Gas Sensor Response Research Articles

Synthesis of ZnO@Fe2O3 microflowers with enhanced performance in volatile organic compound detection

Metal-oxide semiconductor is widely applied in gas sensor for volatile organic compound detection. However, these sensors usually exhibit poor selectivity and inferior sensitivity. Here, ZnO@Fe2O3 microflowers were synthesized using FeOOH microflowers as precursors via a simple solution reaction route, followed by heat treatment. The ZnO@Fe2O3 microflowers were characterized using a series of techniques, and their sensing responses to volatile organic compounds (VOCs) were evaluated in comparison with those of pristine Fe2O3. The ZnO@Fe2O3 microflower sensor exhibited better responses to several gases, especially acetone, with a response of 74.3 towards 100 ppm acetone, which is 2.85 times higher than that of the Fe2O3 microflower sensor. The sensor also presented high selectivity, reproducibility, and stability in sensing different VOCs. The large specific surface area, heterostructure, favorable hierarchical flower-like nanostructure assembled by the nanosheets, and high porosity of the ZnO@Fe2O3 microflowers contributed to its enhanced gas-sensing responses. Overall, this synthetic strategy for fabricating flower-like ZnO@Fe2O3 nanostructures can be widely applied.

Accurate first-principles simulation for the response of 2D chemiresistive gas sensors

The realm of chemiresistive gas sensors has witnessed a notable surge in interest in two-dimensional (2D) materials. The advancement of high-performance 2D gas sensing materials necessitates a quantitative theoretical method capable of accurately predicting their response. In this context, we present our first-principles framework for calculating the response of 2D materials, incorporating both carrier concentration and mobility. We showcase our method by applying it to prototype NH3 sensing on 2D MoS2 and comparing the results with prior experiments in the literature. Our approach offers a thorough solution for carrier concentration, taking into account the electronic structure around the Fermi level. In conjunction with the mobility calculation, this enables us to provide a quantitative prediction of the response profile and limit of detection (LOD), yielding a notably improved alignment with prior experimental findings. Further analysis quantifies the contributions of carrier concentration and mobility to the overall response of 2D MoS2 to NH3. We identify that discrepancies in the charge-transfer-based method primarily stem from overestimating carrier concentrations. Our method opens exciting opportunities to explore carrier mobility-dominated sensing materials, facilitates efficient screening of promising gas sensing materials, and quantitative understanding of the sensing mechanism.

Multi-task deep learning model for quantitative volatile organic compounds analysis by feature fusion of electronic nose sensing

In exploring pattern recognition for electronic noses via deep neural networks, traditional networks encounter key challenges, such as low training efficiency, and neglect of spatial-temporal attributes of gas sensor response sequences. In this study, an unmanned gas-sensing test system is used to generate a large dataset to ensure robust model training. The Gramian angular field-Markov transition field is utilized to convert time sequences into images. Using advanced image processing tools, the images are then subsequently compressed with data augmentation. This method fully preserves temporal and spatial features within the sequences, thus enhancing model performance. Furthermore, the proposed multi-task learning (MTL) framework competently performs simultaneous classification and regression tasks. The primary component of the MTL network, majorly constituted of convolutional neural networks, emphasizes the spatial features of the sequences. The integration of a long short-term memory layer ensures the preservation of temporal feature analysis of the input data, thereby enhancing predictive performance. When images are compressed to only 3.9 % of the original data, substantial information can still be preserved. Subsequently, the model trained by such compressed images attains an accuracy of 95.31 % and an R2 score of 0.9510 for classification and regression tasks, respectively. Our work reveals the remarkable potential of integrating temporal and spatial features in pattern recognition, promoting the potency of multi-tasking deep learning networks in electronic nose technology.

Long-Term Stability Test for Femtosecond Laser-Irradiated SnO2-Nanowire Gas Sensor for C7H8 Gas Sensing

In this study, femtosecond (FS) laser irradiation with different laser energy densities of 138, 276, and 414 mJ/cm2 is applied to SnO2-nanowire (NW) gas sensors, and the effect of the FS laser irradiation on the gas sensor response toward toluene (C7H8) gas is investigated. The FS laser irradiation causes oxygen deficiency in the SnO2 NWs and forms SnO and SnOx. Moreover, an embossing surface with multiple nano-sized bumps is created on the SnO2 NW surface because of the FS laser irradiation. The FS laser-irradiated SnO2-NW gas sensor exhibits superior sensing performance compared with the pristine SnO2-NW gas sensor. Moreover, the FS laser energy density significantly affects gas-sensing performance, and the highest sensor response is achieved by the gas sensor irradiated at 138 mJ/cm2. The long-term stability test of the laser-irradiated SnO2-NW gas sensor is performed by comparing fresh and 6-month-old gas sensors in different gas concentrations and relative humidity levels. Comparable gas-sensing behaviors are examined between the fresh and 6-month-old gas sensor, and this verifies the robustness of the laser-irradiated SnO2-NW gas sensor.

Utilization of jarosite and manganite mineral as raw material to fabricate metal-oxide composite film for gas sensor application

This study explores the utilization of Indonesia’s abundant geological resources, specifically jarosite and manganite minerals, to develop composite films for ethanol gas sensing applications. With jarosite’s Fe2O3 composition and manganite’s diverse applications in manganese oxide minerals, these minerals serve as promising raw materials. Building on prior research that employed Fe2O3 and manganese oxide composites, our focus lies in creating a cost-effective composite film comprising iron, manganese, and zinc oxides to enhance ethanol gas sensing capabilities. The fabrication process involves mineral extraction through a precipitation method, followed by composite synthesis and film formation using a screen-printing technique. Analysis of the resulting composite film’s morphological and crystal structure through SEM and XRD machines provides porosity and crystallinity characteristics. Examining electrical characteristics reveals the gas sensor behavior, emphasizing sensitivity and response in an ethanol environment. This study aims to contribute to gas sensor technology advancements, leveraging Indonesia’s geological wealth, promoting cost efficiency, and addressing critical aspects of sensitivity in gas sensor applications.

Prediction of total volatile basic nitrogen (TVB-N) in fish meal using a metal-oxide semiconductor electronic nose based on the VMD-SSA-LSTM algorithm.

The total volatile basic nitrogen (TVB-N) is the main indicator for evaluating the freshness of fish meal, and accurate detection and monitoring of TVB-N is of great significance for the health of animals and humans. Here, to realize fast and accurate identification of TVB-N, in this article, a self-developed electronic nose (e-nose) was used, and the mapping relationship between the gas sensor response characteristic information and TVB-N value was established to complete the freshness detection. The TVB-N variation curve was decomposed into seven subsequences with different frequency scales by means of variational mode decomposition (VMD). Each subsequence was modelled using different long short-term memory (LSTM) models, and finally, the final TVB-N prediction result was obtained by adding the prediction results based on different frequency components. To improve the performance of the LSTM, the sparrow search algorithm (SSA) was used to optimize the number of hidden units, learning rate and regularization coefficient of LSTM. The prediction results indicated that the high accuracy was obtained by the VMD-LSTM model optimized by SSA in predicting TVB-N. The coefficient of determination (R2), the root-mean-squared error (RMSE) and relative standard deviation (RSD) between the predicted value and the actual value of TVBN were 0.91, 0.115 and 6.39%. This method improves the performance of e-nose in detecting the freshness of fish meal and provides a reference for the quality detection of e-nose in other materials. © 2024 Society of Chemical Industry.

Analysis of the acoustoelectric response of SAW gas sensors using a COM model

Surface acoustic wave (SAW) gas sensors based on the acoustoelectric effect exhibit wide application prospects for in situ gas detection. However, establishing accurate models for calculating the scattering parameters of SAW gas sensors remains a challenge. Here, we present a coupling of modes (COM) model that includes the acoustoelectric effect and specifically explains the nonmonotonic variation in the center frequency with respect to the sensing film’s sheet conductivity. Several sensing parameters of the gas sensors, including the center frequency, insertion loss, and phase, were experimentally compared for accuracy and practicality. Finally, the frequency of the phase extremum (FPE) shift was determined to vary monotonically, and the range of selectable test points was wide, making the FPE an appropriate response parameter for leveraging in SAW gas sensors. The simulation results of the COM model were highly consistent with the experimental results. Our study is proposed to provide theoretical guidance for the future development of gas SAW sensors.

High performance H2 sensors based on NiO-SnO2 nanosheets in temperature-pulsed operation mode

Enhancements in the responses of semiconductor gas sensors for hydrogen (H2) are imperative to ensure the safety for industrial processes and fuel cells applications. Alternative to the conventional method of maintaining an optimum isothermal temperature, this study presents a novel technique that sequentially modulates the physisorption and chemisorption processes of the target gas and oxygen species through a temperature-pulsed strategy. This method substantially amplified the electrical responses of a NiO-doped SnO2 gas sensor to H2 vapor. Under the optimum pulsed-heating condition, the sensor achieved a remarkable response of 252–300 ppm H2, which is comparable to or better than that of many existing H2 sensors. The integration of a pulse-driven microheater with a heterojunction-forming sensing layer has led to improved sensitivity, providing additional opportunities for H2 monitoring.

Photovoltaic induced self-powered gas sensor based on 2D MoS2 incorporated NbSe2 nanorods heterostructure for NH3 gas sensing at room temperature

Two-dimensional (2D) transition metal dichalcogenides (TMDs) have attracted significant attention for their optical and gas-sensing applications due to their exceptional sensitivity. Reliable selectivity and low power consumption are two major requirements for photodetector and gas sensor applications in next-generation electronic devices and the Internet of Things. Self-powered sensors (especially photovoltaic gas sensors) can solve these problems. In this study, for the first time, we report 2D TMDs (NbSe2-MoS2 hybrid) on a SiO2/Si substrate to fabricate photovoltaic self-powered gas sensors. The gas sensors are operated by the photovoltaic effect of the NbSe2-MoS2 nanostructure, which is prepared using the liquid phase exfoliation process. Initially, it was revealed that the present hybrid material exhibits photovoltaic properties under light illumination, with a circuit current of 0.25 µA and a circuit voltage of 34 mV. The NbSe2-MoS2 nanostructure characteristics were then used for NH3 gas sensing at different concentrations, and the gas sensing response was detected from low (8.8 % at 10 ppm) to high (28.8 % at 500 ppm) concentrations. The built-in electric field occurred between the NbSe2-MoS2 junction and eventually operated as a driving force for NbSe2-MoS2 gas sensing without an external bias voltage. The physisorption of gas molecules on their surface prompts a charge-transfer mechanism that improves the gas sensor response. The combined outcome of NbSe2-MoS2 heterostructures could pave way to next-generation gas sensing device fabrications.

A comparative study on the gas sensing performance of SnO2 and GO-SnO2 sensor devices.

Using Modified Hummer’s technique, eco-friendly carbon derivative (GO) nanoparticles were obtained from polyethylene terephthalate (PET) precursor. Nanocomposite of GO-SnO2 and undoped SnO2 were synthesized using the coprecipitation method. The as-prepared nanoparticles were subjected to diverse analytical processes employing Transmission electron microscopy (TEM) to study the internal morphological properties of the nanoparticles. Energy dispersive X-ray spectroscopy (EDX) was used to examine elemental quantifications of the nanopowders. Fourier-transform infrared (FTIR) spectroscopy was used to analyze bond structures and functional groups. Dynamic responses of various gas sensor devices to 20 ppm concentrations of methane (CH4) and hydrogen (H2) were investigated as a function of time at room temperature. The GO-SnO2 nanocomposite sensing device demonstrated an ideal detection response with values of 5.00 and 5.08, corresponding to methane and hydrogen analyte gases. The doped SnO2 sensor device outperformed the pure SnO2, accounting for the GO-SnO2 > SnO2 order. Regarding the target gases, the synthesized nanocomposite demonstrated stability and selectivity in the following order of magnitude: H2 > CH4. The GO doping effect was found to have introduced surface defects, increased pores, and enabled more oxygen-active sites to be formed on the sensor device’s surface for dynamic gas sensing response, providing a comparatively enhanced sensor response.

Enhanced response characteristics of NO2 gas sensor based on ultrathin SnS2 nanoplates: Experimental and DFT study

Layered-metal dichalcogenides with extraordinary characteristics of vast surface area, tunable bandgap and superior adsorption capability enable the potential for application in gas sensors. However, the synthesis of effective material for enhanced response performance remains a challenge. Herein, we exploited a fascinating sensitivity and selectivity towards NO2 gas detection using SnS2 nanoflakes prepared via the hydrothermal method. SnS2 nanoflakes with a thickness of 25 nm and an average diameter of approximately 500 nm show the potential for the detection of NO2 gas at low concentrations of ppb levels. The sensing properties of the SnS2 sensors were investigated for different concentrations of NO2 at various operating temperatures. The sensor exhibits the highest gas-sensing response of 161 at 250 οC upon exposure to 5 ppm of NO2 gas with fast response and recovery times. In addition, the sensor shows excellent selectivity with a low detection limit of ppb level. The electronic structure and gas-sensing mechanism are elucidated via finding density of states, charge density, and band structure based on DFT study which is calculated by the Vienna ab-initio simulation package (VASP). The considerable small adsorption energy reveals a physisorption of the NO2 molecules on the SnS2 surface (-0.174 eV), indicating the SnS2 nanoflakes are intriguing candidates for the speedy detection of NO2 gas.

Advanced triethylamine sensor utilizing 3D microspheres of La-doped MoO3: Performance enhancement and mechanism insights

Triethylamine (TEA) as an excellent solvent, polymer inhibitor and preservative often appears in various places in industrial production, but its harm can not be underestimated. For the detection of TEA, molybdenum trioxide (MoO3) is a great gas-sensitive material, but its response and recovery time are long. In addressing improvements to MoO3, the paper introduced a method involving the introduction of the rare earth metal La and further pinpointed an optimal doping concentration strategy. In this paper, three-dimensional (3D) microspheres of La-doped MoO3 with different doping concentrations were synthesized using a facile hydrothermal method. Among these, the sensor based on 1 wt% La-doped MoO3 exhibits the highest gas-sensing response to TEA, with a response value of approximately 30–20 ppm TEA when the temperature is 240 ℃, accompanied by shortened response and recovery times of 10 and 29 s, respectively. Moreover, this doping level demonstrates excellent selectivity, reproducibility and long-term stability. The enhancement of gas-sensing performance is elucidated through the electron depletion layer theory and the increase in oxygen vacancies. Additionally, first-principles density functional theory (DFT) calculation was employed to deeply analyze the adsorption behavior of the MoO3 towards TEA before and after doping. This study provides valuable insights into the development of high-performance TEA sensors.

Dependence of n-Type Metal-Oxide Gas Sensor Response on the Pressure of Oxygen and Reducing Gases.

The adsorption of oxygen and its reaction with target gases are the basis of the gas detection mechanism by using metal oxides. Here, we present a theoretical analysis of the sensor response, within the ionosorption model, for an n-type polycrystalline semiconductor. Our goal of our work is to reveal the mechanisms of gas sensing from a fundamental point of view. We revisit the existing models in which the sensor response presents a power-law behavior with a reducing gas partial pressure. Then, we show, based on the Wolkenstein theory of chemisorption, that the sensor response depends not only on the reducing gas partial pressure but also on the oxygen partial pressure. We also find that the obtained sensor response does not explicitly depend on the grain size, and if it does, it is exclusively through the rate constants related to the involved reactions.

A photoactivated gas sensor of SnO2 ordered spherical pore array: Electrodeposition-based construction and application in room temperature detection of ethanol gas

The photoactivated semiconductor film gas sensor has received increasing attention in the room temperature detection of environmental gases, but the uncontrolled surface morphology and the associated light area still limit the application and the exploitation of the sensing response potential. Herein, a monolayer colloid crystal template strategy based on electrodeposition was introduced to in situ construct SnO2 ordered spherical macropore array (OSPA) sensors used for ethanol gas detection under a UV-LED. By adjusting the electrodeposition time, various OSPAs with regularly variable heights of pore-wall were obtained. The light area of the array could then be systematically regulated based on the spherical pore-walls’ curve characteristics. The OSPAs showed a nearly 5-fold change in response in detection of 100 ppm ethanol gas under a 265 nm UV-LED, corresponding to the light area from small to large. The highest sensing response is even higher than that of almost all SnO2-based room temperature sensors that have previously been reported. Moreover, the sensor has excellent selectivity and linearity, a 1 ppm lower detection limit, and exceptional long-term stability. These finds are corroborated by analyses of the electrodeposition mechanism, the sensing mechanism, optical simulations, and various characterizations. The strategy provides an efficient way to tune and enhance the sensing response of a photoactivated gas sensor, and is beneficial for exploiting the sensing potential of a semiconductor.

3D porous ZnO microspheres sensitized by Ag quantum dots for highly responsive TEA sensors

The study aims to create a highly responsive gas sensor for TEA. In order to achieve this goal, spherical ZnO with layered structure was synthesized by a simple hydrothermal method. Subsequently, Ag quantum dots (QDs) are precipitated onto the surface of the ZnO microspheres. The ZnO microspheres were analyzed to demonstrate that they are comprised of porous nanosheets measuring roughly 10 μm in diameter. The composite with the optimal mass percentage displayed outstanding sensitivity to triethylamine (TEA), yielding a response of 1223, approximately 90 times higher than that of the pure ZnO sensor. Furthermore, this composite also demonstrated remarkable selectivity towards TEA. The exceptional detection results were achieved due to the catalytic influence of Ag as a precious metal, coupled with the distinctive structure of quantum dots and ZnO materials.

Алгоритм комп'ютерної обробки кінетичних залежностей відгуку газового сенсора з інтелектуальними компонентами

The purpose of the work is to develop an algorithm using intelligent components that will allow processing of experimental data of response kinetics of resistive gas sensors based on the algorithm of the model of the stretched exponential function of Kohlrausch-Williams-Watts, without operator intervention. The problems of implementing full automation of the information-measuring system for the study of the main characteristics of gas-sensitive sensors - the selection of the most informative time interval - are describe. The algorithm for processing the experimental kinetic dependence of the response of gas sensors based on the model of a stretched exponential function with intelligent components that allow choosing the most informative time interval from the processed kinetic dependences is present.

A highly sensitive MoS2 nanosheet gas sensor prepared by mechanically exfoliating for room temperature H2S detection

Hydrogen sulfide (H2S) is a hazardous gas that is highly hazardous to human health, even at extremely low concentrations. Due to surface defects easily caused by hydrothermal or stepwise self-assembly methods, the response of the molybdenum disulfide (MoS2) gas sensor usually does not exceed 60%. In this article, mechanical exfoliation and full dry transfer techniques were used to reduce the surface defects of MoS2 nanosheets, improving the response of gas sensors to H2S at room temperature. The response to H2S was about 80% at a concentration of 15 ppm and about 12% at a concentration as low as 500 ppb. In addition, for 10 ppm H2S, applying a negative gate voltage, the response can be increased by approximately 10% to enhance the gas response. This study demonstrates the enormous potential of the gas sensor based on mechanical exfoliated MoS2 nanosheets for detecting low concentrations of H2S, providing new insight into the materials preparation of highly sensitive gas sensors.

Pt decorated Janus WSSe monolayer: A gas-sensitive material candidate for SF6 decomposition gases based on the first-principles

In gas insulated switchgear, unavoidable partial discharge faults cause SF6 to decompose various low-fluorine compounds. These compounds react with micro-water to form acids, leading to gas insulated switchgear corrosion as well as reduced insulation properties. For this reason, on-line monitoring of SF6 decomposition gases is essential. In this work, based on density functional theory, the structures of pristine WSSe and platinum doped WSSe monolayer are established, and eight adsorption systems of SO2, SO2F2, SOF2 and HF gas molecules on pristine WSSe and Pt-WSSe monolayer are constructed by geometrical optimization. By analyzing parameters such as adsorption energy, charge density, density of states, orbital theory, conductivity, sensing response and recovery time, the adsorption performance and gas-sensing mechanism of each adsorption system were investigated. The analytical results showed that both intrinsic WSSe and Pt-WSSe were unsuitable for HF gas detection and exhibited physical adsorption. The adsorption energies of Pt-WSSe for SO2, SO2F2, and SOF2 were −1.596 eV, −1.702 eV, and −2.288 eV, respectively, which showed strong chemisorption. At the optimum operating temperature, the Pt-WSSe/SO2F2 system has a fast recovery time of 1.928 s, a high response of 28.436 and a strong resistivity change, and this gas-sensitive material is well suited for the detection of this gas molecule. The Pt-WSSe/SO2 system has a small response value of 1.928 and the Pt-WSSe/SOF2 system has a strong adsorption energy of −2.288 eV. Therefore, the Pt-WSSe monolayer is not suitable as a gas-sensitive material for SO2 and SOF2 detection. This work provides theoretical guidance for the future development of low power, highly sensitive, fast response gas sensors for gas insulated switchgear fault detection.

Design of an economic, portable, compact, and indigenous instrument setup for measuring sensing characteristics of thin film gas sensors.

Thin film gas sensor characterization is very demanding for various applications because of technical design trade-offs in commercially available gas sensors. For gas sensing characterization, a suitable gas-testing experimental setup is very much needed in this context. Various factors in the experimental setup can affect a thin film gas sensor's response beyond gas exposure. These factors include the test chamber's volume, relative humidity, uniform operating temperature, uniform pressure, uniform gas density, uniform gas distribution, uniform gas concentration in the gas chamber, and uniform relative gas flow velocity over the surface of the sensor. All these environmental parameters, not being so predictive in nature, induce an inherent design trade-off in the experimental setup design. Although all the commercially available gas testing experimental setups are equally good considering the dedicated purpose for which they are made. However, all of them are for generic applications but not for specific applications because of their inherent trade-offs in their usability features. Those trade-offs always provide an opportunity to introduce a new setup with its own unique advantages. Hence, in this article, we have presented a portable, compact, indigenous gas sensing experimental setup for studying the performance of gas sensors. We have characterized and tested the setup using a ZnO based thin film gas sensor when exposed to CO2 gas at concentrations ranging from 1445 to 4631 ppm. The proposed gas sensing setup's compact size offers unique advantages, including portability and compatibility for uniform environmental conditions.

UV-activated semiconductor gas sensor response measurement for formaldehyde detection

The gas sensing characteristics of ultraviolet light-emitting diodes (UV-LEDs)-activated semiconductor sensors were investigated to detect formaldehyde (HCHO) as a model volatile organic compound (VOC). As the major drawback of formaldehyde gas sensors is the low durability of the sensing material, efforts were made to establish a suitable metal oxide semiconductor and to enhance its stability throughout the sensing process. In2O3 nanoparticles (NPs) as the sensing material showed restructuring caused by exposure to different concentrations of formaldehyde in the presence of UV radiation when its morphology and structure were analyzed. UV radiation in the presence of formaldehyde was found to play a critical role in nanoparticles agglomeration, as well as its response inconsistency and instability.The novel method of measuring UV radiation elimination in the initial stages of the response curve was deemed effective for sensing layer preservation in this study. The scanning electron microscopy (SEM) results showed that this approach prevented any notable deformation in the nanoparticles’ shape and size and resulted in reproducible responses to various formaldehyde concentrations (10–50 ppm) in the steady-state and transient (5 min exposure) phases of the response curve. Hence, a short-time UV exposure has the potential to be applied in practical gas sensing applications in which the sensor can be automatically turned off a few minutes after any target gas detection. The gas sensor response slope in the transient phase of the response curve was found to be a very good indicator of target gas concentration and to obtain fast and consistent results while preserving the sensing material from restructuring. The findings of this study can be incorporated into the development of UV-LED-activated gas sensors where stable and fast response measurements of VOCs are required.