journal article·2024-10

Synergistic energy harvesting and humidity sensing with single electrode triboelectric nanogenerator

Swayam Aryam Behera, Sugato Hajra, Swati Panda, Alok Kumar Sahu, Perumal Alagarsamy, Yogendra Kumar Mishra, Hoe Joon Kim, P. Ganga Raju Achary

Ceramics International· Volume 50· Issue 19
Publisher page

Abstract

Humidity sensors using triboelectric nanogenerators (TENGs) technology can provide continuous operation without the need for additional batteries. These sensors provide sustainable and self-powered humidity monitoring solutions, that can be utilized in various agriculture platforms and food processing industries. In this work, a sol-gel method is utilized to process the bismuth ferrite (abbreviated as BFO) materials and a simple mould pressing method to obtain freestanding Ethylene-vinyl acetate (abbreviated EVA)-BFO composites. These composites were characterized to shed light upon structural and microstructural properties. The single electrode mode operating TENG was fabricated having 2 cm × 2 cm active area at various wt.% of BFO onto EVA-based composites to compare the electrical response. The 5 wt.% BFO-EVA-based composites/FEP-based TENG generates a voltage and current of 45 V and 800 nA. Further, the TENG device was tested for long-term stability for 400 s, and charging of various capacitors having capacitance values such as 0.1 μF, 1 μF, 4.7 μF, and 10 μF along with 3 times charging/discharging cycles of 0.1 μF capacitor have been demonstrated. The humidity sensing mechanism elucidated which follows the conduction process based on the Grotthuss proton hopping mechanism. The TENG demonstrates a sensitivity of 0.53 V/RH% over the relative humidity range from 25 % to 85 %. The powering of the wristwatch confirms that fabricated TENG can be a reliable power source for future low-power electronics.
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Research context

OpenAlex topics: Advanced Sensor and Energy Harvesting Materials · Conducting polymers and applications · Gas Sensing Nanomaterials and Sensors

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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