Innovative Integration of Triboelectric Nanogenerators into Signature Stamps for Energy Harvesting, Self-Powered Electronic Devices, and Smart Applications

Author:

Bochu Lakshakoti1ORCID,Potu Supraja2ORCID,Navaneeth Madathil2ORCID,Khanapuram Uday Kumar2ORCID,Rajaboina Rakesh Kumar2ORCID,Kodali Prakash1ORCID

Affiliation:

1. Flexible Electronics Lab, Department of Electronics and Communication Engineering, National Institute of Technology-Warangal, Warangal 506004, India

2. Energy Materials and Devices Lab, Department of Physics, National Institute of Technology-Warangal, Warangal 506004, India

Abstract

In this manuscript, we present a novel approach for integrating Triboelectric Nanogenerators (TENGs) into signature stamps, termed Stamp TENG (S-TENG). We have modified a commercially available stamp holder to integrate triboelectric layers for multiple applications like effective energy harvesting, sensing, and embedded electronics for data prediction. S-TENG has been further explored in remote monitoring systems for elderly individuals and for gathering real-time statistics regarding persons or events at specific locations. The S-TENG is fabricated using FEP and Al as functional layers. It demonstrates an output voltage of 310 V, a current of 165 μA, and a power density of 14.8 W/m2. The simplicity of the S-TENG’s design is noteworthy. Its ability to generate energy through simple, repetitive stamping actions, which anyone can perform without specialized training, stands out as a key feature. The device is also designed for ease of use, being handheld and user-friendly. Its flexible and adaptable structure ensures that individuals with varying physical capabilities can comfortably operate it. An impressive capability of the TENG is its ability to illuminate 320 LEDs with each stamp press momentarily. Furthermore, using energy management circuits, the S-TENG can power small electronic gadgets such as digital watches and thermometers for a few seconds. In addition, when integrated with electronics, the S-TENG shows great potential in data prediction for various practical applications.

Funder

SERB, DST, Govt. of India

CRIF, National Institute of Technology, Warangal

Publisher

MDPI AG

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