Evidence map›Paper›PMID 38708106›Full record

ArticleRSC advances2024

Effective separation of dyes/salts by sulfonated covalent organic framework membranes based on phenolamine network conditioning.

Zekun Zhou, Zezhen Zhang, Shuman Feng, Lulu Liu, Weishan Deng, Lili Wu

Abstract read
In one paragraph

Article in RSC advances, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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

6 authors.

Zekun ZhouSchool of Materials Science and Engineering, Wuhan University of Technology Wuhan 430070 China polym_wl@whut.edu.cn.
Zezhen ZhangSchool of Materials Science and Engineering, Wuhan University of Technology Wuhan 430070 China polym_wl@whut.edu.cn.
Shuman FengDepartment of Neurology, Henan Provincial People's Hospital, Zhengzhou University People's Hospital Zhengzhou Henan 450003 China.
Lulu LiuSchool of Materials Science and Engineering, Wuhan University of Technology Wuhan 430070 China polym_wl@whut.edu.cn.
Weishan DengSchool of Materials Science and Engineering, Wuhan University of Technology Wuhan 430070 China polym_wl@whut.edu.cn.
Lili WuSchool of Materials Science and Engineering, Wuhan University of Technology Wuhan 430070 China polym_wl@whut.edu.cn.ORCID https://orcid.org/0000-0001-9200-3863

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study developed a modified polyacrylonitrile (PAN) membrane controlled by a phenol-amine network and enhanced with a sulfonated covalent organic framework (SCOF), aimed at improving the efficiency of textile wastewater treatment. Utilizing a phenol-amine network control strategy allows for precise manipulation of interfacial reactions in the synthesis of SCOF, achieving highly uniform modification on the surface of the PAN membrane. This modified membrane demonstrated high rejection of over 98% for various water-soluble dyes, including Alcian blue 8GX, Coomassie Brilliant Blue G250, methyl blue, congo red, and rose bengal, and also exhibited specific selectivity in processing salt-containing wastewater. By adjusting the deposition time of the phenol-amine and the concentration of SCOF monomers, optimal retention performance and permeate flux were achieved, effectively separating dyes and salts. This research provides a new and effective solution for treating textile wastewater, especially in separating and recovering dyes and salts, offering broad application prospects in environmental management and water resource management, and highlighting its significant practical implications.

Identifiers

PMID38708106
PMCPMC11066737

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.