Nanomaterial Based Gas Sensors for Environmental Air Pollutant Detection

Topic Information

Dear Colleagues,

Rapid industrialization around the world and the poor monitoring of pollutants in the air is obviously putting ecosystems and human life at greater risk than ever before. Air pollutants, mostly produced from industrial activities, automobiles, and other combustion sources, are being directly emitted into the atmosphere, thereby altering the quality and safety of environmental air and causing a significant threat to the wellbeing and lifestyles of humans. Despite many countries and local authorities introducing certain regulations and mechanisms to combat and control air pollutants, the lack of concerted global efforts and smart technologies to continuously measure, analyze and monitor pollutants is still a pressing issue. Given to their excellent selectivity, sensitivity, and miniaturization, gas sensors based on functional nanomaterials present an alternative nanotechnolgy to detect air pollutants and to monitor the safety and quality of environmental air. Thus, gas sensors based on nanostructured materials, polymers, nanocomposites, and thin films demonstrate excellent features for the detection and determination of both primary and secondary air pollutants. Hence, in light of this pressing issue, this Topic aims at convering the latest nanomaterial-based gas sensors and mechanisms for the detection and determination of air pollutants and the way forward to bring such technologies to a greater usage. We look forward to and welcome your participation in this topic.

Dr. Tesfalem Welearegay
Dr. Radu Ionescu
Topic Editors

Keywords

Participating Journals

Journal Name	Impact Factor	CiteScore	Launched Year	First Decision (median)	APC
Applied Nano applnano	-	-	2020	17.1 Days	CHF 1000
Biosensors biosensors	4.9	6.6	2011	17.1 Days	CHF 2700
Chemosensors chemosensors	3.7	5.0	2013	17.1 Days	CHF 2700
Materials materials	3.1	5.8	2008	15.5 Days	CHF 2600
Sensors sensors	3.4	7.3	2001	16.8 Days	CHF 2600

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15 pages, 5119 KiB  

Open AccessArticle

Influence of Different Pt Functionalization Modes on the Properties of CuO Gas-Sensing Materials

by Xiangxiang Chen, Tianhao Liu, Yunfei Ouyang, Shiyi Huang, Zhaoyang Zhang, Fangzheng Liu, Lu Qiu, Chicheng Wang, Xincheng Lin, Junyan Chen and Yanbai Shen

Sensors 2024, 24(1), 120; https://doi.org/10.3390/s24010120 - 25 Dec 2023

Cited by 1 | Viewed by 1125

Abstract

The functionalization of noble metals is an effective approach to lowering the sensing temperature and improving the sensitivity of metal oxide semiconductor (MOS)-based gas sensors. However, there is a dearth of comparative analyses regarding the differences in sensitization mechanisms between the two functionalization [...] Read more.

The functionalization of noble metals is an effective approach to lowering the sensing temperature and improving the sensitivity of metal oxide semiconductor (MOS)-based gas sensors. However, there is a dearth of comparative analyses regarding the differences in sensitization mechanisms between the two functionalization modes of noble metal loading and doping. In this investigation, we synthesized Pt-doped CuO gas-sensing materials using a one-pot hydrothermal method. And for Pt-loaded CuO, Pt was deposited on the synthesized pristine CuO surface by using a dipping method. We found that both functionalization methods can considerably enhance the response and selectivity of CuO toward NO₂ at low temperatures. However, we observed that CuO with Pt loading had superior sensing performance at 25 °C, while CuO with Pt doping showed more substantial response changes with an increase in the operating temperature. This is mainly due to the different dominant roles of electron sensitization and chemical sensitization resulting from the different forms of Pt present in different functionalization modes. For Pt doping, electron sensitization is stronger, and for Pt loading, chemical sensitization is stronger. The results of this study present innovative ideas for understanding the optimization of noble metal functionalization for the gas-sensing performance of metal oxide semiconductors. Full article

(This article belongs to the Topic Nanomaterial Based Gas Sensors for Environmental Air Pollutant Detection)

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Figure 1

Figure 1
<p>(<b>a</b>) XRD patterns of pristine CuO, 2 mol% Pt-CuO, and 2 mol% Pt@CuO; (<b>b</b>) magnified region of three main CuO diffraction peaks.</p> Full article ">Figure 2
<p>SEM images of 2 mol% Pt@CuO (<b>a</b>,<b>b</b>) and 2 mol% Pt-CuO (<b>c</b>,<b>d</b>); (<b>e</b>) the related EDS patterns.</p> Full article ">Figure 3
<p>TEM images of 2 mol% Pt@CuO (<b>a</b>–<b>c</b>) and 2 mol% Pt-CuO (<b>d</b>–<b>f</b>).</p> Full article ">Figure 4
<p>XPS spectra of Pt@CuO and Pt-CuO. (<b>a</b>,<b>d</b>) Pt 4f, (<b>b</b>,<b>e</b>) Cu 2p; (<b>c</b>,<b>f</b>) O 1s.</p> Full article ">Figure 5
<p>(<b>a</b>,<b>d</b>) Responses, (<b>b</b>,<b>e</b>) response times, and (<b>c</b>,<b>f</b>) recovery times of sensors based on Pt@CuO and Pt-CuO with different Pt concentrations when exposed to 5 ppm NO₂ as a function of operating temperature.</p> Full article ">Figure 6
<p>(<b>a</b>,<b>c</b>) Response–recovery curves of the sensors based on pristine CuO, Pt@CuO and Pt-CuO with different Pt concentrations to NO₂ at respective optimal operating temperature. (<b>b</b>,<b>d</b>) The evolution of sensor response on the function of NO₂ concentration.</p> Full article ">Figure 7
<p>Responses of sensors based on Pt@CuO (<b>a</b>) and Pt-CuO (<b>b</b>) with different Pt concentrations to various gases at their respective optimal operating temperatures.</p> Full article ">Figure 8
<p>Responses of sensors based on Pt@CuO (<b>a</b>) and Pt-CuO (<b>b</b>) with different Pt concentrations to NO₂ at 25 °C.</p> Full article ">Figure 9
<p>Reproducible cycles of gas sensors based on Pt@CuO (<b>a</b>) and Pt-CuO (<b>b</b>) upon exposure to NO₂ at 25 °C.</p> Full article ">Figure 10
<p>(<b>a</b>) Responses, (<b>b</b>) response times, and (<b>c</b>) recovery times of sensors based on Pt@CuO and Pt-CuO at different humidity levels when exposed to 2 ppm NO₂ at 25 °C.</p> Full article ">Figure 11
<p>Plots of (αhν)² versus the energy band gaps of Pt@CuO (<b>a</b>) and Pt-CuO (<b>b</b>).</p> Full article ">

20 pages, 6639 KiB  

Open AccessArticle

Long-Range Network of Air Quality Index Sensors in an Urban Area

by Ionut-Marian Dobra, Vladut-Alexandru Dobra, Adina-Alexandra Dobra, Gabriel Harja, Silviu Folea and Vlad-Dacian Gavra

Sensors 2023, 23(21), 9001; https://doi.org/10.3390/s23219001 - 6 Nov 2023

Viewed by 1278

Abstract

In recent times the escalating pollution within densely populated metropolitan areas has emerged as a significant and pressing concern. Authorities are actively grappling with the challenge of devising solutions to promote a cleaner and more environmentally friendly urban landscapes. This paper outlines the [...] Read more.

In recent times the escalating pollution within densely populated metropolitan areas has emerged as a significant and pressing concern. Authorities are actively grappling with the challenge of devising solutions to promote a cleaner and more environmentally friendly urban landscapes. This paper outlines the potential of establishing a LoRa node network within a densely populated urban environment. Each LoRa node in this network is equipped with an air quality measurement sensor. This interconnected system efficiently transmits all the analyzed data to a gateway, which subsequently sends it to a server or database in real time. These data are then harnessed to create a pollution map for the corresponding area, providing users with the opportunity to assess local pollution levels and their recent variations. Furthermore, this information proves valuable when determining the optimal route between two points in the city, enabling users to select the path with the lowest pollution levels, thus enhancing the overall quality of the urban environment. This advantage contributes to alleviating congestion and reducing excessive pollution often concentrated behind buildings or on adjacent streets. Full article

(This article belongs to the Topic Nanomaterial Based Gas Sensors for Environmental Air Pollutant Detection)

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<p>Communication between end node–gateway–server.</p> Full article ">Figure 2
<p>End node: NUCLEO-WL55JC1 (<b>left</b> side) and gateway: NUCLEO-F746ZG (<b>right</b> side).</p> Full article ">Figure 3
<p>Data received by the server.</p> Full article ">Figure 4
<p>Pimorini BME680 Air Quality sensor.</p> Full article ">Figure 5
<p>End node cluster.</p> Full article ">Figure 6
<p>Multiple end node clusters.</p> Full article ">Figure 7
<p>Gateways’ coverage of a neighborhood from Cluj-Napoca.</p> Full article ">Figure 8
<p>End node coverage of a neighborhood from Cluj-Napoca.</p> Full article ">Figure 9
<p>End node cluster mounted on signal pole (Highlighted by arrow).</p> Full article ">Figure 10
<p>End nodes’ positions on the TTN mapper map (green dot) to be in the range of a gateway for data transmission.</p> Full article ">Figure 11
<p>Diagram of the centralized values for gas measurement from sensors 1, 2, and 3.</p> Full article ">Figure 12
<p>Air pollution map and possible routes with different pollution levels (Red dot—start and destination point, and blue dot—the location of the end nodes).</p> Full article ">

11 pages, 4242 KiB  

Open AccessArticle

Selective NO₂ Detection of CaCu₃Ti₄O₁₂ Ceramic Prepared by the Sol-Gel Technique and DRIFT Measurements to Elucidate the Gas Sensing Mechanism

by Rodrigo Espinoza-González, Josefa Caamaño, Ximena Castillo, Marcelo O. Orlandi, Anderson A. Felix, Marcos Flores, Adriana Blanco, Carmen Castro-Castillo and Francisco Gracia

Materials 2023, 16(9), 3390; https://doi.org/10.3390/ma16093390 - 26 Apr 2023

Cited by 2 | Viewed by 1821

Abstract

NO₂ is one of the main greenhouse gases, which is mainly generated by the combustion of fossil fuels. In addition to its contribution to global warming, this gas is also directly dangerous to humans. The present work reports the structural and gas [...] Read more.

NO₂ is one of the main greenhouse gases, which is mainly generated by the combustion of fossil fuels. In addition to its contribution to global warming, this gas is also directly dangerous to humans. The present work reports the structural and gas sensing properties of the CaCu₃Ti₄O₁₂ compound prepared by the sol-gel technique. Rietveld refinement confirmed the formation of the pseudo-cubic CaCu₃Ti₄O₁₂ compound, with less than 4 wt% of the secondary phases. The microstructural and elemental composition analysis were carried out using scanning electron microscopy and X-ray energy dispersive spectroscopy, respectively, while the elemental oxidation states of the samples were determined by X-ray photoelectron spectroscopy. The gas sensing response of the samples was performed for different concentrations of NO₂, H₂, CO, C₂H₂ and C₂H₄ at temperatures between 100 and 300 °C. The materials exhibited selectivity for NO₂, showing a greater sensor signal at 250 °C, which was correlated with the highest concentration of nitrite and nitrate species on the CCTO surface using DRIFT spectroscopy. Full article

(This article belongs to the Topic Nanomaterial Based Gas Sensors for Environmental Air Pollutant Detection)

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Figure 1

Figure 1
<p>(<b>a</b>) XRD pattern of CCTO sample, (*) <span class="html-italic">K_α</span> peak from (022) reflection. (+) Peak from CuO phase; (<b>b</b>) Rietveld refinement of XRD CCTO pattern.</p> Full article ">Figure 2
<p>SEM image of CCTO sample obtained by secondary electrons detector. Inset: EDS analysis of CCTO particles.</p> Full article ">Figure 3
<p>High-resolution XPS spectra of the different elements present in sample CCTO: (<b>a</b>) Ca2p, (<b>b</b>) Cu2p, (<b>c</b>) Ti2p, and (<b>d</b>) O1s.</p> Full article ">Figure 4
<p>Gas sensing response of CCTO sample as a function of the NO₂ concentration at 250 °C.</p> Full article ">Figure 5
<p>Gas sensing response plots as a function of the temperature of different NO₂ concentrations.</p> Full article ">Figure 6
<p>(<b>a</b>) Gas selectivity at 10 ppm and 250 °C of CCTO sample; (<b>b</b>) sensor signal of CCTO sample at 250 °C for the concentrations of different gases.</p> Full article ">Figure 7
<p>DRIFT spectra of CCTO powders (<b>a</b>) at 250 °C in NO₂/air and NO₂/He mixture atmospheres and (<b>b</b>) in NO₂/air mixture at different temperatures and differential integrated absorbance (inset).</p> Full article ">

30 pages, 18238 KiB  

Open AccessReview

Accelerating the Gas–Solid Interactions for Conductometric Gas Sensors: Impacting Factors and Improvement Strategies

by Hongchao Zhao, Yanjie Wang and Yong Zhou

Materials 2023, 16(8), 3249; https://doi.org/10.3390/ma16083249 - 20 Apr 2023

Cited by 6 | Viewed by 2451

Abstract

Metal oxide-based conductometric gas sensors (CGS) have showcased a vast application potential in the fields of environmental protection and medical diagnosis due to their unique advantages of high cost-effectiveness, expedient miniaturization, and noninvasive and convenient operation. Of multiple parameters to assess the sensor [...] Read more.

Metal oxide-based conductometric gas sensors (CGS) have showcased a vast application potential in the fields of environmental protection and medical diagnosis due to their unique advantages of high cost-effectiveness, expedient miniaturization, and noninvasive and convenient operation. Of multiple parameters to assess the sensor performance, the reaction speeds, including response and recovery times during the gas–solid interactions, are directly correlated to a timely recognition of the target molecule prior to scheduling the relevant processing solutions and an instant restoration aimed for subsequent repeated exposure tests. In this review, we first take metal oxide semiconductors (MOSs) as the case study and conclude the impact of the semiconducting type as well as the grain size and morphology of MOSs on the reaction speeds of related gas sensors. Second, various improvement strategies, primarily including external stimulus (heat and photons), morphological and structural regulation, element doping, and composite engineering, are successively introduced in detail. Finally, challenges and perspectives are proposed so as to provide the design references for future high-performance CGS featuring swift detection and regeneration. Full article

(This article belongs to the Topic Nanomaterial Based Gas Sensors for Environmental Air Pollutant Detection)

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Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>The response time and recovery time of a typical MOS gas sensor.</p> Full article ">Figure 2
<p>AFM micrographs (2 μm × 2 μm) of the as-deposited AZO films with various thicknesses: (<b>a</b>) 65 nm, (<b>b</b>) 188.5 nm, (<b>c</b>) 280 nm, and (<b>d</b>) 390 nm, (<b>e</b>) the effect of film thickness on the dynamic response toward 1000 ppm CO at 300 °C. Reprinted with permission from Ref. [<a href="#B27-materials-16-03249" class="html-bibr">27</a>]. Copyright 2002, Elsevier.</p> Full article ">Figure 3
<p>Schematic model of crystallite size effect on the sensitivity of MOS gas sensors: (<b>a</b>) D ≫ 2L, (<b>b</b>) D ≥ 2L, and (<b>c</b>) D &lt; 2L. Reprinted with permission from Ref. [<a href="#B31-materials-16-03249" class="html-bibr">31</a>]. Copyright 2022, Elsevier.</p> Full article ">Figure 4
<p>Performance of the CuO sensor: (<b>a</b>) The repeatability results for the CO gas-sensing response at 300 °C: run #1 and (<b>b</b>) run #2. (<b>c</b>) Reaction ratio for CO gas concentrations of 1000 and 5000 ppm. Reprinted with permission from Ref. [<a href="#B12-materials-16-03249" class="html-bibr">12</a>]. Copyright 2019, The Royal Society of Chemistry.</p> Full article ">Figure 5
<p>Photo-activated gas-sensing mechanism under UV irradiation.</p> Full article ">Figure 6
<p>(<b>a</b>) Response transients of SnO₂ sensor to 5 ppm NO₂ at 30 °C in dry air under different UV-light irradiation intensities. (<b>b</b>) 90% response (T_RS (90), open symbols) and 10% recovery times (T_RC (10), filled symbols) of SnO₂ sensor with UV-light intensity, together with those of In₂O₃ and WO₃ sensors. Reprinted with permission from Ref. [<a href="#B69-materials-16-03249" class="html-bibr">69</a>]. Copyright 2017, Elsevier. (<b>c</b>) Response and recovery curves of rGO-CeO₂ sensor to 10 ppm NO₂ with or without 365 nm UV-light irradiation and (<b>d</b>) comparison of different recovery methods. Reprinted with permission from Ref. [<a href="#B70-materials-16-03249" class="html-bibr">70</a>]. Copyright 2018, Elsevier. (<b>e</b>) The response (communally) and recovery curves toward 5 ppm NO₂ at room temperature of the In₂O₃ sensor in dark or under visible light irradiation with increasing intensity. The illustration displayed the variation trend of the recovery time and the first recording resistance in recovery with increasing light intensity. In the illustration, a larger blue symbol represents a stronger light. Reprinted with permission from Ref. [<a href="#B71-materials-16-03249" class="html-bibr">71</a>]. Copyright 2021, Elsevier.</p> Full article ">Figure 7
<p>Characterization using (<b>a</b>–<b>c</b>) TEM images and (<b>d</b>–<b>f</b>) AFM graphs of BP-4000 (<b>a</b>,<b>d</b>), BP-7000 (<b>b</b>,<b>e</b>), and BP-12,000 (<b>c</b>,<b>f</b>) samples. (<b>g</b>) dynamic response of BP-12,000 under 1000 ppb NO₂ exposure showing complete recovery over eight cycles. Reprinted with permission from Ref. [<a href="#B78-materials-16-03249" class="html-bibr">78</a>]. Copyright 2020, American Chemical Society.</p> Full article ">Figure 8
<p>The typical FESEM images (<b>a</b>,<b>b</b>) In₂O₃ hierarchical architectures. The inset is the TEM image of In₂O₃ hierarchical architectures. (<b>c</b>) Transient responses of In₂O₃ hierarchical architectures to 100 ppm formaldehyde at 260 °C. Reprinted with permission from Ref. [<a href="#B86-materials-16-03249" class="html-bibr">86</a>]. Copyright 2018, Elsevier. SEM images of (<b>d</b>,<b>e</b>) 0.3% Pt–SnO₂. Reprinted with permission from Ref. [<a href="#B87-materials-16-03249" class="html-bibr">87</a>]. Copyright 2020, Elsevier. (<b>f</b>) SEM of porous flower-like α-Fe₂O₃ with 70 mL ethylene glycol. (<b>g</b>) Response and recovery curve of α-Fe₂O₃ with 70 mL ethylene glycol to 100 ppm acetone at operating temperature 210 °C. Reprinted with permission from Ref. [<a href="#B40-materials-16-03249" class="html-bibr">40</a>]. Copyright 2020, Springer. (<b>h</b>) FESEM images of the cedar-like SnO₂ micro-nanostructure. (<b>i</b>) The transient response of cedar-like SnO₂ sensors exhibits to 100 ppm formaldehyde at 200 °C. Reprinted with permission from Ref. [<a href="#B88-materials-16-03249" class="html-bibr">88</a>]. Copyright 2017, Elsevier. Typical FESEM image of (<b>j</b>) Zn-doped layered SnO₂ nanocones sample. (insets) Schematic illustration of the structure unit of the sample. (<b>k</b>) The transient response and recovery times of the Zn-doped layered SnO₂ sensor toward three different concentrations of TEA (100 ppb, 10 ppm, and 100 ppm) at 70 °C, 57% RH. Reprinted with permission from Ref. [<a href="#B89-materials-16-03249" class="html-bibr">89</a>]. Copyright 2020, American Chemical Society.</p> Full article ">Figure 9
<p>SEM images, TEM images of 5 wt% La-doped SnO₂ nanocomposite (<b>a</b>,<b>b</b>). (<b>c</b>) Dynamic response-recovery curves of pure and 5 wt% La-doped SnO₂ against 75 ppm methanol at 220 °C. Reprinted with permission from Ref. [<a href="#B98-materials-16-03249" class="html-bibr">98</a>]. Copyright 2020, Springer. (<b>d</b>) SEM images of ZnO:Ag thin films with 5 wt% Ag doping. (<b>e</b>) Response time and recovery time of ZnO:Ag (0–5%) thin film deposited on a glass substrate with exposure and removal of NH₃ gas of 25 ppm concentration. Reprinted with permission from Ref. [<a href="#B99-materials-16-03249" class="html-bibr">99</a>]. Copyright 2020, Elsevier.</p> Full article ">Figure 10
<p>Schematic illustrations of (<b>a</b>) energy band structure and (<b>b</b>) NO₂ adsorption for the 2D/2D SnS₂/SnSe₂-2 heterostructure. (<b>c</b>) Response and (<b>d</b>) response and recovery times of SnS₂/SnSe₂–M, SnS₂/SnSe₂–S, and SnS₂/SnSe₂-2 heterostructures toward 4 ppm NO₂ at room temperature. Reprinted with permission from Ref. [<a href="#B108-materials-16-03249" class="html-bibr">108</a>]. Copyright 2022, The Royal Society of Chemistry. (<b>e</b>) Response/recovery time of SnO₂/WSe₂, WSe_2, and SnO₂ sensors upon exposure to 1 ppm NH₃. (<b>f</b>) Energy-band structure of the SnO₂/WSe₂ sensor in air and NH₃ gas (Ec, Eg, Ev, and Ef are the bottom of the conduction band, band gap, top of the valence band, and the fermi-energy level). (<b>g</b>) Illustration of NH₃ sensing mechanism for SnO₂/WSe₂ nanocomposite. Reprinted with permission from Ref. [<a href="#B111-materials-16-03249" class="html-bibr">111</a>]. Copyright 2022, Elsevier.</p> Full article ">Figure 11
<p>(<b>a</b>) Real-time resistance curves of SnO₂-rGO, SnS₂, SnO₂/SnS₂, and SnO₂-rGO/SnS₂ sensors under 10 ppm NO₂ at 120 °C for comparison. Schematic illustration of charge transfer difference between (<b>b</b>) SnO₂-rGO/SnS₂ sensor with novel n-g-n heterojunctions and (<b>c</b>) SnO₂/SnS₂ sensor with traditional n-n junctions. Reprinted with permission from Ref. [<a href="#B116-materials-16-03249" class="html-bibr">116</a>]. Copyright 2021, Elsevier. (<b>d</b>) TEM image of Ag@WO₃ core-shell nanostructures with the core and the shell clearly resolved. Transient response at different temperatures for sensors using 100 ppm alcohol vapor exposure. The upper-right inset in each Figure shows corresponding response and recovery curves for the senor at its optimum working temperature. (<b>e</b>) Pure WO₃, (<b>f</b>) Ag–WO₃ mixture, and (<b>g</b>) Ag@WO₃. Reprinted with permission from Ref. [<a href="#B107-materials-16-03249" class="html-bibr">107</a>]. Copyright 2015, Elsevier.</p> Full article ">Figure 12
<p>(<b>a</b>,<b>b</b>) TEM and HRTEM images of CdS QD/Co₃O₄ synthesized by in situ growth method at 25 °C. Performance of the CdS QD/Co₃O₄ sensor: (<b>c</b>) The response curve of the sensor to 100 ppm H₂S at 25 °C, (<b>d</b>) Response and recovery times of the sensor to H₂S at concentrations ranging from 1 to 100 ppm. Reprinted with permission from Ref. [<a href="#B36-materials-16-03249" class="html-bibr">36</a>]. Copyright 2019, Elsevier. (<b>e</b>) Dynamic response–recovery curves of MoS₂ and MoS₂/PbS gas sensors without a heating device at 5–400 ppm NO₂ concentrations. (<b>f</b>,<b>g</b>) TEM images of MoS₂/PbS composites. Reprinted with permission from Ref. [<a href="#B124-materials-16-03249" class="html-bibr">124</a>]. Copyright 2019, American Chemical Society.</p> Full article ">Figure 13
<p>Performance of the N-MXene sensor: (<b>a</b>) humidity effect on sensor response toward 1 ppm of NH₃. Reprinted with permission from Ref. [<a href="#B175-materials-16-03249" class="html-bibr">175</a>]. Copyright 2021, American Chemical Society. (<b>b</b>) Schematic image of the gas-sensing chamber for enhanced WSe₂ recovery. Gas delivery comprised NO₂ at 500 ppm exposure (500 sccm) and mixed gas (NH₃ and N₂) purging (500 sccm). (<b>c</b>) Recovery time comparison of WSe₂ sensor toward 500 ppm NO₂ at different conditions: N₂ purging @ RT, N₂ purging @ 100 °C and NH₃ and N₂ mixed @RT (<b>d</b>) Schematic image of WSe₂ sensor recovery for NO₂ absorption and desorption using NH₃ and N₂ mixed purging gas. Reprinted with permission from Ref. [<a href="#B177-materials-16-03249" class="html-bibr">177</a>]. Copyright 2018, American Chemical Society.</p> Full article ">

11 pages, 3959 KiB  

Open AccessArticle

Nanoporous Graphene Oxide-Based Quartz Crystal Microbalance Gas Sensor with Dual-Signal Responses for Trimethylamine Detection

by Guangyu Qi, Fangfang Qu, Lu Zhang, Shihao Chen, Mengyuan Bai, Mengjiao Hu, Xinyan Lv, Jinglei Zhang, Zhenhe Wang and Wei Chen

Sensors 2022, 22(24), 9939; https://doi.org/10.3390/s22249939 - 16 Dec 2022

Cited by 6 | Viewed by 2337

Abstract

This paper presents a straightforward method to develop a nanoporous graphene oxide (NGO)-functionalized quartz crystal microbalance (QCM) gas sensor for the detection of trimethylamine (TMA), aiming to form a reliable monitoring mechanism strategy for low-concentration TMA that can still cause serious odor nuisance. [...] Read more.

This paper presents a straightforward method to develop a nanoporous graphene oxide (NGO)-functionalized quartz crystal microbalance (QCM) gas sensor for the detection of trimethylamine (TMA), aiming to form a reliable monitoring mechanism strategy for low-concentration TMA that can still cause serious odor nuisance. The synthesized NGO material was characterized by transmission electron microscopy, X-ray photoelectron spectroscopy, and Fourier transform infrared spectroscopy to verify its structure and morphology. Compared with the bare and GO-based QCM sensors, the NGO-based QCM sensor exhibited ultra-high sensitivity (65.23 Hz/μL), excellent linearity (R² = 0.98), high response/recovery capability (3 s/20 s) and excellent repeatability (RSD = 0.02, n = 3) toward TMA with frequency shift and resistance. Furthermore, the selectivity of the proposed NGO-based sensor to TMA was verified by analysis of the dual-signal responses. It is also proved that increasing the conductivity did not improve the resistance signal. This work confirms that the proposed NGO-based sensor with dual signals provides a new avenue for TMA sensing, and the sensor is expected to become a potential candidate for gas detection. Full article

(This article belongs to the Topic Nanomaterial Based Gas Sensors for Environmental Air Pollutant Detection)

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Figure 1

Figure 1
<p>Schematic diagram of detection based on functionalized QCM sensor chip.</p> Full article ">Figure 2
<p>Characteristics analysis of GO/NGO. (<b>a</b>) TEM image (inserted panel shows synthesized powder) of GO, (<b>b</b>) TEM image (inserted panel shows synthesized powder) of NGO, (<b>c</b>) TEM image of Au NPs, (<b>d</b>) FT-IR spectra of GO and NGO, and (<b>e</b>) XPS spectra of GO and NGO.</p> Full article ">Figure 3
<p>Dynamic responses of QCM sensor to gas vapors. (<b>a</b>) Influence of different nitrogen flow rates on the QCM sensor, (<b>b</b>) the bare QCM sensor to TMA, and (<b>c</b>) the GO-based QCM sensor to TMA and nitrogen.</p> Full article ">Figure 4
<p>Sensing characteristics of QCM sensors to gas vapors. (<b>a</b>) The GO-based QCM sensor, and (<b>b</b>) the NGO-based QCM sensor.</p> Full article ">Figure 5
<p>Sensing performances of QCM sensors for TMA detection. (<b>a</b>) Frequency and resistance response curves of the GO-based QCM sensor, (<b>b</b>) frequency and resistance response curves of the NGO-based QCM sensor, (<b>c</b>) response amplitude regression curves of the GO-based QCM sensor, and (<b>d</b>) response amplitude regression curves of the NGO-based QCM sensor.</p> Full article ">Figure 6
<p>Selectivity of GO and NGO-functionalized QCM sensors to different gases. (<b>a</b>) Frequency response of the GO-based QCM sensor, (<b>b</b>) frequency response of the NGO-based QCM sensor, (<b>c</b>) resistance response of the NGO-based QCM sensor, (<b>d</b>) response amplitude regression curves of the NGO/Au Nps-based QCM sensor, (<b>e</b>) response amplitude regression curves of the NGO/Ag Nps-based QCM sensor, and (<b>f</b>) response amplitude regression curves of the GO/Ag Nps-based QCM sensor.</p> Full article ">

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