Layered Double Hydroxide Based Self-Powered Triboelectric Sensor for Biomechanical Motions

Abstract

Sensing biomechanical motions is advantageous for biomedical health monitoring. Here, we propose a Layered Double Hydroxide (LDH)-based triboelectric sensor (TES) for monitoring biomechanical motions. The triboelectric sensor operates through initial triboelectrification between the friction pair of LDH and aluminum, followed by electrostatic induction in an external electric circuit due to the contact-separation of the two friction layers. To realize the triboelectric sensor, LDH is synthesized using an in-situ hydrothermal method, resulting in a nanostructured LDH with a high surface-to-volume ratio. The synthesized LDH was characterized using X-ray Diffraction (XRD), Scanning Electron Microscopy (SEM), and Fourier Transform Infrared Spectroscopy (FTIR) to confirm its crystallinity, surface morphology, and functional groups. The electrical performance of the TES was measured using a digital oscilloscope. The triboelectric sensor is self-powered, generating a peak-to-peak output voltage (VO) of 10.6 V across a load resistance of 1MΩ and a short-circuit current (ISC) of 22 µA during hand tapping. The TES follows a contact-separation mode of operation, where the mechanical motion induces contact between the frictional layers and separation allows the generated charge to be transferred through an external circuit. Since the triboelectric pulses (high voltages and very low currents) are not suited for conventional electronics, a two-stage amplifier-based interface circuit was designed to interface the sensor with a microcontroller. As a proof of concept, the self-powered TES was interfaced with an Arduino Mega 2560 microcontroller through the interface circuit. The sensorial system monitored the contact-separation induced by hand tapping, and the counting information was displayed on a digital LCD. The self-powered LDH-based triboelectric sensor, along with the two-stage amplifierbased interface circuit, provides a platform for monitoring various biomechanical motions, including walking, with potential applications in biomedical health monitoring.