Evidence map›Paper›PMID 42189057›Full record

ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2026

Trap Depth Modulation and Antenna Effect of Organic Ligands for Enhancing Rare-Earth Long Persistent Luminescence.

Ting Tan, Nian Li, Bangmin Liu, Hao Wang, Xia Huang, Yuanjin Chen, Zhonghao Wang, Chaolong Yang

Abstract read
In one paragraph

Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 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

8 authors.

Ting TanSchool of Materials Science and Engineering, Chongqing University of Technology, Chongqing, China.
Nian LiSchool of Materials Science and Engineering, Chongqing University of Technology, Chongqing, China.
Bangmin LiuSchool of Materials Science and Engineering, Chongqing University of Technology, Chongqing, China.
Hao WangSchool of Materials Science and Engineering, Chongqing University of Technology, Chongqing, China.
Xia HuangSchool of Materials Science and Engineering, Chongqing University of Technology, Chongqing, China.
Yuanjin ChenSchool of Materials Science and Engineering, Chongqing University of Technology, Chongqing, China.
Zhonghao WangSchool of Materials Science and Engineering, Chongqing University of Technology, Chongqing, China.
Chaolong YangSchool of Materials Science and Engineering, Chongqing University of Technology, Chongqing, China.ORCID https://orcid.org/0000-0003-3535-7918

Funding

Chongqing Innovation Support Program for Returned Overseas Students cx2020052National Natural Science Foundation of China 22275025National Natural Science Foundation of China 22575032Natural Science Foundation of Chongqing CSTB2024NSCQ-JQX0015
6 · The paper itself

Abstract

Rare-earth long persistent luminescence (LPL) materials with unique light-storage properties show great promise for diverse applications. However, modifying the optical properties of such materials is extremely challenging due to their inherent characteristics. Here, we propose a coordination modification strategy that not only deepens the trap depth but also enhances the light-capturing capability of rare-earth LPL materials by introducing organic ligands as an antenna. Unlike previous single-case demonstrations, this strategy is systematically validated across multiple LPL hosts with different afterglow colors, including green (SrAl

Indexed as

energy transferlong persistent luminescence materialsorganic–inorganic hybridizationsurface coordinationtrap depth modulation

Identifiers

PMID42189057
PMCPMC13335827

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.