Evidence map›Paper›PMID 36296069›Full record

ReviewMicromachines2022

Microfluidic Gas Sensors: Detection Principle and Applications.

Sreerag Kaaliveetil, Juliana Yang, Saud Alssaidy, Zhenglong Li, Yu-Hsuan Cheng, Niranjan Haridas Menon, Charmi Chande, Sagnik Basuray

Abstract readReview
In one paragraph

Review in Micromachines, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Multimodal Biosensing of Foodborne Pathogens.International journal of molecular sciences · 2024
    Review
  5. Article
  6. Article
  7. Article
  8. Review
  9. Article
  10. Review
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

8 authors.

Sreerag KaaliveetilDepartment of Chemical and Materials Engineering, New Jersey Institute of Technology, Newark, NJ 07102, USA.
Juliana YangDepartment of Biomedical Engineering, New Jersey Institute of Technology, Newark, NJ 07102, USA.
Saud AlssaidyDepartment of Chemical and Materials Engineering, New Jersey Institute of Technology, Newark, NJ 07102, USA.
Zhenglong LiDepartment of Chemical and Materials Engineering, New Jersey Institute of Technology, Newark, NJ 07102, USA.
Yu-Hsuan ChengDepartment of Chemical and Materials Engineering, New Jersey Institute of Technology, Newark, NJ 07102, USA.
Niranjan Haridas MenonDepartment of Chemical and Materials Engineering, New Jersey Institute of Technology, Newark, NJ 07102, USA.
Charmi ChandeDepartment of Chemical and Materials Engineering, New Jersey Institute of Technology, Newark, NJ 07102, USA.
Sagnik BasurayDepartment of Chemical and Materials Engineering, New Jersey Institute of Technology, Newark, NJ 07102, USA.ORCID 0000-0001-9767-9096

Funding

ESTCP ER21-5101National Science Foundation 1751759New Jersey Health Foundation PC 54-20
6 · The paper itself

Abstract

With the rapid growth of emerging point-of-use (POU)/point-of-care (POC) detection technologies, miniaturized sensors for the real-time detection of gases and airborne pathogens have become essential to fight pollution, emerging contaminants, and pandemics. However, the low-cost development of miniaturized gas sensors without compromising selectivity, sensitivity, and response time remains challenging. Microfluidics is a promising technology that has been exploited for decades to overcome such limitations, making it an excellent candidate for POU/POC. However, microfluidic-based gas sensors remain a nascent field. In this review, the evolution of microfluidic gas sensors from basic electronic techniques to more advanced optical techniques such as surface-enhanced Raman spectroscopy to detect analytes is documented in detail. This paper focuses on the various detection methodologies used in microfluidic-based devices for detecting gases and airborne pathogens. Non-continuous microfluidic devices such as bubble/droplet-based microfluidics technology that have been employed to detect gases and airborne pathogens are also discussed. The selectivity, sensitivity, advantages/disadvantages vis-a-vis response time, and fabrication costs for all the microfluidic sensors are tabulated. The microfluidic sensors are grouped based on the target moiety, such as air pollutants such as carbon monoxide and nitrogen oxides, and airborne pathogens such as

Indexed as

gas sensingmicrofluidicsselectivitysensitivity

Identifiers

PMID36296069
PMCPMC9607434

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.