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Advanced Micro- and Nano-Gas Sensors Materials, Devices and Applications

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A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Sensor Materials".

Deadline for manuscript submissions: closed (31 December 2022) | Viewed by 11693

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Special Issue Editors

Prof. Dr. Takeshi Hashishin

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Guest Editor

Faculty of Advanced Science and Technology, Kumamoto University, 2-39-1 Kurokami, Chuo-ku, Kumamoto 860-8555, Japan
Interests: electronic materials; hydrothermal and electrochemical micro/nano design; fabrication of electrodes; electro/electroless plating; gas detection; probing

Prof. Dr. Dzung Viet Dao

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Guest Editor

Mechatronics Engineering Program, School of Engineering and Built Environment, Griffith University, Parklands Drive, Southport, QLD 4222, Australia
Interests: micro/nano machining technology; nanostructured materials and nanoscale sensors; silicon and silicon carbide MEMS sensors; harsh environment sensors; polymer-MEMS; optical-MEMS

Special Issue Information

Dear Colleagues,

This Special Issue deals with the advanced content of micro/nano-sized material development for gas sensors and device development for its application. Specifically, this issue is focused on the following research topics: (1) morphological and structural control of nano- and micro-sized materials with 1-dimensional wire, 2-dimensional sheet, and 3-dimensional hierarchical structure; (2) fabrication of device electrodes using MEMS and NEMS; (3) gas sensing properties for ppb–ppm gases and selective gas detection using the techniques (1) and (2); (4) methane emission control and environmental monitoring rooted in low environmental load; and (5) medical applications such as healthcare.

All researchers conducting research in the area of “Advanced Micro- and Nano-Gas Sensor Materials, Devices, and Applications” and who have results that contribute to the further development of the field are invited to participate in our project. You can contribute both original research papers and reviews to this Special Issue.

Prof. Dr. Takeshi Hashishin

Prof. Dr. Dzung Viet Dao
Guest Editor

Manuscript Submission Information

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Keywords

Gas sensor
Morphological and structural control
Sensing element
Semiconductor
Oxides
Carbon
Defects
Materials/device design
Micro/nano electromechanical systems
Electrodes
ppb–ppm detection
Environmental monitoring
Healthcare

Published Papers (6 papers)

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Research

13 pages, 5000 KiB

Open AccessArticle

Humidity Sensitivity of Chemically Synthesized ZnAl₂O₄/Al

by Takayuki Nakane, Takashi Naka, Minako Nakayama and Tetsuo Uchikoshi

Sensors 2022, 22(16), 6194; https://doi.org/10.3390/s22166194 - 18 Aug 2022

Cited by 2 | Viewed by 1170

Abstract

Humidity sensitivity is evaluated for chemically synthesized ZnAl₂O₄/Al devices. We succeeded in synthesizing the ZnAl₂O₄/Al device by applying chemical techniques only. Hydrothermal treatment for the anodized aluminum (AlO_x/Al) gives us the device of the ZnAl₂O₄/Al structure. All fabrication processes were conducted under 400 °C. The key was focusing on ZnAl₂O₄ as the sensing material instead of MgAl₂O₄, which is generally investigated as the humidity sensor. The evaluation of this ZnAl₂O₄/Al device clarified its effectiveness as a sensor. Both electrical capacitance, C_p, and the resistivity, R_p, measured by an LCR meter, obviously responded to the humidity with good sensitivity and appreciable repeatability. Our synthesis technique is possible in principle to improve on the process for the device with a complex structure providing a large surface area. These characteristics are believed to expand the application study of spinel aluminate devices as the sensor. Full article

(This article belongs to the Special Issue Advanced Micro- and Nano-Gas Sensors Materials, Devices and Applications)

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10 pages, 5654 KiB

Open AccessArticle

VOC Detections by p-Type Semiconducting Sensors Using Nano-Sized SmFeO₃ Particles

by Masami Mori, Ayumu Noguchi and Yoshiteru Itagaki

Sensors 2022, 22(15), 5616; https://doi.org/10.3390/s22155616 - 27 Jul 2022

Cited by 1 | Viewed by 1160

Abstract

Nano-sized SmFeO₃ particles are prepared by the pyrolysis of heteronuclear cyano-complex, Sm[Fe(CN)₆]·4H₂O at a temperature of 600 °C in ozone. The low temperature decomposition followed in ozone successfully yielded fine particles with a high specific surface area of 20.0 m³/g (sample A). The fine particles were classified into further smaller particles with a unimodal size distribution and this process yielded a high specific surface area of 26.0 m³/g (sample B). These semiconducting powders were deposited on a sensor electrode by electrophoretic deposition (EPD) and tested on their sensing properties to VOCs. The sensors consisting of samples A and B both showed good responses to ethanol at 285 and 320 °C. The sensor with sample B showed extraordinarily good selectivity of ethanol for toluene at 320 °C. This could be because the detection film of sample B with moderately grown particles selectively reduced the reaction activity of toluene. The sensor with sample B also exhibited good selectivity of ethanol for hexane and dichloromethane. Full article

(This article belongs to the Special Issue Advanced Micro- and Nano-Gas Sensors Materials, Devices and Applications)

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13 pages, 2063 KiB

Open AccessArticle

Useful High-Entropy Source on Spinel Oxides for Gas Detection

by Takeshi Hashishin, Haruka Taniguchi, Fei Li and Hiroya Abe

Sensors 2022, 22(11), 4233; https://doi.org/10.3390/s22114233 - 1 Jun 2022

Cited by 4 | Viewed by 2344

Abstract

This study aimed to identify a useful high-entropy source for gas detection by spinel oxides that are composed of five cations in nearly equal molar amounts and free of impurities. The sensor responses of the spinel oxides [1# (CoCrFeMnNi)₃O₄, 2# (CoCrFeMnZn)₃O₄, 3# (CoCrFeNiZn)₃O₄, 4# (CoCrMnNiZn)₃O₄, 5# (CoFeMnNiZn)₃O₄, and 6# (CrFeMnNiZn)₃O₄] were evaluated for the test gases (7 ppm NO₂, 5000 ppm H₂, 3 ppm NH₃, and 3 ppm H₂S). In response to NO₂, 1# and 2# showed p-type behavior while 3–6# showed n-type semiconductor behavior. There are three p-type and one n-type AO structural compositions in AB₂O₄[AO·B₂O₃] type spinel, and 1# showed a stable AO composition because cation migration from site B to site A is unlikely. Therefore, it was assumed that 1# exhibited p-type behavior. The p-type behavior of 2# was influenced by Cr oxide ions that were present at the B site and the stable p-type behavior of zinc oxide at the A site. The spinel oxides 3# to 6# exhibited n-type behavior with the other cationic oxides rather than the dominant p-type behavior exhibited by the Zn oxide ions that are stable at the A site. In contrast, the sensor response to the reducing gases H₂, NH₃, and H₂S showed p-type semiconductor behavior, with a particularly selective response to H₂S. The sensor responses of the five-element spinel oxides in this study tended to be higher than that of the two-element Ni ferrites and three-element Ni-Zn ferrites reported previously. Additionally, the susceptibility to sulfurization was evaluated using the thermodynamic equilibrium theory for the AO and B₂O₃ compositions. The oxides of Cr, Fe, and Mn ions in the B₂O₃ composition did not respond to H₂S because they were not sulfurized. The increase in the sensor response due to sulfurization was attributed to the decrease in the depletion layer owing to electron sensitization, as the top surface of the p-type semiconductors, ZnO and NiO, transformed to n-type semiconductors, ZnS and NiS, respectively. High-entropy oxides prepared using the hydrothermal method with an equimolar combination of five cations from six elements (Cr, Mn, Fe, Co, Ni, and Zn) can be used as a guideline for the design of high-sensitivity spinel-type composite oxide gas sensors. Full article

(This article belongs to the Special Issue Advanced Micro- and Nano-Gas Sensors Materials, Devices and Applications)

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10 pages, 2902 KiB

Open AccessArticle

Low-Dimensional Palladium on Graphite-on-Paper Substrate for Hydrogen Sensing

by Boyi Wang, Takeshi Hashishin, Dzung Viet Dao and Yong Zhu

Sensors 2022, 22(10), 3926; https://doi.org/10.3390/s22103926 - 22 May 2022

Viewed by 1259

Abstract

To stabilize the detection signal of palladium-based hydrogen sensors on paper substrates, a graphite intermediate layer was painted on the surface of paper. The graphite-on-paper (GOP) substrate offers advantages such as good thermo-electrical conductivity, low cost, and uncomplicated preparation technology. Quasi-1-dimensional palladium (Pd) thin films with 8 nm and 60 nm thicknesses were deposited on the GOP substrates using the vacuum evaporation technique. Thanks to the unique properties of the GOP substrate, a continuous Pd microfiber network structure appeared after deposition of the ultra-thin Pd film. Additionally, the sensing performance of the palladium-based hydrogen sensor was not affected, whether using GOP or paper substrate at 25 °C. Surprisingly, heating-induced loss of sensitivity was restrained due to the increased electrical conductivity of the GOP substrate at 50 °C. Full article

(This article belongs to the Special Issue Advanced Micro- and Nano-Gas Sensors Materials, Devices and Applications)

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14 pages, 4944 KiB

Open AccessArticle

Electrochemical Detection of Ethanol in Air Using Graphene Oxide Nanosheets Combined with Au-WO₃

by Aynul Sakinah Ahmad Fauzi, Nur Laila Hamidah, Shota Kitamura, Taiga Kodama, Kosuke Sonda, Ghina Kifayah Putri, Takeshi Shinkai, Muhammad Sohail Ahmad, Yusuke Inomata, Armando T. Quitain and Tetsuya Kida

Sensors 2022, 22(9), 3194; https://doi.org/10.3390/s22093194 - 21 Apr 2022

Cited by 10 | Viewed by 2479

Abstract

Detection, monitoring, and analysis of ethanol are important in various fields such as health care, food industries, and safety control. In this study, we report that a solid electrolyte gas sensor based on a proton-conducting membrane is promising for detecting ethanol in air. We focused on graphene oxide (GO) as a new solid electrolyte because it shows a high proton conductivity at room temperature. GO nanosheets are synthesized by oxidation and exfoliation of expanded graphite via the Tour’s method. GO membranes are fabricated by stacking GO nanosheets by vacuum filtration. To detect ethanol, Au-loaded WO₃ is used as the sensing electrode due to the excellent activity of gold nanoparticles for the catalysis of organic molecules. Au-WO₃ is coupled with rGO (reduced graphene oxide) to facilitate the electron transport in the electrode. Ce ions are intercalated into the GO membrane to facilitate proton transport. The sensor based on the Ce doped-GO membrane combined with Au-WO₃/rGO as a sensing electrode shows good electric potential difference (ΔV) responses to ethanol in the air at room temperature. The sensor signal reaches more than 600 mV in response to ethanol at 40 ppm in air, making it possible to detect ethanol at a few ppb (parts per billion) level. The ethanol sensing mechanism was discussed in terms of the mixed-potential theory and catalysis of ethanol on Au-WO₃. Full article

(This article belongs to the Special Issue Advanced Micro- and Nano-Gas Sensors Materials, Devices and Applications)

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16 pages, 3213 KiB

Open AccessArticle

Balanced Distribution Adaptation for Metal Oxide Semiconductor Gas Sensor Array Drift Compensation

by Zongze Jiang, Peng Xu, Yongbin Du, Feng Yuan and Kai Song

Sensors 2021, 21(10), 3403; https://doi.org/10.3390/s21103403 - 13 May 2021

Cited by 8 | Viewed by 2240

Abstract

Drift compensation is an important issue for metal oxide semiconductor (MOS) gas sensor arrays. General machine learning methods require constant calibration and a large amount of label gas data. At the same time, recalibration will cause a lot of costs, and label gas is difficult to obtain in practice. In this paper, a novel drift compensation method based on balanced distribution adaptation (BDA) is proposed. First, the BDA drift compensation method can adjust the conditional distribution and marginal distribution between the two domains through the weight balance factor, thereby more effectively reducing the mismatch between the two domains. When the BDA method performs classification tasks through machine learning, no labeled data is required in the target domain. Then, the particle swarm optimization algorithm is used to improve the accuracy of drift compensation. Individuals in the population are initialized randomly, and their fitness values are calculated. Iterative optimization of the population individuals is conducted until the optimal weight balance factor parameters are calculated. Finally, the BDA method is experimentally verified on the public gas sensor drift data set. Experimental results showed that the BDA method was significantly better than the existing joint distribution adaptation (JDA) method and other standard drift compensation methods such as K-Nearest Neighbor (KNN). In the two setting groups, the recognition accuracy was 4.54% and 1.62% ahead of the JDA method, and 12.23% and 15.83% ahead of the KNN method. Full article

(This article belongs to the Special Issue Advanced Micro- and Nano-Gas Sensors Materials, Devices and Applications)

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