Evidence map›Paper›PMID 33120971›Full record

ArticlePolymers2020

Hierarchical Structured Polyimide-Silica Hybrid Nano/Microfiber Filters Welded by Solvent Vapor for Air Filtration.

Dawei Li, Ying Shen, Lanlan Wang, Feng Liu, Bingyao Deng, Qingsheng Liu

Abstract read
In one paragraph

Article in Polymers, 2020. 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. Electrospun Nanofiber Membranes for Air Filtration: A Review.Nanomaterials (Basel, Switzerland) · 2022
    Review
  2. A Cleanable Self-Assembled Nano-SiOMaterials (Basel, Switzerland) · 2021
    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.

Dawei LiKey Laboratory of Eco-Textiles (Ministry of Education), Nonwoven Technology Laboratory, Jiangnan University, Wuxi 214122, China.
Ying ShenKey Laboratory of Eco-Textiles (Ministry of Education), Nonwoven Technology Laboratory, Jiangnan University, Wuxi 214122, China.
Lanlan WangKey Laboratory of Eco-Textiles (Ministry of Education), Nonwoven Technology Laboratory, Jiangnan University, Wuxi 214122, China.
Feng LiuKey Laboratory of Eco-Textiles (Ministry of Education), Nonwoven Technology Laboratory, Jiangnan University, Wuxi 214122, China.
Bingyao DengKey Laboratory of Eco-Textiles (Ministry of Education), Nonwoven Technology Laboratory, Jiangnan University, Wuxi 214122, China.ORCID 0000-0001-5652-3503
Qingsheng LiuKey Laboratory of Eco-Textiles (Ministry of Education), Nonwoven Technology Laboratory, Jiangnan University, Wuxi 214122, China.

Funding

China Postdoctoral Science Foundation 2019M651699Fundamental Research Funds for the Central Universities JUSRP51907ANational Defense Cultivation Project of Fundamental Research Funds for the Central Universities JUSRP41904National Key Research and Development Program of China 2019YFC1904502National Natural Science Foundation of China 51908246Postgraduate Research & Practice Innovation Program of Jiangsu Provence KYCX18_1823
6 · The paper itself

Abstract

Electrospun polymer membranes were considered to be promising materials for fine particulate matter (PM) filtration. However, the poor mechanical properties of the electrospun membrane restricted their application for pressure-driven air filtration. Herein, strength-enhanced electrospun polyimide (PI) membranes were demonstrated via a synergistic approach. Solvent-vapor treatment was utilized to introduce extra bonding at the cross points of PI nanofiber, while SiO

Indexed as

air filtrationelectrospinninghierarchical structurehybrid nano/microfiber filters

Identifiers

PMID33120971
PMCPMC7693890

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.