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Abstract 2D transition metal borides (MBenes) with abundant surface terminals hold great promise in molecular sensing applications. However, MBenes from etching with fluorine‐containing reagents present inert ‐fluorine groups on the surface, which hinders their sensing capability. Herein, the multilayer fluorine‐free MoBTx MBene (where Tx represents O, OH, and Cl) with hydrophilic structure is prepared by a hydrothermal‐assisted hydrochloric acid etching strategy based on guidance from the first‐principle calculations. Significantly, the fluorine‐free MoBTx‐based humidity sensor is fabricated and demonstrates low resistance and excellent humidity performance, achieving a response of 90% to 98%RH and a high resolution of 1%RH at room temperature. By combining the experimental results with the first‐principles calculations, the interactions between MoBTx and H2O, including the adsorption and intercalation of H2O, are understood first in depth. Finally, the portable humidity early warning system for real‐time monitoring and early warning of infant enuresis and back sweating illustrates its potential for humidity sensing applications. This work not only provides guidance for preparation of fluorine‐free MBenes, but also contributes to advancing their exploration in sensing applications.

Abstract Amid growing interest in the precise detection of volatile organic compounds (VOCs) in industrial field, the demand for highly effective gas sensors is at an all‐time high. However, traditional sensors with their classic single‐output signal, bulky and complex integrated structure when forming array often involve complicated technology and high cost, limiting their widespread adoption. Here, this study introduces a novel approach, employing an integrated YSZ‐based (YSZ: yttria‐stabilized zirconia) mixed potential sensor equipped with a triple‐sensing electrode array, to efficiently detect and differentiate six types of VOCs gases. This innovative sensor integrates NiSb2O6, CuSb2O6, and MgSb2O6 sensing electrodes (SEs), which are sensitive to pentane, isoprene, n‐propanol, acetone, acetic acid, and formaldehyde gases. Through feature engineering based on intuitive spike‐based response values, it accentuates the distinct characteristics of every gas. Eventually, an average classification accuracy of 98.8% and an overall R‐squared error (R2) of 99.3% for concentration regression toward six target gases can be achieved, showcasing the potential to quantitatively distinguish between industrial hazardous VOCs gases.

Abstract The fast booming of wearable electronics provides great opportunities for intelligent gas detection with improved healthcare of mining workers, and a variety of gas sensors have been simultaneously developed. However, these sensing systems are always limited to single gas detection and are highly susceptible to the inference of ubiquitous moisture, resulting in less accuracy in the analysis of gas compositions in real mining conditions. To address these challenges, we propose a synergistic strategy based on sensor integration and machine learning algorithms to realize precise NH3 and NO2 gas detections under real mining conditions. A wearable sensing array based on the graphene and polyaniline composite is developed to largely enhance the sensitivity and selectivity under mixed gas conditions. Further introduction of backpropagation neural network (BP‐NN) and partial least squares (PLS) algorithms could improve the accuracy of gas identification and concentration prediction and settle the inference of moisture, realizing over 99% theoretical prediction level on NH3 and NO2 concentrations within a wide relative humidity range, showing great promise in real mining detection. As proof of concept, a wireless wearable bracelet, integrated with sensing arrays and machine‐learning algorithms, is developed for wireless real‐time warning of hazardous gases in mines under different humidity conditions.

Abstract The recent surge in demand for human–machine interaction (HMI), Internet of Things (IoTs), and artificial intelligence (AI) has created both opportunities and challenges for room‐temperature wearable gas sensors. These sensors serve as a source of perceptual information and can be easily integrated into wearable electronic devices due to their portability and miniaturization. In recent years, various types of wearable room temperature gas sensors have been developed for fields like environmental monitoring, healthcare, smart home, industrial security, food safety monitoring, and public security. These sensors not only adjust to the movements of human effortlessly but also have reduced power consumption. Therefore, room temperature wearable gas sensors hold great promise for the development of integrated intelligent gas sensing system worn on the human body. These sensors can be fabricated using various sensing materials to detect diverse target gases. This review provides a comprehensive summary of the preparation of sensing materials with extraordinary sensing capabilities at room temperature. Additionally, the article includes a brief discussion of the sensing mechanism, employing four models to explain it: oxygen adsorption, direct electron transfer, proton transfer, and ions conduction. Finally, this article discusses the various applications and future perspectives of room‐temperature wearable gas sensors.

Abstract In this study, Sb‐doped SnO2 nanosphere composite polypyrrole nanohybrid with different doping ratios (0–5 mol%, Sb:Sn) and composite ratios (0–30 mol%, Sb‐doped SnO2:polypyrrole) is synthesized by hydrothermal method and in situ chemical oxidation method. The flexible sensors are fabricated by drop‐casting the materials on polyamide substrate and gas sensing performances are investigated systematically at room temperature. The results show that the 3 at% Sb‐doped 20 mol% SnO2/polypyrrole nanohybrid exhibits excellent sensitivity (≈213% toward 100 ppm NH3) at room temperature, which are about 3 times as much as those of polypyrrole, as well as excellent selectivity and humidity resistance, reliable repeatability, and good robustness. The enhance sensing performance can be attributed to the formation of p‐n junction between conducting polymers and metal oxide semiconductor materials and the doping of Sb elements allows more electrons to transfer to polypyrrole, which further thickens the depletion layer and decreases hole concentrations in air. Therefore, Sb‐doped SnO2/polypyrrole nanohybrid may be a promising sensitive material for the design and manufacture of room temperature flexible ammonia gas sensors.

Sensors based on triboelectric nanogenerators (TENGs) are increasingly gaining attention because of their self-powered capabilities and excellent sensing performance. In this work, we report a Mo2CTx-based triboelectric sensor (Mo-TES) consisting of a Mo2CTx/polydimethylsiloxane (PDMS) composite film. The impact of the mass fraction (wt%) and force of Mo2CTx particles on the output performance of Mo-TES was systematically explored. When Mo2CTx particles is 3 wt%, Mo-TES3 achieves an open-circuit voltage of 86.89 V, a short-circuit current of 578.12 nA, and a power density of 12.45 μW/cm2. It also demonstrates the ability to charge capacitors with varying capacitance values. Additionally, the Mo-TES3 demonstrates greater sensitivity than the Mo-TES0 and a faster recovery time of 78 ms. Meanwhile, the Mo-TES3 also demonstrates excellent stability in water washing and antifatigue testing. This demonstrates the effectiveness of Mo-TES as a pressure sensor. Furthermore, leveraging the principle of electrostatic induction, the triboelectric sensor has the potential to achieve non-contact sensing, making it a promising candidate for disease prevention and safety protection.

Abstract Environmentally friendly degradable sensors with both hazardous gases and pressure efficient sensing capabilities are highly desired for various promising applications, including environmental pollution monitoring/prevention, wisdom medical, wearable smart devices, and artificial intelligence. However, the transient gas and pressure sensors based on only identical sensing material that concurrently meets the above detection needs have not been reported. Here, we present transient all-MXene NO2 and pressure sensors employing three-dimensional porous crumpled MXene spheres prepared by ultrasonic spray pyrolysis technology as the sensing layer, accompanied with water-soluble polyvinyl alcohol substrates embedded with patterned MXene electrodes. The gas sensor achieves a ppb-level of highly selective NO2 sensing, with a response of up to 12.11% at 5 ppm NO2 and a detection range of 50 ppb–5 ppm, while the pressure sensor has an extremely wide linear pressure detection range of 0.14–22.22 kPa and fast response time of 34 ms. In parallel, all-MXene NO2 and pressure sensors can be rapidly degraded in medical H2O2 within 6 h. This work provides a new avenue toward environmental monitoring, human physiological signal monitoring, and recyclable transient electronics.

Spectral clustering algorithms are often used to find clusters in the community detection problem. Recently, a degree-corrected spectral clustering algorithm was proposed. However, it is only used for partitioning graphs which are generated from stochastic blockmodels. This paper studies the degree-corrected spectral clustering algorithm based on the spectral graph theory and shows that it gives a good approximation of the optimal clustering for a wide class of graphs. Moreover, we also give theoretical support for finding an appropriate degree-correction. Several numerical experiments for community detection are conducted in this paper to evaluate our method.

Carbon monoxide (CO) is one of the most toxic gases to human life. Therefore, the effective monitoring of it down to ppb level is of great significance. Herein, a series of In2O3 nanofibers modified with Au or Pd species or simultaneous Au and Pd species have been prepared by electrospinning combined with a calcination process. The as-obtained samples are applied for the detection of CO. Gas-sensing investigations indicate that 2 at% Au and 2 at% Pd-co-modified In2O3 nanofibers exhibit the highest response (21.7) to 100 ppm CO at 180 °C, and the response value is ~8.5 times higher than that of pure In2O3 nanofibers. More importantly, the detection limit to CO is about 200 ppb with a response value of 1.23, and is obviously lower than that (6 ppm) of pure In2O3 nanofibers. In addition, the sensor also shows good stability within 19 days. These demonstrate that co-modifying In2O3 nanofibers with suitable amounts of Pd and Au species might be a meaningful strategy for the development of high-performance carbon monoxide gas sensors.