Search

This article describes a simple though extremely effective sensor for acetone monitoring in the breath. The sensor is capable of monitoring the presence of acetone at parts per million (ppm) concentrations, thus being suitable for a diabetes diagnosis. It has a dimension of $3 {\,\,\mathrm {mm}} \times 6 {\,\,\mathrm {mm}}$ and a cost of less than one dollar. The small dimensions allow one to greatly limit the power required to increase its temperature, and its high selectivity with respect to other gases present in the breath reduces the risk of false-positive responses. The sensor is based on a thin alumina substrate on which platinum strips are deposited on both faces. A thin Nb2O5 layer with a nanometric thickness provides the required sensitivity and selectivity. Sensor prototypes have been characterized by field emission scanning electron microscopy (FESEM) and X-ray photoelectron spectroscopy (XPS) and proved an inherent linear response up to a few ppm of acetone. [ABSTRACT FROM AUTHOR]

In this paper, the impact of the bias networks on a radio frequency (RF) power amplifier (PA) is analyzed and discussed comprehensively. Both the different sizes and positions of the bias microstrip line circuit have been studied for a broadband class AB PA. Both simulations and measurements show that the performance of the PA can be greatly improved with the adjustment of the bias circuit by effecting the harmonic impedance of the whole matching circuit. Compared with the existing works, the fabricated PA based on the proposed technique provides the best performance, thereby demonstrating the effectiveness of the developed bias circuit optimization method. [ABSTRACT FROM AUTHOR]

Provides information on the results of the effect of temperature on the direct current behavior, the small signal performance and the noise properties of advanced transistors up to microwave frequencies. Cryogenic measurements of packaged devices; On-wafer temperature-dependent measurements; Scattering parameter measurement.

In this article, we present a novel autocorrelation-based frequency estimation algorithm for single-tone sinusoidal signals. In comparison to other state-of-the-art frequency estimation methods, the proposed one provides a better tradeoff between accuracy, complexity, and estimation range. In particular, the algorithm is able to achieve the Cramer–Rao lower bound for moderate and high signal-to-noise ratio, and its implementation is feasible even in resource-constrained microcontrollers, as those commonly used in the Industrial Internet-of-Things (IIoT) applications and low-cost instrumentation. Finally, we investigate the performance of the algorithm in the case of a practical IIoT application, i.e., frequency estimation of unbalanced three-phase power systems, showing that it outperforms several other autocorrelation-based estimators. [ABSTRACT FROM AUTHOR]

The development and application of a hydrogen dual sensor (HDS) for the application in the fuel cell (FC) field, is reported. The dual sensing device is based on a ceramic platform head with a semiconducting metal oxide layer (MOx) printed on Pt interdigitated contacts on one side and a Pt serpentine resistance on the back side. MOx layer acts as a conductometric (resistive) gas sensor, allowing to detect low H 2 concentrations in air with high sensitivity and fast response, making it suitable as a leak hydrogen sensor. The proposed Co-doped SnO 2 layer shows high sensitivity to hydrogen (R 0 /R = 90, for 2000 ppm of H 2 ) at 250 °C in air, and with fast response (<3 s). Pt resistance serves as a thermal conductivity sensor, and can used to monitor the whole range of hydrogen concentration (0–100%) in the fuel cell feed line with short response-recovery times, lower than 13 s and 14 s, respectively. The effect of the main functional parameters on the sensor response have been evaluated by bench tests. The results demonstrate that the dual sensor, in spite of its simplicity and cheapness, is promising for application in safety and efficiency control systems for FC power source. [ABSTRACT FROM AUTHOR]

Presents a study that investigated the noise resistance of field-effect transistors at microwave frequencies. Comparison of the findings with the results of studies of transistor noise characterization; Correlation between the performance of the noise resistance and frequency; Relationship between the performance of the noise resistance and the temperature.

An extended-reality (XR) platform for real-time monitoring of patients' health during surgical procedures is proposed. The proposed system provides real-time access to a comprehensive set of patients' information, which are made promptly available to the surgical team in the operating room (OR). In particular, the XR platform supports the medical staff by automatically acquiring the patient's vitals from the operating room instrumentation and displaying them in real-time directly on an XR headset. Furthermore, information regarding the patient clinical record is also shown upon request. Finally, the XR-based monitoring platform also allows displaying in XR the video stream coming directly from the endoscope. The innovative aspect of the proposed XR-based monitoring platform lies in the comprehensiveness of the available information, in its modularity and flexibility (in terms of adaption to different sources of data), ease of use, and most importantly, in a reliable communication, which are critical requirements for the healthcare field. To validate the proposed system, experimental tests were conducted using instrumentation typically available in the operating room (i.e., a respiratory ventilator, a patient monitor for intensive care, and an endoscope). The overall results showed (i) an accuracy of the data communication greater than 99 %, along with (ii) an average time response below ms, and (iii) satisfying feedback from the SUS questionnaires filled out by the physicians after intensive use. [ABSTRACT FROM AUTHOR]

In this work, a SAW resonator is characterized in terms of admittance (Y-) parameters in the temperature range spanning from 0 °C to 100 °C, with the aim of highlighting how its physical properties are affected by the temperature change. A lumped-element equivalent-circuit model is used to represent the device under test at the considered temperature conditions and a parameters extraction process based on a Lorentzian fitting is developed for the determination of the equivalent-circuit elements in the investigated temperature range. A very good agreement is observed between the performed measurements and the model simulations. The characterization process and the subsequent equivalent-circuit parameters extraction at different temperature values are described and discussed. [ABSTRACT FROM AUTHOR]

The knowledge of the small-signal equivalent circuit of microwave GaAs field effect transistors (FETs) is crucial for the design of low-noise amplifiers and is very useful to support the analysis of the transistor performance. This paper reports the results of our experimental activity concerning the application of an improved procedure for the direct extraction of the model element values from scattering (S-) parameter measurements. This analytical procedure was tested on low-noise pseudomorphic high electron mobility transistors (pHEMTs) up to 6 GHz and at cryogenic temperatures without any optimization or tuning adjustment. This paper reports the behavior of the intrinsic elements versus bias condition; the experimental results were found to match the theoretical expectations. The very good agreement between the simulated and measured S-parameters confirms the validity of the proposed method. To carry out the experimental activity, a properly designed cryogenic setup operating in our laboratory, which allows performing direct current (dc) and microwave characterization down to 30 K, was employed. [ABSTRACT FROM AUTHOR]

Wireless sensor elements integrated with miniaturized antennas are useful in various applications such as wearable chemical and environmental sensors and Internet-of-Things (IoT) sensor nodes. A major problem in antenna operation is detuning of the antenna bandwidth due to loading by the sensor element. In this article, we report on the integration of an interdigitated capacitor (IDC), acting as a sensor, into an aperture coupled patch (ACP) antenna, such that weak coupling is established between the IDC and the rectangular patch resonator. Because of low mutual coupling, during the sensing process the antenna is not detuned out of its operational bandwidth and its performance is not compromised by the presence of the sensor and vice versa. A sensing material (barium titanate film) is deposited on the IDC located at the edge of the microstrip line used to slot-feed the ACP antenna. A change in the material permittivity is transduced into a variation of resonant frequency of the antenna. We describe the design and fabrication of the IDC sensor-integrated ACP antenna and demonstrate the measured sensing performance at different temperatures and relative humidity concentrations. [ABSTRACT FROM AUTHOR]

In this article, the electrochemical monitoring of phenol (Ph) in water by using a nanostructured MnO2-modified screen-printed carbon electrode (MnO2-SPCE) is reported. MnO2 nanoparticles were synthesized by the redox-precipitation method. Morphological, textural, and microstructural characteristics were investigated by scanning electron microscopy (SEM), X-ray diffraction, Raman, Brunauer–Emmett–Teller (BET) surface area, and pore volume analyses. Electrochemical properties of the modified MnO2-SPCE electrode have been investigated by cyclic voltammetry and linear sweep voltammetry. The detection of Ph in water by the developed sensor was exploited using square wave voltammetry and chronoamperometry. The sensor showed good characteristics, such as simple fabrication, low cost, good sensitivity, stability, reproducibility, and selectivity, against inorganic analytes and other phenolic compounds. The reported results demonstrated the great potential of nanostructured MnO2 in developing high performances electrochemical sensors to be utilized in the field of environmental pollution monitoring. [ABSTRACT FROM AUTHOR]

In the present work, a spar-buoy scaled model was designed and built through a "Lab-on-Sea" unit, equipped with an energy harvesting system. Such a system is based on deformable bands, which are loyal to the unit, to convert wave motion energy into electricity by means of piezo patch transducers. In a preliminary stage, the scaled model, suitable for tests in a controlled ripples-type wave motion channel, was tested in order to verify the "fixed-point" assumption in pitch and roll motions and, consequently, to optimize energy harvesting. A special type of structure was designed, numerically simulated, and experimentally verified. The proposed solution represents an advantageous compromise between the lightness of the used materials and the amount of recoverable energy. The energy, which was obtained from the piezo patch transducers during the simulations in the laboratory, was found to be enough to self-sustain the feasible on-board sensors and the remote data transmission system. [ABSTRACT FROM AUTHOR]

Here, this article reports about the design of a soft sensor (SS) able to monitor the hazardous gases in industrial plants. The SS is designed to estimate the gas concentrations by means of the measurements coming from an array of sensors, avoiding at the same time the humidity and temperature influence on array outputs. The SS has been designed with a data-driven approach, using a set of experimental data acquired in a laboratory. The design methodologies of two different SSs are compared, with the aim of obtaining both the good performance and a low computational complexity. As a first approach, a principal component analysis (PCA) has been performed to exploit the high correlation among some of the measures coming from the sensor array. A classical multilayer perceptron neural network is then trained to estimate the relationships between the PCA outputs and the gas concentrations. As a second approach, a deep belief network (DBN) has been considered. The data here reported show a good accuracy in the evaluation of several gas concentrations, even in the presence of noised measurements, allowing an efficient risk warning. Even if both the methods gave a similar performance, a lower number of model parameters and a lower noise sensitivity are obtained when using DBNs. [ABSTRACT FROM AUTHOR]

Neurodegenerative diseases such as Alzheimer, Parkinson, motor neuron, and Chorea affect millions of people today. Their effect on the central nervous system causes the loss of brain functions as well as motor disturbances and sometimes cognitive deficits. In such a scenario, the monitoring and evaluation of early symptoms are mandatory for the improvement of the patient’s quality of life. Here, the authors describe the development, the laboratory calibration, and the “in-field validation” under the medical supervision of a movement tremors recorder for subjects affected by neurodegenerative diseases. The developed device is based on an array of four accelerometers connected to an embedded development board. This system is able to monitor tremor/movement, accidental falls, and, moreover, it can track the Alzheimer subjects’ geographical position. A remote supervisor can collect data from the system through Bluetooth, Wi-Fi, or GSM connections. A data compression algorithm was developed directly on board in order to increase the efficiency of data transmission and reduce power consumptions. [ABSTRACT FROM AUTHOR]

Abstract 2D-SnS 2 flakes were synthesized via a wet chemical route and deposited as a thin film onto the Pt-interdigitated contacts of a ceramic substrate with aim to fabricate a conductometric sensor. The 2D-SnS 2 sensing film was then annealed "in situ" under controlled conditions at different temperatures up to 400 °C. The morphological, microstructural and electrical properties of the sensing film, before and after the thermal treatment, were characterized by "in situ" techniques. SEM analysis has shown that the 2D flake morphology was maintained after thermal treatments, whereas Raman and EDX analysis have highlighted the partial/total modification of the SnS 2 phase towards the SnO 2. As a consequence of the formation of 2D-SnS 2 /SnO 2-x mixed phases, a dramatic change of the electrical properties of the sensing film has been also observed. Conductometric gas sensors based on hybrid SnS 2 -SnO 2-x nanoflakes were then obtained by simple self-annealing treatments of 2D-SnS 2 film directly on the sensor substrate. The fabricated sensors were tested toward ammonia (NH 3) as target gas. Results evidence that increasing the annealing temperature of the 2D-SnS 2 sensitive film, the electrical resistance of the sensing layer decreases while the response towards ammonia increases, showing the maximum at an annealing treatment of 250 °C. This behaviour was explained on the basis of the morphological, microstructural and electrical modifications observed, highlighting the role of 2D-SnS 2 /SnO 2-x mixed phases in determining the sensing properties towards ammonia. Highlights • Synthesis of two-dimensional (2D) SnS 2 flakes by a wet chemical route. • Formation of SnS 2 -SnO 2-x heterostructures by self-annealing of SnS 2 sensing layer on a sensor substrate. • Effect of annealing temperature on the electrical and NH 3 sensing properties of the sensing layer. • SnS 2 -SnO 2-x mixed phases show improved NH 3 sensing properties than pure SnS 2 or SnO 2 phases. [ABSTRACT FROM AUTHOR]

In this paper, the evaluation of the gas sensing performance of chemoresistive sensor devices based on M-doped CuO (M = Sn, Zn) nanoparticles prepared by a simple wet chemical method is reported. The morphology of samples has been assessed by scanning electron microscope and transmission electron microscope. The sensors were fabricated, depositing by drop coating the nanoparticles on the sensor substrate platform, and the electrical performance upon exposure to different gases in the air was recorded. The CuO-based gas sensors present a p-type semiconductor behavior. The results of electrical tests have shown that Sn and Zn effectively act as promoters improving the gas sensing properties of CuO toward some volatile organic compounds such as acetone and ethanol. Zn–CuO sensor resulted the most sensitive and selective to acetone, revealing that the appropriate choice of dopant plays a key role in the design of CuO-based sensors. [ABSTRACT FROM AUTHOR]

Spinels (AB 2 O 4 ) metal oxides have gain extensive attention in recent years for gas sensing applications. In the present work, the synthesis, characterization and hydrogen sensing characteristics of nanostructured Sm-doped cobalt ferrite (Sm x -CoFe 2−x O 4 ) have been reported. The structural and morphological properties of the synthetized material were studied by X-ray diffraction (XRD), scanning electron microscopy, micro-Raman and X-ray photoelectron spectroscopy (XPS). In order to check the potential applicability of the synthesized Sm-doped Co-ferrite for hydrogen leak sensing, a simple conductometric sensor has been fabricated and tested. The electrical behavior of the sensor has been recorded by exposure to hydrogen and some interfering gases. The results demonstrated that the sensor developed is promising for the detection of hydrogen leak as it possesses good sensitivity, stable behavior and fast response and recovery. [ABSTRACT FROM AUTHOR]

This paper reports on the high sensitivity of sub-spherical In 2 O 3 -Pt nanoparticles (NPs) for detecting ppb levels of acetone, a biomarker for diabetes. The In 2 O 3 -Pt NPs, in the form of monodisperse metal-oxide In 2 O 3 NPs with diameters of 6–8 nm, decorated with 2 wt% Pt metal NPs (2–3 nm) on the surface, were synthesized by a novel non-aqueous sol–gel route. NPs samples were investigated by X-ray powder diffraction (XRPD), using the advanced whole powder pattern modeling (WPPM) method, and high-resolution transmission electron microscopy (HR-TEM). The advantage of this preparative process is that it preserves metallic platinum NPs formed during the synthesis. The highly sensitive acetone sensor based on these NPs, showed a lower detection limit as low as 10 ppb or less, which is the lowest detection limit ever reported for any chemoresistive acetone sensors. This exceptional performance is likely due to the key role played by very small Pt metal NPs uniformly distributed in the In 2 O 3 -Pt nanostructure. The developed sensor would be suitable for use as a highly sensitive, practical breath acetone checker for daily diet and diabetes management and diagnosis. [ABSTRACT FROM AUTHOR]

This work addresses an innovative processing strategy to improve the classification of Steady-State Visually Evoked Potentials (SSVEPs). This strategy resorts to the combined use of fast Fourier transform and Canonical Correlation Analysis in time domain, and manages to outperform by over 5% previous results obtained for highly wearable, single-channel Brain–Computer Interfaces. In fact, a classification accuracy of 90% is reached with only 2-s time response. Then, the proposed algorithm is employed for an experimental characterization of three different Augmented Reality (AR) devices (namely, Microsoft Hololens I, Epson Moverio BT-350, and Oculus Rift S). These devices are used to generate the flickering stimuli necessary to the SSVEP induction. Also, in the three pieces of instrumentation under test, the number of simultaneous visual stimuli was increased with respect to the state-of-art solutions. The aim of the experimental characterization was to evaluate the influence of different AR technologies on the elicitation of user's SSVEPs. Classification accuracy, time response, and information transfer rate were used as figures of merit on nine volunteers for each piece of instrumentation. Experimental results show that choosing an adequate AR headset is crucial for obtaining satisfying performance: in fact, it can be observed that the classification accuracy obtained with Microsoft Hololens is about 20% greater than Epson Moverio one. • Highly wearable, single-channel SSVEP-based BCI. • Enhanced SSVEP classification algorithm. • Performance comparison between AR HMDs used for SSVEPs elicitation. • Metrological characterization in terms of classification accuracy and time response. [ABSTRACT FROM AUTHOR]

Abstract: The light-enhanced NO2 sensing behavior of mesoporous In2O3 is measured and interpreted by means of a new sensing model. The model aims at explaining (i) the drop in electronic resistance of n-type semiconducting In2O3 under UV light exposure, (ii) the light-enhanced reaction to oxidizing gases, and (iii) the faster reaction and regeneration in mesoporous In2O3 as compared to non-porous material. Contrary to the conventional double Schottky model the dominating factor for the change in resistance is a change of oxygen vacancy donor states (0.18eV below the conduction band) in the bulk phase due to photoreduction, instead of chemisorption. For the faster reaction and regeneration we propose an explanation based on enhanced oxygen diffusion in the In2O3 crystal lattice, specifically dominant in the mesoporous structure. The response of ordered mesoporous In2O3 to NO2 is stronger than in case of unstructured bulk material (with an average grain size of ca. 40nm). The reaction is significantly accelerated by illuminating the samples with UV light. However, the response of the mesoporous material is weaker in the illuminated case. [Copyright &y& Elsevier]

ZnO nanomaterials with different shapes were synthesized, characterized and tested in the selective monitoring of low concentration of CO and NO2 in air. ZnO nanoparticles (NPs) and nanofibers (NFs) were synthesized by a modified sol-gel method in supercritical conditions and electrospinning technique, respectively. CO and NO2 sensing tests have demonstrated that the annealing temperature and shape of zinc oxide nanomaterials are the key factors in modulating the electrical and sensing properties. Specifically, ZnO NPs annealed at high temperature (700 °C) have been found sensitive to CO, while they displayed negligible response to NO2. The opposite behavior has been registered for the one-dimensional ZnO NFs annealed at medium temperature (400 °C). Due to their adaptable sensitivity/selectivity characteristics, the developed sensors show promising applications in dual air quality control systems for closed ambient such as automotive cabin, parking garage and tunnels. [ABSTRACT FROM AUTHOR]

Abstract: Crystalline SnO2/reduced graphene oxide (RGO) nanocomposites were synthesized by a one-pot microwave-assisted non-aqueous sol–gel method, in which partially reduction of the graphene oxide and nanoparticle formation occurs simultaneously. Composite samples with different SnO2 loadings on the RGO were prepared and characterized by TEM, XRD, TGA-DSC and FT-IR. Chemoresistive devices, consisting of a thick layer of the samples synthesized on alumina substrates provided with Pt interdigitated electrodes, were fabricated and their electrical and NO2 sensing characteristics investigated. The results obtained have shown the possibility of a fine tuning of the sensing characteristics of the devices fabricated by simply controlling the amount of metal oxide nanoparticles loaded onto the reduced graphene oxide sheets. This was explained on the basis of the critical role played by the n-SnO2/p-RGO heterojunction formed on the composite materials. [Copyright &y& Elsevier]

Hydrogen is a valuable fuel for the next energy scenario. Unfortunately, hydrogen is highly flammable at concentrations higher than 4% in air. This aspect makes the monitoring of H2 leaks an essential issue for safety reasons, especially in the transportation field. In this paper, nanocomposites based on Pt-doped TiO2/multiwalled carbon nanotubes (MWCNTs) have been introduced as sensitive materials for H2 at low temperatures. Pt-TiO2/MWNTs nanocomposites with different composition have been prepared by a simple wet chemical procedure and their morphological, microstructural and electrical properties were investigated. Resistive thick-film devices have been fabricated printing the hybrid nanocomposites on alumina substrates provided with Pt interdigitated electrodes. Electrical tests in air have shown that embedding MWCNTs in the TiO2 matrix modify markedly the electrical conductivity, providing a means to decrease the resistance of the sensing layer. Pt acts as a catalytic additive. Pt-TiO2/MWNTs-based sensors were found to be sensitive to hydrogen at concentrations between 0.5 and 3% in air, satisfying the requisites for practical applications in hydrogen leak detection devices. [ABSTRACT FROM AUTHOR]

Background The diffusion of high-performance analytical technology has opened prospects for breath diagnosis as a non-invasive diagnostic tool. In this study, ion mobility spectrometry (IMS) and cavity ring-down spectroscopy (CRDS) techniques were used to analyse ammonia gas (NH3) in real-time in breath from patients undergoing haemodialysis (HD) treatment and any correlation with blood urea nitrogen (BUN) levels and Kt/V were investigated. Methods We studied 20 patients on intermittent HD treatment. The first breath samples were taken before the start of dialysis and further breath samples were taken every hour during the treatment and after the end of the session. An evaluation was also made of 20 healthy volunteers, acting as controls [healthy subjects (HS)]. Results Breath ammonia concentrations were higher in CRDS-HD (914.5 ± 301.4 versus 280 ± 120 parts per billion (p.p.b.), P < 0.0001) and IMS-HD patients (964.4 ± 402.4 versus 280 ± 120 p.p.b., P < 0.0001) than in HS. We assessed real-time variations in the levels of NH3 and showed a continuous decrease in the levels of NH3. Expired NH3 correlated directly with BUN levels, both in the IMS-HD (P = 0.002; r = 0.84; P = 0.009; r = 0.76) and in the CRDS-HD group (P = 0.005; r = 0.80; P = 0.008; r = 0.77), respectively, both before and at the end of dialysis. A direct correlation with Kt/V was found in both groups studied (IMS-HD: P = 0.003; r = 0.82; CRDS-HD: P = 0.006; r = 0.79). Conclusions Breath monitoring of NH3 with IMS and CRDS techniques could be useful to assess the real-time clinical status of patients during HD. By using pre-dialysis ammonia values, an approximate calculation of the Kt/Vurea ratio can be established. [ABSTRACT FROM PUBLISHER]

A model is proposed for the drop in electronic resistance of n-type semiconducting indium oxide (In2O3) upon illumination with light (350 nm, 3.5 eV) as well as for the (light-enhanced) sensitivity of In2O3 to oxidizing gases. Essential features of the model are photoreduction and a rate-limiting oxygen-diffusion step. Ordered, mesoporous In2O3 with a high specific surface area serves as a versatile system for experimental studies. Analytical techniques comprise conductivity measurements under a controlled atmosphere (synthetic air, pure N2) and temperature-resolved in-situ Fourier transform infrared (FTIR) spectroscopy. IR measurements reveal that oxygen vacancies form a donor level 0.18 eV below the conduction band. [ABSTRACT FROM AUTHOR]

Pure, mixed and doped metal oxides (MOX) have attracted great interest for the development of electrical and electrochemical sensors since they are cheaper, faster, easier to operate and capable of online analysis and real-time identification. This review focuses on highly sensitive chemoresistive type sensors based on doped-SnO2, RhO, ZnO-Ca, Smx-CoFe2−xO4 semiconductors used to detect toxic gases (H2, CO, NO2) and volatile organic compounds (VOCs) (e.g., acetone, ethanol) in monitoring of gaseous markers in the breath of patients with specific pathologies and for environmental pollution control. Interesting results about the monitoring of biochemical substances as dopamine, epinephrine, serotonin and glucose have been also reported using electrochemical sensors based on hybrid MOX nanocomposite modified glassy carbon and screen-printed carbon electrodes. The fundamental sensing mechanisms and commercial limitations of the MOX-based electrical and electrochemical sensors are discussed providing research directions to bridge the existing gap between new sensing concepts and real-world analytical applications. [ABSTRACT FROM AUTHOR]

The studied sensor consists of a microstrip interdigital capacitor covered by a gas sensing layer made of titanium dioxide (TiO2). To explore the gas sensing properties of the developed sensor, oxygen detection is considered as a case study. The sensor is electrically characterized using the complex scattering parameters measured with a vector network analyzer (VNA). The experimental investigation is performed over a frequency range of 1.5 GHz to 2.9 GHz by placing the sensor inside a polytetrafluoroethylene (PTFE) test chamber with a binary gas mixture composed of oxygen and nitrogen. The frequency-dependent response of the sensor is investigated in detail and further modelled using an artificial neural network (ANN) approach. The proposed modelling procedure allows mimicking the measured sensor performance over the whole range of oxygen concentration, going from 0% to 100%, and predicting the behavior of the resonant frequencies that can be used as sensing parameters. [ABSTRACT FROM AUTHOR]