Triboelectric Nanogenerators for Condition Monitoring of Machines, Infrastructure and Environment

ABSTRACT With the emergence of triboelectric nanogenerators (TENGs), the monitoring technology based on the triboelectric effect is becoming more and more popular due to the advantages of the wide selection of materials and flexible working modes. Traditional condition monitoring technologies for machines, infrastructure, and environment (MIE) are usually based on piezoelectric effects, thermal effects, and acoustic effects, which need external power to drive. The advancement of TENGs provides more possibilities to enable condition monitoring technologies with self‐driving ability in the society of artificial intelligence of things (AIoT) systems. The flexible structure design and materials selection facilitate the condition monitoring of modern MIE in a more economical and effective way. An increasing number of related works are emerging. In these regards, this paper reviews the state of the art in condition monitoring based on TENGs for the applications of MIE and related interdisciplinary research, such as materials science, information, engineering, and so forth. The introduction of condition monitoring for MIE is illustrated and the basic mechanism of TENG is introduced first. Subsequently, the condition monitoring based on TENG technologies for machines, infrastructure, and environment is elucidated respectively. The most popular and hot research trends are pointed out and the current challenges are also discussed and illustrated, thus giving hints and guidance for future research trends.

Authors

Institutions

Publication Details

Journal
Interdisciplinary materials
Published
2025-08-28
DOI
https://doi.org/10.1002/idm2.70004
Citations
1
Primary Topic
Advanced Sensor and Energy Harvesting Materials
Type
article
Field-Weighted Citation Impact
0.67
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Triboelectric Nanogenerators for Condition Monitoring of Machines, Infrastructure and Environment

Guozhang Dai, Zhiyuan Yang, Junho Choi, Mang Gao et al.
1 citations
Interdisciplinary materials
Advanced Sensor and Energy Harvesting Materials
0.67
article

Triboelectric Nanogenerators for Condition Monitoring of Machines, Infrastructure and Environment

Guozhang Dai, Zhiyuan Yang, Junho Choi, Mang Gao, Yafeng Pang, Junliang Yang, Chengkuo Lee
article en
1 citations

Abstract

ABSTRACT With the emergence of triboelectric nanogenerators (TENGs), the monitoring technology based on the triboelectric effect is becoming more and more popular due to the advantages of the wide selection of materials and flexible working modes. Traditional condition monitoring technologies for machines, infrastructure, and environment (MIE) are usually based on piezoelectric effects, thermal effects, and acoustic effects, which need external power to drive. The advancement of TENGs provides more possibilities to enable condition monitoring technologies with self‐driving ability in the society of artificial intelligence of things (AIoT) systems. The flexible structure design and materials selection facilitate the condition monitoring of modern MIE in a more economical and effective way. An increasing number of related works are emerging. In these regards, this paper reviews the state of the art in condition monitoring based on TENGs for the applications of MIE and related interdisciplinary research, such as materials science, information, engineering, and so forth. The introduction of condition monitoring for MIE is illustrated and the basic mechanism of TENG is introduced first. Subsequently, the condition monitoring based on TENG technologies for machines, infrastructure, and environment is elucidated respectively. The most popular and hot research trends are pointed out and the current challenges are also discussed and illustrated, thus giving hints and guidance for future research trends.

Interdisciplinary materialsVol. 4(5)
Tongji University (CN), Central South University (CN), National University of Singapore (SG), Hunan University (CN), Tokyo City University (JP), The University of Tokyo (JP)
Openalex Percentile: Top 27%
Advanced Sensor and Energy Harvesting Materials
0.67
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.