Evidence map›Paper›PMID 42627924›Full record

ArticleScience advances2026

Unifying energy and information harvesting for high-rate self-powered sensing.

Hongyong Yu, Yawei Wang, Hengxu Du, Ziyue Xi, Yizhou Li, Yaozi Zheng, Jixiang Chen, Quanke Su, Guobiao Hu, Taili Du and 1 more

Abstract read
In one paragraph

Article in Science advances, 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

11 authors.

Hongyong YuMarine Engineering College, Dalian Maritime University, Dalian, 116026, China.ORCID 0000-0002-7195-7139
Yawei WangThrust of the Internet of Things, The Hong Kong University of Science and Technology (Guangzhou), Guangzhou 511400, China.ORCID 0000-0002-7041-030X
Hengxu DuMarine Engineering College, Dalian Maritime University, Dalian, 116026, China.
Ziyue XiMarine Engineering College, Dalian Maritime University, Dalian, 116026, China.
Yizhou LiThrust of the Internet of Things, The Hong Kong University of Science and Technology (Guangzhou), Guangzhou 511400, China.ORCID 0009-0009-3977-9115
Yaozi ZhengThrust of the Internet of Things, The Hong Kong University of Science and Technology (Guangzhou), Guangzhou 511400, China.
Jixiang ChenCollege of Marine Electrical Engineering, Dalian Maritime University, Dalian 116026, China.
Quanke SuThrust of Intelligent Transportation, The Hong Kong University of Science and Technology (Guangzhou), Guangzhou 511400, China.
Guobiao HuThrust of the Internet of Things, The Hong Kong University of Science and Technology (Guangzhou), Guangzhou 511400, China.ORCID 0000-0002-1288-7564
Taili DuMarine Engineering College, Dalian Maritime University, Dalian, 116026, China.ORCID 0000-0002-4218-0084
Minyi XuMarine Engineering College, Dalian Maritime University, Dalian, 116026, China.ORCID 0000-0002-3772-8340

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

High-fidelity sensing remains highly challenging in self-powered systems, as the limited power of energy harvesters constrains data acquisition and transmission. In this work, we present a wireless, intelligent, self-powered environmental node (WISE-Node) that simultaneously harvests energy and collects sensing information from ambient vibrations. Its multi-contact triboelectric vibration energy harvester (MC-TVEH) achieves an ultra-wide bandwidth of 10-300 Hz, delivering peak and RMS power densities of 13.42 kW/m

Identifiers

PMID42627924
PMCPMC13496209

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.