Evidence map›Paper›PMID 37110900›Full record

ReviewNanomaterials (Basel, Switzerland)2023

Smart Triboelectric Nanogenerators Based on Stimulus-Response Materials: From Intelligent Applications to Self-Powered Systems.

Xueqing Wang, Qinghao Qin, Yin Lu, Yajun Mi, Jiajing Meng, Zequan Zhao, Han Wu, Xia Cao, Ning Wang

Abstract readReview
In one paragraph

Review in Nanomaterials (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
  4. Article
  5. Review
  6. Nanoelectronics: Materials, Devices and Applications.Nanomaterials (Basel, Switzerland) · 2024
    Article
  7. Review
  8. Ferroelectric Material in Triboelectric Nanogenerator.Materials (Basel, Switzerland) · 2024
    Review
  9. Review
  10. Review
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.

Xueqing WangCenter for Green Innovation, School of Mathematics and Physics, University of Science and Technology Beijing, Beijing 100083, China.
Qinghao QinCenter for Green Innovation, School of Mathematics and Physics, University of Science and Technology Beijing, Beijing 100083, China.
Yin LuCenter for Green Innovation, School of Mathematics and Physics, University of Science and Technology Beijing, Beijing 100083, China.
Yajun MiCenter for Green Innovation, School of Mathematics and Physics, University of Science and Technology Beijing, Beijing 100083, China.
Jiajing MengCenter for Green Innovation, School of Mathematics and Physics, University of Science and Technology Beijing, Beijing 100083, China.
Zequan ZhaoCenter for Green Innovation, School of Mathematics and Physics, University of Science and Technology Beijing, Beijing 100083, China.
Han WuCenter for Green Innovation, School of Mathematics and Physics, University of Science and Technology Beijing, Beijing 100083, China.
Xia CaoBeijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing 100083, China.
Ning WangCenter for Green Innovation, School of Mathematics and Physics, University of Science and Technology Beijing, Beijing 100083, China.ORCID 0000-0001-9772-7270

Funding

National Natural Science Foundation of China NSFC No. 51873020the University Basic Scientific Research Business Fee FRF-MP-20-38
6 · The paper itself

Abstract

Smart responsive materials can react to external stimuli via a reversible mechanism and can be directly combined with a triboelectric nanogenerator (TENG) to deliver various intelligent applications, such as sensors, actuators, robots, artificial muscles, and controlled drug delivery. Not only that, mechanical energy in the reversible response of innovative materials can be scavenged and transformed into decipherable electrical signals. Because of the high dependence of amplitude and frequency on environmental stimuli, self-powered intelligent systems may be thus built and present an immediate response to stress, electrical current, temperature, magnetic field, or even chemical compounds. This review summarizes the recent research progress of smart TENGs based on stimulus-response materials. After briefly introducing the working principle of TENG, we discuss the implementation of smart materials in TENGs with a classification of several sub-groups: shape-memory alloy, piezoelectric materials, magneto-rheological, and electro-rheological materials. While we focus on their design strategy and function collaboration, applications in robots, clinical treatment, and sensors are described in detail to show the versatility and promising future of smart TNEGs. In the end, challenges and outlooks in this field are highlighted, with an aim to promote the integration of varied advanced intelligent technologies into compact, diverse functional packages in a self-powered mode.

Indexed as

energy conversionself-powered systemsmart materialsstimuli-responsivetriboelectric nanogenerator

Identifiers

PMID37110900
PMCPMC10141953

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.