Ferroelectric Gradient Microfoams as High-Performance Self-Powered Flexible Pressure Sensors

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Flexible pressure sensors hold great application potential in intelligence robots, biomimetic prosthetics and health monitoring. To mimic human skin’s perception of pressure, it is essential that a flexible pressure sensor must be applicable to a broad pressure range aside of its high sensitivity. However, while various transduction mechanisms covering a broad pressure range have been adopted in pressure detection, an unreconciled tradeoff exists between high sensitivity and a broad working range of pressures in the current flexible pressure sensors. This fundamental tradeoff limits the practical applications of the flexible pressure sensors in various healthcare and wearable electronics. This project proposes fundamental research for the development of a new class of flexible ferroelectric sensors that will resolve the tradeoffs. Findings from this project will pave the way toward flexible tactile sensors with high sensitivity over a broad detection range, multi-modal detection capability, and self-powered characteristic, together with remarkable mechanical stability and durability. The educational goal is to foster the multidisciplinary training environment for undergraduate and graduate students and build next-generation workforce who will be well prepared to undertake new scientific and engineering challenges. This project will promote the minority involvement and participation in science and engineering research at Penn State.Ferroelectric microfoams are mechanically flexible and highly mechanosensitive. However, the pressure sensors based on the foams with uniform porosity lose detection sensitivity beyond the critical load at which the microskeletons in the foam buckle. To overcome this limitation, this research team aims to develop high-performance gradient microfoam sensors. With gradient porosity, the detrimental buckling mode can be shielded by simultaneously activating other deformation modes in the ferroelectric foam, thereby enabling both high sensitivity and broad detection range. An integrated approach, involving multiphysics modeling, materials synthesis, and comprehensive characterization of mechanical, piezoelectric, and sensing properties, will be adopted to fulfill the goals. The multiphysics modeling will identify a set of key parameters that govern mechanical flexibility, detection sensitivity and operation range, which will guide the design and optimization of the gradient foam sensors. The proposed synthesis approach involves the fabrication of the microfoam with gradient porosity followed by grafting of molecular ferroelectric crystals onto the foam. The performance of the sensors will be characterized and demonstrated at different loading regimes and loading modes. This in-depth understanding and characterization will lead to the processing of the gradient ferroelectric microfoam sensors with unprecedented precision and performance. Knowledge generated within this project will also foster transformative progress in broadening applications of molecular ferroelectrics, a newly developed class of electroactive materials, in sensors and other electronic devices.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.