces, where maximum sensitivity of about 0.0433 mV/kPa is achieved with sensor electrodes with 53-74~micrometer abrasions. More variability is also observed through augmented electrode roughness, suggesting greater flexibility for IPMC sensor design. These results align with predictions from the existing physics-based chemoelectromechanical model. 
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