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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 2019) | Viewed by 61712

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Dr. Qiliang Li

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College of Engineering and Computing, George Mason University, Fairfax, VA 22030, USA
Interests: wide-bandgap semiconductor; sensors; nanoelectronics; artificial intelligence
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Gas sensors and smart sensing systems are critical for the emerging Internet-of-things era and rising awareness of environment monitoring. The research and development of gas sensors are focused on achieving high sensitivity and precise discrimination at a variety of testing conditions. The recent approaches on the sensor performance optimization include new functional materials, designing new device structures, advanced feature analysis and new algorithms, violet light to activate charge carriers, heating the sensors, decoration with gas absorbing layers, cross-reactive sensor arrays, and so on. In addition, the research on integrating gas sensors and arrays into a small system for smart sensing is gaining intensive interest for environment monitoring, target tracking and remote sensing. This Special Issue aims to solicit original research papers, as well as review articles, with a focus on theoretical and experimental approaches on smart gas sensors and sensing systems. The list of topics includes, but is not limited to

Preparation of sensing materials
Nanowires and nanoparticles for gas sensors
Feature analysis for precise gas detection
Cross-reactive sensors and sensor arrays
Gas sensors based on conventional semiconductors
Metal oxides for chemical detection
Polymers for gas sensing
Two-dimensional materials for gas sensors
Sensors in harsh conditions
Reliability issues in gas sensing
Simulation of gas sensing and smart systems
Integration of gas sensors with smart systems
Sensor application in IOT technology
Sensors in Robotics
New applications of gas sensors and sensing systems

Dr. Qiliang Li
Guest Editor

Manuscript Submission Information

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Keywords

gas sensors
smart sensing systems
functional materials
graphene
semiconductors
metal oxides
feature analysis
cross-reactive sensing

Published Papers (11 papers)

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Research

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12 pages, 5289 KiB

Open AccessArticle

A limiting Current Oxygen Sensor Constituted of (CeO₂)_0.95(Y₂O₃)_0.05 as Solid Electrolyte Layer and (CeO₂)_0.75(ZrO₂)_0.25 as Dense Diffusion Barrier Layer

by Xiangnan Wang, Tao Liu and Jingkun Yu

Sensors 2019, 19(16), 3511; https://doi.org/10.3390/s19163511 - 10 Aug 2019

Cited by 6 | Viewed by 3016

Abstract

Using the co-precipitation method to synthesize (CeO₂)_0.95(Y₂O₃)_0.05 (YDC) and solid reaction method to synthesize (CeO₂)_0.75(ZrO₂)_0.25 (ZDC), and the crystal structure, micro-structure, total conductivity and electronic conductivity of the two materials was measured with X-ray diffraction (XRD), scanning electron microscope (SEM), DC van der Pauw and Hebb-Wagner methods. A limiting current oxygen sensor was prepared with YDC solid electrolyte and a ZDC dense diffusion barrier layer by employing platinum pasting bonding. Sensing characteristics of the sensor were obtained at different conditions, including temperature (T), oxygen concentration (x(O₂)) and water vapor pressure (p(H₂O)), and the influence of various conditions on sensing performance was studied. The long-term stability of the sensor was measured in an oxygen concentration of 1.2% and at a temperature of 800 °C for 120 h. XRD results show that the phase structure of both YDC and ZDC belongs to the cubic phase. SEM results show that both YDC and ZDC layers are dense layers, which are then qualified to be the composition materials of the sensor. The limiting current (I_L) of the sensor is obtained and the sensor exhibits good sensing characteristics to satisfy the Knudsen model. Log(I_L·T) depends linearly on 1000/T with a squared correlation coefficient (R²) of 0.9904; I_L depends linearly on x(O₂) with an R² of 0.9726; and sensing characteristics are not affected by p(H₂O). It was found that the oxygen sensor has good long-term stability. Full article

(This article belongs to the Special Issue Gas Sensors and Smart Sensing Systems)

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13 pages, 2044 KiB

Open AccessArticle

Real-Time Ozone Sensor Based on Selective Oxidation of Methylene Blue in Mesoporous Silica Films

by Christelle Ghazaly, Marc Hébrant, Eddy Langlois, Blandine Castel, Marianne Guillemot and Mathieu Etienne

Sensors 2019, 19(16), 3508; https://doi.org/10.3390/s19163508 - 10 Aug 2019

Cited by 8 | Viewed by 3624

Abstract

Sensitive and selective personal exposure monitors are needed to assess ozone (O₃) concentrations in the workplace atmosphere in real time for the analysis and prevention of health risks. Here, a cumulative gas sensor using visible spectroscopy for real-time O₃ determination is described. The sensing chip is a mesoporous silica thin film deposited on transparent glass and impregnated with methylene blue (MB). The sensor is reproducible, stable for at least 50 days, sensitive to 10 ppb O₃ (one-tenth of the occupational exposure limit value in France, Swiss, Canada, U.K., Japan, and the USA) with a measurement range tested up to 500 ppb, and insensitive to NO₂ and to large variation in relative humidity. A model and its derivative as a function of time are proposed to convert in real time the sensor response to concentrations, and an excellent correlation was obtained between those data and reference O₃ concentrations. This sensor is based on a relatively cheap sensing material and a robust detection system, and its analytical performance makes it suitable for monitoring real-time O₃ concentrations in workplaces to promote a safer environment for workers. Full article

(This article belongs to the Special Issue Gas Sensors and Smart Sensing Systems)

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10 pages, 2280 KiB

Open AccessArticle

Tuning the Polarity of MoTe₂ FETs by Varying the Channel Thickness for Gas-Sensing Applications

by Asha Rani, Kyle DiCamillo, Md Ashfaque Hossain Khan, Makarand Paranjape and Mona E. Zaghloul

Sensors 2019, 19(11), 2551; https://doi.org/10.3390/s19112551 - 04 Jun 2019

Cited by 34 | Viewed by 5079

Abstract

In this study, electrical characteristics of MoTe₂ field-effect transistors (FETs) are investigated as a function of channel thickness. The conductivity type in FETs, fabricated from exfoliated MoTe₂ crystals, switched from p-type to ambipolar to n-type conduction with increasing MoTe₂ channel thickness from 10.6 nm to 56.7 nm. This change in flake-thickness-dependent conducting behavior of MoTe₂ FETs can be attributed to modulation of the Schottky barrier height and related bandgap alignment. Change in polarity as a function of channel thickness variation is also used for ammonia (NH₃) sensing, which confirms the p- and n-type behavior of MoTe₂ devices. Full article

(This article belongs to the Special Issue Gas Sensors and Smart Sensing Systems)

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11 pages, 3918 KiB

Open AccessArticle

Fingerprinting of Nitroaromatic Explosives Realized by Aphen-functionalized Titanium Dioxide

by Guanshun Xie and Bingxin Liu

Sensors 2019, 19(10), 2407; https://doi.org/10.3390/s19102407 - 27 May 2019

Cited by 6 | Viewed by 3256

Abstract

Developing sensing materials for military explosives and improvised explosive precursors is of great significance to maintaining homeland security. 5-Nitro-1,10-phenanthroline (Aphen)-modified TiO₂ nanospheres are prepared though coordination interactions, which broaden the absorption band edge of TiO₂ and shift it to the visible region. A sensor array based on an individual TiO₂/Aphen sensor is constructed by regulating the excitation wavelength (365 nm, 450 nm, 550 nm). TiO₂/Aphen shows significant response to nitroaromatic explosives since the Aphen capped on the surface of TiO₂ can chemically recognize and absorb nitroaromatic explosives by the formation of the corresponding Meisenheimer complex. The photocatalytic mechanism is proved to be the primary sensing mechanism after anchoring nitroaromatic explosives to TiO₂. The fingerprint patterns obtained by combining kinetics and thermodynamics validated that the single TiO₂/Aphen sensor can identify at least six nitroaromatic explosives and improvised explosives within 8 s and the biggest response reaches 80%. Furthermore, the TiO₂/Aphen may allow the contactless detection of various explosives, which is of great significance to maintaining homeland security. Full article

(This article belongs to the Special Issue Gas Sensors and Smart Sensing Systems)

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14 pages, 6509 KiB

Open AccessArticle

Preparation and Characterization of Developed Cu_xSn_1−xO₂ Nanocomposite and Its Promising Methane Gas Sensing Properties

by Nagih M. Shaalan, Dalia Hamad, Abdullah Aljaafari, Atta Y. Abdel-Latief and Mostafa A. Abdel-Rahim

Sensors 2019, 19(10), 2257; https://doi.org/10.3390/s19102257 - 16 May 2019

Cited by 24 | Viewed by 2877

Abstract

Novel materials with nanostructures are effective in controlling the physical properties needed for specific applications. The use of active and sensing materials is increasing in many applications, such as gas sensing. In the present work, we attempted to synthesize incorporated Cu²⁺ into the SnO₂ matrix as Cu_xSn_1−xO₂ nanocomposite using a cost-effective precursor and method. It was observed that, at low concentrations of copper precursor, only SnO₂ phase could be detected by X-ray diffraction (XRD)_. The distribution of Cu in the SnO₂ matrix was further measured by elemental analysis of energy-dispersive X-ray (EDX) mapping and X-ray fluorescence (XRF). At high copper concentration, a separated monoclinic phase of CuO was formed (noted here as CuO/SnO₂). The average crystallite size was slightly reduced from 5.9 nm to 4.7 nm with low doping of 0.00–5.00% Cu but increased up to 15.0 nm at high doping of 10.00% Cu upon the formation of separated SnO₂ and CuO phases. The formation of Cu–SnO₂ or CuO phases at low and high concentrations was also observed by photoluminescent spectra. Here, only the emission peak of SnO₂ with a slight blueshift was recorded at low concentrations, while only the CuO emission peak was recorded at high concentration. The effect of Cu concentration on the sensing properties of SnO₂ toward methane (CH₄) gas was also investigated. It was found that the sensor embedded with 2.00% Cu exhibited an excellent sensitivity of 69.0 at 350 °C and a short response–recovery time compared with the other sensors reported here. The sensing mechanism of Cu_xSn_1−xO₂ and CuO/SnO₂ is thus proposed based on Cu incorporation. Full article

(This article belongs to the Special Issue Gas Sensors and Smart Sensing Systems)

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12 pages, 3312 KiB

Open AccessArticle

Autonomous Visual Perception for Unmanned Surface Vehicle Navigation in an Unknown Environment

by Wenqiang Zhan, Changshi Xiao, Yuanqiao Wen, Chunhui Zhou, Haiwen Yuan, Supu Xiu, Yimeng Zhang, Xiong Zou, Xin Liu and Qiliang Li

Sensors 2019, 19(10), 2216; https://doi.org/10.3390/s19102216 - 14 May 2019

Cited by 32 | Viewed by 3584

Abstract

Robust detection and recognition of water surfaces are critical for autonomous navigation of unmanned surface vehicles (USVs), since any none-water region is likely an obstacle posing a potential danger to the sailing vehicle. A novel water region visual detection method is proposed in this paper. First, the input image pixels are clustered into different regions and each pixel is assigned a label tag and a confidence value by adaptive multistage segmentation algorithm. Then the resulting label map and associated confidence map are fed into a convolutional neural network (CNN) as training samples to train the network online. Finally, the online trained CNN is used to segment the input image again but with greater precision and stronger robustness. Compared with other deep-learning image segmentation algorithms, the proposed method has two advantages. Firstly, it dispenses with the need of manual labeling training samples which is a costly and painful task. Secondly, it allows real-time online training for CNN, making the network adaptive to the navigational environment. Another contribution of this work relates to the training process of neuro network. An effective network training method is designed to learn from the imperfect training data. We present the experiments in the lake with a various scene and demonstrate that our proposed method could be applied to recognize the water region in the unknown navigation environment automatically. Full article

(This article belongs to the Special Issue Gas Sensors and Smart Sensing Systems)

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12 pages, 2746 KiB

Open AccessArticle

Gas Sensors Based on Mechanically Exfoliated MoS₂ Nanosheets for Room-Temperature NO₂ Detection

by Wenli Li, Yong Zhang, Xia Long, Juexian Cao, Xin Xin, Xiaoxiao Guan, Jinfeng Peng and Xuejun Zheng

Sensors 2019, 19(9), 2123; https://doi.org/10.3390/s19092123 - 08 May 2019

Cited by 76 | Viewed by 9547

Abstract

The unique properties of MoS₂ nanosheets make them a promising candidate for high-performance room temperature gas detection. Herein, few-layer MoS₂ nanosheets (FLMN) prepared via mechanical exfoliation are coated on a substrate with interdigital electrodes for room-temperature NO₂ detection. Interestingly, compared with other NO₂ gas sensors based on MoS₂, FLMN gas sensors exhibit high responsivity for room-temperature NO₂ detection, and NO₂ is easily desorbed from the sensor surface with an ultrafast recovery behavior, with recovery times around 2 s. The high responsivity is related to the fact that the adsorbed NO₂ can affect the electron states within the entire material, which is attributed to the very small thickness of the MoS₂ nanosheets. First-principles calculations were carried out based on the density functional theory (DFT) to verify that the ultrafast recovery behavior arises from the weak van der Waals binding between NO₂ and the MoS₂ surface. Our work suggests that FLMN prepared via mechanical exfoliation have a great potential for fabricating high-performance NO₂ gas sensors. Full article

(This article belongs to the Special Issue Gas Sensors and Smart Sensing Systems)

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12 pages, 4563 KiB

Open AccessArticle

A Sensor Array Realized by a Single Flexible TiO₂/POMs Film to Contactless Detection of Triacetone Triperoxide

by Xiaorong Lü, Puqi Hao, Guanshun Xie, Junyuan Duan, Li Gao and Bingxin Liu

Sensors 2019, 19(4), 915; https://doi.org/10.3390/s19040915 - 21 Feb 2019

Cited by 15 | Viewed by 3359

Abstract

The homemade explosive, triacetone triperoxide (TATP), is easy to synthesize, sensitive to detonation but hard to detect directly. Vapor sensor arrays composed of a few sensor materials have the potential to discriminate TATP, but the stability of the sensor array is always a tricky problem since each sensor may encounter a device fault. Thus, a sensor array based on a single optoelectronic TiO₂/PW₁₁ sensor was first constructed by regulating the excitation wavelength to discriminate TATP from other explosives. By in situ doping of Na₃PW₁₂O₄₀, a Keggin structure of PW₁₁ formed on the TiO₂ to promote the photoinduced electron-hole separation, thus obviously improving the detection sensitivity of the sensor film and shortening the response time. The response of the TiO₂/PW₁₁ sensor film to TATP under 365, 450 and 550 nm illumination is 81%, 42%, and 37%, respectively. The TiO₂/PW₁₁ sensor features selectivity to TATP and is able to detect less than 50 ppb. The flexibility and stability of the flexible sensor film is also demonstrated with the extent of bending. Furthermore, the sensing response cannot be affected by ambient air below 60% relative humidity. Full article

(This article belongs to the Special Issue Gas Sensors and Smart Sensing Systems)

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11 pages, 4474 KiB

Open AccessArticle

NO₂ Selective Sensor Based on α-Fe₂O₃ Nanoparticles Synthesized via Hydrothermal Technique

by Mokhtar Hjiri, Mohamed Salah Aida and Giovanni Neri

Sensors 2019, 19(1), 167; https://doi.org/10.3390/s19010167 - 05 Jan 2019

Cited by 41 | Viewed by 4893

Abstract

In the present work, hematite (α-Fe₂O₃) nanopowders were successfully prepared via a hydrothermal route. The morphology and microstructure of the synthesized nanopowders were analyzed by using scanning and transmission electron microscopy (SEM and TEM, respectively) analysis and X-ray diffraction. Gas sensing devices were fabricated by printing α-Fe₂O₃ nanopowders on alumina substrates provided with an interdigitated platinum electrode. To determine the sensor sensitivity toward NO₂, one of the main environmental pollutants, tests with low concentrations of NO₂ in air were carried out. The results of sensing tests performed at the operating temperature of 200 °C have shown that the α-Fe₂O₃ sensor exhibits p-type semiconductor behavior and high sensitivity. Further, the dynamics exhibited by the sensor are also very fast. Lastly, to determine the selectivity of the α-Fe₂O₃ sensor, it was tested toward different gases. The sensor displayed large selectivity to nitrogen dioxide, which can be attributed to larger affinity towards NO₂ in comparison to other pollutant gases present in the environment, such as CO and CO₂. Full article

(This article belongs to the Special Issue Gas Sensors and Smart Sensing Systems)

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Review

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39 pages, 4307 KiB

Open AccessReview

Recent Advances in Electrochemical Sensors for Detecting Toxic Gases: NO₂, SO₂ and H₂S

by Md Ashfaque Hossain Khan, Mulpuri V. Rao and Qiliang Li

Sensors 2019, 19(4), 905; https://doi.org/10.3390/s19040905 - 21 Feb 2019

Cited by 227 | Viewed by 18112

Abstract

Toxic gases, such as NO_x, SO_x, H₂S and other S-containing gases, cause numerous harmful effects on human health even at very low gas concentrations. Reliable detection of various gases in low concentration is mandatory in the fields such as industrial plants, environmental monitoring, air quality assurance, automotive technologies and so on. In this paper, the recent advances in electrochemical sensors for toxic gas detections were reviewed and summarized with a focus on NO₂, SO₂ and H₂S gas sensors. The recent progress of the detection of each of these toxic gases was categorized by the highly explored sensing materials over the past few decades. The important sensing performance parameters like sensitivity/response, response and recovery times at certain gas concentration and operating temperature for different sensor materials and structures have been summarized and tabulated to provide a thorough performance comparison. A novel metric, sensitivity per ppm/response time ratio has been calculated for each sensor in order to compare the overall sensing performance on the same reference. It is found that hybrid materials-based sensors exhibit the highest average ratio for NO₂ gas sensing, whereas GaN and metal-oxide based sensors possess the highest ratio for SO₂ and H₂S gas sensing, respectively. Recently, significant research efforts have been made exploring new sensor materials, such as graphene and its derivatives, transition metal dichalcogenides (TMDs), GaN, metal-metal oxide nanostructures, solid electrolytes and organic materials to detect the above-mentioned toxic gases. In addition, the contemporary progress in SO₂ gas sensors based on zeolite and paper and H₂S gas sensors based on colorimetric and metal-organic framework (MOF) structures have also been reviewed. Finally, this work reviewed the recent first principle studies on the interaction between gas molecules and novel promising materials like arsenene, borophene, blue phosphorene, GeSe monolayer and germanene. The goal is to understand the surface interaction mechanism. Full article

(This article belongs to the Special Issue Gas Sensors and Smart Sensing Systems)

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Other

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15 pages, 3764 KiB

Open AccessProject Report

Olfaction, Vision, and Semantics for Mobile Robots. Results of the IRO Project

by Javier Monroy, Jose-Raul Ruiz-Sarmiento, Francisco-Angel Moreno, Cipriano Galindo and Javier Gonzalez-Jimenez

Sensors 2019, 19(16), 3488; https://doi.org/10.3390/s19163488 - 09 Aug 2019

Cited by 7 | Viewed by 3661

Abstract

Olfaction is a valuable source of information about the environment that has not been sufficiently exploited in mobile robotics yet. Certainly, odor information can contribute to other sensing modalities, e.g., vision, to accomplish high-level robot activities, such as task planning or execution in human environments. This paper organizes and puts together the developments and experiences on combining olfaction and vision into robotics applications, as the result of our five-years long project IRO: Improvement of the sensory and autonomous capability of Robots through Olfaction. Particularly, it investigates mechanisms to exploit odor information (usually coming in the form of the type of volatile and its concentration) in problems such as object recognition and scene–activity understanding. A distinctive aspect of this research is the special attention paid to the role of semantics within the robot perception and decision-making processes. The obtained results have improved the robot capabilities in terms of efficiency, autonomy, and usefulness, as reported in our publications. Full article

(This article belongs to the Special Issue Gas Sensors and Smart Sensing Systems)

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