Pt Loading of Phosphorus-Doped Carbon Nanotube Aerogels in Fuel Cell-Type Gas Sensors for Ultrasensitive H2 Detection.

A phosphorus-doped carbon nanotube (CNT) aerogel as the support material was loaded with Pt nanoparticles in fuel cell-type gas sensors for ultrasensitive H2 detection. The high surface area of the CNT scaffold is favorable to providing abundant active sites, and the high electrical conductivity facilitates the transport of carriers generated by electrochemical reactions. In addition, the CNT aerogel was doped with phosphorus (P) to further enhance the conductivity and electrochemical catalytic activity. As a result, the fuel cell-type gas sensor using the Pt/CNT aerogel doped with the optimal P content as the sensing material shows considerable performance for H2 detection at room temperature. The sensor exhibits an ultrahigh response of -921.9 µA to 15,000 ppm of H2. The sensitivity is -0.063 µA/ppm, which is 21 times higher than that of the conventional Pt/CF counterpart. The sensor also exhibits excellent repeatability and humidity resistance, as well as fast response/recovery; the response/recovery times are 31 and 4 s to 3000 ppm of H2, respectively. The modulation of the structure and catalytic properties of the support material is responsible for the improvement of the sensor performance, thus providing a feasible solution for optimizing the performance of fuel cell-type gas sensors.

Integrated Mixed Potential Gas Sensor with Efficient Structure for Discriminative Volatile Organic Compounds Detection.

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.

Self-Healing, Laminated, and Low Resistance NH3 Sensor Based on 6,6',6″-(Nitrilotris(benzene-4,1-diyl))tris(5-phenylpyrazine-2,3-dicarbonitrile) Sensing Material Operating at Room Temperature.

With the rapid development of the concept of the Internet of Things (IoT), gas sensors with the function of simulating the human sense of smell became irreplaceable as a key element. Among them, ammonia (NH3) sensors played an important role in respiration tests, environmental monitoring, safety, and other fields. However, the fabrication of the high-performance device with high stability and resistance to mechanical damages was still a challenge. In this work, polyurethane (PU) with excellent self-healing ability was applied as the substrate, and the sensor was designed from new sensitive material design and device structure optimization, through applying the organic molecule with groups which could absorb NH3 and the laminated structure to shorten the electronic transmission path to achieve a low resistance state and favorable sensing properties. Accordingly, a room temperature flexible NH3 sensor based on 6,6',6″-(nitrilotris(benzene-4,1-diyl))tris(5-phenylpyrazine-2,3-dicarbonitrile) (TPA-3DCNPZ) was successfully developed. The device could self-heal by means of a thermal evaporation assisted method. It exhibited a detection limit of 1 ppm at 98% relative humidity (RH), as well as great stability, selectivity, bending flexibility, and self-healing properties. The improved NH3 sensing performance under high RH was further investigated by complex impedance plots (CIPs) and density functional theory (DFT), attributing to the enhanced adsorption of NH3. The TPA-3DCNPZ based NH3 sensors proved to have great potential for application on simulated exhaled breath to determine the severity of kidney diseases and the progress of treatment. This work also provided new ideas for the construction of high-performance room temperature NH3 sensors.

Wearable Gas Sensor Based on Reticular Antimony-Doped SnO2/PANI Nanocomposite Realizing Intelligent Detection of Ammonia within a Wide Range of Humidity.

Wearable gas sensors demonstrate broad potential for environmental monitoring and breath analysis applications. Typically, they require a highly stable and high-performance flexible gas sensing unit that can work with a small, flexible circuit to enable real-time accurate concentration analysis and prediction. This work proposes a flexible gas sensor using antimony-doped tin dioxide composite polyaniline as the sensing material for room-temperature ammonia detection over a wide humidity range. The sensor exhibits high sensitivity (response value at 33.1 toward 100 ppm ammonia at 70% relative humidity), excellent selectivity, and good long-term and mechanical stability. The increased sensitivity is due to a reduction in the hole concentration of polyaniline in air, achieved through compositing and doping. Subsequently, regression analysis equations are developed to establish the relationship between the gas concentration and sensor response under varying environmental humidity conditions. The sensor was integrated with a small, low-power circuit module to form a wearable smart bracelet with signal acquisition, processing, and wireless transmission functions, which could achieve early and remote warning of gas leakage in different humidity environments. This research demonstrates a promising approach to designing high-performance, high-stability, and flexible gas sensors and their corresponding wireless sensing systems.

Pattern Recognition with Temperature Regulation: A Single YSZ-Based Mixed Potential Sensor Classifies Multiple Mixtures of Isoprene, n-Propanol, and Acetone.

Gas sensors integrated with machine learning algorithms have aroused keen interest in pattern recognition, which ameliorates the drawback of poor selectivity on a sensor. Among various kinds of gas sensors, the yttria-stabilized zirconia (YSZ)-based mixed potential-type sensor possesses advantages of low cost, simple structure, high sensitivity, and superior stability. However, as the number of sensors increases, the increased power consumption and more complicated integration technology may impede their extensive application. Herein, we focus on the development of a single YSZ-based mixed potential sensor from sensing material to machine learning for effective detection and discrimination of unary, binary, and ternary gas mixtures. The sensor that is sensitive to isoprene, n-propanol, and acetone is manufactured with the MgSb2O6 sensing electrode prepared by a simple sol-gel method. Unique response patterns for specific gas mixtures could be generated with temperature regulation. We chose seven algorithm models to be separately trained for discrimination. In order to realize more accurate discrimination, we further discuss the selection of suitable feature parameters and its reasons. With temperature regulation coefficients which are easily available as feature input to model, a single sensor is verified to achieve elevated accuracy rates of 95 and 99% for the discrimination of seven gases (three unary gases, three binary gas mixtures, and one ternary gas mixture) and redefined six gas mixtures. This article provides a potential new approach via a mixed potential sensor instead of a sensor array that could provide a wide application prospect in the field of electronic nose and artificial olfaction.

Machine Learning-Assisted Volatile Organic Compound Gas Classification Based on Polarized Mixed-Potential Gas Sensors.

The performance of electrochemical gas sensors depends on the reactions at the three-phase boundary. In this work, a mixed-potential gas sensor containing a counter electrode, a reference electrode, and a sensitive electrode was constructed. By applying a bias voltage to the counter electrode, the three-phase boundary can be polarized. The polarization state of the three-phase boundary determined the gas-sensitive performance. Taking 100 ppm ethanol vapor as an example, by regulating the polarization state of the three-phase boundary, the response value of the sensor can be adjusted from -170 to 40 mV, and the sensitivity can be controlled from -126.4 to 42.6 mV/decade. The working temperature of the sensor can be reduced after polarizing the three-phase boundary, lowering the power consumption from 1.14 to 0.625 W. The sensor also showed good stability and short response-recovery time (3 s). Based on this sensor, the Random Forest algorithm reached 99% accuracy in identifying the kind of VOC vapors. This accuracy was made possible by the ability to generate several signals concurrently. The above gas-sensitive performance improvements were due to the polarized three-phase boundary.

Highly Efficient Red/NIR-Emissive Fluorescent Probe with Polarity-Sensitive Character for Visualizing Cellular Lipid Droplets and Determining Their Polarity.

Lipid droplets (LDs), which are ubiquitous organelles existing in almost all eukaryotic cells, have attracted a lot of attention in the field of cell biology over the last decade. For the biological study of LDs via fluorescence imaging, the superior LD fluorescent probes with environmental polarity-sensitive character are highly desired and powerful but are very scarce. Herein, we have newly developed such a kind of fluorescent probe named LDs-Red which enables us to visualize LDs and to further reveal their polarity information. This fluorescent probe displays the advantages of intense red/near-infrared emission, high LD staining specificity, and good photostability; thus, it would be very useful for LD fluorescence imaging application. As a result, the three-dimensional confocal imaging to visualize spatial distribution of LDs and the multicolor confocal imaging to simultaneously observe LDs and other cellular organelles have been realized using this new LD fluorescent probe. Furthermore, the polarity-sensitive emission character of this probe enables us to quantitatively determine the LD polarity via spectral scan imaging. Consequently, the cancer cells (HepG2, HeLa, and Panc02) displaying lower polarity of LDs than the normal cells (L929, U251, and HT22) have been systematically demonstrated. In addition, this polarity-sensitive probe displaying shorter fluorescence wavelengths in cancer cells than in normal cells has an important and potential ability to distinguish them.

Highly Selective Mixed Potential Methanol Gas Sensor Based on a Ce0.8Gd0.2O1.95 Solid Electrolyte and Au Sensing Electrode.

A Ce0.8Gd0.2O1.95-based mixed potential type sensor attached with a commercially available Au paste sensing electrode material was fabricated to detect methanol. The optimum working temperature of the sensor was 545 °C, and the response value to 100 ppm methanol was -53 mV. The selectivity of the sensor was poor. The addition of a 4A molecular sieve filter layer and the method of pattern recognition were combined to improve it. Only gas molecules smaller than the pore diameter of the 4A molecular sieve were able to pass through the zeolite channel, and the selectivity coefficient of the sensor to methanol was improved by adding the filter layer. Meanwhile, there was an obvious distinction between the response and recovery times of the sensor toward methanol, ethanol, acetone, n-butanol, and n-pentanol. Next, the pattern recognition method was adopted. The relationship between the response value and the logarithm of gas concentration and the relationship between the maximum rate of the response process and the gas concentration were plotted separately. By comprehensively considering the two characteristic parameters of the response value and the maximum value of the differential response signal, the purpose of qualitative identification of gas types and quantitative analysis of gas concentrations was hopefully achieved.

Self-Assembly 3D Porous Crumpled MXene Spheres as Efficient Gas and Pressure Sensing Material for Transient All-MXene Sensors.

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.

Machine Learning-Assisted Development of Sensitive Electrode Materials for Mixed Potential-Type NO2 Gas Sensors.

Yttrium-stabilized zirconia (YSZ)-based mixed potential-type NOx sensors have broad application prospects in automotive exhaust gas detection. Great efforts continue to be made in developing high-performance sensitive electrode materials for mixed potential-type NO2 gas sensors. However, only five kinds of new sensing electrode materials have been developed for this type of gas sensor in the last 3 years. In this work, four different tree-based machine learning models were trained to find potentially sensitive electrode materials for NO2 detection. More than 400 materials were selected from 8000 materials by the above machine learning models. To further verify the reliability of the model, 13 of these materials containing unexploited elements were selected as sensitive electrode materials for making sensors and testing their gas-sensing performances. The experimental results showed that all 13 materials exhibited good gas-sensing performance for NO2. More interestingly, an electrode material BPO4, which does not contain any metal elements, was also screened out and showed good sensing properties to NO2. In a short period of time, 13 new sensitive electrode materials for NO2 detection were targeted and screened, which was difficult to achieve by a trial-and-error procedure.

Novel quaternary oxide semiconductor for the application of gas sensors with long-term stability.

In this paper, quaternary oxide semiconductor was applied as sensing material for the fabrication of gas sensors. One-step solvothermal method was utilized to synthesize the sensing material. Various characterization methods including XRD, XPS, SEM, HRTEM were employed to analyze the composition and structure of the sensing material. Composite composed of CuInW2O8 and CuWO4 was successfully prepared at last characterized by XRD result. The SEM result revealed the structure of the sensing material: nanoparticles assembled spindle-like nanostructure with ~200 nm long axis and ~60 nm short axis. Sensor based on the spindle-like nanostructures was systemically tested to acquire the information about the sensing properties. The sensor exhibited responses to acetone at the operating temperatures from 190 to 275 °C. The results showed that the sensor was more sensitive to acetone compared with other gases at the optimal operating temperature of 210 °C. The response of the sensor was also tested under the relative humidity from 25 RH% to 95 RH% at the operating temperature of 210 °C. The response variation was only 13.9%, demonstrating that the sensor possessed strong anti-humidity ability. It was worth noting that the sensor showed acceptable long-term stability compared with other acetone sensors. The gas sensing mechanism was also discussed here. This work might provide ideas for the development of novel sensitive materials for the application of gas sensors.

Integrating Target-Responsive Hydrogels with Smartphone for On-Site ppb-Level Quantitation of Organophosphate Pesticides.

Precise on-site profiling of organophosphate pesticides (OPs) is of significant importance for monitoring pollution and estimating poisoning. Herein, we designed a simple and convenient portable kit based on Ag+-responsive hydrogels for accurate detection of OPs. The newly developed hydrogels employed o-phenylenediamine (OPD) and silicon quantum dots (SiQDs) as indicator, which possessed ratiometric response. In this sensor, OPs as inhibitor of acetylcholinesterase prevented the generation of thiocholine, which blocked the formation of metal-polymer with Ag+, further triggered the oxidation of OPD to yield yellow 2,3-diaminophenazine (DAP) with fluorescence emission at 557 nm. The fluorescence intensity of SiQDs (444 nm) was quenched by DAP through inner filter effect (IFE) process, emerging a typical ratiometric response. Interestingly, the ratiometric signal of kit, which was recorded by smartphone's camera, can be transduced by ImageJ software into the hue parameter that was linearly proportional to the concentration of OPs. The simplicity of portable kit combined with smartphone operation, which possessed high sensitivity (detection limit <10 ng mL-1) and rapid sample-to-answer detection time (45 min) in agricultural sample, indicating that the methodology offered a new sight for portable monitoring of food safety and human health.

Improvement of Gas and Humidity Sensing Properties of Organ-like MXene by Alkaline Treatment.

Ti3C2T x MXene with an organ-like structure was synthesized from Ti3AlC2 (MAX phase) through the typical hydrofluoric (HF) acid etching method. Ti3C2T x MXene was further alkaline-treated with a sodium hydroxide solution to obtain alkalized Ti3C2T x. Room-temperature planar-type gas- and humidity-sensing devices were also fabricated by utilizing Ti3C2T x MXene and alkalized Ti3C2T x sensing material based on the dip coating method, respectively. The intercalation of the alkali metal ion (Na+) and the increase of the surface terminal oxygen-fluorine ratio ([O]/[F]) in Ti3C2T x can effectively improve humidity- and gas-sensing properties at room temperature. The developed alkalized Ti3C2T x sensor exhibited excellent humidity-sensing characteristics (approximately 60 times response signal change) in the relative humidity (RH) with a range of 11-95% and considerable NH3 sensing performance (28.87% response value to 100 ppm of NH3) at room temperature. The improvement of NH3 and humidity-sensing properties indicated that alkalized Ti3C2T x has great potential in chemical sensors, especially in NH3 and humidity sensors.

Realizing the Control of Electronic Energy Level Structure and Gas-Sensing Selectivity over Heteroatom-Doped In2O3 Spheres with an Inverse Opal Microstructure.

Understanding the effect of substitutional doping on gas-sensing performances is essential for designing high-activity sensing nanomaterials. Herein, formaldehyde sensors based on gallium-doped In2O3 inverse opal (IO-(Ga xIn1- x)2O3) microspheres were purposefully prepared by a simple ultrasonic spray pyrolysis method combined with self-assembled sulfonated polystyrene sphere templates. The well-aligned inverse opal structure, with three different-sized pores, plays the dual role of accelerating the diffusion of gas molecules and providing more active sites. The Ga substitutional doping can alter the electronic energy level structure of (Ga xIn1- x)2O3, leading to the elevation of the Fermi level and the modulation of the band gap close to a suitable value (3.90 eV), hence, effectively optimizing the oxidative catalytic activity for preferential CH2O oxidation and increasing the amount of adsorbed oxygen. More importantly, the gas selectivity could be controlled by varying the energy level of adsorbed oxygen. Accordingly, the IO-(Ga0.2In0.8)2O3 microsphere sensor showed a high response toward formaldehyde with fast response and recovery speeds, and ultralow detection limit (50 ppb). Our findings finally offer implications for designing Fermi level-tailorable semiconductor nanomaterials for the control of selectivity and monitoring indoor air pollutants.

Ultrasensitive gas sensor based on hollow tungsten trioxide-nickel oxide (WO3-NiO) nanoflowers for fast and selective xylene detection.

In this work, 5-20 at% gas-accessible WO3-NiO hollow nanoflowers were synthesized through a one-step hydrothermal route and used to fabricate metal oxide semiconductor (MOS) based gas sensor. The gas-accessible WO3-NiO hollow nanostructures showed much larger BET surface areas (168.0-203.8 m2 g-1) than that of the pure NiO (45.9 m2 g-1). In the comprehensive gas sensing test, the gas device based on 10 at% WO3-NiO hollow microspheres exhibited the best xylene sensing performance, showing ultrahigh xylene sensitivity (354.7-50 ppm) with short response-recovery times within 1 min. (51 and 57 s respectively) and ultralow detection limit (1.5-50 ppb xylene). Additionally, the 10 at% WO3-NiO based sensor also showed superior xylene selectivity against other interfering gases in a wide temperature range (250-350 °C). Especially at the optimal 300 °C, the 50-ppm xylene sensitivity was 8.1 and 10.3 times higher than that of 50-ppm representative acetone (Sxylene/Sacetone = 8.1) and ethanol (Sxylene/Sethanol = 10.3) gases, respectively. The mechanisms for the excellent xylene sensing performance were also discussed.

Novel Self-Assembly Route Assisted Ultra-Fast Trace Volatile Organic Compounds Gas Sensing Based on Three-Dimensional Opal Microspheres Composites for Diabetes Diagnosis.

The development of ultra-fast response semiconductor gas sensors for high-accuracy detection of trace volatile organic compounds in human exhaled breath still remains a challenge. Herein, we propose a novel self-assembly synthesis concept for preparing intricate three-dimensional (3D) opal porous (OP) SnO2-ZnO hollow microspheres (HM), by employing sulfonated polystyrene (S-PS) spheres template-assisted ultrasonic spray pyrolysis. The high gas accessibility of the unique opal hollow structures resulted in the existence of 3D interconnection and bimodal (mesoscale and macroscale) pores, and the n-n heterojunction-induced change in oxygen adsorption. The 3D OP SnO2-ZnO HM sensor exhibited high response and ultra-fast dynamic process (response time ∼4 s and recovery time ∼17 s) to 1.8 ppm acetone under highly humid ambient condition (98% relative humidity), and it could rapidly identify the states of the exhaled breath of healthy people and simulated diabetics. In addition, the rational structure design of the 3D OP SnO2 HM enables the ultra-fast detection (within 1 s) of ethanol in simulation drunk driving testing. Our results obtained in this work provided not only a facile self-assembly approach to fabricate metal oxides with 3D OP HM structures but also a new methodology for achieving noninvasive real-time exhaled breath detection.

Gas sensor based on samarium oxide loaded mulberry-shaped tin oxide for highly selective and sub ppm-level acetone detection.

Mulberry-shaped tin oxide (SnO2) hierarchical architectures and samarium oxide (Sm2O3) loaded tin oxide with different amounts (0.5, 1, 2.5, and 4 mol% Sm2O3) were successfully synthesized by facile hydrothermal synthesis method and simple isometric impregnation method. The gas sensing performance of the sensors based on pure SnO2 and Sm2O3 loaded SnO2 materials were systematically investigated. The results indicated that Sm2O3 loading considerably affected the improvement of the sensing performance of the SnO2 sensor. The 2.5 mol% Sm2O3/SnO2 exhibited the highest response (41.14) to 100 ppm acetone, the response was 2.29 times higher than that of pure SnO2 (18). In addition, with 2.5 mol% Sm2O3 loading, the low detection threshold of the sensor dropped from 500 ppb to 100 ppb. The enhanced gas sensing performance was mainly bacause of the increased oxygen vacancies created by the substitution of samarium in the SnO2 lattice, which enhanced the adsorption of oxygen and the exceptional catalytic effect of Sm2O3.

High-response and low-temperature nitrogen dioxide gas sensor based on gold-loaded mesoporous indium trioxide.

Nitrogen dioxide (NO2), as a typical threatening atmospheric pollutant, is hazardous to the environment and human health. Thus, the development of a gas sensor with high response and low detection limit for NO2 detection is highly important. The highly ordered mesoporous indium trioxide (In2O3) prepared by simple nanocasting method using mesoporous silica as template and decorated with Au nanoparticles was investigated for NO2 detection. The prepared materials were characterized by X-ray diffraction, transmission electron microscopy, and X-ray photoelectron spectroscopy. Characterization results showed that the samples exhibited ordered mesostructure and were successfully decorated with Au. The gas sensing performance of the sensors based on a series of Au-loaded mesoporous In2O3 were systematically investigated. The Au loading level strongly affected the sensing performance toward NO2. The optimal sensor, which was based on 0.5 wt% Au-loaded In2O3, displayed high sensor response and low detection limit of 10 ppb at low operating temperature of 65 °C. The excellent sensing properties were mainly attributed to the ordered mesoporous structure and the catalytic performance of Au. We believe that the Au-loaded mesoporous In2O3 can provide a promising platform for NO2 gas sensors with excellent performance.

Hydrothermal synthesis of hierarchical CoO/SnO2 nanostructures for ethanol gas sensor.

In this work, ethanol gas sensor with high performance was fabricated successfully with hierarchical CoO/SnO2 heterojunction by two-steps hydrothermal method. The response value of CoO/SnO2 sensor is up to 145 at 250 °C when exposed to 100 ppm ethanol gas, which is much higher than that (13.5) of SnO2 sensor. These good sensing performances mainly attribute to the formation of the CoO/SnO2 heterojunction, which makes great variation of resistance in air and ethanol gas. Thus, the combination of n-type SnO2 and p-type CoO provides an effective strategy to design new ethanol gas sensors. The unique nanostructure also played an important role in detecting ethanol, due to its contribution in facilitating the transport rate of the ethanol gas molecules. Also, we provide a general two-step strategy for designing the heterojunction based on the SnO2 nanostructure.