Affiliation:
1. Centre for Print Research (CFPR) The University of the West of England Bristol UK
2. Nottingham School of Art and Design (NSAD), Nottingham Trent University Nottingham Nottinghamshire UK
3. Faculty of Environment, Science and Economy, Department of Engineering University of Exeter Exeter UK
Abstract
AbstractThe human body continuously generates ambient mechanical energy through diverse movements, such as walking and cycling, which can be harvested via various renewable energy harvesting mechanisms. Triboelectric Nanogenerator (TENG) stands out as one of the most promising emerging renewable energy harvesting technologies for wearable applications due to its ability to harness various forms of mechanical energies, including vibrations, pressure, and rotations, and convert them into electricity. However, their application is limited due to challenges in achieving performance, flexibility, low power consumption, and durability. Here, we present a robust and high‐performance self‐powered system integrated into cotton fabric by incorporating a textile‐based triboelectric nanogenerator (T‐TENG) based on 2D materials, addressing both energy harvesting and storage. The proposed system extracts significant ambient mechanical energy from human body movements and stores it in a textile supercapacitor (T‐Supercap). The integration of 2D materials (graphene and MoS2) in fabrication enhances the performance of T‐TENG significantly, as demonstrated by a record‐high open‐circuit voltage of 1068 V and a power density of 14.64 W/m2 under a force of 22 N. The developed T‐TENG in this study effectively powers 200+ LEDs and a miniature watch while also charging the T‐Supercap with 4‐5 N force for efficient miniature electronics operation. Integrated as a step counter within a sock, the T‐TENG serves as a self‐powered step counter sensor. This work establishes a promising platform for wearable electronic textiles, contributing significantly to the advancement of sustainable and autonomous self‐powered wearable technologies.image
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