Evidence map›Paper›PMID 41541613›Full record

ArticleSensors and actuators. B, Chemical2025

3D printed microcyclones for enhanced collection, separation, and recovery of sub-micrometer bioaerosols.

Proma Bhattacharya, Dewansh Rastogi, Sima Mehraji, Juan Camarero de la Torre, Aarav Mehta, Sheldon Tai, Ali Hasani, Anna Pulley, Alycia Smith, William Smith and 3 more

Abstract read
In one paragraph

Article in Sensors and actuators. B, Chemical, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

13 authors.

Proma BhattacharyaDepartment of Mechanical Engineering, University of Maryland, College Park, MD 20742, USA.ORCID 0000-0002-6305-8387
Dewansh RastogiDepartment of Chemical and Biomolecular Engineering, University of Maryland, College Park, MD 20742, USA.ORCID 0000-0002-5416-0048
Sima MehrajiDepartment of Mechanical Engineering, University of Maryland, College Park, MD 20742, USA.ORCID 0000-0003-4015-2888
Juan Camarero de la TorreDepartment of Mechanical Engineering, University of Maryland, College Park, MD 20742, USA.
Aarav MehtaDepartment of Mechanical Engineering, University of Maryland, College Park, MD 20742, USA.
Sheldon TaiDepartment of Global, Environmental, and Occupational Health, School of Public Health, University of Maryland, College Park, MD 20742, USA.ORCID 0000-0001-6834-2152
Ali HasaniDepartment of Global, Environmental, and Occupational Health, School of Public Health, University of Maryland, College Park, MD 20742, USA.ORCID 0000-0002-2612-0364
Anna PulleyDepartment of Global, Environmental, and Occupational Health, School of Public Health, University of Maryland, College Park, MD 20742, USA.ORCID 0009-0000-0312-607X
Alycia SmithDepartment of Global, Environmental, and Occupational Health, School of Public Health, University of Maryland, College Park, MD 20742, USA.ORCID 0000-0001-9559-6764
William SmithDepartment of Global, Environmental, and Occupational Health, School of Public Health, University of Maryland, College Park, MD 20742, USA.
Akua Asa-AwukuRobert E. Fischell Institute for Biomedical Devices, University of Maryland, College Park, MD 20742, USA.
Donald K MiltonRobert E. Fischell Institute for Biomedical Devices, University of Maryland, College Park, MD 20742, USA.
Don L DeVoeDepartment of Mechanical Engineering, University of Maryland, College Park, MD 20742, USA.ORCID 0000-0002-7740-9993

Funding

Evaluating Modes of Influenza Transmission using a Randomized Controlled Trial (EMIT-2-RCT)U19AI162130 · NIAID · UNIV OF MARYLAND, COLLEGE PARK · PI SREBRIC, JELENA · 2021 to 2025
$15.2M
Microcyclone arrays for high resolution bioaerosol fractionation and viable virus collectionR21AI166519 · NIAID · UNIV OF MARYLAND, COLLEGE PARK · PI DEVOE, DON L · 2023 to 2024
$428k
NIAID NIH HHS R21 AI166519NIAID NIH HHS U19 AI162130
6 · The paper itself

Abstract

The collection and separation of aerosols is necessary to support the capture and analysis of particulate matter that can impact human health, enabling effective monitoring and prediction of exposure risk, and supporting fundamental studies of aerosol generation, transport, and distribution. Of particular concern are sub-micrometer particles which can deeply infiltrate the lungs, but efficient separation and capture of these smaller particles is challenging. In the case of bioaerosols, effective recovery of biological particles following capture often involves significant dilution of the collected sample, hindering downstream analysis. Here we report a miniature 3D printed cyclone-based platform capable of highly effective separation and recovery of submicron bioaerosols with well-defined cut-off sizes. Using a set of geometrically similar microcyclones fabricated at different size scales, with minimum channel dimensions of 0.75 mm, cut diameters as low as 0.05 μm are achieved at aerosol flow rates up to 5 L/min, with sharp cut-offs yielding nearly 100 % capture efficiency for larger particulates. Furthermore, captured influenza virus is recovered from the devices with up to 85 % efficiency and minimal dilution via a rapid elution process that takes advantage of the low internal microcyclone volume. The high capture efficiency for submicron particles enabled by the microcyclone platform, together with its compact form factor, effective sample recovery, tunable cut size, and cost-effective manufacture, makes the technology a promising tool for broad applications in aerosol and bioaerosol monitoring.

Indexed as

BioaerosolsCyclonesInertial separation

Identifiers

PMID41541613
PMCPMC12803735

What OpenQuestion holds

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Registered trials

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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.