Evidence map›Paper›PMID 37959871›Full record

ArticleMolecules (Basel, Switzerland)2023

Three-Dimensional Porous PVDF Foam Imprinted Membranes with High Flux and Selectivity toward Artemisinin/Artemether.

Weibai Bian, Ruixuan Zhang, Xiaohui Chen, Chuanxun Zhang, Minjia Meng

Open access · goldAbstract read
In one paragraph

Article in Molecules (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.6field-weighted citation impact, top 38% of its field
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

1 citing paper in PubMed, 4 citations in OpenAlex.

  1. Article
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

5 authors at 2 institutions in 1 country.

Weibai BianSchool of Photoelectric Engineering, Changzhou Institute of Technology, Changzhou 213032, China.
Ruixuan ZhangSchool of Photoelectric Engineering, Changzhou Institute of Technology, Changzhou 213032, China.
Xiaohui ChenSchool of Photoelectric Engineering, Changzhou Institute of Technology, Changzhou 213032, China.
Chuanxun ZhangSchool of Chemistry and Chemical Engineering, Jiangsu University, Zhenjiang 212013, China.
Minjia MengSchool of Chemistry and Chemical Engineering, Jiangsu University, Zhenjiang 212013, China.
Changzhou Institute of Technology · CNJiangsu University · CN

Funding

National Natural Science Foundation of China No.22202022, 22102012, 22272011Natural Science Foundation of the Jiangsu Higher Education Institutions of China No. 22KJB450001, 23KJA440002
6 · The paper itself

Abstract

In this study, a new 3D porous PVDF-foam-imprinted membrane (PPIM) for the selective separation of artemisinin (ART) was first prepared via the dopamine adhesion of pre-synthesized MIPs into the interior of the PPIM. In the PPIM, the pre-synthesized molecularly imprinted polymers (MIPs) with artesunate (ARU) as a dummy template were uniformly loaded on the interior of the membrane, avoiding the defects of recognition site encapsulation found in the conventional membrane. This membrane also exhibited excellent flux, which is beneficial in practical separation applications. The PPIM was systematically characterized via FT-IR, SEM, pore-size distribution analysis, water contact angle test, membrane flux, and mechanical performance analysis, respectively. In the static adsorption experiment, the pseudo-second-order kinetic model better fitted the rebinding data of ART. Under dynamic conditions, the ART adsorption capacity of the PPIM could be further remarkably improved by tailoring the flow rate to 3 mL min

Indexed as

artemisininfoam imprinted membraneshigh fluxselective separation

Identifiers

PMID37959871
PMCPMC10647727
OpenAlexW4388408555

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.