Evidence map›Paper›PMID 34068612›Full record

ArticleMembranes2021

Organic Nanobowls Modified Thin Film Composite Membrane for Enhanced Purification Performance toward Different Water Resources.

Changjin Ou, Sisi Li, Zhongyi Wang, Juan Qin, Qian Wang, Zhipeng Liao, Jiansheng Li

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Membranes, 2021. 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. Article
  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

7 authors.

Changjin OuNantong Key Laboratory of Intelligent and New Energy Materials, School of Chemistry and Chemical Engineering, Nantong University, Nantong 222100, China.
Sisi LiNantong Key Laboratory of Intelligent and New Energy Materials, School of Chemistry and Chemical Engineering, Nantong University, Nantong 222100, China.
Zhongyi WangNantong Key Laboratory of Intelligent and New Energy Materials, School of Chemistry and Chemical Engineering, Nantong University, Nantong 222100, China.
Juan QinNantong Key Laboratory of Intelligent and New Energy Materials, School of Chemistry and Chemical Engineering, Nantong University, Nantong 222100, China.
Qian WangSchool of Materials Science and Chemical Engineering, Xi'an Technological University, Xi'an 710021, China.
Zhipeng LiaoNantong Key Laboratory of Intelligent and New Energy Materials, School of Chemistry and Chemical Engineering, Nantong University, Nantong 222100, China.ORCID 0000-0003-0804-2371
Jiansheng LiKey Laboratory of New Membrane Materials, Ministry of Industry and Information Technology, School of Environment and Biological Engineering, Nanjing University of Science and Technology, Nanjing 210094, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The structure and composition of nanofillers have a significant influence on polyamide nanofiltration (NF) membranes. In this work, an asymmetric organic nanobowl containing a concave cavity was synthesized and incorporated into a polyamide layer to prepare thin film nanocomposite (TFN) membranes via an interfacial polymerization process. Benefiting from the hydrophilicity, hollow cavity and charge property of the compatible organic nanobowls, the separation performance of the developed TFN membrane was significantly improved. The corresponding water fluxes increased to 119.44 ± 5.56, 141.82 ± 3.24 and 130.27 ± 2.05 L/(m

Indexed as

antifouling propertynanofillernanofiltrationthin film composite membranewater purification

Identifiers

PMID34068612
PMCPMC8151631

What OpenQuestion holds

Textmetadata
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.