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Review
. 2022 Oct 11;13(10):1716.
doi: 10.3390/mi13101716.

Microfluidic Gas Sensors: Detection Principle and Applications

Affiliations
Review

Microfluidic Gas Sensors: Detection Principle and Applications

Sreerag Kaaliveetil et al. Micromachines (Basel). .

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 E. coli and SARS-CoV-2. The possible application scenarios for the various microfluidic devices are critically examined.

Keywords: gas sensing; microfluidics; selectivity; sensitivity.

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Conflict of interest statement

The authors declare no conflict of interest. The funders had no role in the design of the study, in the collection, analyses, or interpretation of data, in the writing of the manuscript, or in the decision to publish the results.

Figures

Figure 1
Figure 1
(A) Schematic of microfluidic channel with chromium, gold and Parylene C coating. (B) Schematic of microfluidic channel with chromium, gold, Parylene C and Cytonix coating. (C,D) Contact angle values for DI water on coating without and with cytonix. (E) Schematic of microfluidic channel with microfeatures. (F) Microscopic image of microfeatures. (AD) Reproduced under the terms of CC BY 4.0 license from [12] Copyright (2019), The Authors, published by Nature. (E,F) Reprinted from [16], Copyright (2022), with permission from Elsevier.
Figure 2
Figure 2
(A) Schematic representation of PEDOT: PSS-coated microfluidic channel integrated with gas sensor (B) Temporal response of the sensor to the target gas along the microchannels coated with PEDOT: PSS. Reproduced under the terms of CC BY 4.0 license from [11] Copyright 2017, The Authors, published by Nature.
Figure 3
Figure 3
(A) Structure of FET (B) Modified FET used for gas sensing.
Figure 4
Figure 4
(A) Schematic representation of bioelectronic nose (B) Real−time measurements of change in conductance when Bare and ORP coated SWNT is exposed to TMA. (C) Calibration curve of the bioelectronic nose. Reprinted from [8], Copyright (2015), with permission from Elsevier.
Figure 5
Figure 5
Illustration of (A) Au microchannel electrode and (B) Au macrodisk electrode. (C) Long-term chronoamperometry for 10–100% vol H2 PtNP modified Au microchannel. Reprinted from [23], Copyright (2019), with permission from Elsevier.
Figure 6
Figure 6
(A) Schematic of the microfluidic platform (B) Calibration curve of microfluidic colorimetric sensor (C) reaction reservoir images when exposed to different concentration of gaseous formaldehyde. Reproduced under the terms of CC BY 4.0 license from [24] Copyright 2018, The Authors, published by MDPI.
Figure 7
Figure 7
(A) A schematic diagram showing the structure of microfluidic platform (B) Optical setup for the real-time detection of the target analytes (C) Real-time fluorescence and scattering signal acquired for all three bacterial cells. Light scattering intensity shows the presence of non-bacterial cells (D) Bacterial cell concentrations measured using the micro-optofluidic platform, cell counting using fluorescence microscopy, and colony counting. Reproduced under the terms of CC BY 4.0 license from [25] Copyright 2015, The Authors, published by Nature.
Figure 8
Figure 8
Schematic showing the working of bubble-based microfluidic gas sensor in producing gas chromatographs. Reproduced with permission from [35] Copyright 2015, The Authors, published by Royal Society of Chemistry.
Figure 9
Figure 9
The movement of an MTB-Ba sulfate solution droplet during a measuring. Reproduced under the terms of CC BY 4.0 license from [38] Copyright 2020, The Authors, published by MDPI.

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