Evidence map›Paper›PMID 41866787›Full record

ArticleAdvanced materials (Deerfield Beach, Fla.)2026

Chromatic-Invariant Photothermal Fabrics Enabled by Narrow-Bandgap Organic Semiconductors for Wearable Solar Energy Harvesting.

Jingshuai Zhu, Jianming Chen, Shiyu Liao, Jiaxin Zheng, Shiguo Chen, Yuanfeng Wang, Xungai Wang

Abstract read
In one paragraph

Article in Advanced materials (Deerfield Beach, Fla.), 2026. 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

7 authors.

Jingshuai ZhuCollege of Materials Science and Engineering, Shenzhen University, Shenzhen, China.
Jianming ChenJoint Research Centre for Fiber Innovations and Renewable Materials (JRC-FIRM), School of Fashion and Textiles, The Hong Kong Polytechnic University, Kowloon, Hong Kong, China.ORCID https://orcid.org/0000-0002-8505-7107
Shiyu LiaoJoint Research Centre for Fiber Innovations and Renewable Materials (JRC-FIRM), School of Fashion and Textiles, The Hong Kong Polytechnic University, Kowloon, Hong Kong, China.
Jiaxin ZhengSchool of Advanced Materials, Peking University, Shenzhen Graduate School, Shenzhen, China.
Shiguo ChenCollege of Materials Science and Engineering, Shenzhen University, Shenzhen, China.
Yuanfeng WangCollege of Materials Science and Engineering, Shenzhen University, Shenzhen, China.
Xungai WangZhejiang Sci-Tech University, College of Textile Science and Engineering, Hangzhou, China.

Funding

Basic and Applied Basic Research Foundation of Guangdong Province 2025A1515011283Basic and Applied Basic Research Foundation of Guangdong Province 2026A1515010735Guangdong Special Support Plan 2024TQ08A690Hong Kong Polytechnic University Postdoc Matching Fund Scheme P0049004National Natural Science Foundation of China 52473060National Natural Science Foundation of China 52503274RI-IWEAR Project P0046096Shenzhen Science and Technology Program JCYJ20240813142829039
6 · The paper itself

Abstract

The increasing popularity of outdoor activewear has placed higher demands on its thermal comfort, multi-functionality, and esthetics. Existing photothermal fabrics for cold weathers are based on visible light absorption, which limits color design options. Herein, a chromatic-invariant photothermal material is developed and integrated onto fabrics to prepare novel photothermal clothing, achieving 4°C-8°C temperature increase within only 5 min under 1000 W m

Indexed as

chromatic‐invariantfabric thermal managementnear‐infrared absorptionorganic semiconductorphotothermal molecules

Identifiers

PMID41866787
PMCPMC13103635

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.