Evidence map›Paper›PMID 42356969›Full record

ArticlePolymers2026

Carbon-Core/Molecular-State-Regulated Red/Blue Dual-Emission Carbon Quantum Dots Covalently Anchored on Polyvinyl Alcohol for Multifunctional Agricultural Films in Greenhouse Potato Production.

Zhimin Ye, Jiwei Liu, Maolin Wang, Kun Huang, Li Zhang, Yuanyuan Jiang, Ying Wang, Yunsong Zhang, Li Lin

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Polymers, 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

9 authors.

Zhimin YeCollege of Science, Sichuan Agricultural University, Ya'an 625014, China.
Jiwei LiuCollege of Science, Sichuan Agricultural University, Ya'an 625014, China.
Maolin WangCollege of Science, Sichuan Agricultural University, Ya'an 625014, China.
Kun HuangNational Engineering Research Center of Clean Technology in Leather Industry, Sichuan University, Chengdu 610065, China.
Li ZhangCollege of Science, Sichuan Agricultural University, Ya'an 625014, China.
Yuanyuan JiangCollege of Science, Sichuan Agricultural University, Ya'an 625014, China.
Ying WangCollege of Water Conservancy and Hydropower Engineering, Sichuan Agricultural University, Ya'an 625014, China.
Yunsong ZhangCollege of Science, Sichuan Agricultural University, Ya'an 625014, China.ORCID 0000-0002-5154-7642
Li LinCollege of Science, Sichuan Agricultural University, Ya'an 625014, China.

Funding

National University of Modern Languages SCCXTD-2020-19Natural Science Foundation for Youth Project of Sichuan Province No.2023NSFSC1121Sichuan Science and Technology Plan Project of International Cooperation, P. R. China No. 2020YFH0209Start-up Grants of Sichuan Agricultural University for Talent, P.R. China No. 03120313
6 · The paper itself

Abstract

For agricultural films, spectral matching, UV protection, and environmental durability are essential for efficient crop production. A self-cleaning silane-crosslinked red/blue dual-emission carbon dot/polyvinyl alcohol composite film (KH/RB-CQDs/PVA) was fabricated via a covalent anchoring strategy. RB-CQDs were synthesized by a two-step hydrothermal method using o-phenylenediamine: initial blue-emitting carbon cores formed, then phosphoric acid-assisted secondary treatment covalently bridged residual precursor-derived red fluorophores onto cores through pyrophosphate bonds, as evidenced by TEM, XPS,

Indexed as

covalent anchoringdual-emission carbon quantum dotsmultifunctional agricultural filmsphotosynthesis enhancementself-cleaning

Identifiers

PMID42356969
PMCPMC13307153

What OpenQuestion holds

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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.