Maximizing charge transfer efficiency in droplet-driven IDE-TENGs via top electrode engineering

Abstract The droplet-based triboelectric nanogenerator (TENG) has attracted widespread attention in the field of energy harvesting due to its simple structure, low cost, and excellent environmental friendliness. By utilizing triboelectric and contact electrification effects, it efficiently converts the kinetic energy of droplets into electrical energy, offering a new technological pathway for the development of sustainable miniature energy systems. To enhance its electrical output performance, this study introduces a dual-layer electrode structure and investigates the impact of the width, number, and position of the top electrode on the electrical output of the interdigital electrode-based triboelectric nanogenerator (IDE-based TENG). The results show that while the width and number of the top electrodes have minimal effect on the output, the optimal position of the top electrode significantly boosts current generation, particularly when the droplet reaches its maximum spread and makes contact with the top electrode, achieving the highest current output. By optimizing the design of the top electrode, charge separation efficiency and charge transfer pathways are improved, leading to maximum increases in short-circuit current ( I SC ), open-circuit voltage ( V OC ) and charge amount by 4.2, 1.2 and 2.1 times, respectively. This study offers a theoretical foundation and design guidance for optimizing IDE-based TENG electrical output performance and provides valuable insights for enhancing the performance of droplet energy harvesters and other energy collection devices. Additionally, the optimized design presents new solutions for practical applications in fields like smart homes, environmental monitoring, and green energy technologies, with particular promise in rain droplet detection and automatic window control.

Authors

Institutions

Publication Details

Journal
Smart Materials and Structures
Published
2025-07-30
DOI
https://doi.org/10.1088/1361-665x/adf613
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Maximizing charge transfer efficiency in droplet-driven IDE-TENGs via top electrode engineering

Wenjun Wu, Jun Lv, Jiliang Mo, Shun Li et al.
Smart Materials and Structures
Advanced Memory and Neural Computing
article

Maximizing charge transfer efficiency in droplet-driven IDE-TENGs via top electrode engineering

Wenjun Wu, Jun Lv, Jiliang Mo, Shun Li, Yixian Hu, Jing Zhao
article en

Abstract

Abstract The droplet-based triboelectric nanogenerator (TENG) has attracted widespread attention in the field of energy harvesting due to its simple structure, low cost, and excellent environmental friendliness. By utilizing triboelectric and contact electrification effects, it efficiently converts the kinetic energy of droplets into electrical energy, offering a new technological pathway for the development of sustainable miniature energy systems. To enhance its electrical output performance, this study introduces a dual-layer electrode structure and investigates the impact of the width, number, and position of the top electrode on the electrical output of the interdigital electrode-based triboelectric nanogenerator (IDE-based TENG). The results show that while the width and number of the top electrodes have minimal effect on the output, the optimal position of the top electrode significantly boosts current generation, particularly when the droplet reaches its maximum spread and makes contact with the top electrode, achieving the highest current output. By optimizing the design of the top electrode, charge separation efficiency and charge transfer pathways are improved, leading to maximum increases in short-circuit current ( I SC ), open-circuit voltage ( V OC ) and charge amount by 4.2, 1.2 and 2.1 times, respectively. This study offers a theoretical foundation and design guidance for optimizing IDE-based TENG electrical output performance and provides valuable insights for enhancing the performance of droplet energy harvesters and other energy collection devices. Additionally, the optimized design presents new solutions for practical applications in fields like smart homes, environmental monitoring, and green energy technologies, with particular promise in rain droplet detection and automatic window control.

Smart Materials and StructuresVol. 34(8)
Science and Technology Department of Sichuan Province (CN), Southwest Jiaotong University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 83%
Advanced Memory and Neural Computing
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.