Data · collection · 2022
Supplementary material from "On the design of particle filters inspired by animal noses"
Listed in DataCite
Passive filtering is a common strategy to reduce airborne disease transmission and particulate contaminants across scales spanning orders of magnitude.
Description
The engineering of high-performance filters with relatively low flow resistance but high virus- or particle-blocking efficiency is a non-trivial problem of paramount relevance, as evidenced in the variety of industrial filtration systems and face masks. Next-generation industrial filters and masks should retain sufficiently small droplets and aerosols while having low resistance.
We introduce a novel 3D-printable particle filter inspired by animals’ complex nasal anatomy. Unlike standard random-media-based filters, the proposed concept relies on equally spaced channels with tortuous airflow paths. These two strategies induce distinct effects: a reduced resistance and a high likelihood of particle trapping by altering their trajectories with tortuous paths and induced local flow instability.
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The structures are tested for pressure drop and particle filtering efficiency over different airflow rates. We have also cross-validated the observed efficiency through numerical simulations. We found that the designed filters exhibit a lower pressure drop, compared to commercial masks and filters, while capturing particles bigger than approximately μ m
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Where it is published
- Repository landing page rs.figshare.com/collections/Supplementary_material_from_On_the_design_of_parti… ↗
landing page · from DataCite
- DOI doi.org/10.6084/m9.figshare.c.5859630.v1 ↗
DOI / persistent id · from DataCite
Documentation and papers
- Creative Commons Attribution 4.0 International creativecommons.org/licenses/by/4.0/legalcode ↗
license · from DataCite
- IsSupplementTo 10.1098/rsif.2021.0849 doi.org/10.1098/rsif.2021.0849 ↗
publication · from DataCite
Catalogue records · 2
- DataCite API api.datacite.org/dois/10.6084/m9.figshare.c.5859630.v1 ↗
metadata API · from DataCite
- DataCite Commons commons.datacite.org/doi.org/10.6084/m9.figshare.c.5859630.v1 ↗
catalogue entry · from DataCite
Topics
- Stated by source
- Basic medicine · Computer and information sciences · Health sciences
- Inferred from text
- Disease 75%
Related
Provenance · 1 source records, 11 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| DataCite | 10.6084/m9.figshare.c.5859630.v1 | 9 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · DataCite | connector:datacite@1.0.0 | /data/attributes/rightsList |
| concepts[disease].local:disease:disease | enrichment · DataCite | keyword-concept-rules@1.0.0 | title+description (75%) |
| concepts[field].fos:basic-medicine | source · DataCite | connector:datacite@1.0.0 | |
| concepts[field].fos:computer-and-information-sciences | source · DataCite | connector:datacite@1.0.0 | |
| concepts[field].fos:health-sciences | source · DataCite | connector:datacite@1.0.0 | |
| created_date | source · DataCite | connector:datacite@1.0.0 | |
| description | source · DataCite | connector:datacite@1.0.0 | /data/attributes/descriptions |
| license | source · DataCite | connector:datacite@1.0.0 | /data/attributes/rightsList |
| publication_date | source · DataCite | connector:datacite@1.0.0 | /data/attributes/dates |
| title | source · DataCite | connector:datacite@1.0.0 | /data/attributes/titles/0/title |
| updated_date | source · DataCite | connector:datacite@1.0.0 |