Evidence map›Paper›PMID 42865168›Full record

ArticleSe pu = Chinese journal of chromatography2026

[Preparation and chiral separation performance evaluation of a high performance liquid chromatography stationary phase based on a [2+4]-type chiral porous organic cage Pim].

Chun Chen, Ya-Nan Gong, Bang-Jin Wang, Sheng-Ming Xie, Jun-Hui Zhang, Li-Ming Yuan

Abstract readEnglish Abstract
In one paragraph

Article in Se pu = Chinese journal of chromatography, 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

6 authors.

Chun ChenYunnan Key Laboratory of Modern Separation Analysis and Substance Transformation,College of Chemistry and Chemical Engineering,Yunnan Normal University,Kunming 650500,China.
Ya-Nan GongYunnan Key Laboratory of Modern Separation Analysis and Substance Transformation,College of Chemistry and Chemical Engineering,Yunnan Normal University,Kunming 650500,China.
Bang-Jin WangYunnan Key Laboratory of Modern Separation Analysis and Substance Transformation,College of Chemistry and Chemical Engineering,Yunnan Normal University,Kunming 650500,China.
Sheng-Ming XieYunnan Key Laboratory of Modern Separation Analysis and Substance Transformation,College of Chemistry and Chemical Engineering,Yunnan Normal University,Kunming 650500,China.
Jun-Hui ZhangYunnan Key Laboratory of Modern Separation Analysis and Substance Transformation,College of Chemistry and Chemical Engineering,Yunnan Normal University,Kunming 650500,China.
Li-Ming YuanYunnan Key Laboratory of Modern Separation Analysis and Substance Transformation,College of Chemistry and Chemical Engineering,Yunnan Normal University,Kunming 650500,China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Porous organic cages (POCs) represent a class of emerging porous materials assembled from discrete three-dimensional cage-like molecules via intermolecular interactions. Owing to their good solubility and unique pore structures, they show great potential in gas adsorption, molecular recognition, separation, catalysis, and sensing. In this study, a phenolphthalein-based tetraaldehyde compound was synthesized via the Duff reaction using phenolphthalein as the substrate and trifluoroacetic acid (TFA) combined with hexamethylenetetramine (HMTA) as the formylation reagent. Subsequently, a [2+4]-type chiral imine POC, Pim (C

Indexed as

chiral porous organic cagechiral stationary phase (CSP)enantioseparationhigh performance liquid chromatography (HPLC)

Identifiers

PMID42865168
PMCPMC13659878

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.