Detection Of Nitrogen Dioxide Research Articles

Construction of a CoNiHHTP MOF/PHI Z-Scheme Heterojunction for ppb Level NO2 Photoelectric Sensing with 405 nm Irradiation at RT.

Ultrasensitive photoelectric detection of nitrogen dioxide (NO2) with PHI under visible light irradiation at room temperature (RT) remains an ongoing challenge due to the low charge separation and scarce adsorption sites. In this work, a dimensionally matched ultrathin CoNiHHTP MOF/PHI Z-scheme heterojunction is successfully constructed by taking advantage of the π-π interactions existing between the CoNiHHTP MOF and PHI. The amount-optimized heterojunction possesses a record detection limit of 1 ppb (response = 15.6%) for NO2 under 405 nm irradiation at RT, with reduced responsive (3.6 min) and recovery (2.7 min) times, good selectivity and reversibility, and long-time stability (150 days) compared with PHI, even superior to others reported at RT. Based on the time-resolved photoluminescence spectra, in situ X-ray photoelectron spectra, and diffuse reflectance infrared Fourier transform spectroscopy results, the resulting sensing performance is attributed to the favorable Z-scheme charge transfer and separation. Moreover, the Ni nodes favorably present in adjacent metal sites between the lamellae contribute to charge transfer and redistribution, whereas Co nodes could act as selective centers for promoted adsorption of NO2. Interestingly, it is confirmed that the CoNiHHTP MOF/PHI heterojunction could effectively reduce the influence of O2 in the gas-sensitive reaction due to their unique bimetallic (Co and Ni) nodes, which is also favorable for the improved sensing performances for NO2. This work provides a feasible strategy to develop promising PHI-based optoelectronic gas sensors at RT.

Aerosol-Synthesized Surfactant-Free Single-Walled Carbon Nanotube-Based NO2 Sensors: Unprecedentedly High Sensitivity and Fast Recovery.

This study pioneers a chemical sensor based on surfactant-free aerosol-synthesized single-walled carbon nanotube (SWCNT) films for detecting nitrogen dioxide (NO2). Unlike conventional CNTs, the SWCNTs used in this study exhibit one of the highest surface-to-volume ratios. They show minimal bundling without the need for surfactants and have the lowest number of defects among reported CNTs. Furthermore, the dry-transferrable and facile one-step lamination resultsin promising industrial viability. When applied to devices, the sensor shows excellent sensitivity (41.6% at 500ppb), rapid response/recovery time (14.2/120.8s), a remarkably low limit of detection (below ≈0.161ppb), minimal noise, repeatability for more than 50 cycles without fluctuation, and long-term stability for longer than 6months. This is the best performance reported for a pure CNT-based sensor. In addition, the aerosol SWCNTs demonstrate consistent gas-sensing performance even after 5000 bending cycles, indicating their suitability for wearable applications. Based on experimental and theoretical analyses, the proposed aerosol CNTs are expected to overcome the limitations associated with conventional CNT-based sensors, thereby offering a promising avenue for various sensor applications.

Machine learning‐assisted wearable sensor array for comprehensive ammonia and nitrogen dioxide detection in wide relative humidity range

AbstractThe 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.image

Enhanced Gas Sensing Performance of CuO-ZnO Composite Nanostructures for Low-Concentration NO2 Detection

The detection of nitrogen dioxide (NO2) is essential for safeguarding human health and addressing environmental sustainability. That is why, in the last decades, gas sensors have been developed to detect NO2 to overcome these hazards. This study explores the use of a novel CuO-ZnO composite synthesized through a polyol and sol–gel technique to enhance gas sensing performance. The CuO-ZnO composite offers the advantage of a synergic combination of its properties, leading to improved sensitivity, selectivity, and low detection limit. The innovative polyol technique employed in this research enables the controlled synthesis of hierarchical CuO and porous ZnO structures. The composite formation is achieved using the sol–gel method, resulting in CuO-ZnO composites with different ratios. The structural, morphological, and optical properties of the materials have been characterized using FESEM, X-ray diffraction, and UV-vis spectroscopy. Gas sensing experiments demonstrate enhanced performance, particularly in sensitivity and selectivity for NO2, even at low concentrations. The composites also exhibit improved baseline stability compared to pristine CuO and ZnO. This study explains the influence of humidity on gas sensing properties by examining interactions between water molecules and sensor surfaces. Notably, the developed CuO-ZnO composite displays excellent selectivity towards NO2, attributed to favorable bonding characteristics and acid-base properties. Overall, this research contributes to advancing gas sensor technology, providing a promising potential for sensitive and selective NO2 detection, thereby addressing critical needs for human health and environmental protection.

Leveraging electronic interactions in poly (O-toluidine)/ cadmium sulfide nanocomposite for improved nitrogen dioxide sensing

Detecting nitrogen dioxide (NO2) at room temperature remains challenging for current gas sensor technologies. This study aims to address these limitations by developing chemiresistive sensors based on poly (O-toluidine) (POT)/Cadmium sulfide (CdS) nanocomposites. The combination of POT and CdS nanoparticles creates a specialized architecture to enable swift and sensitive NO2 detection at room temperature. Gas sensing evaluations demonstrated significant performance enhancements including 104/73 s response/recovery times and 73% sensitivity at 60 ppm NO2. The sensors also showed repeatability over cycles and stability over 60 days. Comparative analysis confirmed that integrating POT with CdS amplifies sensitivity and reduces response times compared to using POT alone. This establishes a materials-by-design strategy to surpass existing gas sensing limitations.

Mesoporous and Encapsulated In2O3/Ti3C2Tx Schottky Heterojunctions for Rapid and ppb-Level NO2 Detection at Room Temperature.

Rapid and ultrasensitive detection of toxic gases at room temperature is highly desired in health protection but presents grand challenges in the sensing materials reported so far. Here, we present a gas sensor based on novel zero dimensional (0D)/two dimensional (2D) indium oxide (In2O3)/titanium carbide (Ti3C2Tx) Schottky heterostructures with a high surface area and rich oxygen vacancies for parts per billion (ppb) level nitrogen dioxide (NO2) detection at room temperature. The In2O3/Ti3C2Tx gas sensor exhibits a fast response time (4 s), good response (193.45% to 250 ppb NO2), high selectivity, and excellent cycling stability. The rich surface oxygen vacancies play the role of active sites for the adsorption of NO2 molecules, and the Schottky junctions effectively adjust the charge-transfer behavior through the conduction tunnel in the sensing material. Furthermore, In2O3 nanoparticles almost fully cover the Ti3C2Tx nanosheets which can avoid the oxidation of Ti3C2Tx, thus contributing to the good cycling stability of the sensing materials. This work sheds light on the sensing mechanism of heterojunction nanostructures and provides an efficient pathway to construct high-performance gas sensors through the rational design of active sites.

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.

Synthesis of Bitter gourd-shaped Cu-doped ZnO nanostructures and their investigation for the detection of NO2 gas at low concentrations

Nitrogen dioxide (NO2) exposure can have several adverse health impacts on people, especially the respiratory system. Low selectivity, a lack of long-term stability, and structural and morphological optimization are some challenges associated with using ZnO for NO2 gas sensing. Therefore, we intended copper (Cu) doping in ZnO to alter its shape and gas-sensing characteristics. This study explores the synthesis, properties, and gas-sensing capabilities of bitter gourd-shaped Cu-doped zinc oxide (ZnO) nanostructures for the detection of nitrogen dioxide (NO2). A facile hydrothermal synthesis method was employed to synthesize bitter gourd-shaped Cu-doped ZnO nanostructures and comprehensively characterized by several techniques. Comprehensive characterizations of our produced Cu-doped ZnO nanomaterial demonstrated by X-ray diffraction (XRD), Scanning electron microscope (SEM), Energy-dispersive X-ray spectroscopy (EDS), and different energy spectrum. The material was annealed at 400 °C in a controlled dry air environment to improve its suitability for gas sensor applications. A series of temperature-ranging experiments were conducted to get gas-sensing readings from 25 °C to 300 °C. The resulting sensor, founded upon the distinctive morphology of Cu-doped ZnO structures reminiscent of the intricate shape of bitter gourd, unveiled good selectivity with a pronounced affinity for detecting NO2 gas. Notably, the zenith of its performance was attained at an operating temperature of 200 °C, where its selectivity and sensitivity were most pronounced. Even at a low concentration of 1 ppm, the sensors displayed a maximum response of 3.7, highlighting their high sensitivity. The sensors demonstrated excellent reproducibility, selectivity, and a low detection limit. These findings position bitter gourd-shaped Cu-doped ZnO nanostructures as promising candidates for NO2 sensing applications across diverse environments.

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.

WO3/WS2 nanoflowers fabricated by low-temperature in-situ oxidation for rapid detection of nitrogen dioxide

Long response time and serious baseline drift have always hampered the practical applications of two-dimensional transition metal sulfides (TMD) in the field of gas sensors. Here, we constructed flower-like WO3/WS2 heterojunction materials via a low-temperature in-situ oxidation method to detect NO2 gas. The WO3/WS2 sensors exhibit satisfactory improvements in the response speed, sensitivity, selectivity, and baseline drift in comparison with the original WS2 sensor. The WO3/WS2 materials with different WO3 ratios were obtained by in-situ oxidizing WS2 under different calcination temperatures. The gas-sensing results show that the W-200 sensor has a gas response of Ra/Rg = 2.3–32 ppm NO2, a rapid response time of 27 s, and a low detection limit of 100 ppb, accompanied by good selectivity and reproducibility to NO2 at the optimal working temperature of 79 °C, making it a promising candidate for the optimization of WS2-based gas sensors in practical use.

Room-temperature ppb-level NO2 sensor based on three-dimensional Mo2CTx nano-crumpled spheres

Achieving ppb-level nitrogen dioxide (NO2) detection is of great significance in environmental monitoring and human daily life. The construction of portable and high-performance NO2 sensor working at room temperature is the focus of attention. In this work, three-dimensional Mo2CTx nano-crumpled spheres (MS) sensitive material was designed and prepared via ultrasonic spray pyrolysis method, and a room-temperature planar type MS-based NO2 sensor was successfully developed using drop-casting onto PI substrate with Au interdigital electrode. The sensor utilizing MS sensitive material exhibits the highest response value (−23.53%) to 5 ppm NO2 and a lowest detection limit of 30 ppb at room temperature, also the excellent selectivity. Characterization and density functional theory calculation prove that the excellent NO2 sensing properties are attributed to the increased specific surface area and more exposed edge-rich active sites which are caused by small size three-dimensional nano-crumpled spheres structure. This study provides a new strategy for improving the sensing performance of MXenes-based gas sensor and a new method for the construction of room temperature ppb-level NO2 sensor.

Response Surface Modeling of the Steady-State Impedance Responses of Gas Sensor Arrays Comprising Functionalized Carbon Nanotubes to Detect Ozone and Nitrogen Dioxide.

Carbon nanotube (CNT) sensors provide a versatile chemical platform for ambient monitoring of ozone (O3) and nitrogen dioxide (NO2), two important airborne pollutants known to cause acute respiratory and cardiovascular health problems. CNTs have shown great potential for use as sensing layers due to their unique properties, including high surface to volume ratio, numerous active sites and crystal facets with high surface reactivity, and high thermal and electrical conductivity. With operational advantages such as compactness, low-power operation, and easy integration with electronics devices, nanotechnology is expected to have a significant impact on portable low-cost environmental sensors. Enhanced sensitivity is feasible by functionalizing the CNTs with polymers, metals, and metal oxides. This paper focuses on the design and performance of a two-element array of O3 and NO2 sensors comprising single-walled CNTs functionalized by covalent modification with organic functional groups. Unlike the conventional chemiresistor in which the change in DC resistance across the sensor terminals is measured, we characterize the sensor array response by measuring both the magnitude and phase of the AC impedance. Multivariate response provides higher degrees of freedom in sensor array data processing. The complex impedance of each sensor is measured at 5 kHz in a controlled gas-flow chamber using gas mixtures with O3 in the 60-120 ppb range and NO2 between 20 and 80 ppb. The measured data reveal response change in the 26-36% range for the O3 sensor and 5-31% for the NO2 sensor. Multivariate optimization is used to fit the laboratory measurements to a response surface mathematical model, from which sensitivity and selectivity are calculated. The ozone sensor exhibits high sensitivity (e.g., 5 to 6 MΩ/ppb for the impedance magnitude) and high selectivity (0.8 to 0.9) for interferent (NO2) levels below 30 ppb. However, the NO2 sensor is not selective.

Ammonia and nitrogen dioxide detection using ZnO/CNT nanocomposite synthesized by sol–gel technique

Ammonia and nitrogen dioxide detection using ZnO/CNT nanocomposite synthesized by sol–gel technique

Carbon Nanofibers Synthesized at Different Pressures for Detection of NO2 at Room Temperature

In this paper, room-temperature chemiresistive gas sensors for NO2 detection based on CVD-grown carbon nanofibers (CNFs) were investigated. Transmission electron microscopy, low-temperature nitrogen adsorption, and X-ray diffraction were used to investigate the carbon nanomaterials. CNFs were synthesized in a wide range of pressure (1–5 bar) by COx-free decomposition of methane over the Ni/Al2O3 catalyst. It was found that the increase in pressure during the synthesis of CNFs induced the later deactivation of the catalyst, and the yield of CNFs decreased when increasing pressure. Sensing properties were determined in a dynamic flow-through installation at NO2 concentrations ranging from 1 to 400 ppm. Ammonia detection was tested for comparison in a range of 100–500 ppm. The obtained sensors based on CNFs synthesized at 1 bar showed high responses of 1.7%, 5.0%, and 10.0% to 1 ppm, 5 ppm, and 10 ppm NO2 at 25 ± 2 °C, respectively. It was shown that the obtained non-modified carbon nanomaterials can be used successfully used for room temperature detection of nitrogen dioxide. It was found that the increase in relative humidity (RH) of air induced growth of response, and this effect was facilitated after reaching RH ~35% for CNFs synthesized at elevated pressures.

Enabling Quick Response to Nitrogen Dioxide at Room Temperature and Limit of Detection to Ppb Level by Heavily n-Doped Graphene Hybrid Transistor.

Sensitive detection of nitrogen dioxide (NO2) is of significance in many areas for health and environmental protections. In this work, we developed an efficient NO2 sensor that can respond within seconds at room temperature, and the limit of detection (LOD) is as low as 100 ppb. Coating cyano-substituted poly(p-phenylene vinylene) (CN-PPV) films on graphene (G) layers can dope G sheets effectively to a heavy n state. The influences of solution concentrations and annealing temperatures on the n-doping effect were investigated in detail. The CN-PPV-G transistors fabricated with the optimized parameters demonstrate active sensing abilities toward NO2. The n-doping state of CN-PPV-G is reduced dramatically by NO2, which is a strong p-doping compound. Upon exposure to 25 ppm of NO2, our CN-PPV-G sensors react in 10 s, indicating it is almost an immediate response. LOD is determined as low as 100 ppb. The ultrahigh responding speed and low LOD are not affected in dry air. Furthermore, cycling use of our sensors can be realized through simple annealing. The superior features shown by our CN-PPV-G sensors are highly desired in the applications of monitoring the level of NO2 in situ and setting immediate alarms. Our results also suggest that transfer curves of transistors can react very promptly to the stimulus of target gas and, thus, are very promising in the development of fast-response sensing devices although the response values may not reach maximum as a tradeoff.

A Compact NO2 Gas Sensor with an Optimized Photoacoustic Cell and 450 nm-LD

In this paper, a compact ambient gas sensor with an optimized photoacoustic cell is reported. The relationship between the geometric dimensions (usually radius and length) of the photoacoustic cell (PAC) and the acoustic signal was studied through theoretical and finite element analysis. Then an optimized H-type PAC with a volume of 80 mm × 30 mm × 30 mm was machined out. The gas capacity is only 18.85 millilitres. The performance of the photoacoustic cell has been verified experimentally by the detection of nitrogen dioxide (NO2) standard gas. With an electret microphone and an economically self-designed 450 nm laser module, the detection of NO2 concentration was executed. The experimental results show good linearity with a fitting R-square of 0.9991. With an SNR (signal-to-noise ratio) of 41.247, the minimum detection limit (MDL) of the system can reach 4.85 ppb (1σ). With an analysis of allan variance, the MDL can achieve 0.11 ppb with a 228 s integration time. By replacing the light source, the system shows great potential for sensitive and compact detectors for other ambient gasses as well.

Correlating Air Pollution Concentrations and Vehicular Emissions in an Italian Roadway Tunnel by Means of Low Cost Sensors

There is an increasing scientific interest in studying vehicular traffic pollution in road tunnels. This is due both to the interest in evaluating the effect that the different polluting gases can have on the driving style of motorists and also to the hypothesis that tunnels could be considered as closed systems in which the vehicular traffic–pollution correlation is easier to study because it is more easily separated from other effects. In this work, a system of low-cost IoT sensor nodes for the detection of carbon monoxide (CO), nitrogen dioxide (NO2), ozone (O3), particulate matters (PM1, PM2.5, PM10), relative humidity (RH) and temperature (T) has been installed in an Italian tunnel, where vehicular traffic has been measured and classified for type of vehicles. The results of the measurement campaign, which lasted 3 months, from April to June 2022, allowed us to state that road tunnels actually behave like closed and isolated systems in which pollution may be directly correlated to the traffic volume and type. Furthermore, data show that quite high values of the major pollutants are observable in the tunnel in comparison to the external environment. As such, IoT sensor nodes may contribute to a distributed measuring approach on the road tunnel system mechanics assessment including, as an example, the operational impacts of forced ventilation.

A DFT Based Approach for NO2 Sensing Using Vander Wall Hetero Monolayer

In the present study, two-dimensional (2-D) pristine and distorted hexagonal Zig-Zag Boron Nitride nano-ribbon (h-BNNR) has been used as a gas sensing material to detect Nitrogen dioxide (NO2). Distorted structures such as Al-doped, P-doped, and Stone–Wales defected structures are considered here as an electro-sensing material. The First principle density functional theory (DFT) computations-based ab initio approach has been used to investigate the electrochemical properties of pristine and distorted h-ZBNNR in presence of NO2. Upon NO2 adsorption, the conduction band/valance band and energy gap of the ribbon are decreased significantly. An increase in the transmission of electrons has been observed in increasing the bias voltage. Extensive simulations using Quantum wise have been done to validate the efficacy of the proposed gas sensor.

Facile Electrodeposition-Based Chemosensors Using PANI and C-Hybrid Nanomaterials for the Selective Detection of Ammonia and Nitrogen Dioxide at Room Temperature

Sensor systems for monitoring indoor air quality are vital for the precise quantification of the mechanisms which lead to the deterioration of human health, with a typical person spending an average of 20 h a day in an enclosed space. Thus, a series of layered chemoresistive sensors, obtained by the facile electrodeposition of carbon nanomaterial-enhanced PANI composites, have been tested for the selective detection of two core indoor pollutants: ammonia and nitrogen dioxide. The sensors were tested with respect to sensitivity and selectivity to the target gasses, with performance being assessed based on response linearity and repeatability at room temperature. Of the tested sensors, two have been identified as having an adequate performance on ammonia, with sensitivities of up to 96.99% and resolutions of up to 0.85 ppm being observed, while on nitrogen dioxide, despite the successful sensor having a lower sensitivity, 10.71%, it has shown high resolution, 1.25 ppm, and linearity over a large concentration domain. These high performances highlight the viability of multi-layers chemosensors based on the electrodeposition of nanomaterial-enhanced conductive polymers for the detection of pollutant gasses, with finetuning of the detection layer allowing the accurate monitoring of a wide range of gasses.

Design of a fiber-optic sensor with ultrahigh resolution for nitrogen dioxide detection based on gain-enhanced surface plasmon resonance

Surface plasmon resonance in optical fibers can result in the creation of a highly sensitive device, compact and robust sensor. Nitrogen dioxide is one of the foremost greenhouse gases responsible for deteoriation of ecosystem and breathing disorder, it plays a direct role in global climate change. To date, all studies on surface plasmon resonance in optical fibers have relied on passive excitation. For the very first time, we propose a novel sensor architecture based on a gain enhancement of surface plasmons in optical fibers in this paper to detect nitrogen dioxide in the atmosphere. Hence, a pair of fiber gratings is embedded in the core, resulting in the formation of a cavity in which incident light with the Bragg wavelength is confined and simulated first in absence of NO2 environment and then by introducing NO2 concentration ranging from (10–100) ppm to accomplish our work, we observed change in reflectance peak varying in accordance with increasing concentration. Thus, the constructive interference between these waves results in optical field gain by a magnitude of 4. Our results indicate that a significant improvement in sensor performance is obtained on active surface plasmon excitation, anticipating to be of importance in high-precision applications.