Triboelectric Nanogenerators for Food Quality Monitoring: Mechanisms and Applications.

Jinghan Zhang, Feijie Wang, Shiqiang Ouyang, Qianru Meng, Zhongli Liu, Yueming Hu, Yan Ma, Shufeng Ma, Liqiang Wang

Abstract readReview

In one paragraph

Review in Small (Weinheim an der Bergstrasse, Germany), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing papers in PubMed

–field-weighted citation impact

1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Jinghan ZhangJiangsu Provincial Key Laboratory of Food Advanced Manufacturing Equipment Technology, School of Mechanical Engineering, Jiangnan University, Wuxi, China.

Feijie WangJiangsu Provincial Key Laboratory of Food Advanced Manufacturing Equipment Technology, School of Mechanical Engineering, Jiangnan University, Wuxi, China.

Shiqiang OuyangJiangsu Provincial Key Laboratory of Food Advanced Manufacturing Equipment Technology, School of Mechanical Engineering, Jiangnan University, Wuxi, China.

Qianru MengJiangsu Provincial Key Laboratory of Food Advanced Manufacturing Equipment Technology, School of Mechanical Engineering, Jiangnan University, Wuxi, China.

Zhongli LiuJiangsu Provincial Key Laboratory of Food Advanced Manufacturing Equipment Technology, School of Mechanical Engineering, Jiangnan University, Wuxi, China.

Yueming HuJiangsu Provincial Key Laboratory of Food Advanced Manufacturing Equipment Technology, School of Mechanical Engineering, Jiangnan University, Wuxi, China.

Yan MaJiangsu Provincial Key Laboratory of Food Advanced Manufacturing Equipment Technology, School of Mechanical Engineering, Jiangnan University, Wuxi, China.

Shufeng MaState Key Laboratory of Food Science and Technology, School of Food Science and Technology, Jiangnan University, Wuxi, China.

Liqiang WangJiangsu Provincial Key Laboratory of Food Advanced Manufacturing Equipment Technology, School of Mechanical Engineering, Jiangnan University, Wuxi, China.ORCID 0009-0009-8064-2276

Funding

Jiangsu Key Laboratory of Advanced Food Manufacturing Equipment and Technology FMZ202304Postgraduate Research & Practice Innovation Program of Jiangsu Province KYCX25_2648

6 · The paper itself

Abstract

Triboelectric nanogenerators (TENGs) are emerging self-powered sensing technologies that harvest low-frequency mechanical energy and convert it into electrical signals, demonstrating strong potential for real-time food quality and safety monitoring. This paper reviews the energy conversion mechanisms of TENG and recent advances in sensing within the food supply chain, with a focus on signal generation and response patterns in complex food systems. By exploiting the synergy between triboelectric generation and electrostatic induction, TENG produces electrical responses to external stimuli across food production, processing, transportation, and storage stages. Four TENG operating modes (contact-separation, lateral sliding, single-electrode, and independent friction layer) are summarized, along with their signal conversion mechanisms and interface control strategies from mechanical, environmental, and biological perspectives. Building on this foundation, recent advances in TENG applications is outlined, including logistics damage monitoring, smart packaging microenvironment sensing, liquid quality analysis, and pathogen detection. To address challenges such as limited selectivity, poor long-term stability, biocompatibility concerns, and complex integration, strategies are proposed, including interface functionalization, multimodal signal fusion, energy optimization, and machine learning-assisted analysis. This review provides theoretical and technical guidance for developing self-powered food safety monitoring systems and promotes TENG advancement toward higher sensitivity, intelligence, and integration.

Indexed as

Electric Power SuppliesFood QualityNanotechnologyenergy harvestingfood quality monitoringself‐powered sensingsignal conversion mechanismssmart packagingtriboelectric nanogenerators

Identifiers

PMID42478534

DOI10.1002/smll.74710

PMCPMC13548908

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.