Gas Sensor Elements Research Articles

Development of High-Performance Ethanol Gas Sensors Based on La2O3 Nanoparticles-Embedded Porous SnO2 Nanofibers.

Porous pure SnO2 nanofibers (NFs) and La2O3 nanoparticles (NPs)-embedded porous SnO2 NFs were successfully synthesized via electrospinning followed by calcination. These materials were systematically evaluated as gas-sensing elements in metal-oxide-semiconductor (MOS) sensors. The La2O3 NPs embedded in porous SnO2 NFs demonstrated superior gas-sensing performance compared to pure SnO2 NFs. Specifically, the incorporation of La2O3 resulted in a 12-fold enhancement in gas-sensing response towards ethanol, significantly improving both sensitivity and selectivity by tuning the carrier concentration and modifying oxygen deficiencies and chemisorbed oxygen levels. Thus, La2O3 NPs embedded in SnO2 NFs present a promising strategy for the development of high-performance ethanol gas sensors.

СУЧАСНІ ТЕНДЕНЦІЇ У КОНСТРУЮВАННІ ЧУТЛИВИХ ШАРІВ ДЛЯ ОПТИЧНИХ СЕНСОРІВ ТОКСИЧНИХ РЕЧОВИН

The main trends in the creation of sensitive elements of gas sensors for the detection of toxic substances in polluted areas, in industrial premises and the atmosphere are analyzed. An important aspect of the application of gas sensors is the monitoring of the quality of food products, especially of animal origin, since the consumption of spoiled products can be a great danger to human health. The principles of operation and new directions in the field of gas sensor technologies based on thin films of polymers and their nanostructures and composites with semiconductor materials of various types are outlined. Modern trends in the creation of detectors of harmful substances involve the use of new sensor media based on nanostructured components of various nature and the formation of thin film structures, using new, advanced nanotechnological approaches. It is promising to use new compositions of indicator substances (copolymers and layered structures based on poly-3,4-ethylenedioxythiophene, polyanisidine, pentacene, carbon and silicon nanoclusters), and new technological methods of their formation ("in situ" polymerization, layered assembly, electropolymerization and etc.), which do not require the use of complex, expensive equipment. The principles of construction of multifunctional gas sensors are presented. The construction of a gas sensor is proposed, the information signal of which is determined by the selective absorption of the optical medium interacting with the gas. To obtain spectral characteristics, optocouples are used, which consist of controlled sources of optical radiation and photosensitive elements. The key issue for the successful implementation of all improvements in gas sensors and nanosensors at the current stage will remain the search for substances and structures that are highly sensitive to the action of toxic gases, including components of explosive and poisonous substances, and can selectively react to their presence by changing optical and/or electrical properties.

Features of gas environment influence on the electrical properties of nano- and microcrystals ZnO

Nanocrystalline powder based on ZnO:Mn is used to create sensitive elements of gas sensors. It is shown that the nanocrystalline material has a structure similar, from an energy point of view, to the structure of micro-sized ZnO:Ag ceramics, which contains intercrystalline potential barriers formed by chemisorbed oxygen.Adsorbed water can have a significant effect on the electrical conductivity of sensors at operating temperatures below T = 100oC. When evacuated, flammable gases such as propane or butane influence electrical conductivity opposite to what is observed in a normal air atmosphere containing oxygen.

Tin Oxide Modification of Indium Oxide Gas Sensitive Layers to Increase Efficiency of Gas Sensors

Monitoring of air pollutions is one of actual trends in the development of industrial and domestic instrumentation. There are sets of tasks for improving gas analytical instruments because of increasing demand for control of a concentration of explosive and toxic gases on a level with maximum allowable concentration. The aim of the paper was to investigate the methods of formation and elemental composition of indium oxide films modified with tin oxide on the surface of gas sensor elements as one of the promising compounds for improving the detection efficiency of explosive and toxic gases in the environment. The processes of formation of gas-sensitive films deposited on the surface of nichrome alloy information electrodes were studied in this article. Substrates of anodic aluminum oxide with area of 10 × 10 mm2 and a thickness of 45 ± 0,5 μm were chosen for research. Two layers on the surface of the samples were formed. The first layer was formed from NiCr alloy (Ni – 80 %, Cr – 20 %) with a thickness of ≈ 0.3 μm by ion-plasma sputtering. The second layer was based on indium oxide with addition of tin oxide with thicknesses from ≈ 0.3 μm to ≈ 1.0 µm and coated with sol-gel technology. Five samples of gas-sensitive films were formed with different methods of deposition and heat treatment. Scanning electron microscopy was used for study of films’ morphology and elemental compositions of samples. The most perfect continuous semiconductor films were obtained by multilayer applying of a sol-gel paste. When semiconductor films were processed at annealing temperatures of 700 °C and higher in vacuum so there was observed cracking of semiconductor films up to a layer of NiCr alloy. The developed surface of gas-sensitive films allows to reach high sensitivity and affectivity of semiconductor sensors for control of air gas composition.

Sensitive liquid crystal composites for optical sensors

The paper presents a comparative analysis of liquid crystal cholesteric-nematic mixtures for their use as sensitive elements of gas sensors. Liquid crystal mixtures based on nematic mixture E7 and cholesteric impurity CB15 were considered. In order to determine the optimal mixture, a study of the spectral characteristics of the mixtures was carried out, and the main transmission peaks were determined for different concentrations of the optically active impurity. The temperature characteristics were measured to determine the threshold values for the transition of the mixtures to the isotropic state and stable temperature areas. As a result of the conducted research, we can state that as a sensitive element of optical sensors, it is advisable to use liquid crystal mixtures with impurity concentrations of CB15 of 38% and 44%. Their main transmission peaks are in the visible region of the spectrum of 500-600 nm. The temperature characteristics are slightly better in the 38% mixture, but we can claim a slightly higher sensitivity to organic substances in the 44% mixture. Further research of mixtures can be carried out during the direct development of optical sensors.

ID2S4FH: A Novel Framework of Intelligent Decision Support System for Fire Hazards

Modern societies and industrial sectors are serviced through storage and distribution centres (SDCs) such as supermarkets, malls, warehouses, etc. Large quantities of supplies are stocked here, e.g., food grains, clothes, shoes, pharmaceuticals, electronics, plastics, edible oils, electrical wires/equipment, petroleum products, painting materials, etc. Fires due to the burning of these materials are categorized into six classes, viz., Class A, Class B, Class C, Class D, Class K, and Class F. A fire is extinguished better when the right type of fire retardant is used. A thumb rule on firefighting also says, “never fight a fire if you do not know what is burning”. In this paper, we have proposed an Intelligent Decision Support System (ID2S4FH) to generate a real-time ‘fire-map’ of such SDCs during a fire hazard. We have interfaced six tin-oxide-based gas sensor elements, a temperature and humidity sensor, and a particulate matter (PM) sensor with microcontrollers to capture the real-time signature patterns of the ambient air. We burned sixteen different types of materials belonging to six classes of fire and created a dataset consisting of 2400 samples. The sensor array responses were then pre-processed and analysed using various classifiers trained in different analysis space domains. Among the classifiers, four classifiers achieved ‘all correct’ identification of the fire classes of 80 unknown test samples, and the lowest mean squared error (MSE) achieved was 2.81 × 10−3. During a fire hazard, our proposed ID2S4FH can generate real-time fire maps of SDCs and help firefighters to extinguish the fire using the appropriate fire retardant.

An IoT-Enabled E-Nose for Remote Detection and Monitoring of Airborne Pollution Hazards Using LoRa Network Protocol.

Detection and monitoring of airborne hazards using e-noses has been lifesaving and prevented accidents in real-world scenarios. E-noses generate unique signature patterns for various volatile organic compounds (VOCs) and, by leveraging artificial intelligence, detect the presence of various VOCs, gases, and smokes onsite. Widespread monitoring of airborne hazards across many remote locations is possible by creating a network of gas sensors using Internet connectivity, which consumes significant power. Long-range (LoRa)-based wireless networks do not require Internet connectivity while operating independently. Therefore, we propose a networked intelligent gas sensor system (N-IGSS) which uses a LoRa low-power wide-area networking protocol for real-time airborne pollution hazard detection and monitoring. We developed a gas sensor node by using an array of seven cross-selective tin-oxide-based metal-oxide semiconductor (MOX) gas sensor elements interfaced with a low-power microcontroller and a LoRa module. Experimentally, we exposed the sensor node to six classes i.e., five VOCs plus ambient air and as released by burning samples of tobacco, paints, carpets, alcohol, and incense sticks. Using the proposed two-stage analysis space transformation approach, the captured dataset was first preprocessed using the standardized linear discriminant analysis (SLDA) method. Four different classifiers, namely AdaBoost, XGBoost, Random Forest (RF), and Multi-Layer Perceptron (MLP), were then trained and tested in the SLDA transformation space. The proposed N-IGSS achieved "all correct" identification of 30 unknown test samples with a low mean squared error (MSE) of 1.42 × 10-4 over a distance of 590 m.

High-performance selective NO2 gas sensor based on In2O3–graphene–Cu nanocomposites

The control of atmosphere content and concentration of specific gases are important tasks in many industrial processes, agriculture, environmental and medical applications. Thus there is a high demand to develop new advanced materials with enhanced gas sensing characteristics including high gas selectivity. Herein we report the result of a study on the synthesis, characterization, and investigation of gas sensing properties of In2O3–graphene–Cu composite nanomaterials for sensing elements of single-electrode semiconductor gas sensors. The nanocomposite has a closely interconnected and highly defective structure, which is characterized by high sensitivity to various oxidizing and reducing gases and selectivity to NO2. The In2O3-based materials were obtained by sol–gel method, by adding 0–6 wt% of pre-synthesized graphene–Cu powder into In-containing gel before xerogel formation. The graphene–Cu flakes played the role of centers for In2O3 nucleation and then crystal growth terminators. This led to the formation of structural defects, influencing the surface energy state and concentration of free electrons. The concentration of defects increases with the increase of graphene–Cu content from 1 to 4 wt%, which also affects the gas-sensing properties of the nanocomposites. The sensors show a high sensing response to both oxidizing (NO2) and reducing (acetone, ethanol, methane) gases at an optimal working heating current of 91–161 mA (280–510 °C). The sensor with nanocomposite with 4 wt% of graphene–Cu additive showed the highest sensitivity to NO2 (46 ppm) in comparison with other tested gases with an absolute value of sensing response of (− ) 225 mV at a heating current of 131 mA (430 °C) and linear dependence of sensing response to NO2 concentration.

E-nose based on a high-integrated and low-power metal oxide gas sensor array

To improve the poor selectivity of a semiconductor gas-sensor system, an array of sensors can be utilized. However, this increases the system’s size and power consumption. To overcome these limitations, we propose a high-integrated and highly selective electronic nose (E-nose) comprising two independent gas-sensing elements on a low-power microhotplate (MHP). Pd-SnO2 nanoflowers and Pd-WO3 microparticles were prepared and printed on a bridge-structured MHP 20 µm apart and over an area of 110 µm × 45 µm. This was achieved using electrohydrodynamic inkjet printing aided by in-situ infrared laser curing to form an array of sensors. A power of 17 mW was required to increase the temperature of the MHP to 300 °C, which is the optimal operating temperature of the two gas sensors. Thus, a high response and low cross-sensitivity were achieved for hydrogen, ammonia, hydrogen–ammonia, ethanol, acetone, ethanol–acetone, toluene, and formaldehyde. A wavelet transform was used to reduce the noise and dimensionality of the signals from the gas-sensor array. Qualitative identification of the eight gases with an accuracy of 99.86% was achieved using the k-nearest neighbor (kNN) model. A p neighbors back propagation neural network (pN-BPNN) model was established to remove interfering samples to quantitatively estimate the gas concentration. The quantitative identification accuracy of pN-BPNN was higher than that of the standard back propagation neural network (BPNN) model with the average absolute percentage error of hydrogen detection in the range of 15–500 ppm, decreasing from 5.44% to 2.08%.

Quasi-2D SnO2 Thin Films for Gas Sensors: Chemoresistive Response and Temperature Effect on Adsorption of Analytes

We performed in silico calculations of electrical conductivity of quasi-2D SnO2 thin films with a (110) surface-prospect material for sensitive element of gas sensors. Electronic structure, charge transfer and chemoresistive response of quasi-2D SnO2 thin films during adsorption of alcohol molecules (ethanol, methanol, isopropanol and butanol) and ketones (acetone, cyclopentanone and cyclohexanone) were calculated. It was found that the electrical conductivity of quasi-2D SnO2 thin films decreases within 4-15% during adsorption of analytes. The influence of temperature on the concentration of analytes on the surface of quasi-2D SnO2 thin films was explored in dependence analyte's type.

Surface plasmon resonance chemical sensor modified with α-naphthylmethacrylate nano thin film for chloroform detection

The research on the rapid and sensitive detection of pollution caused by the products and technologies used has recently attracted attention in the literature. In the detection of volatile organic compounds (VOCs), polymers/monomers are used in the production of sensitive, fast-responding, reversible thin-film gas sensor elements. In this work, the monomer α-Naphthylmethacrylate was selected as thin film sensor element. The α-Naphthylmethacrylate-based nano thin films were prepared with technique of LB. Monomer LB thin films fabricated onto gold-coated glass substrate to investigate their vapour sensing properties by using Surface Plasmon Resonance (SPR) optical technique. This prepared monomer-based thin film sensor exposed to five different concentrations of chloroform vapors varying between 13.98x103-69.9x103 ppm and the sensor response values were recorded. Swelling dynamics’ of this monomer thin film sensor was also illuminated by using Fick's early-time diffusion law. Diffusion coefficients of α-Naphthylmethacrylate LB thin film sensor materials exposed to the five different concentrations of chloroform vapor were calculated with the help of reflected light intensity graph data and Fick's Law as a function of time. It was determined that the diffusion coefficient values of the first and second slope regions as varying between 5.72x10-17-21.97x10-17 cm2s-1 and 3.06x10-17-6.25x10-17 cm2s-1, respectively. SPR kinetic measurement results showed that α-Naphthylmethacrylate material is promising for the detection of chloroform vapor.

МОДЕЛИРОВАНИЯ СВОЙСТВ МАТЕРИАЛОВ СЕНСОРОВ ГАЗОВ НА ОСНОВЕ КОБАЛЬТСОДЕРЖАЩЕГО ПОЛИАКРИЛОНИТРИЛА С ИСПОЛЬЗОВАНИЕМ РЕГРЕССИОННОГО АНАЛИЗА И НЕЙРОННЫХ СЕТЕЙ

A modeling approach has been developed for materials based on organic semiconductorsand their physicochemical and gas-sensitive properties. For modeling, such methods as multiplelinear and non-linear regression, neural networks were used. As an input vector for modeling theproperties of metal-containing polyacrylonitrile are the parameters of the technological process offorming materials: the mass fraction of the alloying component (cobalt) in the film-forming solution,technological modes of IR annealing: temperature, time of the first and second stages. Outputvector - functional characteristics and physical and chemical properties of materials (resistivity,gas sensitivity coefficient, stability and selectivity). Abstract—Metal–carbon systems with Co metalparticles based on polyacrylonitrile have been synthesized by IR pyrolysis. The resistance valueswere measured in the medium of the detected gas (chlorine). Modeling of the functional characteristicsand physicochemical properties of materials was carried out on the basis of data obtainedfrom the study of 200 samples of cobalt/polyacrylonitrile films. Multiple linear regression proved to be effective for predicting resistivity values. Neural networks are used to predict the gassensitivity coefficient, selectivity, and stability of cobalt-containing polyacrylonitrile films.An artificial neural network in the form of a multilayer perceptron was built to predict the gassensitivity coefficient of gas sensor elements based on the data of technological processes for obtainingmaterial (mass fraction of the alloying component (cobalt) in the film-forming solution,technological modes of IR annealing: temperature, time of the first and second stages). Complianceof the synthesized model was checked: with experimental data: correlation coefficientR=0.82, root-mean-square error st=0.017. The synthesized models satisfactorily describe the collecteddata within the experimental error, which makes it possible to optimize the chemical compositionand heat treatment conditions.

Zero-Padding and Spatial Augmentation-Based Gas Sensor Node Optimization Approach in Resource-Constrained 6G-IoT Paradigm.

Ultra-low-power is a key performance indicator in 6G-IoT ecosystems. Sensor nodes in this eco-system are also capable of running light-weight artificial intelligence (AI) models. In this work, we have achieved high performance in a gas sensor system using Convolutional Neural Network (CNN) with a smaller number of gas sensor elements. We have identified redundant gas sensor elements in a gas sensor array and removed them to reduce the power consumption without significant deviation in the node’s performance. The inevitable variation in the performance due to removing redundant sensor elements has been compensated using specialized data pre-processing (zero-padded virtual sensors and spatial augmentation) and CNN. The experiment is demonstrated to classify and quantify the four hazardous gases, viz., acetone, carbon tetrachloride, ethyl methyl ketone, and xylene. The performance of the unoptimized gas sensor array has been taken as a “baseline” to compare the performance of the optimized gas sensor array. Our proposed approach reduces the power consumption from 10 Watts to 5 Watts; classification performance sustained to 100 percent while quantification performance compensated up to a mean squared error (MSE) of 1.12 × 10−2. Thus, our power-efficient optimization paves the way to “computation on edge”, even in the resource-constrained 6G-IoT paradigm.

SnO2 AND ZnO FILMS STRUCTURED USING POLYMERS FOR AMMONIA DETECTION

The electrophysical properties in air and in the atmosphere with ammonia vapor content of nanosized films of ZnO and SnO2 structured in the process of production using polymers were studied. The investigated electrophysical properties of those films in air and in an atmosphere containing ammonia vapors showed the presence of significant changes in the conductivity of both types of films. The nature of these changes is somewhat different. In ammonia vapors, the current in a zinc oxide film is many times greater than in air. And the tin oxide film in ammonia vapor becomes more high-resistant in comparison with its resistance in air. It was found that the conductivity of both types of films is controlled by intercrystalline potential barriers. However, upon contact with ammonia vapors, these barriers decrease in the zinc oxide films, while the opposite process is observed in the tin dioxide film. The reversible nature of the processes of ammonia molecules interaction with oxide films is observed in both cases. Both for ZnO and for SnO2 the sensitivity to ammonia is recorded already at room temperature. It was also established that the initial characteristics of both types of films were quickly restored without additional measures. These facts make the studied nanostructured films of ZnO and SnO2 using polymers to be promising material for sensitive elements for ammonia gas sensors.

Kinetic models for sensory response of multicomponent oxide nanomaterials with a hierarchical pore system

A kinetic model for sensory response of multicomponent oxide nanomaterials used as sensing elements of gas sensors and vacuum gauges is proposed. It is shown that gas-sensitive properties of nanomaterials depend both on their qualitative and quantitative composition, and morphostructure to determine the presence of a hierarchical pore system therein.

Non-injective gas sensor arrays: identifying undetectable composition changes

Metal-organic frameworks (MOFs) are nanoporous materials with good prospects as recognition elements for gas sensors owing to their adsorptive sensitivity and selectivity. A gravimetric, MOF-based sensor functions by measuring the mass of gas adsorbed in a MOF. Changes in the gas composition are expected to produce detectable changes in the mass of gas adsorbed in the MOF. In practical settings, multiple components of the gas adsorb into the MOF and contribute to the sensor response. As a result, there are typically many distinct gas compositions that produce the same single-sensor response. The response vector of a gas sensor array places multiple constraints on the gas composition. Still, if the number of degrees of freedom in the gas composition is greater than the number of MOFs in the sensor array, the map from gas compositions to response vectors will be non-injective (many-to-one). Here, we outline a mathematical method to determine undetectable changes in gas composition to which non-injective gas sensor arrays are unresponsive. This is important for understanding their limitations and vulnerabilities. We focus on gravimetric, MOF-based gas sensor arrays. Our method relies on a mixed-gas adsorption model in the MOFs comprising the sensor array, which gives the mass of gas adsorbed in each MOF as a function of the gas composition. The singular value decomposition of the Jacobian matrix of the adsorption model uncovers (i) the unresponsive directions and (ii) the responsive directions, ranked by sensitivity, in gas composition space. We illustrate the identification of unresponsive subspaces and ranked responsive directions for gas sensor arrays based on Co-MOF-74 and HKUST-1 aimed at quantitative sensing of CH4/N2/CO2/C2H6 mixtures relevant to natural gas sensing.

Mo-doped SnO2 nanotubes sensor with abundant oxygen vacancies for ethanol detection

This work describes a synthesizing method for Mo-doped SnO2 nanotubes (NTs) with uniform morphology by combining electrostatic spinning and air sintering. The method uses Mo ions to do substitutional doping of Sn ions in SnO2 to construct new lattice defects (such as oxygen vacancies), which provides more active sites for gas adsorption. Ethanol was taken as an example to study gas sensitivity characteristics of synthesized products. The analysis showed that 5 mol% of Mo-doped SnO2 nanotubes sensor exhibited the highest response (46.8) to 100 ppm ethanol at a lower optimum temperature (220 °C) and reduced the response/recovery time to 7/103 s. Also, it manifested excellent selectivity and long-term stability. The functionalized nanotubes structure and optimized parameters (oxygen vacancies concentration, metal vacancies defects, carrier concentration, catalytic sites, and base resistance increased) are the reasons for enhancing gas-sensing performance. This work provides direction that the optimal doping concentration of transition metal elements for metal-oxide NTs gas sensors can achieve the best sensing response.

Creation of thin films on the surface of InP with a controlled gas-sensitive signal under the influence of PbO + Y2O3 compositions

Thin-film objects with a reproducible temperature dependence of the resistance, thermally stable, and easy to obtain can be used as the sensitive elements in semiconductor gas sensors. The aim of this study was to create thin films on the InP surface under the influence of an oxide chemostimulator + inert component (PbO + Y2O3, respectively) compositions and to determine their gas-sensitive properties and their dependence on the formula of the composition.Thin films were synthesised on the InP surface by the method of chemically stimulated thermal oxidation under the influence of various PbO + Y2O3 compositions. The thickness of the formed films, their elemental and chemical composition were determined (by laser ellipsometry, X-ray phase analysis, and infra-red spectroscopy). A number of experiments were carried out to establish the gas-sensitive properties of the obtained films with respect to ammonia with concentrations of 120, 100, and 80 ppm.By chemically stimulated thermal oxidation, we obtained thin films with semiconductor properties on the InP surface. It was determined that the samples had n-type conductivity. A gas-sensitive response was detected in the presence of ammonia in the atmosphere. The ability to create thin films with a predetermined value of sensory response was demonstrated

Preparation of Fe2O3-ZnO Nanocomposites: Structure and Optical Properties

Background: The synthesis of Fe2O3/ZnO nanocomposites has gained wide acceptance in recent years due to its magnetic, photoluminescence and catalytic properties, and as an active element in gas sensors. This type of composite particle has potential biological and biomedical applications such as the detection of cancer cells, bacteria and viruses, and for magnetic separation. Objective: In the present study, first we synthesized the Fe2O3/ZnO nanoparticles, and then the structural, optical and surface morphological properties were investigated by XRD, HRTEM, FESEM, XRF and FTIR analyses. Methods: Fe2O3-ZnO nanoparticles were fabricated by a solgel synthesis method by combining iron chloride hexahydrate and zinc sulfate heptahydrate. In the beginning, 2g of Polyvinylpyrrolidone (PVP) stabilizer was dissolved in 100 mL deionized water and then 5 g FeCl3 was added to the solution with stirring at room temperature. Then 5g of ZnSO4 was added to the solution and synthesis temperature was increased to 100 °C. The product was evaporated for 3 hours, cooled to room temperature and finally calcined at 600 °C for 3 hours. Result: The XRD results showed single-phase Fe2O3-ZnO nanocomposites with a hexagonal wurtzite structure of ZnO and spinel phase of rhombohedral α-Fe2O3. The crystallite size of as-prepared sample was determined at about 45 nm and annealed one was calculated around 40 nm. The SEM images showed that the Fe-Zn nanoparticles changed from spherical shape to rod shape by increasing the temperature after annealing. The TEM studies showed the core-shell nanoparticles with a mean diameter of 47 nm. The sharp peaks in the FTIR spectrum determined the stretching vibrations of Fe and Zn groups in the frequencies of 620, 565 cm-1 and 410 cm-1. Conclusion: The XRD data indicates a single-phase Fe2O3-ZnO structure. The SEM images show that the nanoparticles changed from sphere-like shape to rod-like shape by increasing the annealing temperature. TEM image exhibits the core-shell Fe-Zn nanoparticles with an average diameter of about 37 nm. From the FTIR data, it is shown that the presence of Fe-Zn stretching mode and the intensity of the peaks increased by increasing the annealing temperature. XRF analysis showed peaks of iron and ferrite elements, and an increase in the Zn weight percent was observed from 26.35 %Wt. to 49.26 %Wt. with increasing temperature.

Effect of Oxygen on the Gas-Sensitive Properties of α-Ga2O3/ε-Ga2O3 Structures

Miniature O2 sensors with low energy consumption are of practical interest for the chemical and metallurgical industries, development of systems for analyzing the performance of internal combustion engines and as functional elements of artificial lung ventilation devices. The requirements for miniaturization, high sensitivity, speed and relative cheapness are satisfied by O2 sensors based on β-Ga2O3. The chemical and thermal stability of β-Ga2O3 allows developing gas sensors with extremely high operating temperatures of 400-1100 °C ensuring high reproducibility of their characteristics and high speed of operation. In turn, the high operating temperatures of O2 β-Ga2O3 sensors are their drawback causing high energy consumption.Previously, we studied the effect of H2 on the gas-sensitive properties of the α-Ga2O3/ε-Ga2O3 structure with Pt contacts grown by the halide vapor phase epitaxy (HVPE) on the patterned sapphire substrates (PSS) [1]. Low operating temperatures, weak dependence of properties on the humidity and control of selectivity by means of voltage changes indicate that the research of α-Ga2O3/ε-Ga2O3 structures as sensitive elements of gas sensors is promising. We presume that in addition to increasing the applied voltage to the structures, the sensitivity of α-Ga2O3/ε-Ga2O3 to certain gases, in particular O2 can be increased by reducing the level of doping with a donor impurity. Thus this work is devoted to research the effect of O2 on gas-sensitive properties of α-Ga2O3/ε-Ga2O3 structures doped with Sn.Ga2O3 films were grown by the HVPE in Perfect Crystals LLC. PSS of (0001) orientation and 430 microns in thickness were used as substrates. During the synthesis, the films were doped with Sn. To measure the gas-sensitive properties of the α-Ga2O3/ε-Ga2O3 structures Pt contacts were formed on their surface.The samples consisted of a mixture of α and ε phases with the orientation (0001). Using scanning and transmission electron microscopy, it was found that the α-phase forms columnar structures at the top of the sapphire cone, and the ε-phase fills the gaps between the columns. The characteristic triangular shape of columnar structures indicates that they consist of α-Ga2O3 with trigonal symmetry. ɛ-Ga2O3 has a grain but not polycrystalline structure taking into account the XRD results.Figure 1 shows the I-U characteristics of α-Ga2O3/ε-Ga2O3 structures at the exposure of O2 in a wide range of concentrations C O2 from 2 to 100 % at temperature T = 200 °C. The current through the samples decreases with C O2 increasing. In the range of the T = 180 - 200 °C, at T = 200 °C, the highest response to O2 are observed. It is worth noting that the operating temperatures of the α-Ga2O3/ε-Ga2O3 structures in the reaction to O2 are significantly lower than the operating temperatures of O2 β-Ga2O3 sensors. These low values of T are an advantage in developing gas-analytical systems with low energy consumption. The concentration dependences of the response at the T = 180 - 200 °C are approximated fairly accurately by a power function: response ~ C O2 b , where b is the exponent that depends on the temperature.Figure 1-Effect of O2 on I-U characteristics of α-Ga2O3/ε-Ga2O3.A decrease in the Sn impurity concentration in α-Ga2O3/ε-Ga2O3 from ~4×1018 cm-3 to ~1.5×1017 cm-3 leads to a significant sensitivity to O2 in the temperature range from 180 to 220 °C at low values of the applied voltage U ≤ 7.5 V. The I-U characteristics of α-Ga2O3/ε-Ga2O3 structures in a dry gas mixture N2 + O2 are described by the model of MSM structures based on the theory of thermoelectronic emission in diode approximation with the resistance of the semiconductor layer exceeding the resistance of the space charge regions at the metal/semiconductor interface. The sensory effect consists in the chemisorption of oxygen molecules on the surface of ε-Ga2O3 that according to SEM has a grain structure. As a result, the energy barrier at the grain boundaries of ε-Ga2O3 increases leading to a decrease in the current. The studied structures showed high sensitivity to relatively low concentrations (0.745 %) of H2 and CO at the T = 180-220 °C and practically did not react to the effects of NO2 and CH4.This research was financially supported by the Russian Scientific Foundation, grant No 20-79-10043.[1] A V Almaev, V I Nikolaev, S I Stepanov, A I Pechnikov, A V Chikiryaka, N N Yakovlev, V M Kalygina, V V Kopyev and E V Chernikov. J. Phys. D: Appl. Phys. 53 (2020) 414004 (9pp) https://doi.org/10.1088/1361-6463/ab9c69 Figure 1