Evidence map›Paper›PMID 41450633›Full record

ArticleJACS Au2025

Synthesis and Persistence Length Study of Defect-Free and Non-Aggregated Conjugated Ladder Polymers.

James Shao-Jiun Yang, Vijaya Sundar Jeyaraj, Guorong Ma, Daniel Doria, Xiaodan Gu, Daniel Tabor, Lei Fang

Abstract read
In one paragraph

Article in JACS Au, 2025. 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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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

7 authors.

James Shao-Jiun YangDepartment of Chemistry, Texas A&M University, College Station, Texas 77843, United States.ORCID https://orcid.org/0000-0002-2068-3692
Vijaya Sundar JeyarajDepartment of Chemistry, Texas A&M University, College Station, Texas 77843, United States.ORCID https://orcid.org/0000-0003-2109-4299
Guorong MaSchool of Polymer Science and Engineering, Center for Optoelectronic Materials and Devices, The University of Southern Mississippi, Hattiesburg, Mississippi 39406, United States.
Daniel DoriaDepartment of Chemistry, Texas A&M University, College Station, Texas 77843, United States.
Xiaodan GuSchool of Polymer Science and Engineering, Center for Optoelectronic Materials and Devices, The University of Southern Mississippi, Hattiesburg, Mississippi 39406, United States.ORCID https://orcid.org/0000-0002-1123-3673
Daniel TaborDepartment of Chemistry, Texas A&M University, College Station, Texas 77843, United States.ORCID https://orcid.org/0000-0002-8680-6667
Lei FangDepartment of Chemistry, Texas A&M University, College Station, Texas 77843, United States.ORCID https://orcid.org/0000-0003-4757-5664

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A fundamental understanding of the solution properties of conjugated ladder polymers (CLPs) is essential for advancing their design, synthesis, and solution processing toward high-performance optoelectronic applications. Nevertheless, elucidating the solution conformation of CLPs remains a significant challenge in the field of polymer physics, owing to the difficulty of synthesizing defect-free samples, their intrinsically low solubility that results in weak signals and limited analytical accuracy, the pronounced tendency of CLPs to aggregate even when dissolved, and the absence of reliable theoretical models. Here, these fundamental challenges are addressed by the synthesis, neutron scattering measurements, and computational simulations of two model CLPs,

Indexed as

conjugated ladder polymersmachine learningneutron scatteringpersistence lengthpolymer conformationpolymer synthesissemiflexibility

Identifiers

PMID41450633
PMCPMC12728607

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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.