Smart Gas Sensors: Recent Developments and Future Prospective

Specific Sn-O-Fe Active Sites from Atomically Sn-Doping Porous Fe2O3 for Ultrasensitive NO2 Detection

Conventional gas sensing materials (e.g., metal oxides) suffer from deficient sensitivity and serve cross-sensitivity issues due to the lack of efficient adsorption sites. Herein, the heteroatom atomically doping strategy is demonstrated to significantly enhance the sensing performance of metal oxides-based gas sensing materials. Specifically, the Sn atoms were incorporated into porous Fe2O3 in the form of atomically dispersed sites. As revealed by X-ray absorption spectroscopy and atomic-resolution scanning transmission electron microscopy, these Sn atoms successfully occupy the Fe sites in the Fe2O3 lattice, forming the unique Sn-O-Fe sites. Compared to Fe-O-Fe sites (from bare Fe2O3) and Sn-O-Sn sites (from SnO2/Fe2O3 with high Sn loading), the Sn-O-Fe sites on porous Fe2O3 exhibit a superior sensitivity (Rg/Ra = 2646.6) to 1 ppm NO2, along with dramatically increased selectivity and ultra-low limits of detection (10 ppb). Further theoretical calculations suggest that the strong adsorption of NO2 on Sn-O-Fe sites (N atom on Sn site, O atom on Fe site) contributes a more efficient gas response, compared to NO2 on Fe-O-Fe sites and other gases on Sn-O-Fe sites. Moreover, the incorporated Sn atoms reduce the bandgap of Fe2O3, not only facilitating the electron release but also increasing the NO2 adsorption at a low working temperature (150 °C). This work introduces an effective strategy to construct effective adsorption sites that show a unique response to specific gas molecules, potentially promoting the rational design of atomically modified gas sensing materials with high sensitivity and high selectivity.

Robust Odor Detection in Electronic Nose Using Transfer-Learning Powered Scentformer Model

Mimicking the olfactory system of humans, the use of electronic noses (E-noses) for the detection of odors in nature has become a hot research topic. This study presents a novel E-nose based on deep learning architecture called Scentformer, which addresses the limitations of the current E-nose like a narrow detection range and limited generalizability across different scenarios. Armed with a self-adaptive data down-sampling method, the E-nose is capable of detecting 55 different natural odors with the classification accuracy of 99.94%, and the model embedded in the E-nose is analyzed using Shapley Additive exPlanations analysis, providing a quantitative interpretation of the E-nose performance. Furthermore, leveraging Scentformer's transfer learning ability, the E-nose efficiently adapts to new odors and gases. Rather than retraining all layers of the model on the new odor data set, only the fully connected layers need to be trained for the pretrained model. Using only 1‰ data of the retrained model, the pretrained model-based E-nose can also achieve classification accuracies of 99.14% across various odor and gas concentrations. This provides a robust approach to the detection of diverse direct current signals in real-world applications.

Assessment of Odour Emission During the Composting Process by Using Olfactory Methods and Gas Sensor Array Measurements

The final stage of green waste treatment typically occurs in composting plants, where waste is biologically stabilised through the activity of microorganisms. The composting process is accompanied by the emission of volatile organic compounds responsible for odour perception. Such nuisance odours are commonly regarded as atmospheric air pollutants and are subject to monitoring and legal regulation. Olfactometry remains the standard method for quantifying odours. Unfortunately, due to its dependence on human evaluators, it is often regarded as both labour-intensive and costly. Electronic noses are an emerging measurement method that could be used for such applications. This manuscript reports experimental measurements that were carried out at a composting facility specialising in the processing of biodegradable materials. VOC concentration was measured by the TSI OmniTrak™ Solution. The efficiency of the deodourisation process was evaluated by means of field olfactometry. A gas sensor array of a PEN3 electronic nose was used for the on-site measurements of emitted gas characteristics. A strong correlation between measurements by the three distinct techniques was confirmed. Three different phases of the composting process could be distinguished in the collected results.

Wearable Humidity Sensor Using Cs3Cu2I5 Metal Halides with Hydroxyl Selective Phase Transition for Breath Monitoring

The low-dimensional metal halide Cs3Cu2I5 exhibits unique electrical and chemical properties. Notably, it undergoes a phase transition to CsCu2I3 upon exposure to hydroxyl (-OH) gas, resulting in significant changes in its electrical characteristics. In this study, we developed a highly selective semiconductor-based gas sensor utilizing Cs3Cu2I5. The material was synthesized on an Al2O3 substrate with carbon electrodes using a solution-based process, enabling gas sensing based on its electrical properties. The sensor was further integrated into an Arduino-based real-time monitoring system for wearable applications. The final system was mounted onto a face mask, enabling the real-time detection of human respiration. This research presents a next-generation sensor platform for real-time respiratory monitoring, demonstrating the potential of Cs3Cu2I5 in advanced wearable bio-gas sensing applications.

Applications of Carbon-Based Multivariable Chemical Sensors for Analyte Recognition

Over recent decades, carbon-based chemical sensor technologies have advanced significantly. Nevertheless, significant opportunities persist for enhancing analyte recognition capabilities, particularly in complex environments. Conventional monovariable sensors exhibit inherent limitations, such as susceptibility to interference from coexisting analytes, which results in response overlap. Although sensor arrays, through modification of multiple sensing materials, offer a potential solution for analyte recognition, their practical applications are constrained by intricate material modification processes. In this context, multivariable chemical sensors have emerged as a promising alternative, enabling the generation of multiple outputs to construct a comprehensive sensing space for analyte recognition, while utilizing a single sensing material. Among various carbon-based materials, carbon nanotubes (CNTs) and graphene have emerged as ideal candidates for constructing high-performance chemical sensors, owing to their well-established batch fabrication processes, superior electrical properties, and outstanding sensing capabilities. This review examines the progress of carbon-based multivariable chemical sensors, focusing on CNTs/graphene as sensing materials and field-effect transistors as transducers for analyte recognition. The discussion encompasses fundamental aspects of these sensors, including sensing materials, sensor architectures, performance metrics, pattern recognition algorithms, and multivariable sensing mechanism. Furthermore, the review highlights innovative multivariable extraction schemes and their practical applications when integrated with advanced pattern recognition algorithms.

Bimetallic Strip-Inspired Dual-Layer Covalent Organic Framework Membrane for Smart Organic Vapor Response

Vapor-driven smart materials show significant advantages in areas such as intelligent control, gas detection, and information transmission. However, their typically singular response mechanisms pose challenges for achieving binary response behaviors within a single system. Drawing inspiration from bimetallic strips, a dual-layer covalent organic framework (DL-COF) membrane is developed with a hierarchical pore structure. This membrane exhibits asymmetric expansion or contraction on either side when exposed to morpholine and 1,4-dioxane vapors, enabling binary response behaviors. The driving forces underlying these binary responses are the shifts in hydrogen bond equilibrium caused by chain-like hydrogen bonding and the swelling effects within the two layers, which have different degrees of crystallinity. The hierarchical pore structure further enhances rapid mass transfer, enabling the DL-COF membrane to achieve an impressive response time of just 0.6 s. By leveraging its distinct responsiveness to different vapors, the DL-COF membrane can be effectively utilized for the visual translation of encrypted information, enabling the reliable decoding of gas-encrypted Morse code from continuous programmatic vapor inputs.

Construction of Biomimetic Nanochannel, Property Regulation, and Biomarker Detection

The significance of biomimetic nanochannel in the field of biosensors is gaining increasing recognition. The controllable construction of biomimetic nanochannels and their performance modulation have demonstrated great importance and obtained wide interest. The nanochannels offer high sensitivity, enabling sensors to swiftly identify target biomarkers in complex biological samples, with detection limits reaching the picomolar level. Furthermore, they demonstrate exceptional selectivity and reproducibility, making them ideal tools for biomarker detection. In recent years, biosensors utilizing biomimetic nanochannel have shown remarkable performance in detecting a wide range of biomarkers. This review aims to explore the opportunities and challenges associated with biomimetic nanochannel technology in biosensor applications, focusing on the construction and performance modulation of these nanochannels, as well as their applications in detecting nucleic acids, proteins, organisms, and small molecules. Providing forward-looking insights into this cutting-edge field is aspired, with particular emphasis on technological advancements, addressing current challenges, and discussing future trends.

Editorial for the Applications and Challenges for Gas Sensors

Gas sensors, widely used in various fields, are devices used to detect the presence of a specific gas within a certain area or to continuously measure the concentration of gas components [...].

Selectivity in Chemiresistive Gas Sensors: Strategies and Challenges

The demand for highly functional chemical gas sensors has surged due to the increasing awareness of human health to monitor metabolic disorders or noncommunicable diseases, safety measures against harmful greenhouse and/or explosive gases, and determination of food freshness. Over the years of dedicated research, several types of chemiresistive gas sensors have been realized with appreciable sensitivities toward various gases. However, critical issues such as poor selectivity and sluggish response/recovery speeds continue to impede their widespread commercialization. Specifically, the mechanisms behind the selective response of some chemiresistive materials toward specific gas analytes remain unclear. In this review, we discuss state-of-the-art strategies employed to attain gas-selective chemiresistive materials, with particular emphasis on materials design, surface modification or functionalization with catalysts, defect engineering, material structure control, and integration with physical/chemical gas filtration media. The nature of material surface-gas interactions and the supporting mechanisms are elucidated, opening opportunities for optimizing the materials design, fine-tuning the gas sensing performance, and guiding the selection of the most appropriate materials for the accurate detection of specific gases. This review concludes with recommendations for future research directions and potential opportunities for further selectivity improvements.

Highly Selective Room-Temperature Blue LED-Enhanced NO2 Gas Sensors Based on ZnO-MoS2-TiO2 Heterostructures

This study presents the fabrication and characterization of highly selective, room-temperature gas sensors based on ternary zinc oxide-molybdenum disulfide-titanium dioxide (ZnO-MoS2-TiO2) nanoheterostructures. Integrating two-dimensional (2D) MoS2 with oxide nano materials synergistically combines their unique properties, significantly enhancing gas sensing performance. Comprehensive structural and chemical analyses, including scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDX), Raman spectroscopy, and Fourier transform infrared spectroscopy (FTIR), confirmed the successful synthesis and composition of the ternary nanoheterostructures. The sensors demonstrated excellent selectivity in detecting low concentrations of nitrogen dioxide (NO2) among target gases such as ammonia (NH3), methane (CH4), and carbon dioxide (CO2) at room temperature, achieving up to 58% sensitivity at 4 ppm and 6% at 0.1 ppm for NO2. The prototypes demonstrated outstanding selectivity and a short response time of approximately 0.51 min. The impact of light-assisted enhancement was examined under 1 mW/cm2 weak ultraviolet (UV), blue, yellow, and red light-emitting diode (LED) illuminations, with the blue LED proving to deliver the highest sensor responsiveness. These results position ternary ZnO-MoS2-TiO2 nanoheterostructures as highly sensitive and selective room-temperature NO2 gas sensors that are suitable for applications in environmental monitoring, public health, and industrial processes.

Ultrasensitive Chemiresistive Gas Sensors Based on Dual-Mesoporous Zinc Stannate Composites for Room Temperature Rice Quality Monitoring

The integration of dual-mesoporous structures, the construction of heterojunctions, and the incorporation of highly concentrated oxygen vacancies are pivotal for advancing metal oxide-based gas sensors. Nonetheless, achieving an optimal design that simultaneously combines mesoporous structures, precise heterojunction modulation, and controlled oxygen vacancies through a one-step process remains challenging. This study proposes an innovative method for fabricating zinc stannate semiconductors featuring dual-mesoporous structures and tunable oxygen vacancies via a direct solution precursor plasma spray technique. As a proof of concept, the resulting zinc stannate-based coatings are applied to detect 2-undecanone, a key biomarker for rice aging. Remarkably, the zinc oxide/zinc stannate heterojunctions with a well-defined secondary pore structure exhibit exceptional gas-sensing performance for 2-undecanone at room temperature. Furthermore, practical experiments indicate that the developed sensor effectively identifies adulteration in various rice varieties. These results underscore the potential of this method for designing metal oxides with tailored properties for high-performance gas sensors. The enhanced adsorption capacity and dual-mesoporous features of this semiconductor make it a promising candidate for sensing applications in agricultural food safety inspections.

Ultra-Sensitive NO2 Detection at Room Temperature Enabled by ZnO@MoO3 Core-Shell Nanocomposite

The sensitive detection of NO2 is crucial for environmental monitoring and improving quality of life. Herein, a ZnO@MoO3 core-shell nanocomposite was fabricated via a simple stepwise solution self-assembly and heat-treatment process. Remarkably, the ZnO@MoO3 sensor exhibited a high response value of 5.4 to 2 ppm NO2 at room temperature. Furthermore, it displayed excellent selectivity against interference gases such as CO2, NH3, methanol, ethylene, and trimethylamine, along with outstanding stability and repeatability under varying humidity conditions. The exceptional sensing performance of the ZnO@MoO3 sensor is attributed to the synergistic effects between ZnO and MoO3, as well as the enhanced electron transfer rate enabled by the heterostructures. This work provides an effective strategy for advancing NO2 sensing capabilities in metal oxide composite sensors.

Graphene-Based Fiber Materials for Gas Sensing Applications: State of the Art Review

The importance of gas sensors is apparent as the detection of gases and pollutants is crucial for environmental monitoring and human safety. Gas sensing devices also hold the potential for medical applications as health monitoring and disease diagnostic tools. Gas sensors fabricated from graphene-based fibers present a promising advancement in the field of sensing technology due to their enhanced sensitivity and selectivity. The diverse chemical and mechanical properties of graphene-based fibers-such as high surface area, flexibility, and structural stability-establish them as ideal gas-sensing materials. Most significantly, graphene fibers can be readily tuned to detect a wide range of gases, making them highly versatile in gas-sensing technologies. This review focuses on graphene-based composite fibers for gas sensors, with an emphasis on the preparation processes used to achieve these fibers and the gas sensing mechanisms involved in their sensors. Graphene fiber gas sensors are presented based on the chemical composition of their target gases, with detailed discussions on their sensitivity and performance. This review reveals that graphene-based fibers can be prepared through various methods and can be effectively integrated into gas-sensing devices for a diverse range of applications. By presenting an overview of developments in this field over the past decade, this review highlights the potential of graphene-based fiber sensors and their prospective integration into future technologies.