Evidence map›Paper›PMID 41011907›Full record

ReviewMicromachines2025

Recent Progress of Powering IoT Based on Thermoelectric Technology.

Jinhong Dai, Haitao Deng, Jingwen Huang, Xiaosheng Zhang

Abstract readReview
In one paragraph

Review in Micromachines, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

4 authors.

Jinhong DaiSchool of Integrated Circuit Science and Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China.
Haitao DengInstitute of Industrial Science, The University of Tokyo, Tokyo 153-8505, Japan.
Jingwen HuangSchool of Integrated Circuit Science and Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China.ORCID 0009-0009-0498-3570
Xiaosheng ZhangSchool of Integrated Circuit Science and Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China.ORCID 0000-0001-9719-0573

Funding

Fundamental Research Funds for the Central Universities No. ZYGX2019Z002Key R&D Program of Sichuan Province No. 2022JDTD0020, No. 2020ZHCG0038National Key Research and Development Program of China No. 2022YFB3206100National Natural Science Foundation of China No. 62074029, No. 61905035, No. 61971108, No. 62004029, No. 51905554Natural Science Foundation of Sichuan Province No. 2022NSFSC1941Sichuan Science and Technology Program No. 2020JDJQ0036, No. 2019YJ0198, No. 2020YJ0015
6 · The paper itself

Abstract

With the rapid advancement of electronic devices, Internet of Things (IoT) technology has become increasingly integrated into everyday life. However, its broader development has been restricted by challenges related to long-term maintenance and the frequent need for power source replacements. Among the available power supply solutions, thermoelectric power generation has garnered significant interest due to its high reliability. Nevertheless, the widespread application of thermoelectric generators (TEGs) in IoT remains limited due to their relatively low conversion efficiency and structural fragility. This review systematically summarizes recent strategies aimed at enhancing the output performance and durability of TEGs through improvements in manufacturing processes and performance optimization techniques. It highlights several fabrication methods capable of endowing devices with superior flexibility and reliability, including screen printing, chemical vapor deposition (CVD), and electrospray deposition. Additionally, we discuss two key approaches for improving power generation performance: advanced material selection and multi-mechanism hybridization. Finally, the article explores the applications of TEGs in thermal energy harvesting from wearable devices, ambient environments, and aerospace fields, demonstrating their substantial potential to provide sustainable energy for IoT devices.

Indexed as

IoTMEMSseeback effectthermoelectric generator

Identifiers

PMID41011907
PMCPMC12471465

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.