Evidence map›Paper›PMID 37396231›Full record

ArticleACS omega2023

Exploring the Core Parameters of CNC-Based Chiral Nematic Structures for Enhancing the Dissymmetry Factor of Right-Handed Circularly Polarized Luminescence.

Guodan Wei, Mengfan Lu, Kai Feng, Sijia Ma, Yuqian Jiang, Zhaoxia Jin

Abstract read
In one paragraph

Article in ACS omega, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

6 authors.

Guodan WeiKey Laboratory of Advanced Light Conversion Materials and Biophotonics, Department of Chemistry, Renmin University of China, 100872 Beijing, People's Republic of China.
Mengfan LuKey Laboratory of Advanced Light Conversion Materials and Biophotonics, Department of Chemistry, Renmin University of China, 100872 Beijing, People's Republic of China.
Kai FengKey Laboratory of Advanced Light Conversion Materials and Biophotonics, Department of Chemistry, Renmin University of China, 100872 Beijing, People's Republic of China.
Sijia MaBeijing National Laboratory for Molecular Science (BNLMS), Key Laboratory of Colloid, Interface and Chemical Thermodynamics, Institute of Chemistry, Chinese Academy of Sciences, ZhongGuanCun North First Street 2, 100190 Beijing, People's Republic of China.
Yuqian JiangKey Laboratory of Nanosystem and Hierarchical Fabrication, National Center for Nano-Science and Technology, 100190 Beijing, People's Republic of China.ORCID https://orcid.org/0000-0002-7013-4704
Zhaoxia JinKey Laboratory of Advanced Light Conversion Materials and Biophotonics, Department of Chemistry, Renmin University of China, 100872 Beijing, People's Republic of China.ORCID https://orcid.org/0000-0002-6108-0636

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The chiral nematic nanostructure formed from cellulose nanocrystal (CNC) self-assembly has shown great potential as a matrix for generating circularly polarized luminescent (CPL) light with a high dissymmetry factor. Exploring the relationship between the device composition and structure and the light dissymmetry factor is crucial to a common strategy for a strongly dissymmetric CPL light. In this study, we have compared the single-layered and double-layered CNC-based CPL devices with different luminophores, such as rhodamine 6G (R6G), methylene blue (MB), crystal violet (CV), and silicon quantum dots (Si QDs). We demonstrated that forming a double-layered structure of CNCs nanocomposites is a simple but effective pathway for enhancing the CPL dissymmetry factor for CNC-based CPL materials containing different luminophores. The |

Identifiers

PMID37396231
PMCPMC10308516

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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.