Nitrogen Dioxide Sensor Research Articles

Ti3C2Tx/MoO3 composite as an ultrasensitive and selective sensing material for a room-temperature nitrogen dioxide sensor

Due to the significant impacts of nitrogen dioxide (NO2) on human health, even at low concentrations, NO2 sensors have been developed to detect the low range of NO2 gas in the environment to monitor air quality and take steps to reduce NO2 exposure. Ti3C2Tx, which has excellent conductivity and active surface sites (−O/–OH groups), is used in various applications, including gas sensors. The gas-sensing properties of sensors based on 2D Ti3C2Tx MXene exhibit high sensitivity, low operating temperature, and high signal-to-noise ratio for most gases. However, due to its insensitivity toward NO2 gas, the heterostructure of MXene with metal oxide semiconductors (MOSs) has been studied specifically for NO2 detection. This study uses MXene/MoO3 composite as an ultrasensitive and selective sensing layer for NO2 gas at low-ranged concentrations. The MXene/MoO3 composite is prepared using a facile sonication method with different mass ratios for sensor device fabrication. A composite of MXene and MoO3 with a 1:1 mass ratio is coated on the interdigitated electrodes for NO2 detection (1:1 MX/Mo sensor). The 1:1 MX/Mo sensor showed excellent NO2 sensing performance with 24.56 % gas response at 1 ppm NO2, 2.39 times and 3.53 times higher than pure MoO3 and MXene sensors, respectively. The 1:1 MX/Mo sensor is demonstrated to be capable of very low concentration of 50–97 ppb NO2 detection (at room temperature). The sensor also exhibits wide-range detection from 0.05 ppm to 10 ppm of NO2, a higher response rate, good stability, and good selectivity for NO2 compared to NH3, CO, CO2, and H2. Besides, the 1:1 MX/Mo based sensor shows better sensing performance at room temperature than at high temperatures at 50 °C. Based on its good performance, the 1:1 MX/Mo based sensor is expected to be further applied to monitor NO2 gas in ambient air or soil environment.

Chemiresistive NO2 sensor: A comparative study of rGO/MCPTPP and rGO/TPTP/MCPTPP composite

This study presents a chemiresistive nitrogen dioxide (NO2) sensor based on reduced graphene oxide (rGO) combined with 5, 10, 15, 20-Tetra-p-tolyl-21 H, 23 H-porphine (TPTP) and 5-(4-Methoxycarbonylphenyl)-10,15,20-triphenyl-21 H,23 H-porphine (MCPTPP). Structural, spectroscopic, morphological, and electrical characterizations of rGO/MCPTPP and rGO/TPTP/MCPTPP were carried out using X-ray diffraction, FTIR, AFM, SEM and current-voltage (I-V) respectively. The flexible ITO-coated electrodes were used to investigate sensing properties. The rGO/TPTP/MCPTPP-based sensor exhibited exceptional selectivity, sensitivity, and reproducibility toward NO2 analytes detection. MCPTPP and TPTP enhanced sensor performance due to their unique interactions with NO2. The rGO/TPTP/MCPTPP sensor exhibited remarkable linearity with a wide dynamic range of 400–100 ppm at (room temperature) RT and remained linear for low concentrations, specifically 35–1 ppm. The sensors also displayed excellent reproducibility over multiple sensing cycles. The superior performance of these sensors makes them promising candidates for various environmental monitoring and industrial applications requiring precise and reliable NO2 detection.

Eco-friendly triboelectric nanogenerator for self-powering stacked In2O3 nanosheets/PPy nanoparticles-based NO2 gas sensor

As atmospheric issues and energy crises worsen, developing environmentally friendly, low-cost, high-performance self-powered gas sensing systems for gas pollutant monitoring is crucial for the development of ecological civilization. In this work, an eco-friendly self-powered nitrogen dioxide (NO2) sensor (EFNS) system based on an eco-friendly triboelectric nanogenerator (EF-TENG) is reported. The system comprises a power supply unit (EF-TENG) and a sensing unit (In2O3/PPy sensor), connected through a signal stabilization circuit. EF-TENG utilizes eco-friendly and biodegradable gelatin and PLA/PBAT as the friction layer. By introducing leaf structures on the gelatin surface using a template method, the output voltage and current of EF-TENG were increased by 1.44 and 1.67 times, respectively. The peak power density and root mean square power density of EF-TENG reached 1386 mW m−2 and 185.35 mW m−2, respectively. Additionally, EF-TENG exhibited excellent long-term stability, maintaining a stable output voltage (∼24 V) after rectification and voltage stabilization treatment under conditions of 15–55°C and 40–80 % RH. Additionally, an In2O3/PPy heterostructure sensor was prepared, and the EFNS system was constructed through impedance matching effects, revealing the NO2 response mechanism of the In2O3/PPy heterostructure. This achieved a wide detection range and highly sensitive (Vg/Va = 355 %@30 ppm) detection of NO2. This work provides insights into eco-friendly self-powered gas sensors and sensing mechanisms, offering ideas for the development of environmental monitoring sensors and clean energy harvesting devices.

Dynamic Response and Swift Recovery of Filament Heater‐Integrated Low‐Power Transparent CNT Gas Sensor

AbstractDesigning a transparent carbon nanotube (CNT) gas sensor for nitrogen dioxide (NO2) detection at room temperature (RT), which is unaffected by humidity, is a critical challenge in various technologies. To solve this issue, a filament‐based memristor heater (MH) embedded low‐power CNT gas sensor is proposed to address humidity‐related issues, and dynamic response with a low power consumption of 6.15 µW and swift recovery of <1 ms/30.8 µW is successfully demonstrated, without any serious effects on humidity. This study reveals that the MH can effectively heat the surface of the active region due to the joule heating effect, which improves the absorption and desorption of the target gases and mitigates the influence on the humidity, which is in a response that is below 7.5%. As a result, it is believed that the proposed MH‐embedded transparent CNT gas sensors can address the humidity issues and slow response/recovery with ultralow‐power consumption and high‐accuracy gas sensing characteristics.

Cost-Efficient measurement platform and machine-learning-based sensor calibration for precise NO2 pollution monitoring

Air quality significantly impacts human health, the environment, and the economy. Precise real-time monitoring of air pollution is crucial for managing associated risks and developing appropriate short- and long-term measures. Nitrogen dioxide (NO2) stands as a common pollutant, with elevated levels posing risks to the human respiratory tract, exacerbating respiratory infections and asthma, and potentially leading to chronic lung diseases. Notwithstanding, precise NO2 detection typically demands complex and costly equipment. This paper explores NO2 monitoring using low-cost platforms, meticulously calibrated for reliability. An integrated measurement unit is first presented that contains primary and supplementary nitrogen dioxide sensors, as well as auxiliary detectors for evaluating outside and inside temperature and humidity. The calibration process utilizes data acquired over the period of five months from various reference stations. Employing machine learning with an artificial neural network (ANN)-based and kriging interpolation surrogate models, the correction strategy integrates additive and multiplicative enhancement, predicted by the ANN through auxiliary sensor data such as temperature, humidity, and the sensor-detected NO2 levels. Extensive verification studies showcase that this calibration approach notably enhances monitoring precision (coefficient of determination surpassing 0.85 concerning reference data, and RMSE of less than four μg/m3), rendering low-cost NO2 detection practical and dependable.

Controllable synthesis of heterostructured CuO–ZnO microspheres for NO2 gas sensors

Nitrogen dioxide (NO2) sensors experience the drawback of requiring high operating temperatures because of the low charge transfer ability of gas-sensing materials. Herein, an advanced NO2 sensor resistant to interference is designed using the interfacial energy barriers of a hierarchical CuO/ZnO composite. With the benefits of abundant desirable defect features, and the amplification effect of heterojunctions, the sensor based on CuO/ZnO composite with 10% Cu(CH3COO)2·H2O (S2) shows outstanding performance in terms of faster response and recovery time (1.8-fold/1.1-fold), higher response (3.1-fold), and lower power consumption (140℃ decrease) compared to the pristine ZnO sensor. Furthermore, the composite sensor exhibits long-term stability and reproducibility, indicating the potential promise of CuO/ZnO heterojunctions in interference-resistant detection of low-concentration NO2 in real applications. This study not only provides a rational solution to designing advanced gas sensors by tuning the interfacial energy barriers of heterojunctions, but also provides a fundamental understanding of CuO structures in the gas-sensing field.

On Memory-Based Precise Calibration of Cost-Efficient NO2 Sensor Using Artificial Intelligence and Global Response Correction

Nitrogen dioxide (NO2) is a prevalent air pollutant, particularly abundant in densely populated urban regions. Given its harmful impact on health and the environment, precise real-time monitoring of NO2 concentration is crucial, particularly for devising and executing risk mitigation strategies. However, achieving precise measurements of NO2 is challenging due to the need for expensive and cumbersome equipment. This has spurred the development of more affordable alternatives, although their reliability is often uncertain. The aim of this study is to present a new method for accurately calibrating low-cost NO2 sensors. Our approach utilizes artificial intelligence techniques, particularly neural networks (NNs) acting as surrogates, trained to forecast sensor correction coefficients. These predictions rely on environmental variables (temperature, humidity, etc.), data from additional nitrogen dioxide sensors, and a short series of previous NO2 readings from the main sensor, all serving as inputs for the NN metamodel. As shown, integrating short-time-scale previous measurements significantly improves the quality of the calibration process, further bolstered by global response correction. Similar enhancements are achieved by considering environmental parameter differentials. Our calibration approach has been validated using a custom-built, cost-efficient monitoring platform and reference data collected over five months from high-performance public stations in Gdansk, Poland. The results demonstrate outstanding correction quality, with a correlation coefficient close to 0.93 compared to the reference data and an RMSE below 2.8 µg/m3. This establishes the calibrated sensor as a practical and cost-effective alternative to expensive traditional NO2 monitoring stations.

Fast response 2D semiconductor gas sensor for memory-type NO2 detection: Test system construction, performance evaluation, and mechanism study

Two-dimensional (2D) materials, such as those in the graphene family, tin-selenide, and transition metal sulfides (TMDs), hold great promise for various applications, including gas-sensitive devices, photodetectors, and lithium batteries. In this study, we propose a fast response gas sensor for ppb-level nitrogen dioxide (NO2) detection using two-dimensional (2D) semiconductor molybdenum disulfide (MoS2). Firstly, we have constructed a gas-sensitive test system to evaluate the performance of the device. The test results demonstrate that the constructed device responds significantly to gas concentrations as low as 40 ppb and as high as 10 ppm, with a fast response time of around 8 s. We have also analyzed and explained the relevant mechanism of the response to NO2. By providing detailed insights into the construction and performance analysis of the test system, as well as the related mechanism study, our research offers valuable information for the development of fast response memory-type gas sensors for ppb-level NO2 detection.

Electronic control and measurement unit of conductometric nitrogen dioxide sensor in the atmosphere

High levels of air pollution lead to various negative consequences, including deterioration in public health. One of the main air pollutants in industrial cities is nitrogen dioxide. Nitrogen dioxide (NO2) is produced by various industrial processes. It is highly toxic and can cause various diseases such as bronchitis, asthma and other respiratory diseases. Despite all efforts to reduce NO2 emissions, the problem of air pollution remains relevant. Therefore, it is important to continue research into the development of new methods for continuous atmospheric monitoring and timely detection of emissions. One of the main tasks of the modern branch of science in the development of a monitoring system is the development of a sensitive, reliable and inexpensive gas sensor for NO2 in the air. The tasks of this work are design, construct, assemble and test a new original electronic control and measurement unit for a previously developed conductometric sensor for nitrogen dioxide in the atmosphere which is capable of recording and interpreting the signal in the form of a numerical response and displaying it on the screen. As a result of the work carried out, a new original electronic control and measurement unit was developed and constructed for the previously developed conductometric gas sensor for nitrogen dioxide in the atmosphere which is capable of recording and interpreting the signal in the form of a numerical response and displaying it on the screen. The developed device was tested in a system with a gas sensor with a p-type semiconductor gas-sensitive element. It has been established that for a model atmosphere of 50 ppm NO2 + N2, the sensor response recorded by the developed device is equal to (10,4 ± 0,2)∙10-3, and for a model atmosphere of 10 ppm NO2 + N2 – (6,2 ± 0,2)∙10-3. The obtained values can be used to determine the concentration of nitrogen dioxide under real atmospheric monitoring conditions.

Identification of the Safe Variation Limits for the Optimization of the Measurements in Low-Cost Electrochemical Air Quality Sensors

Nowadays, the study of air quality has become an increasingly prominent field of research, particularly in large urban centers, given its significant impact on human health. In many countries, government departments and research centers use official high-cost scientific instruments to monitor air quality in their regions. Meanwhile, concerned citizens interested in studying the air quality of their local areas often employ low-cost air quality sensors for monitoring purposes. The optimization and evaluation of low-cost sensors have been a field of research by many research groups. This paper presents an extensive study to identify the safe percentage change limits that low-cost electrochemical air quality sensors can have, in order to optimize their measurements. For this work, three low-cost air quality monitoring stations were used, which include an electrochemical sensor for nitrogen dioxide (NO2) (Alphasense NO2-B43F) and an electrochemical sensor for ozone (O3) (Alphasense OX-B431). The aim of this work is to explore the variance of the aforementioned sensors and how this variability can be used to optimize the measurements of low-cost electrochemical sensors, closer to real ones. The analysis is conducted by employing diagrams, boxplot and violin curves of the groups of sensors used, with satisfactory results.

Fast Nitrogen Dioxide Sensing with Ultralow‐Power Nanotube Gas Sensors

AbstractThe study reports fast, ultralow‐power operation of carbon nanotube‐based nitrogen dioxide (NO2) sensors enabled by nanotube self‐heating and transient sensing. The self‐heating effect in the nanotube channel significantly accelerates the desorption of gas molecules, reducing the sensor recovery time to a minute. As gas molecules re‐adsorb on the nanotube after cooling, the initial rate of the sensor transient is used to determine NO2 concentration within a few minutes. To accelerate and optimize the operation of the sensor, the study considered temperature profiles along the self‐heated carbon nanotube, their effect on different sensing regions, and a physical model‐based fit. As a result, the nanotube‐based NO2 sensor demonstrates recovery and readout times below 5 min and an extrapolated limit of detection below 10 ppb. The peak power consumption of this operation mode is below 6 µW. The combination of fast readout, fast recovery, low limit of detection, and ultralow power consumption demonstrated in this work shows strong promise of carbon nanotube‐based NO2 sensors in mobile or Internet‐of‐Things (IoT) applications.

DFT investigation and Polypyrrole sensitization mechanism of a selective NO2 sensor for room temperature application based on MXene@PPy heterojunction

Assembling a heterojunction-based composite nanomaterial to simultaneously achieve higher response and superior selectivity towards NO2 under room-temperature conditions remains a great challenge. In this work, the MXene@Polypyrrole heterojunction was synthesized via a facile in-suit chemical polymerization approach. The distribution of sphere-like PPy nanoparticles was confirmed via various characterization techniques. The response value of the 0.5MXP sensor toward 50 ppm NO2 is significantly higher than that of the pristine MXene based sensor, entailing greater response (6.5-fold). Nearly 98.11% recovery to the base resistance was observed in each sensing cycle. Noteworthy, the Schottky barriers formed between MXene and PPy contact surface, leading to the ideal selectivity and a lower limit of detection. Additionally, the sensor was tested for a 31-days-period with minimal deviation, predicting outstanding reproducibility and durability. The detailed polypyrrole sensitization mechanism containing selectivity mechanism, underlying heterojunction mechanism as well as the Density Function Theory (DFT) calculation were also revealed, offering new ideas for the development of room-temperature nitrogen dioxide sensors. Simultaneously, DFT calculation (21 models, 42 images) revealed the adsorption energy, electron transfer, and charge density differences between the NO2 molecules and the substrate (MXene, PPy and MXene@PPy). In summary, the outstanding MXene surface functionalization has been exploited by decorating with polypyrrole (PPy) nanoparticles.

Unexpected Performance Improvements of Nitrogen Dioxide and Ozone Sensors by Including Carbon Monoxide Sensor Signal.

Low-cost air quality (LCAQ) sensors are increasingly being used for community air quality monitoring. However, data collected by low-cost sensors contain significant noise, and proper calibration of these sensors remains a widely discussed, but not yet fully addressed, area of concern. In this study, several LCAQ sensors measuring nitrogen dioxide (NO2) and ozone (O3) were deployed in six cities in the United States (Atlanta, GA; New York City, NY; Sacramento, CA; Riverside, CA; Portland, OR; Phoenix, AZ) to evaluate the impacts of different climatic and geographical conditions on their performance and calibration. Three calibration methods were applied, including regression via linear and polynomial models and random forest methods. When signals from carbon monoxide (CO) sensors were included in the calibration models for NO2 and O3 sensors, model performance generally increased, with pronounced improvements in selected cities such as Riverside and New York City. Such improvements may be due to (1) temporal co-variation between concentrations of CO and NO2 and/or between CO and O3; (2) different performance levels of low-cost CO, NO2, and O3 sensors; and (3) different impacts of environmental conditions on sensor performance. The results showed an innovative approach for improving the calibration of NO2 and O3 sensors by including CO sensor signals into the calibration models. Community users of LCAQ sensors may be able to apply these findings further to enhance the data quality of their deployed NO2 and O3 monitors.

NO2 Sensor Based on Faraday Rotation Spectroscopy Using Ring Array Permanent Magnets.

Faraday rotation spectroscopy (FRS) exploits the magneto-optical effect to achieve highly selective and sensitive detection of paramagnetic molecules. Usually, a solenoid coil is used to provide a longitudinal magnetic field to produce the magneto-optical effect. However, such a method has the disadvantages of excessive power consumption and susceptibility to electromagnetic interference. In the present work, a novel FRS approach based on a combination of a neodymium iron boron permanent magnet ring array and a Herriott multipass absorption cell is proposed. A longitudinal magnetic field was generated by using 14 identical neodymium iron boron permanent magnet rings combined in a non-equidistant form according to their magnetic field's spatial distribution characteristics. The average magnetic field strength within a length of 380 mm was 346 gauss. A quantum cascade laser was used to target the optimum 441 ← 440 Q-branch nitrogen dioxide transition at 1613.25 cm-1 (6.2 μm) with an optical power of 40 mW. Coupling to a Herriott multipass absorption cell, a minimum detection limit of 0.4 ppb was achieved with an integration time of 70 s. The low-power FRS nitrogen dioxide sensor proposed in this work is expected to be developed into a robust field-deployable environment monitoring system.

NO2-sensing proprieties of WS2/WO3 heterostructures obtained by hydrothermal treatment of tungsten oxide seed materials

This work reports on the preparation of WS2/WO3 heterostructures for the development of nitrogen dioxide (NO2) sensors via a novel wet-chemical hydrothermal route approach. Different tungsten oxides were used as seed materials, and the heterostructure were formed using thioacetamide as a source of sulfur during a second hydrothermal treatment step. Structural and morphological characterizations demonstrated that the heterostructures can be described as WS2 nanosheets deposited over the tungsten oxide phase. Compared against the respective tungsten oxide seed materials, the heterostructures exhibited significant enhancement of the sensor response to NO2. High sensor signal to a 5 ppm exposure level was observed for the WS2/WO3 microplates at a working temperature of 200 °C, with good selectivity against reducing gases and a sub 2 ppm lower detection limit. To explain the enhancement of the sensor signal, we proposed an electronic sensitization mechanism based on the electronic barriers introduced by the p-n semiconductor junctions. Overall, this work introduces a low-cost, low-temperature, versatile wet-chemical synthetic route for the fabrication of transition metal dichalcogenide-metal oxide heterostructures with potential applications for the development of sensors capable of detecting NO2 at ppm levels.

Effect of Ultraviolet Activation on Sub-ppm NO2 Sensing Dynamics of Poly(3-hexylthiophene)-Bearing Graft Copolymers.

Nitrogen dioxide (NO2) sensors utilising graft copolymers bearing poly(3-hexylthiophene) chains have been developed and investigated in terms of their operation parameters using different carrier gases (N2 or air) and in either dark conditions or with ultraviolet (UV) irradiation. Interestingly, sensor performance improved upon transition from N2 to air, with the inverse being true for most NO2 sensors. UV irradiation both improved sensor dynamics and stabilised the sensor electrical baseline, allowing sensors based on SilPEG to fulfil the requirements of sensing solutions used in industry (below 10% baseline drift after sensors reach saturation) and making them promising candidates for further development and applications. Based on conducted multi-variate experiments, an initial mechanism underlying the interplay of exposure to oxygen (present in air) and UV irradiation was postulated.

Self-Powered Nitrogen Dioxide Sensor Based on Pd-Decorated ZnO/MoSe2 Nanocomposite Driven by Triboelectric Nanogenerator.

This paper introduces a high-performance self-powered nitrogen dioxide gas sensor based on Pd-modified ZnO/MoSe2 nanocomposites. Poly(vinyl alcohol) (PVA) nanofibers were prepared by high-voltage electrospinning and tribological nanogenerators (TENGs) were designed. The output voltage of TENG and the performance of the generator at different frequencies were measured. The absolute value of the maximum positive and negative voltage exceeds 200 V. Then, the output voltage of a single ZnO thin-film sensor, Pd@ZnO thin-film sensor and Pd@ZnO/MoSe2 thin-film sensor was tested by using the energy generated by TENG at 5 Hz, when the thin-film sensor was exposed to 1-50 ppm NO2 gas. The experimental results showed that the sensing response of the Pd@ZnO/MoSe2 thin-film sensor was higher than that of the single ZnO film sensor and Pd@ZnO thin-film sensor. The TENG-driven response rate of the Pd@ZnO/MoSe2 sensor on exposure to 50 ppm NO2 gas was 13.8. At the same time, the sensor had good repeatability and selectivity. The synthetic Pd@ZnO/MoSe2 ternary nanocomposite was an ideal material for the NO2 sensor, with excellent structure and performance.

Reversible Switching from P- to N-Type NO2 Sensing in ZnO Rods/rGO by Changing the NO2 Concentration, Temperature, and Doping Ratio

Gas sensors based on hybrid materials of reduced graphene oxide/metal oxide semiconductors are an effective way to improve sensor performance. In this paper, rGO (reduced graphene oxide) was uniformly and compactly anchored on the surface of presynthesized ZnO rods using a facile hydrothermal synthesis. The ZnO rods and reduced graphene oxide combined to form an np-type heterojunction structure for use in a nitrogen dioxide (NO2) sensor. Compared with pure ZnO rods and rGO, the ZnO rod/rGO composites display abnormal sensing behavior in the form of reversible transitions from p- to n-type sensing induced by changes in the NO2 gas concentration (C) and temperature (T). Based on familiar phase diagrams, a binary (T–C) transition diagram was created in terms of the gas-sensing response, which can be directly used to design and control p–n transitions. In addition, we also found that as the doping ratios (c) change, the semiconductor type of the composite also changes. Finally, the mechanisms underlying the NO2-sensing transitions are described based on the dual conduction path model: electron transfer in the internal region and chemical reactions at the surface. This reversible p–n transition of ZnO/rGO materials upon NO2 sensing is interesting and holds great potential for the efficient detection of NO2.

A Low Cost Outdoor Air Pollution Monitoring Device With Power Controlled Built-In PM Sensor

Recent advances in wireless communication technology and the Internet of Things (IoT) have provided an opportunity for mass deployment of low cost sensor nodes to measure air pollution in real-time over a large geographical area. This article presents the design of a low cost, innovative Air Pollution Monitoring Device (APMD) along with the evaluation of its advanced features. An on-board Particulate Matter (PM) sensor is designed to measure PM <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2.5</sub> and PM <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">10</sub> . APMD additionally has electrochemical sensors to measure carbon monoxide, sulphur dioxide, nitrogen dioxide, ozone, besides temperature and humidity sensors. The node is equipped with a solar energy harvesting unit and a rechargeable battery as a backup to power up the module. By utilizing an on-board GPS subsystem, APMD packs all these gathered air quality data in a frame with physical location, time, and date, and sends them to a cloud server. The node can communicate through WiFi and NB-IoT connectivity. For validating the quality of sensing, the developed APMD was co-located with an accurate reference sensor node and a series of field data were collected over seven days. In a fully ON state, the on-board PM sensor saves up to 94% energy while maintaining root mean square error (RMSE) of 0.58 for PM <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2.5</sub> and 2.5 for PM <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">10</sub> . A power control mechanism is also applied on the PM sensor to control the speed of the fan by applying a pulse width modulated (PWM) signal at the switch connected to the power supply of fan. At 100 ms switching period with 30% duty cycle, the on-board PM sensor is 97% energy efficient compared to the commercial sensor, while maintaining sensing error (RMSE) as low as 0.7 for PM <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2.5</sub> and 2.7 for PM <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">10</sub> . Our outdoor deployment studies demonstrate that the designed APMD is 90.8% more power efficient than the reference setup with significantly higher coverage range, while maintaining an acceptable range of sensing error.

High sensitivity and anti-humidity gas sensor for nitrogen dioxide based on Ce/SnO2 nanomaterials

In this paper, the SnO2 and Ce/SnO2 nanomaterials are synthesized through a simple hydrothermal route and used for detecting NO2 gas. The SnO2 materials exhibit a good linearity for NO2 detection, and the limit of detection is calculated to be as low as about 5 ppb at 10% humidity. The humidity dependence of the gas sensing characteristics of metal oxide semiconductors has been one of the greatest obstacles for gas sensor applications. The NO2 gas sensing response of SnO2 and Ce/SnO2 also are investigated at 50% humidity. The Ce/SnO2 materials show higher response than pure SnO2. The gas sensing mechanism of Ce/SnO2 material is discussed in detailed. The reach results provide a new way for increasing the anti-humidity of the metal oxide semiconductor gas sensor.