↓ Skip to main content

Aerosol Filtration Efficiency of Common Fabrics Used in Respiratory Cloth Masks

Overview of attention for article published in ACS Nano, April 2020
Altmetric Badge

About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • One of the highest-scoring outputs from this source (#1 of 9,955)
  • High Attention Score compared to outputs of the same age (99th percentile)
  • High Attention Score compared to outputs of the same age and source (99th percentile)

Mentioned by

news
279 news outlets
blogs
29 blogs
twitter
6250 tweeters
facebook
16 Facebook pages
reddit
8 Redditors
video
4 video uploaders

Citations

dimensions_citation
84 Dimensions

Readers on

mendeley
594 Mendeley
Title
Aerosol Filtration Efficiency of Common Fabrics Used in Respiratory Cloth Masks
Published in
ACS Nano, April 2020
DOI 10.1021/acsnano.0c03252
Pubmed ID
Authors

Abhiteja Konda, Abhinav Prakash, Gregory A. Moss, Michael Schmoldt, Gregory D. Grant, Supratik Guha

Abstract

The emergence of a pandemic affecting the respiratory system can result in a significant demand for face masks. This includes the use of cloth masks by large sections of the public, as can be seen during the current global spread of COVID-19. However, there is limited knowledge available on the performance of various commonly available fabrics used in cloth masks. Importantly, there is a need to evaluate filtration efficiencies as a function of aerosol particulate sizes in the 10 nm to 10 μm range, which is particularly relevant for respiratory virus transmission. We have carried out these studies for several common fabrics including cotton, silk, chiffon, flannel, various synthetics, and their combinations. Although the filtration efficiencies for various fabrics when a single layer was used ranged from 5 to 80% and 5 to 95% for particle sizes of <300 nm and >300 nm, respectively, the efficiencies improved when multiple layers were used and when using a specific combination of different fabrics. Filtration efficiencies of the hybrids (such as cotton–silk, cotton–chiffon, cotton–flannel) was >80% (for particles <300 nm) and >90% (for particles >300 nm). We speculate that the enhanced performance of the hybrids is likely due to the combined effect of mechanical and electrostatic-based filtration. Cotton, the most widely used material for cloth masks performs better at higher weave densities (<i>i.e.</i>, thread count) and can make a significant difference in filtration efficiencies. Our studies also imply that gaps (as caused by an improper fit of the mask) can result in over a 60% decrease in the filtration efficiency, implying the need for future cloth mask design studies to take into account issues of “fit” and leakage, while allowing the exhaled air to vent efficiently. Overall, we find that combinations of various commonly available fabrics used in cloth masks can potentially provide significant protection against the transmission of aerosol particles.

Twitter Demographics

The data shown below were collected from the profiles of 6,250 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 594 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 594 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 107 18%
Student > Ph. D. Student 82 14%
Student > Bachelor 68 11%
Student > Master 55 9%
Other 39 7%
Other 140 24%
Unknown 103 17%
Readers by discipline Count As %
Medicine and Dentistry 91 15%
Engineering 74 12%
Biochemistry, Genetics and Molecular Biology 34 6%
Agricultural and Biological Sciences 31 5%
Chemistry 27 5%
Other 185 31%
Unknown 152 26%

Attention Score in Context

This research output has an Altmetric Attention Score of 6487. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 23 October 2020.
All research outputs
#176
of 16,075,831 outputs
Outputs from ACS Nano
#1
of 9,955 outputs
Outputs of similar age
#58
of 280,021 outputs
Outputs of similar age from ACS Nano
#1
of 296 outputs
Altmetric has tracked 16,075,831 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 9,955 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.5. This one has done particularly well, scoring higher than 99% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 280,021 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 99% of its contemporaries.
We're also able to compare this research output to 296 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 99% of its contemporaries.