Metal Oxide Semiconductor Gas Sensors Research Articles

Highly Sensitive Diethylamine Detection at Room Temperature Using g-C3N4 Nanosheets Decorated with CuO Hollow Polyhedral Structures.

Chemiresistive-based metal oxide semiconductor (MOS) gas sensors are widely used in gas sensing due to their advantageous properties. Graphitic carbon nitride (g-C3N4) and metal oxide heterostructure materials can improve charge transport properties, selectivity, and sensitivity in MOS gas sensor materials. Herein, for the first time, CuO hollow polyhedral structures (HPSs) were synthesized via a hydrothermal technique and annealed at different temperatures, with the 400 °C annealed (CuO-400 HPSs) demonstrating remarkable sensing capabilities for diethylamine (DEA) gas at room temperature (RT). The x-g-C3N4 nanosheets were decorated with CuO HPSs in varying amounts (x = 0.8, 1.8, 2.1, and 3.1 wt %) and then annealed at 400 °C for x-g-C3N4-CuO-400 hollow polyhedral heterostructures (HPHSs). Indeed, among the synthesized samples, the 1.8%-g-C3N4-CuO-400 HPHSs have a higher sensitivity to DEA (resistance change in gas (Rg) and air (Ra); Rg/Ra= 65 @ 20 ppm), a low detection limit (Rg/Ra= 6 @ 500 ppb), wide dynamic response (Rg/Ra= 190 @ 80 ppm), strong stability (30 days), and 21.6 times higher sensitivity than pure CuO at RT toward 20 ppm of DEA. The exceptional gas-sensing behavior can be attributed to various factors, including controlled annealing conditions that result in the formation of well-defined structures and greater porosity, efficient charge transfer properties resulting from an optimized ratio of g-C3N4 to CuO in HPHSs, an abundance of defects, unsaturated Cu sites, and synergistic effects. The study presents a universal strategy for generating sensitive and selective g-C3N4-based composite materials for low-temperature gas sensors.

High-performance gas sensor utilizing g-C3N4/In2O3 composite for low concentration prediction to NO2

The demand for gas sensors is experiencing rapid growth, driven by the increasing need for air quality detection in the face of environmental pollution and industrial emissions. However, the widely used metal oxide semiconductor (MOS) gas sensors suffer from drawbacks such as low ability to predict gas concentration and poor selectivity. In this work, a sensor array was fabricated consisting of 10 various gas sensors and combined with an advanced deep learning algorithm to achieve precise predictions of nitrogen dioxide (NO2) at low concentrations. First, graphitic carbon nitride (g-C3N4) and In2O3 nanoparticles were composited with different mass ratios, resulting in the formation of distinct g-C3N4/In2O3 composites as sensing materials. Afterward, SEM, TEM, and XRD were employed to characterize the morphology, structure, and elemental composition of the samples. Furthermore, sensing properties including response, selectivity, and repeatability, are studied for 10 gas sensors based on g-C3N4/In2O3 composites. Finally, the convolutional neural network-efficient channel attention-gate recursive unit (CNN-AGRU) model was proposed to analyze the patterns of the signals collected from the sensor array when exposed to various NO2 concentrations from 1 to 9 ppm. The results demonstrated the integration of high-selectivity sensing materials to NO2 and an advanced deep learning algorithm CNN-AGRU enables to realize a high concentration prediction accuracy of about 97.04% and a low prediction error of 0.20527 ppm for NO2 gas.

Wireless Gas Sensor Based on the Mesoporous ZnO-SnO2 Heterostructure Enables Ultrasensitive and Rapid Detection of 3-Methylbutyraldehyde.

Achieving ultrasensitive and rapid detection of 3-methylbutyraldehyde is crucial for monitoring chemical intermediate leakage in pharmaceutical and chemical industries as well as diagnosing ventilator-associated pneumonia by monitoring exhaled gas. However, developing a sensitive and rapid method for detecting 3-methylbutyraldehyde poses challenges. Herein, a wireless chemiresistive gas sensor based on a mesoporous ZnO-SnO2 heterostructure is fabricated to enable the ultrasensitive and rapid detection of 3-methylbutyraldehyde for the first time. The mesoporous ZnO-SnO2 heterostructure exhibits a uniform spherical shape (∼79 nm in diameter), a high specific surface area (54.8 m2 g-1), a small crystal size (∼4 nm), and a large pore size (6.7 nm). The gas sensor demonstrates high response (18.98@20 ppm), short response/recovery times (13/13 s), and a low detection limit (0.48 ppm) toward 3-methylbutyraldehyde. Furthermore, a real-time monitoring system is developed utilizing microelectromechanical systems gas sensors. The modification of amorphous ZnO on the mesoporous SnO2 pore wall can effectively increase the chemisorbed oxygen content and the thickness of the electron depletion layer at the gas-solid interface, which facilitates the interface redox reaction and enhances the sensing performance. This work presents an initial example of semiconductor metal oxide gas sensors for efficient detection of 3-methylbutyraldehyde that holds great potential for ensuring safety during chemical production and disease diagnosis.

WO3 Nanoplates Decorated with Au and SnO2 Nanoparticles for Real-Time Detection of Foodborne Pathogens.

Nowadays, metal oxide semiconductor gas sensors have diverse applications ranging from human health to smart agriculture with the development of Internet of Things (IoT) technologies. However, high operating temperatures and an unsatisfactory detection capability (high sensitivity, fast response/recovery speed, etc.) hinder their integration into the IoT. Herein, a ternary heterostructure was prepared by decorating WO3 nanoplates with Au and SnO2 nanoparticles through a facial photochemical deposition method. This was employed as a sensing material for 3-hydroxy-2-butanone (3H-2B), a biomarker of Listeria monocytogenes. These Au/SnO2-WO3 nanoplate-based sensors exhibited an excellent response (Ra/Rg = 662) to 25 ppm 3H-2B, which was 24 times higher than that of pure WO3 nanoplates at 140 °C. Moreover, the 3H-2B sensor showed an ultrafast response and recovery speed to 25 ppm 3H-2B as well as high selectivity. These excellent sensing performances could be attributed to the rich Au/SnO2-WO3 active interfaces and the excellent transport of carriers in nanoplates. Furthermore, a wireless portable gas sensor equipped with the Au/SnO2-WO3 nanoplates was assembled, which was tested using 3H-2B with known concentrations to study the possibilities of real-time gas monitoring in food quality and safety.

Bimetallic Au and Pd Nanoparticles Modified WO3 Nanosheets for Enhancing the Sensitivity and Selectivity of Formaldehyde Assessment in Aquatic Products.

Formaldehyde, a common illegal additive in aquatic products, poses a threat to people's health and lives. In this study, a novel metal oxide semiconductor gas sensor based on AuPd-modified WO3 nanosheets (NSs) had been developed for the highly efficient detection of formaldehyde. WO3 NS modified with 2.0% AuPd nanoparticles showed a higher response (Ra/Rg = 94.2) to 50 ppm of formaldehyde at 210 °C, which was 36 times more than the pristine WO3 NS. In addition, the AuPd/WO3 gas sensor had a relatively short response/recovery time of 10 s/9 s for 50 ppm of formaldehyde at 210 °C, with good immunity to other interfering gases and good stability for formaldehyde. The excellent gas-sensitive performance was attributed to the chemical sensitization of Au, the electronic sensitization of Pd, and the synergistic effect of bimetallic AuPd, which facilitated the recognition and response of formaldehyde molecules. Additionally, the high sensitivity and broad application prospect of the 2.0% AuPd/WO3 NS composite-based sensor in real sample detection were also confirmed by using the above sensor for the detection of formaldehyde in aquatic products such as squid and shrimp.

Fast-Response and Low-Power Self-Heating Gas Sensor Using Metal/Metal Oxide/Metal (MMOM) Structured Nanowires.

With the escalating global awareness of air quality management, the need for continuous and reliable monitoring of toxic gases by using low-power operating systems has become increasingly important. One of which, semiconductor metal oxide gas sensors have received great attention due to their high/fast response and simple working mechanism. More specifically, self-heating metal oxide gas sensors, wherein direct thermal activation in the sensing material, have been sought for their low power-consuming characteristics. However, previous works have neglected to address the temperature distribution within the sensing material, resulting in inefficient gas response and prolonged response/recovery times, particularly due to the low-temperature regions. Here, we present a unique metal/metal oxide/metal (MMOM) nanowire architecture that conductively confines heat to the sensing material, achieving high uniformity in the temperature distribution. The proposed structure enables uniform thermal activation within the sensing material, allowing the sensor to efficiently react with the toxic gas. As a result, the proposed MMOM gas sensor showed significantly enhanced gas response (from 6.7 to 20.1% at 30 ppm), response time (from 195 to 17 s at 30 ppm), and limit of detection (∼1 ppm) when compared to those of conventional single-material structures upon exposure to carbon monoxide. Furthermore, the proposed work demonstrated low power consumption (2.36 mW) and high thermal durability (1500 on/off cycles), demonstrating its potential for practical applications in reliable and low-power operating gas sensor systems. These results propose a new paradigm for power-efficient and robust self-heating metal oxide gas sensors with potential implications for other fields requiring thermal engineering.

A Mini-Review on Metal Oxide Semiconductor Gas Sensors for Carbon Monoxide Detection at Room Temperature

Carbon monoxide can cause severe harm to humans even at low concentrations. Metal Oxide Semiconductor (MOS) carbon monoxide gas sensors have excellent sensing performance regarding sensitivity, selectivity, response speed, and stability, making them very desirable candidates for carbon monoxide monitoring. However, MOS gas sensors generally work at temperatures higher than room temperature, and need a heating source that causes high power consumption. High power consumption is a great problem for long-term portable monitoring devices for point-of-care or wireless sensor nodes for IoT application. Room-temperature MOS carbon monoxide gas sensors can function well without a heater, making them rather suitable for IoT or portable applications. This review first introduces the primary working mechanism of MOS carbon monoxide sensors and then gives a detailed introduction to and analysis of room-temperature MOS carbon monoxide sensing materials, such as ZnO, SnO2, and TiO2. Lastly, several mechanisms for room-temperature carbon monoxide sensors based on MOSs are discussed. The review will be interesting to engineers and researchers working on MOS gas sensors.

Enhanced Acetone Sensing Properties Based on Au-Pd Decorated ZnO Nanorod Gas Sensor.

The mature processes of metal oxide semiconductors (MOS) have attracted considerable interest. However, the low sensitivity of metal oxide semiconductor gas sensors is still challenging, and constrains its practical applications. Bimetallic nanoparticles are of interest owing to their excellent catalytic properties. This excellent feature of bimetallic nanoparticles can solve the problems existing in MOS gas sensors, such as the low response, high operating temperature and slow response time. To enhance acetone sensing performance, we successfully synthesized Au-Pd/ZnO nanorods. In this work, we discovered that Au-Pd nanoparticles modified on ZnO nanorods can remarkably enhance sensor response. The Au-Pd/ZnO gas sensor has long-term stability and an excellent response/recovery process. This excellent sensing performance is attributed to the synergistic catalytic effect of bimetallic AuPd nanoparticles. Moreover, the electronic and chemical sensitization of noble metals also makes a great contribution. This work presents a simple method for preparing Au-Pd/ZnO nanorods and provides a new solution for the detection of acetone based on metal oxide semiconductor.

Ultra-dense SnO2 QDs-decorated MXene nanosheets with high water dispersibility for rapid NH3 sensing at room temperature

The demand for sensitive and rapidly detecting gas sensors is increasing across various industries, ranging from environmental monitoring to medical diagnostics. Various harmful gases pose significant health risks, necessitating detection below permissible exposure limits where metal oxide semiconductor (MOS) gas sensors have garnered attention due to their sensitivity, rapid response, and cost-effectiveness. However, their high operating temperatures and limited portability have presented challenges. In this study, a novel gas sensing approach utilizing a hybrid material consisting of SnO2 quantum dot (QD) nanoparticles integrated with Ti3C2Tx MXene sheets has been developed. Originating from the abundance of nucleation sites on MXene for particle deposition, SnO2 QD nanoparticles of 2–3 nm size were densely decorated. In contrast with previous approaches, SnO2-Ti3C2Tx hybrids were in a water-dispersible form, allowing excellent solution processability. The resulting hybrid, water-dispersible SnO2-Ti3C2Tx MXene (WSM), exhibited remarkable improvements in gas response and response time at room temperature. Particularly, WSM demonstrated exceptional selectivity for ammonia gas, with a more than hundredfold increase in response compared to pristine MXene. Furthermore, the excellent dispersibility of WSM in water was also utilized to fabricate MXene-based sensors entirely through solution processes, demonstrating comparable performance to traditionally created WSM sensors.

Detection of lung cancer and stages via breath analysis using a self-made electronic nose device

ABSTRACT Background Breathomics is an emerging area focusing on monitoring and diagnosing pulmonary diseases, especially lung cancer. This research aims to employ metabolomic methods to create a breathprint in human-expelled air to rapidly identify lung cancer and its stages. Research design and methods An electronic nose (e-nose) system with five metal oxide semiconductor (MOS) gas sensors, a microcontroller, and machine learning algorithms was designed and developed for this application. The volunteers in this study include 114 patients with lung cancer and 147 healthy controls to understand the clinical potential of the e-nose system to detect lung cancer and its stages. Results In the training phase, in discriminating lung cancer from controls, the XGBoost classifier model with 10-fold cross-validation gave an accuracy of 91.67%. In the validation phase, the XGBoost classifier model correctly identified 35 out of 42 patients with lung cancer samples and 44 out of 51 healthy control samples providing an overall sensitivity of 83.33% and specificity of 86.27%. Conclusions These results indicate that the exhaled breath VOC analysis method may be developed as a new diagnostic tool for lung cancer detection. The advantages of e-nose based diagnostics, such as an easy and painless method of sampling, and low-cost procedures, will make it an excellent diagnostic method in the future.

Ultratrace eNose Sensing of VOCs toward Breath Analysis Applications Utilizing an eNose-Based Analyzer.

This proof-of-principle study presents the ability of the recently developed iLovEnose to measure ultratrace levels of volatile organic compounds (VOCs) in simulated human breath based on the combination of multiple gas sensors. The iLovEnose was developed by our research team as a test bed for gas sensors that can be hosted in three serially connected compact low-volume and temperature-controlled compartments. Herein, the eNose system was equipped with conventional semiconducting metal oxide (MOX) gas sensors using a variety of base technologies providing 11 different sensor signals that were evaluated to determine six VOCs of interest at eight low to ultralow concentration levels (i.e., ranging from 3 to 0.075 ppm) at humid conditions (90% rh at 22 °C). The measurements were randomized and performed four times over a period of 2 weeks. Partial least-squares regression analysis was applied to estimate the concentration of these six analytes. It was shown that the iLovEnose system is able to discriminate between these VOCs and provide reliable quantitative information relevant for future applications in exhaled breath analysis as a diagnostic disease detection or monitoring device.

Exploring the Contribution of Intelligent Nanomaterials in Gas Sensing

AbstractGas sensors are crucial in various industries like chemicals, food processing, pharmaceuticals, health monitoring through breath analysis, as well as in household and environmental monitoring to ensure human safety. Chemo‐resistive gas sensors based on metal oxides convert gas information into electrical signals by interacting with adsorption and desorption processes. For metal oxide semiconductor gas sensors, sensitivity and selectivity enhancements are achieved through doping, functionalization, composite formations, heterojunction creation, and morphological adjustments. The formation of heterojunctions notably boosts the efficacy of the sensing material, leveraging synergistic effects to reinforce adsorption rates, catalytic activity acceleration, and the depletion interface for electrons and holes. Over the past few decades, nanomaterials have played a critical role in gas sensing applications. They have enabled the detection of a wide array of harmful and polluting gases, as well as volatile organic compounds serving as disease biomarkers. Additionally, incorporating heterostructure nanomaterials into heterojunctions significantly impacts sensing performance and detection speed. This review discussed various types of gas sensing devices, categorizing them based on the sensing elements employed, each possessing its own set of unique advantages and disadvantages. Nevertheless, the review underscored the importance of several key parameters and factors that influence the performance of gas sensors. Additionally, recent advancements in the utilization of nanomaterial composites for gas sensor applications, particularly in the detection of gases such as ammonia, hydrogen sulphide, and sulphur dioxide vapours, were discussed. Furthermore, the review highlights recent research endeavours and fundamental parameters, including sensitivity, detection limits, selectivity, response times, and recovery times.

Preparation of laser induced periodic surface structures for gas sensing thin films and gas sensing verification of a NiO based sensor structure

Abstract This study presents different approaches to increase the sensing area of NiO based semiconducting metal oxide gas sensors. Micro- and nanopatterned laser induced periodic surface structures (LIPSS) are generated on silicon and Si/SiO2 substrates. The surface morphologies of the fabricated samples are examined by FE SEM. We select the silicon samples with an intermediate Si3N4 layer due to its superior isolation quality over the thermal oxide for evaluating the hydrogen and acetone sensitivity of a NiO based test sensor.

A deep learning approach for gas sensor data regression: Incorporating surface state model and GRU-based model

Metal–oxide–semiconductor (MOS) gas sensors are widely used for gas detection and monitoring. However, MOS gas sensors have always suffered from instability in the link between gas sensor data and the measured gas concentration. In this paper, we propose a novel deep learning approach that combines the surface state model and a Gated Recurrent Unit (GRU)-based regression to enhance the analysis of gas sensor data. The surface state model provides valuable insights into the microscopic surface processes underlying the conductivity response to pulse heating, while the GRU model effectively captures the temporal dependencies present in time-series data. The experimental results demonstrate that the theory guided model GRU+β outperforms the elementary GRU algorithm in terms of accuracy and astringent speed. The incorporation of the surface state model and the parameter rate enhances the model’s accuracy and provides valuable information for learning pulse-heated regression tasks with better generalization. This research exhibits superiority of integrating domain knowledge and deep learning techniques in the field of gas sensor data analysis. The proposed approach offers a practical framework for improving the understanding and prediction of gas concentrations, facilitating better decision-making in various practical applications.

Ni-doped Co3O4 the influence of different exposed crystal facets and doping amount on the humidity sensitivity: Experiment and theory

Water vapor causes the baseline resistance, response, recovery time, and long-term stability of the metal oxide semiconductor (MOS) gas sensors to change in different humidity. Combining first-principle and experimental can provide an in-depth understanding of the sensing mechanism from the atomic and molecular scales. In this work, we examined the humidity sensitivity of different concentrations of Ni-doped Co3O4 in detail. Co48O64 (110) and Co48O64(111) were constructed by HR-TEM and doped with single, double, and treble Ni atoms on both surfaces. We calculated the adsorption of water and n-butanol molecule on these eight surfaces. The results show that Ni doping improves the moisture resistance properties of Co48O64 (110) and Co48O64(111), and the sensing properties of C3H9OH adsorbed on Ni2Co46O64 (110) and Ni2Co46O64(111) are higher than single and treble Ni atoms doping. To investigate the humidity sensitivity further, we synthesized nanorods Co3O4 with and without Ni doping. The experimental results showed that the humidity sensitivity of Ni-Co3O4 was significantly lower than that of Co3O4. The decrease in the response value for the C3H9OH may be attributed to the change in the concentration of the Ni doping or the difference in the primarily exposed crystal facet.

Humidity-tolerant and highly sensitive gas sensor for hydrogen sulfide based on WO3 nanocubes modified with CeO2.

The influence of ambient humidity on the gas-sensing characteristics of metal oxide semiconductors has been one of the greatest obstacles for gas-sensing applications. In this paper, the pure WO3 and CeO2-modified WO3 nanocubes were prepared by a simple hydrothermal method, and their gas-sensing characteristics in dry and humid atmospheres were investigated. The results show that CeO2/WO3 demonstrated excellent gas-sensing properties toward H2S with high sensitivity and high selectivity at 115 °C. Noteworthy, the humidity independence of the CeO2/WO3 increased compared to the WO3. The response retentions over the whole humidity range of the CeO2/WO3-6 and CeO2/WO3-15 sensors were 70.3, and 76%, respectively, which were much higher than the WO3 sensor (17.9%). The gas-sensing mechanism of CeO2-modified WO3 is discussed based on the gas sensitivity properties. The obtained results provide a promising route to enhance the anti-humidity properties of metal oxide semiconductor gas sensors.

Overall perspective of electrospun semiconductor metal oxides as high-performance gas sensor materials for NOx detection.

Gas sensors based on nanostructured semiconductor metal oxide (SMO) materials have been extensively investigated as key components due to their advantages over other materials, namely, high sensitivity, stability, affordability, rapid response and simplicity. However, the difficulty of working at high temperatures, response in lower concentration and their selectivity are huge challenges of SMO materials for detecting gases. Therefore, researchers have not stopped their quest to develop new gas sensors based on SMOs with higher performance. This paper begins by highlighting the importance of nitrogen monoxide (NO) and nitrogen dioxide (NO2) detection for human health and addresses the challenges associated with existing methods in effectively detecting them. Subsequently, the mechanism of SMO gas sensors, analysis of their structure and fabrication techniques focusing on electrospinning technique, as well as their advantages, difficulties, and structural design challenges are discussed. Research on enhancing the sensing performance through tuning the fabrication parameters are summarized as well. Finally, the problems and potential of SMO based gas sensors to detect NOx are revealed, and the future possibilities are stated.

MOF-derived Al3+-doped Co3O4 nanocomposites for highly n-butanol gas sensing performance at low operating temperature

High-performance gas sensors based on metal oxides for detecting Volatile Organic Compounds (VOCs) at low operating temperatures have garnered considerable attention due to their practical utility and energy efficiency. In this study, we synthesized the Al/Co metal-organic framework (MOF) by using a hydrothermal method. Subsequently, Al3+-doped Co3O4 (Al3+-Co3O4) nanocomposites with varying Al3+ concentrations were obtained through calcination. When applied to gas sensors, the Al3+-Co3O4 nanocomposites-based gas sensors exhibited excellent sensing properties toward n-butanol at a low operating temperature (100 ℃). Specifically, the response of the 10% Al3+-Co3O4 nanocomposite to 20 ppm n-butanol reached 116.7, representing an approximately 5.5-fold improvement compared to pristine Co3O4. The gas sensor based on the 10% Al3+-Co3O4 nanocomposite also demonstrated commendable repeatability, selectivity, and stability. This suggests that Al3+ doping results in Al3+-Co3O4 possessing a more intact spherical morphology. Doping significantly enhances the gas-sensing performance of Al3+-Co3O4 due to increased oxygen vacancies and a narrower band gap energy. These findings inspire the development of new p-type metal oxide semiconductor gas sensors operating at low temperatures.

Advancements in Improving Selectivity of Metal Oxide Semiconductor Gas Sensors Opening New Perspectives for Their Application in Food Industry

Volatile compounds not only contribute to the distinct flavors and aromas found in foods and beverages, but can also serve as indicators for spoilage, contamination, or the presence of potentially harmful substances. As the odor of food raw materials and products carries valuable information about their state, gas sensors play a pivotal role in ensuring food safety and quality at various stages of its production and distribution. Among gas detection devices that are widely used in the food industry, metal oxide semiconductor (MOS) gas sensors are of the greatest importance. Ongoing research and development efforts have led to significant improvements in their performance, rendering them immensely useful tools for monitoring and ensuring food product quality; however, aspects related to their limited selectivity still remain a challenge. This review explores various strategies and technologies that have been employed to enhance the selectivity of MOS gas sensors, encompassing the innovative sensor designs, integration of advanced materials, and improvement of measurement methodology and pattern recognize algorithms. The discussed advances in MOS gas sensors, such as reducing cross-sensitivity to interfering gases, improving detection limits, and providing more accurate assessment of volatile organic compounds (VOCs) could lead to further expansion of their applications in a variety of areas, including food processing and storage, ultimately benefiting both industry and consumers.

Amorphous CoSnO3 for conductometric triethylamine gas sensing

Amorphous CoSnO3 was synthesized by heating CoSn(OH)6 at 300 ℃. Characterization results indicate that the metal-hydroxyl bond in CoSn(OH)6 is converted into metal-oxygen bond in CoSnO3. The synthesized CoSnO3 is completely amorphous and consisted of nanocubes with an average size of about 70 nm. Gas sensing results show that the amorphous CoSnO3 exhibits an immense response of 202.2 to the triethylamine (TEA) vapor with a concentration of 100 ppm at the temperature of 100 ℃. The experimental results also confirmed the superior gas selectivity and long-term stability of the amorphous CoSnO3. The enhanced gas detection properties were attributed to the abundant oxygen vacancy defects, large specific surface area and advanced porosity induced by the amorphous structure of CoSnO3. The presented synthesis strategy could facilitate the advancement of metal oxide semiconductor (MOS) gas sensors hereafter.