Evidence map›Paper›PMID 40532008›Full record

ArticleScience advances2025

Roadbed tribological energy harvester.

Pengfei Ji, Jing Wen, Xiaobo Gao, Hao Li, Huisheng Cai, Kai Lv, Zhong Lin Wang, Baodong Chen

Abstract read
In one paragraph

Article in Science advances, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

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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

8 authors.

Pengfei JiBeijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing 101400, P. R. China.ORCID 0009-0001-5783-5493
Jing WenShougang Group Company Limited Research Institute of Technology, Beijing 100043, P. R. China.ORCID 0000-0001-6483-298X
Xiaobo GaoBeijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing 101400, P. R. China.
Hao LiBeijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing 101400, P. R. China.
Huisheng CaiSchool of Materials Science and Engineering, Inner Mongolia University of Technology, Hohhot 010051, P. R. China.ORCID 0000-0002-9361-0750
Kai LvSchool of Materials Science and Engineering, Inner Mongolia University of Technology, Hohhot 010051, P. R. China.ORCID 0009-0001-0481-3899
Zhong Lin WangBeijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing 101400, P. R. China.ORCID 0000-0002-5530-0380
Baodong ChenBeijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences, Beijing 101400, P. R. China.ORCID 0000-0002-4647-0089

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Roadbed tribological energy (RTE) is a promising recoverable resource with an estimated potential on the terawatt scale, generated annually by the interaction between tires and road surfaces. However, RTE remains underutilized due to the lack of effective energy harvesting technologies that can address its high-entropy characteristics. Here, we present a revolutionary harvester formed by a freestanding layer triboelectric nanogenerator array embedded in the road. The harvester effectively converts low-grade vibratory RTE into electrical energy. It demonstrates the potential to achieve a peak power of 16.409 milliwatts and an average power of 2.2 milliwatts from a compact 78-square centimeter road area under a single tire impact, with a triboelectric conversion efficiency of 11.723%. In addition, we developed a self-powered intelligent and connected transportation system (SP-ICTS), integrating a five-in-one harvesting array. Experimental findings show that the system can meet the SP-ICTS's electricity requirements along a 1-kilometer segment with a 50-meter harvester.

Identifiers

PMID40532008
PMCPMC13112539

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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.