Evidence map›Paper›PMID 41022746›Full record

ArticleNature communications2025

Temperature adaptive self-regenerating ionic thermoelectric cycles for time domain thermal energy harvesting.

Qikai Li, Mao Yu, Chunlin Pang, Xinya Wu, Shuaihua Wang, Huan Li, Yupeng Wang, Weishu Liu, Shien-Ping Feng

Abstract read
In one paragraph

Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

9 authors.

Qikai Li *Department of Systems Engineering, City University of Hong Kong, Kowloon, Hong Kong SAR, China.
Mao Yu *Department of Materials Science and Engineering, Southern University of Science and Technology, Shenzhen, Guangdong, China.
Chunlin PangDepartment of Systems Engineering, City University of Hong Kong, Kowloon, Hong Kong SAR, China.ORCID http://orcid.org/0009-0002-5149-5827
Xinya WuDepartment of Systems Engineering, City University of Hong Kong, Kowloon, Hong Kong SAR, China.ORCID http://orcid.org/0009-0008-1696-9859
Shuaihua WangDepartment of Materials Science and Engineering, Southern University of Science and Technology, Shenzhen, Guangdong, China.
Huan LiDepartment of Materials Science and Engineering, Southern University of Science and Technology, Shenzhen, Guangdong, China.
Yupeng WangDepartment of Materials Science and Engineering, Southern University of Science and Technology, Shenzhen, Guangdong, China.
Weishu LiuDepartment of Materials Science and Engineering, Southern University of Science and Technology, Shenzhen, Guangdong, China. liuws@sustech.edu.cn.ORCID http://orcid.org/0000-0001-8643-822X
Shien-Ping FengDepartment of Systems Engineering, City University of Hong Kong, Kowloon, Hong Kong SAR, China. tony.feng@cityu.edu.hk.ORCID http://orcid.org/0000-0002-3941-1363

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The rising demand for sustainable energy solutions has promoted significant interest in ionic thermoelectric materials, which convert low-grade waste heat into electrical energy through spatial temperature gradients. However, diurnal temperature variations, which offer potential for location-independent time-domain thermal energy, remain largely unexplored. To overcome the challenges of harvesting spatially limited thermal energy, this study presents an ionic thermoelectric cycle (t-ITC) designed for time-domain thermal energy harvesting, incorporating two gels with contrasting temperature coefficients. A temperature-adaptive self-regeneration (TASR) strategy is proposed to set the critical regeneration temperature (T

Identifiers

PMID41022746
PMCPMC12480567

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Registered trials

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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.