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This paper presents the integration of a sensing layer over interdigitated electrodes and an electronic circuit on the same flexible printed circuit board. This integration provides an effective technique to use this design as a wearable gas measuring system in a target application, exhibiting high performance, low power consumption, and being lightweight for on-site monitoring. The wearable system proves the concept of using an NFC tag combined with a chemoresistive gas sensor as a cumulative gas sensor, having the possibility of holding the data for a working day, and completely capturing the exposure of a person to NO2 concentrations. Three different types of sensors were tested, depositing the sensing layers on gold electrodes over Kapton substrate: bare graphene, graphene decorated with 5 wt.% zinc oxide nanoflowers, or nanopillars. The deposited layers were characterized using FESEM, EDX, XRD, and Raman spectroscopy to determine their crystalline structure, morphological and chemical compositions. The gas sensing performance of the sensors was analyzed against NO2 (dry and humid conditions) and other interfering species (dry conditions) to check their sensitivity and selectivity. The resultant-built wearable NFC tag system accumulates the data in a non-volatile memory every minute and has an average low power consumption of 24.9 µW in dynamic operation. Also, it can be easily attached to a work vest.
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The need for integrated passive devices (IPDs) emerges from the increasing consumer demand for electronic product miniaturization. Metal-insulator-metal (MIM) capacitors are vital components of IPD systems. Developing new materials and technologies is essential for advancing capacitor characteristics and co-integrating with other electronic passives. Here we present an innovative electrochemical technology joined with the sputter-deposition of Al and Zr layers to synthesize novel planar nanocomposite metal-oxide dielectrics consisting of ZrO2 nanorods self-embedded into the nanoporous Al2O3 matrix such that its pores are entirely filled with zirconium oxide. The technology is utilized in MIM capacitors characterized by modern surface and interface analysis techniques and electrical measurements. In the 95-480 nm thickness range, the best-achieved MIM device characteristics are the one-layer capacitance density of 112 nF·cm-2, the loss tangent of 4·10-3 at frequencies up to 1 MHz, the leakage current density of 40 pA·cm-2, the breakdown field strength of up to 10 MV·cm-1, the energy density of 100 J·cm-3, the quadratic voltage coefficient of capacitance of 4 ppm·V-2, and the temperature coefficient of capacitance of 480 ppm·K-1 at 293-423 K at 1 MHz. The outstanding performance, stability, and tunable capacitors' characteristics allow for their application in low-pass filters, coupling/decoupling/bypass circuits, RC oscillators, energy-storage devices, ultrafast charge/discharge units, or high-precision analog-to-digital converters. The capacitor technology based on the non-porous planar anodic-oxide dielectrics complements the electrochemical conception of IPDs that combined, until now, the anodized aluminum interconnection, microresistors, and microinductors, all co-related in one system for use in portable electronic devices.
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Nanostructured tungsten disulfide (WS2) is one of the most promising candidates for being used as active nanomaterial in chemiresistive gas sensors, as it responds to hydrogen gas at room temperature. This study analyzes the hydrogen sensing mechanism of a nanostructured WS2 layer using near-ambient-pressure X-ray photoelectron spectroscopy (NAP-XPS) and density functional theory (DFT). The W 4f and S 2p NAP-XPS spectra suggest that hydrogen makes physisorption on the WS2 active surface at room temperature and chemisorption on tungsten atoms at temperatures above 150 °C. DFT calculations show that a hydrogen molecule physically adsorbs on the defect-free WS2 monolayer, while it splits and makes chemical bonds with the nearest tungsten atoms on the sulfur point defect. The hydrogen adsorption on the sulfur defect causes a large charge transfer from the WS2 monolayer to the adsorbed hydrogen. In addition, it decreases the intensity of the in-gap state, which is generated by the sulfur point defect. Furthermore, the calculations explain the increase in the resistance of the gas sensor when hydrogen interacts with the WS2 active layer.
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This paper investigates the effect of decorating graphene with zinc oxide (ZnO) nanoparticles (NPs) for the detection of NO2. In this regard, two graphene sensors with different ZnO loadings of 5 wt.% and 20 wt.% were prepared, and their responses towards NO2 at room temperature and different conditions were compared. The experimental results demonstrate that the graphene loaded with 5 wt.% ZnO NPs (G95/5) shows better performance at detecting low concentrations of the target gas than the one loaded with 20 wt.% ZnO NPs (G80/20). Moreover, measurements under dry and humid conditions of the G95/5 sensor revealed that the material is very sensitive to ambient moisture, showing an almost eight-fold increase in NO2 sensitivity when the background changes from dry to 70% relative humidity. Regarding sensor selectivity, it presents a significant selectivity towards NO2 compared to other gas compounds.
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Grafito , Nanopartículas , Óxido de Zinc , Dióxido de NitrógenoRESUMEN
Many research works report a sensitive detection of a wide variety of gas species. However, their in-lab detection is usually performed by using single gases and, therefore, selectivity often remains an unsolved issue. This paper reports a four-sensor array employing different nano-carbon sensitive layers (bare graphene, SnO2@Graphene, WO3@Graphene, and Au@CNTs). The different gas-sensitive films were characterised via several techniques such as FESEM, TEM, and Raman. First, an extensive study was performed to detect isolated NO2, CO2, and NH3molecules, unravelling the sensing mechanism at the operating temperatures applied. Besides, the effect of the ambient moisture was also evaluated. Afterwards, a model for target gas identification and concentration prediction was developed. Indeed, the sensor array was used in mixtures of NO2and CO2for studying the cross-sensitivity and developing a calibration model. As a result, the NO2detection with different background levels of CO2was achieved with anR2of 0.987 and an RMSE of about 22 ppb.
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Pure and dysprosium-loaded ZnO films were grown by radio-frequency magnetron sputtering. The films were characterized using a wide variety of morphological, compositional, optical, and electrical techniques. The crystalline structure, surface homogeneity, and bandgap energies were studied in detail for the developed nanocomposites. The properties of pure and dysprosium-doped ZnO thin films were investigated to detect nitrogen dioxide (NO2) at the ppb range. In particular, ZnO sensors doped with rare-earth materials have been demonstrated as a feasible strategy to improve the sensitivity in comparison to their pure ZnO counterparts. In addition, the sensing performance was studied and discussed under dry and humid environments, revealing noteworthy stability and reliability under different experimental conditions. In this perspective, additional gaseous compounds such as ammonia and ethanol were measured, resulting in extremely low sensing responses. Therefore, the gas-sensing mechanisms were discussed in detail to better understand the NO2 selectivity given by the Dy-doped ZnO layer.
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This paper presents a methodology to quantify oxidizing and reducing gases using n-type and p-type chemiresistive sensors, respectively. Low temperature sensor heating with pulsed UV or visible light modulation is used together with the application of the fast Fourier transform (FFT) to extract sensor response features. These features are further processed via principal component analysis (PCA) and principal component regression (PCR) for achieving gas discrimination and building concentration prediction models with R2 values up to 98% and RMSE values as low as 5% for the total gas concentration range studied. UV and visible light were used to study the influence of the light wavelength in the prediction model performance. We demonstrate that n-type and p-type sensors need to be used together for achieving good quantification of oxidizing and reducing species, respectively, since the semiconductor type defines the prediction model's effectiveness towards an oxidizing or reducing gas. The presented method reduces considerably the total time needed to quantify the gas concentration compared with the results obtained in a previous work. The use of visible light LEDs for performing pulsed light modulation enhances system performance and considerably reduces cost in comparison to previously reported UV light-based approaches.
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Benzene, toluene, and xylene, commonly known as BTX, are hazardous aromatic organic vapors with high toxicity towards living organisms. Many techniques are being developed to provide the community with portable, cost effective, and high performance BTX sensing devices in order to effectively monitor the quality of air. In this paper, we study the effect of decorating graphene with tin oxide (SnO2) or tungsten oxide (WO3) nanoparticles on its performance as a chemoresistive material for detecting BTX vapors. Transmission electron microscopy and environmental scanning electron microscopy are used as morphological characterization techniques. SnO2-decorated graphene displayed high sensitivity towards benzene, toluene, and xylene with the lowest tested concentrations of 2 ppm, 1.5 ppm, and 0.2 ppm, respectively. In addition, we found that, by employing these nanomaterials, the observed response could provide a unique double signal confirmation to identify the presence of benzene vapors for monitoring occupational exposure in the textiles, painting, and adhesives industries or in fuel stations.
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During the few last years, indoor and outdoor Air Quality Monitoring (AQM) has gained a lot of interest among the scientific community due to its direct relation with human health. The Internet of Things (IoT) and, especially, Wireless Sensor Networks (WSN) have given rise to the development of wireless AQM portable systems. This paper presents the development of a LoRa (short for long-range) based sensor network for AQM and gas leakage events detection. The combination of both a commercial gas sensor and a resistance measurement channel for graphene chemoresistive sensors allows both the calculation of an Air Quality Index based on the concentration of reducing species such as volatile organic compounds (VOCs) and CO, and it also makes possible the detection of NO2, which is an important air pollutant. The graphene sensor tested with the LoRa nodes developed allows the detection of NO2 pollution in just 5 min as well as enables monitoring sudden changes in the background level of this pollutant in the atmosphere. The capability of the system of detecting both reducing and oxidizing pollutant agents, alongside its low-cost, low-power, and real-time monitoring features, makes this a solution suitable to be used in wireless AQM and early warning systems.
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Essential oil resins of Aucoumea klaineana (Okoume) and Canarium schweinfurthii (Aiele) species, of the Burseraceae family, were studied to investigate their bioactive constituents and their antibacterial activities. Aiele resin had a higher yield (6.86%) of essential oil than Okoume (3.62%). Twenty-one compounds for Okoume and eighteen for Aiele essential oil were identified using a gas chromatography-mass spectrometry (Gp-C-MS) technique. The main compounds identified in Okoume essential oil were benzenemethanol, α, α,4-trimethyl (28.85%), (+)-3-carene (3,7,7-trimethyl bicyclo[4.1.0]hept-3-ene) (17.93%), D-Limonene ((4R)-1-methyl-4-prop-1-en-2-ylcyclohexene) (19.36%). With regard to the Aiele essential oil, we identified (1R,4S)-1-methyl-4-propan-2-ylcyclohex-2-en-1-ol (26.64%), and 1-methyl-4-propan-2-ylcyclohex-2-en-1-ol (26.83%). Two strains of bacteria, Escherichia coli and Staphylococcus aureus, were used in antibacterial tests. S. aureus was found to be more sensitive to Okoume and Aiele essential oils, with a high inhibition zone ranging from 20 to 16 mm. In comparison, the inhibition zone ranged from 6 to 12 mm for E. coli. An electronic nose (e-nose) combined with pattern analysis methods such as principal component analysis (PCA), discriminant function analysis (DFA), and hierarchical cluster analysis (HCA) were used to discriminate the essential oil samples. In summary, the e-nose and GC-MS allowed the identification of bioactive compounds in the essential oil samples, which have a strong antimicrobial activity, with satisfactory results.
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Antibacterianos , Antiinfecciosos , Burseraceae , Nariz Electrónica , Aceites Volátiles , Antibacterianos/farmacología , Escherichia coli , Gabón , Cromatografía de Gases y Espectrometría de Masas , Pruebas de Sensibilidad Microbiana , Aceites Volátiles/farmacología , Staphylococcus aureusRESUMEN
This paper explores the gas sensing properties of graphene nanolayers decorated with lead halide perovskite (CH3NH3PbBr3) nanocrystals to detect toxic gases such as ammonia (NH3) and nitrogen dioxide (NO2). A chemical-sensitive semiconductor film based on graphene has been achieved, being decorated with CH3NH3PbBr3 perovskite (MAPbBr3) nanocrystals (NCs) synthesized, and characterized by several techniques, such as field emission scanning electron microscopy, transmission electron microscopy and X-ray photoelectron spectroscopy. Reversible responses were obtained towards NO2 and NH3 at room temperature, demonstrating an enhanced sensitivity when the graphene is decorated by MAPbBr3 NCs. Furthermore, the effect of ambient moisture was extensively studied, showing that the use of perovskite NCs in gas sensors can become a promising alternative to other gas sensitive materials, due to the protective character of graphene, resulting from its high hydrophobicity. Besides, a gas sensing mechanism is proposed to understand the effects of MAPbBr3 sensing properties.
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Many sensors are developed over flexible substrates to be used as wearables, which does not guarantee that they will actually withstand being bent. This work evaluates the gas sensing performance of metal oxide devices of three different types, before and after having undergone automated, repetitive bending tests. These tests were aimed at demonstrating that the fabricated sensors were actually flexible, which cannot be taken for granted beforehand. The active layer in these sensors consisted of WO3 nanowires (NWs) grown directly over a Kapton foil by means of the aerosol-assisted chemical vapor deposition. Their response to different H2 concentrations was measured at first. Then, they were cyclically bent, and finally, their response to H2 was measured again. Sensors based on pristine WO3-NWs over Ag electrodes and on Pd-decorated NWs over Au electrodes maintained their performance after having been bent. Ag electrodes covered with Pd-decorated NWs became fragile and lost their usefulness. To summarize, two different types of truly flexible metal oxide gas sensor were fabricated, whereas a third one was not flexible, despite being grown over a flexible substrate following the same method. Finally, we recommend that one standard bending test procedure should be established to clearly determine the flexibility of a sensor considering its intended application.
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Diamondoids, sp3 -hybridized nanometer-sized diamond-like hydrocarbons (nanodiamonds), difunctionalized with hydroxy and primary phosphine oxide groups, enable the assembly of the first sp3 -C-based chemical sensors by vapor deposition. Both pristine nanodiamonds and palladium nanolayered composites can be used to detect toxic NO2 and NH3 gases. This carbon-based gas sensor technology allows reversible NO2 detection down to 50â ppb and NH3 detection at 25-100â ppm concentration with fast response and recovery processes at 100 °C. Reversible gas adsorption and detection is compatible with 50 % humidity conditions. Semiconducting p-type sensing properties are achieved from devices based on primary phosphine-diamantanol, in which high specific area (ca. 140â m2 g-1 ) and channel nanoporosity derive from H-bonding.
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Indium oxide octahedral nanopowders were obtained from an ionic precursor compound after an oxidation process conducted under a low-oxygen atmosphere. This method was found to produce contamination-free indium oxide nanomaterial with very similar morphological and crystalline properties to the one produced by vapor-phase transport, but at significantly lower temperatures and higher yield. The as-synthesized indium oxide was mixed to an organic vehicle and microdrop deposited to form a film bridging the interdigitated silver electrodes patterned on top of a flexible, polyimide (Kapton®), substrate. The gas sensing properties of the flexible chemoresistors towards ammonia vapors, hydrogen, and nitrogen dioxide were investigated. It was found that these sensors were remarkably sensitive to nitrogen dioxide at a low operating temperature of 150 °C. These results are consistent with the performance of vapor-phase transport synthesized indium oxide octahedra sensors on rigid, ceramic substrates. Therefore, the results presented here pave the way for the mass production of inexpensive gas sensors onto flexible substrates via additive manufacturing.
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Here we report on the use of pulsed UV light for activating the gas sensing response of metal oxides. Under pulsed UV light, the resistance of metal oxides presents a ripple due to light-induced transient adsorption and desorption phenomena. This methodology has been applied to tungsten oxide nanoneedle gas sensors operated either at room temperature or under mild heating (50 °C or 100 °C). It has been found that by analyzing the rate of resistance change caused by pulsed UV light, a fast determination of gas concentration is achieved (ten-fold improvement in response time). The technique is useful for detecting both oxidizing (NO2) and reducing (NH3) gases, even in the presence of different levels of ambient humidity. Room temperature operated sensors under pulsed UV light show good response towards ammonia and nitrogen dioxide at low power consumption levels. Increasing their operating temperature to 50 °C or 100 °C has the effect of further increasing sensitivity.
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The properties of multi-wall carbon nanotubes decorated with iridium oxide nanoparticles (IrOx-MWCNTs) are studied to detect harmful gases such as nitrogen dioxide and ammonia. IrOx nanoparticles were synthetized using a two-step method, based on a hydrolysis and acid condensation growth mechanism. The metal oxide nanoparticles obtained were employed for decorating the sidewalls of carbon nanotubes. Iridium-oxide nanoparticle decorated carbon nanotube material showed higher and more stable responses towards NH3 and NO2 than bare carbon nanotubes under different experimental conditions, establishing the optimal operating temperatures and estimating the limits of detection and quantification. Furthermore, the nanomaterials employed were studied using different morphological and compositional characterization techniques and a gas sensing mechanism is proposed.
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Controls of surface potential have been proposed to accelerate the time response of MOX gas sensors. These controls use temperature modulations and a feedback loop based on first-order sigma-delta modulators to keep constant the surface potential. Changes in the surrounding gases, therefore, must be compensated by average temperature produced by the control loop, which is the new output signal. The purpose of this paper is to present a second order sigma-delta control of the surface potential for gas sensors. With this new control strategy, it is possible to obtain a second order zero of the quantization noise in the output signal. This provides a less noisy control of the surface potential, while at the same time some undesired effects of first order modulators, such as the presence of plateaus, are avoided. Experiments proving these performance improvements are presented using a gas sensor made of tungsten oxide nanowires. Plateau avoidance and second order noise shaping is shown with ethanol measurements.
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This paper presents a focused review on the nanomaterials and associated transduction schemes that have been developed for the selective detection of hydrogen sulfide. It presents a quite comprehensive overview of the latest developments, briefly discusses the hydrogen sulfide detection mechanisms, identifying the reasons for the selectivity (or lack of) observed experimentally. It critically reviews performance, shortcomings, and identifies missing or overlooked important aspects. It identifies the most mature/promising materials and approaches for achieving inexpensive hydrogen sulfide sensors that could be employed in widespread, miniaturized, and inexpensive detectors and, suggests what research should be undertaken for ensuring that requirements are met.
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An array of ZnO thin film sensors was obtained by thermal oxidation of physical vapor deposited thin Zn films. Different conditions of the thermal treatment (duration and temperature) were applied in view of obtaining ZnO sensors with different gas sensing properties. Films having undergone a long thermal treatment exhibited high responses to low ethanol concentrations, while short thermal treatments generally led to sensors with high ethanol sensitivity. The sensor array was used to distinguish among Tequilas and Agave liquor. Linear discriminant analysis and the multilayer perceptron neural network reached 100% and 86.3% success rates in the discrimination between real Tequila and Agave liquor and in the identification of Tequila brands, respectively. These results are promising for the development of an inexpensive tool offering low complexity and cost of analysis for detecting fraud in spirits.
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Quality control of essential oils is an important topic in industrial processing of medicinal and aromatic plants. In this paper, the performance of Fuzzy Adaptive Resonant Theory Map (ARTMAP) and linear discriminant analysis (LDA) algorithms are compared in the specific task of quality classification of Rosa damascene essential oil samples (one of the most famous and valuable essential oils in the world) using an electronic nose (EN) system based on seven metal oxide semiconductor (MOS) sensors. First, with the aid of a GC-MS analysis, samples of Rosa damascene essential oils were classified into three different categories (low, middle, and high quality, classes C1, C2, and C3, respectively) based on the total percent of the most crucial qualitative compounds. An ad-hoc electronic nose (EN) system was implemented to sense the samples and acquire signals. Forty-nine features were extracted from the EN sensor matrix (seven parameters to describe each sensor curve response). The extracted features were ordered in relevance by the intra/inter variance criterion (Vr), also known as the Fisher discriminant. A leave-one-out cross validation technique was implemented for estimating the classification accuracy reached by both algorithms. Success rates were calculated using 10, 20, 30, and the entire selected features from the response of the sensor array. The results revealed a maximum classification accuracy of 99% when applying the Fuzzy ARTMAP algorithm and 82% for LDA, using the first 10 features in both cases. Further classification results explained that sub-optimal performance is likely to occur when all the response features are applied. It was found that an electronic nose system employing a Fuzzy ARTMAP classifier could become an accurate, easy, and inexpensive alternative tool for qualitative control in the production of Rosa damascene essential oil.