Synthesis and Sensing Response of Magnesium Antimoniate Oxide (MgSb2O6) in the Presence of Propane Atmospheres at Different Operating Voltages.

Nanoparticles of MgSb2O6 were synthesized using a microwave-assisted wet chemistry method, followed by calcination at 700 °C. Their ability to detect different concentrations of propane gas (C3H8) at various operating voltages was evaluated. The material's crystalline phase was identified using X-ray powder diffraction (XRD). The morphology was analyzed by scanning electron microscopy (SEM), finding bar- and polyhedron-type geometries. Through transmission electron microscopy (TEM), we found particle sizes of 8.87-99.85 nm with an average of ~27.63 nm. Employing ultraviolet-visible (UV-Vis) spectroscopy, we found a band gap value of ~3.86 eV. Thick films made with MgSb2O6 powders were exposed to atmospheres containing 150, 300, 400, and 600 ppm of propane gas for dynamic testing. The time-dependent sensitivities were ~61.09, ~88.80, ~97.65, and ~112.81%. In addition, tests were carried out at different operating voltages (5-50 V), finding very short response and recovery times (~57.25 and ~18.45 s, respectively) at 50 V. The excellent dynamic response of the MgSb2O6 is attributed mainly to the synthesis method because it was possible to obtain nanometric-sized particles. Our results show that the trirutile-type oxide MgSb2O6 possesses the ability, efficiency, and thermal stability to be applied as a gas sensor for propane.

Vectorial Image Representation for Image Classification.

This paper proposes the transformation S→C→, where S is a digital gray-level image and C→ is a vector expressed through the textural space. The proposed transformation is denominated Vectorial Image Representation on the Texture Space (VIR-TS), given that the digital image S is represented by the textural vector C→. This vector C→ contains all of the local texture characteristics in the image of interest, and the texture unit T→ entertains a vectorial character, since it is defined through the resolution of a homogeneous equation system. For the application of this transformation, a new classifier for multiple classes is proposed in the texture space, where the vector C→ is employed as a characteristics vector. To verify its efficiency, it was experimentally deployed for the recognition of digital images of tree barks, obtaining an effective performance. In these experiments, the parametric value λ employed to solve the homogeneous equation system does not affect the results of the image classification. The VIR-TS transform possesses potential applications in specific tasks, such as locating missing persons, and the analysis and classification of diagnostic and medical images.

A New Texture Spectrum Based on Parallel Encoded Texture Unit and Its Application on Image Classification: A Potential Prospect for Vision Sensing.

In industrial applications based on texture classification, efficient and fast classifiers are extremely useful for quality control of industrial processes. The classifier of texture images has to satisfy two requirements: It must be efficient and fast. In this work, a texture unit is coded in parallel, and using observation windows larger than 3×3, a new texture spectrum called Texture Spectrum based on the Parallel Encoded Texture Unit (TS_PETU) is proposed, calculated, and used as a characteristic vector in a multi-class classifier, and then two image databases are classified. The first database contains images from the company Interceramic®® and the images were acquired under controlled conditions, and the second database contains tree stems and the images were acquired in natural environments. Based on our experimental results, the TS_PETU satisfied both requirements (efficiency and speed), was developed for binary images, and had high efficiency, and its compute time could be reduced by applying parallel coding concepts. The classification efficiency increased by using larger observational windows, and this one was selected based on the window size. Since the TS_PETU had high efficiency for Interceramic®® tile classification, we consider that the proposed technique has significant industrial applications.

Photocatalytic Evaluation and Application as a Sensor for the Toxic Atmospheres (Propane and Carbon Monoxide) of Nickel Antimonate (NiSb2O6) Powders.

Nickel antimonate (NiSb2O6) powders were synthesized using a wet chemistry process assisted by microwave radiation and calcination from 600 to 700 °C to evaluate their photocatalytic and gas-sensing properties. The crystalline phase obtained at 800 °C of trirutile-type nickel antimonate was confirmed with powder X-ray diffraction. The morphology and size of the nanostructures were analyzed employing electron microscopy (SEM and TEM), identifying irregular particles and microrods (~277 nm, made up of polyhedral shapes of size ~65 nm), nanorods with an average length of ~77 nm, and nanostructures of polyhedral type of different sizes. UV-vis analysis determined that the bandgap of the powders obtained at 800 °C was ~3.2 eV. The gas sensing tests obtained a maximum response of ~5 for CO (300 ppm) at 300 °C and ~10 for C3H8 (500 ppm) at 300 °C. According to these results, we consider that NiSb2O6 can be applied as a gas sensor. On the other hand, the photocatalytic properties of the antimonate were examined by monitoring the discoloration of malachite green (MG) at five ppm. MG concentration monitoring was carried out using UV-visible spectroscopy, and 85% discoloration was achieved after 200 min of photocatalytic reaction.

Synthesis of ZnAl2O4 and Evaluation of the Response in Propane Atmospheres of Pellets and Thick Films Manufactured with Powders of the Oxide.

ZnAl2O4 nanoparticles were synthesized employing a colloidal method. The oxide powders were obtained at 300 °C, and their crystalline phase was corroborated by X-ray diffraction. The composition and chemical structure of the ZnAl2O4 was carried out by X-ray and photoelectron spectroscopy (XPS). The optical properties were studied by UV-vis spectroscopy, confirming that the ZnAl2O4 nanoparticles had a direct transition with bandgap energy of 3.2 eV. The oxide's microstructures were microbars of ~18.2 nm in size (on average), as analyzed by scanning (SEM) and transmission (TEM) electron microscopies. Dynamic and stationary gas detection tests were performed in controlled propane atmospheres, obtaining variations concerning the concentration of the test gas and the operating temperature. The optimum temperatures for detecting propane concentrations were 200 and 300 °C. In the static test results, the ZnAl2O4 showed increases in propane response since changes in the material's electrical conductance were recorded (conductance = 1/electrical resistance, Ω). The increases were ~2.8 at 200 °C and ~7.8 at 300 °C. The yield shown by the ZnAl2O4 nanoparticles for detecting propane concentrations was optimal compared to other similar oxides categorized as potential gas sensors.

Low-Finesse Fabry-Pérot Interferometers Applied in the Study of the Relation between the Optical Path Difference and Poles Location.

Interferometry sensors are frequently analyzed by applying the Fourier transform because the transformation separates all frequency components of its signal, making its study on a complex plane feasible. In this work, we study the relation between the optical path difference (OPD) and poles location theoretically and experimentally, using the Laplace transform and a pole-zero map. Theory and experiments are in concordance. For our study, only the cosine function was considered, which is filtered from the interference pattern. In experimental work, two unperturbed low-finesse Fabry-Pérot interferometers were used. First, a Fabry-Pérot interferometer that has a cavity length of ~1.6 mm was used. Its optical path difference was 2.33 mm and the poles were localized at points ±i12. rad/nm. Secondly, a Fabry-Pérot interferometer with a cavity length of ~5.2 mm was used, and its optical path difference was 7.59 mm and the poles were localized at points ±i40.4 rad/nm. Experimental results confirmed the theoretical analysis. Our proposal finds practical application for interferometer analysis, signal processing of optical fiber sensors, communication system analysis, and multiplexing systems based on interferometers.

Signal Analysis, Signal Demodulation and Numerical Simulation of a Quasi-Distributed Optical Fiber Sensor Based on FDM/WDM Techniques and Fabry-Pérot Interferometers.

In civil engineering quasi-distributed optical fiber sensors are used for reinforced concrete monitoring, precast concrete monitoring, temperature monitoring, strain monitoring and temperature/strain monitoring. These quasi-distributed sensors necessarily apply some multiplexing technique. However, on many occasions, two or more multiplexing techniques are combined to increase the number of local sensors and then the cost of each sensing point is reduced. In this work, a signal analysis and a new signal demodulation algorithm are reported for a quasi-distributed optic fiber sensor system based on Frequency Division Multiplexing/Wavelength Division Multiplexing (FDM/WDM) and low-precision Fabry-Pérot interferometers. The mathematical analysis and the new algorithm optimize its design, its implementation, improve its functionality and reduce the cost per sensing point. The analysis was corroborated by simulating a quasi-distributed sensor in operation. Theoretical analysis and numerical simulation are in concordance. The optimization considers multiplexing techniques, signal demodulation, physical parameters, system noise, instrumentation, and detection technique. Based on our analysis and previous results reported, the optical sensing system can have more than 4000 local sensors and it has practical applications in civil engineering.

Sensitivity Tests of Pellets Made from Manganese Antimonate Nanoparticles in Carbon Monoxide and Propane Atmospheres.

Nanoparticles of manganese antimonate (MnSb2O6) were prepared using the microwave-assisted colloidal method for its potential application as a gas sensor. For the synthesis of the oxide, manganese nitrate, antimony chloride, ethylenediamine and ethyl alcohol (as a solvent) were used. The precursor material was calcined at 800 °C in air and analyzed by X-ray diffraction. The oxide crystallized into a hexagonal structure with spatial group P321 and cell parameters a = b = 8.8054 Å and c = 4.7229 Å. The microstructure of the material was analyzed by scanning electron microscopy (SEM), finding the growth of microrods with a size of around ~10.27 µm and some other particles with an average size of ~1.3 µm. Photoacoustic spectroscopy (PAS) studies showed that the optical energy band (Eg) of the oxide was of ~1.79 eV. Transmission electron microscopy (TEM) analyses indicated that the size of the nanoparticles was of ~29.5 nm on average. The surface area of the powders was estimated at 14.6 m²/g by the Brunauer⁻Emmett⁻Teller (BET) method. Pellets prepared from the nanoparticles were tested in carbon monoxide (CO) and propane (C3H8) atmospheres at different concentrations (0⁻500 ppm) and operating temperatures (100, 200 and 300 °C). The pellets were very sensitive to changes in gas concentration and temperature: the response of the material rose as the concentration and temperature increased. The results showed that the MnSb2O6 nanoparticles can be a good candidate to be used as a novel gas sensor.

A Theoretical Study and Numerical Simulation of a Quasi-Distributed Sensor Based on the Low-Finesse Fabry-Perot Interferometer: Frequency-Division Multiplexing.

The application of the sensor optical fibers in the areas of scientific instrumentation and industrial instrumentation is very attractive due to its numerous advantages. In the industry of civil engineering for example, quasi-distributed sensors made with optical fiber are used for reliable strain and temperature measurements. Here, a quasi-distributed sensor in the frequency domain is discussed. The sensor consists of a series of low-finesse Fabry-Perot interferometers where each Fabry-Perot interferometer acts as a local sensor. Fabry-Perot interferometers are formed by pairs of identical low reflective Bragg gratings imprinted in a single mode fiber. All interferometer sensors have different cavity length, provoking frequency-domain multiplexing. The optical signal represents the superposition of all interference patterns which can be decomposed using the Fourier transform. The frequency spectrum was analyzed and sensor's properties were defined. Following that, a quasi-distributed sensor was numerically simulated. Our sensor simulation considers sensor properties, signal processing, noise system, and instrumentation. The numerical results show the behavior of resolution vs. signal-to-noise ratio. From our results, the Fabry-Perot sensor has high resolution and low resolution. Both resolutions are conceivable because the Fourier Domain Phase Analysis (FDPA) algorithm elaborates two evaluations of Bragg wavelength shift.

Quantifying a similarity of classes of texture images.

To quantify the concept of similarity between classes of images three measures and algorithms of calculation are proposed. The first measure is calculated through the frequency of misclassification of subimages sampled randomly from images. The second one is calculated through the cross membership of the mass center of a class in a feature space. The third measure is defined through the membership of subimages, using the distance between each subimage and the mass center of a class in a feature space. We study these measures, classifying images in the coordinated clusters representation (CCR) feature space with the minimum distance classifier. A database of images of Rosa Porriño granite tiles, previously classified by three human experts, is used in the experiments. The calculated similarity between classes is in excellent accordance with the qualitative evaluation by the human experts.