Ultra‐Sensitive Nanofiber‐Based Triboelectric Nanogenerator for Energy Harvesting and Self‐Powered Sensing
Abstract
ABSTRACT Triboelectric nanogenerator (TENG) represents a major advancement in capability for self‐powered sensors, with its ability to convert low‐frequency mechanical movements into electricity. These devices serve at present an unmet medical and societal need in the monitoring of human activity and enhancing interactions between humans and machines, the optioned interface for setting up verifiable digital twins. Here, a novel composite nanofibrous TENG (CNF‐TENG) based on borophene@poly(vinylidene fluoride‐co‐hexafluoropropylene) (PVDF‐HFP) is constructed through electrospinning. Comprehensive materials characterization of the exfoliated nanosheets confirms crystalline sheet morphology and validates their incorporation into the fibers. The inclusion of borophene introduces a dual innovation by enhancing both the jet stressing in electrospinning and the quality of doped films. This improvement is attributed to the enhanced effective permittivity through interfacial polarization, which promotes β‐phase formation, electron‐donating capacity, surface charge trapping, and refined fiber morphology, while inducing a transition from a hydrophobic to a superhydrophobic surface state. When paired with nylon 66 nanofibers, the CNF‐TENG exhibits a remarkable sensitivity of 53.8 ± 1.2 V kPa −1 , and a power density of 1.2 W m −2 , representing a 13‐fold enhancement over pristine PVDF‐HFP. An array of 16 ultra‐sensitive CNF‐TENG sensors for possible use in dementia monitoring and sleep disorder mitigation is successfully demonstrated, giving various sleep patterns and physiological data sets.
Article Details
Authors (8)
Sajib Roy
Advanced Technology Institute Department of Computer Science and Electronic Engineering University of Surrey Guildford Surrey UK
Bhaskar Dudem
Advanced Technology Institute Department of Computer Science and Electronic Engineering University of Surrey Guildford Surrey UK
Md Delowar Hussain
Advanced Technology Institute Department of Computer Science and Electronic Engineering University of Surrey Guildford Surrey UK
Vlad Stolojan
Advanced Technology Institute Department of Computer Science and Electronic Engineering University of Surrey Guildford Surrey UK
Seyedeh Sadrieh Emadian
Advanced Technology Institute Department of Computer Science and Electronic Engineering University of Surrey Guildford Surrey UK
Satheesh Krishnamurthy
Advanced Technology Institute Department of Computer Science and Electronic Engineering University of Surrey Guildford Surrey UK
Jae Sung Yun
Advanced Technology Institute Department of Computer Science and Electronic Engineering University of Surrey Guildford Surrey UK
S. Ravi P. Silva