Evidence map›Paper›PMID 35098033›Full record

ReviewEmergent materials2022

Electrospun nanofiber-based respiratory face masks-a review.

Veereshgouda S Naragund, P K Panda

Abstract readReview
In one paragraph

Review in Emergent materials, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 1 pooled it
–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

17 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  10. Electrospun Metal-Organic Framework-Fabric Nanocomposites as Efficient Bactericides.Langmuir : the ACS journal of surfaces and colloids · 2023
    Article
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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

2 authors.

Veereshgouda S NaragundMaterials Science Division, CSIR - National Aerospace Laboratories, HAL Old Airport Road, Kodihalli, Bengaluru, 560017 India.
P K PandaMaterials Science Division, CSIR - National Aerospace Laboratories, HAL Old Airport Road, Kodihalli, Bengaluru, 560017 India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The severe acute respiratory syndrome coronavirus (SARS-CoV-2) pandemic of 2019 forced widespread use of face coverings as a mandatory step towards reducing infection by the virus. The face mask acts as a barrier for transmission of infected aerosols among its user and surrounding people. This has propelled pace of research and development of face masks around the world. This short review is an effort to present advances in materials and designs used for face masks. Details available in scientific literature and company brochures have been accessed and the use of nanomaterials and designs for the new generation of face masks have been discussed. Special attention was given to the face masks based on electrospun nanofiber-based membrane materials due to their nano-sized pores, light weight, and high filtration efficiency; therefore, they are commercially viable and popular among various products available in the market. Incorporation of metal organic framework (MOFs) and graphene have opened avenues to more advanced/multi-functional, reusable, and high capacity adsorption filtration membranes. Rapid prototyping/3-dimensional (3-D) printing techniques have been applied to shorten the time of manufacture of face masks. This review is expected to be very helpful for engineers, scientists, and entrepreneurs working on development of novel face masks required in plenty during this pandemic period.

Indexed as

3-D printingAntimicrobial filtersElectrospinningFace maskFiltration efficiencyNanofiber non-wovens

Identifiers

PMID35098033
PMCPMC8788396

What OpenQuestion holds

Textmetadata
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.