Novel Discrete and Imprinted Fluoride-Selective Sensors: Bridging the Gap from DMSO to Aqueous Samples.

Fluoride in drinking water has beneficial or harmful health effects depending on its concentration. This highlights the need for new low-cost and portable sensors capable of in situ monitoring of F- ions. Unfortunately, achieving high levels of water compatibility and fluoride specificity remains a challenge. Here, four new urea-based discrete sensors are prepared and characterized. The sensors containing anthracenyl- (5) and 9H-fluorenyl- (7) signaling units exhibit intense luminescent emissions in dimethyl sulfoxide, the former being particularly sensitive and selective to fluoride. In water, 5 displays a superior sensitivity (871 M-1) and a detection limit (8 µm) below international guidelines, albeit with cross-sensitivity to H2PO4‾. To enhance the performance, 5 and 7 are embedded into a fluoride-imprinted polymeric matrix to give solid-state sensors (5P and 7P, respectively). 5P shows good sensitivity (360 M-1) and specificity in water. Besides, it has a low detection limit (35 µm) and a response linear range (118-6300 µm) encompassing the limit established by the Environmental Protection Agency (211 µm). Furthermore, 5P also displays good reusability and adequate recovery values in real-sample testing (102 ± 2%), constituting the first example of a low-cost anion-imprinted polymeric probe tailored for the selective sensing of fluoride in aqueous samples.

Hydroelectric Plant Safety: Real-Time Monitoring Utilizing Fiber-Optic Sensors.

In the context of hydroelectric plants, this article emphasizes the imperative of robust monitoring strategies. The utilization of fiber-optic sensors (FOSs) emerges as a promising approach due to their efficient optical transmission, minimal signal attenuation, and resistance to electromagnetic interference. These optical sensors have demonstrated success in diverse structures, including bridges and nuclear plants, especially in challenging environments. This article culminates with the depiction of the development of an array of sensors featuring Fiber Bragg Gratings (FBGs). This array is designed to measure deformation and temperature in protective grids surrounding the turbines at the Santo Antônio Hydroelectric Plant. Implemented in a real-world scenario, the device identifies deformation peaks, indicative of water flow obstructions, thereby contributing significantly to the safety and operational efficiency of the plant.

Coaxial Mach-Zehnder Digital Strain Sensor Made from a Tapered Depressed Cladding Fiber.

An in-line digital optical sensor was proposed. It was built from a tapered depressed-cladding single-mode fiber and modeled as a coaxial Mach-Zehnder interferometer. The principle of operation of the optical digital sensor is based on the computation of the number of optical power transfer turning points (PTTP) from the transmission data of the component. Biconic tapers with high values of PTTP, high spectral resolution, high extinction ratio, and low insertion loss were modeled, fabricated, and characterized. As a proof of concept, an in-line digital strain sensor was fabricated and characterized. It presents a free spectral range of 1.3 nm, and produced 96 PTTP, at λ0 = 1.55 µm, under stretch of ΔL = 707 µm, therefore producing a digital resolution of 7.4 µm/PTTP. The sensor also produced a quasi-symmetric response to stretch and compression.

Implementation of a Fuzzy Inference System to Enhance the Measurement Range of Multilayer Interferometric Sensors.

This work presents a novel methodology to implement a fuzzy inference system (FIS) to overcome the measurement ambiguity that is typically observed in interferometric sensors. This ambiguity occurs when the measurand is determined by tracing the wavelength position of a peak or dip of a spectral fringe. Consequently, the sensor measurement range is typically limited to the equivalent of 1 free spectral range (FSR). Here, it is demonstrated that by using the proposed methodology, the measurement range of this type of sensor can be widened several times by overcoming the ambiguity over some FSR periods. Furthermore, in order to support the viability of the methodology, it was applied to a couple of temperature interferometric sensors. Finally, experimental results demonstrated that it was possible to quintuple the measurement range of one of the tested sensors with a mean absolute error of MAE = 0.0045 °C, while for the second sensor, the measurement range was doubled with an MAE = 0.0073 °C.

Sensing System Based on FBG for Corrosion Monitoring in Metallic Structures.

As corrosion has slow development, its detection at an early age could be an alternative for reducing costs of structural rehabilitation. Therefore, the employment of structural health monitoring (SHM) systems, sensing configurations collecting data over time allowing for observing changes in the properties of the materials and damage emergence, for monitoring corrosion can be a good strategy to measure the damage and to decide the better moment for intervention. Nonetheless, the current corrosion sensor technology and the high costs of the sensing system implementation are limiting this application in the field. In this work, an optical fiber Bragg grating (FBG)-based sensing system is proposed for monitoring the thickness loss of a 1020 carbon steel metal plate subjected to controlled corrosion. The natural frequency of the plate was collected as a function of the corrosion time over 3744 h. To validate the experimental results, ultrasound measures and electrochemical tests were also carried out under similar conditions. The experimental results show adequate reliability, indicating the suitable functionality of the proposed system for monitoring the thickness loss caused by corrosion in metallic structures, in comparison with traditional methods, as ultrasonic and electrochemical measures.

Recent Progress in Amine Gas Sensors for Food Quality Monitoring: Novel Architectures for Sensing Materials and Systems.

The increasing demand for food production has necessitated the development of sensitive and reliable methods of analysis, which allow for the optimization of storage and distribution while ensuring food safety. Methods to quantify and monitor volatile and biogenic amines are key to minimizing the waste of high-protein foods and to enable the safe consumption of fresh products. Novel materials and device designs have allowed the development of portable and reliable sensors that make use of different transduction methods for amine detection and food quality monitoring. Herein, we review the past decade's advances in volatile amine sensors for food quality monitoring. First, the role of volatile and biogenic amines as a food-quality index is presented. Moreover, a comprehensive overview of the distinct amine gas sensors is provided according to the transduction method, operation strategies, and distinct materials (e.g., metal oxide semiconductors, conjugated polymers, carbon nanotubes, graphene and its derivatives, transition metal dichalcogenides, metal organic frameworks, MXenes, quantum dots, and dyes, among others) employed in each case. These include chemoresistive, fluorometric, colorimetric, and microgravimetric sensors. Emphasis is also given to sensor arrays that record the food quality fingerprints and wireless devices that operate as radiofrequency identification (RFID) tags. Finally, challenges and future opportunities on the development of new amine sensors are presented aiming to encourage further research and technological development of reliable, integrated, and remotely accessible devices for food-quality monitoring.

High Sensitivity Surface Plasmon Resonance Sensor Based on a Ge-Doped Defect and D-Shaped Microstructured Optical Fiber.

In this work a plasmonic sensor with a D-Shaped microstructured optical fiber (MOF) is proposed to detect a wide range of analyte refractive index (RI ;na) by doping the pure silica (SiO2) core with distinct concentrations of Germanium Dioxide (GeO2), causing the presentation of high spectral sensitivity. In this case, the fiber is shaped by polishing a coating of SiO2, on the region that will be doped with GeO2, in the polished area, a thin gold (Au) layer, which constitutes the plasmonic material, is introduced, followed by the analyte, in a way which the gold layer is deposited between the SiO2. and the analyte. The numerical results obtained in the study shows that the sensor can determine efficiently a range of 0.13 refractive index units (RIU), with a limit operation where na varies from 1.32 to 1.45. Within this application, the sensor has reached an average wavelength sensitivity (WS) of up to 11,650.63 nm/RIU. With this level of sensitivity, the D-Shaped format and wide range of na detection, the proposed fiber has great potential for sensing applications in several areas.

Techniques and Materials for Optical Fiber Sensors Sealing in Dynamic Environments with High Pressure and High Temperature.

We detail a study of the techniques and sealing materials for optical fiber sensors used in dynamic environments with high pressure (>300 bar) and high temperature (>300 °C). The sealing techniques and materials are the key for the robustness of sensors in harsh dynamic environments, such as large combustion engines. The sealing materials and techniques studied in this work are high-temperature epoxies, metallic polymer, metallic solders, glass solder, cement, brazing and electroless nickel plating. Because obtaining high temperature simultaneously with high pressure is very difficult in the same chamber in the laboratory, we developed a new and simple method to test sealed fibers in these conditions in the laboratory. In addition, some sensors using the materials tested in the laboratory were also field tested in real thermoelectric combustion engines. The study also discusses the methods of fabrication and the cost-benefit ratio of each method.

FBG-Based Sensor for the Assessment of Heat Transfer Rate of Liquids in a Forced Convective Environment.

The assessment of heat transfer is a complex task, especially for operations in the oil and gas industry, due to the harsh and flammable workspace. In light of the limitations of conventional sensors in harsh environments, this paper presents a fiber Bragg grating (FBG)-based sensor for the assessment of the heat transfer rate (HTR) in different liquids. To better understand the phenomenon of heat distribution, a preliminary analysis is performed by constructing two similar scenarios: those with and without the thermal insulation of a styrofoam box. The results indicate the need for a minimum of thermal power to balance the generated heat with the thermal losses of the setup. In this minimum heat, the behavior of the thermal distribution changes from quadratic to linear. To assess such features, the estimation of the specific heat capacity and the thermal conductivity of water are performed from 3 W to 12 W, in 3 W steps, resulting in a specific heat of 1.144 cal/g °C and thermal conductivity of 0.5682 W/m °C. The calibration and validation of the HTR sensor is performed in a thermostatic bath. The method, based on the temperature slope relative to the time curve, allowed for the measurement of HTR in water and Kryo 51 oil, for different heat insertion configurations. For water, the HTR estimation was 308.782 W, which means an uncertainty of 2.8% with the reference value of the cooling power (300 W). In Kryo 51 oil, the estimated heat absorbed by the oil was 4.38 kW in heating and 718.14 kW in cooling.

An Optimized Self-Compensated Solution for Temperature and Strain Cross-Sensitivity in FBG Interrogators Based on Edge Filter.

Optical fiber sensors based on fiber Bragg gratings (FBGs) are prone to measurement errors if the cross-sensitivity between temperature and strain is not properly considered. This paper describes a self-compensated technique for canceling the undesired influence of temperature in strain measurement. An edge-filter-based interrogator is proposed and the central peaks of two FBGs (sensor and reference) are matched with the positive and negative slopes of a Fabry-Perot interferometer that acts as an optical filter. A tuning process performed by the grey wolf optimizer (GWO) algorithm is required to determine the optimal spectral characteristics of each FBG. The interrogation range is not compromised by the proposed technique, being determined by the spectral characteristics of the optical filter in accordance with the traditional edge-filtering interrogation. Simulations show that, by employing FBGs with optimal characteristics, temperature variations of 30 °C led to an average relative error of 3.4% for strain measurements up to 700µÏµ. The proposed technique was experimentally tested under non-ideal conditions: two FBGs with spectral characteristics different from the optimized results were used. The temperature sensibility decreased by 50.8% as compared to a temperature uncompensated interrogation system based on an edge filter. The non-ideal experimental conditions were simulated and the maximum error between theoretical and experimental data was 5.79%, proving that the results from simulation and experimentation are compatible.

A Low-Cost Three-Dimensional DenseNet Neural Network for Alzheimer's Disease Early Discovery.

Alzheimer's disease is the most prevalent dementia among the elderly population. Early detection is critical because it can help with future planning for those potentially affected. This paper uses a three-dimensional DenseNet architecture to detect Alzheimer's disease in magnetic resonance imaging. Our work is restricted to the use of freely available tools. We constructed a deep neural network classifier with metrics of 0.86¯ mean accuracy, 0.86¯ mean sensitivity (micro-average), 0.86¯ mean specificity (micro-average), and 0.91¯ area under the receiver operating characteristic curve (micro-average) for the task of discriminating between five different disease stages or classes. The use of tools available for free ensures the reproducibility of the study and the applicability of the classification system in developing countries.

A Radiometric Technique for Monitoring the Desulfurization Process of Blister Copper.

In this paper, a novel optical technique for following the progress of the blister copper desulfurization process is presented. The technique is based on the changes observed in the continuous spectrum of the visible-near-infrared (VIS-NIR) radiation that the blister melt emits while the chemical reactions of the sulfur elimination process are taking place. Specifically, the proposed technique uses an optical probe composed of an optical fiber, a collimating lens, and a quartz tube, which is immersed in the melt. This optical probe provides a field of view of the blowing zone where the desulfurization reaction occurs. The experimental results show that the melt VIS-NIR total irradiance evolves inversely to the SO2 concentration reported by a gas analyzer based on differential optical absorption spectroscopy. Furthermore, the blister copper spectral emissivity as well as the total emissivity observed throughout the process show strong correlation with the sulfur content during desulfurization reaction.

Novel external-loop-airlift milliliter scale bioreactors for cell growth studies: Low cost design, CFD analysis and experimental characterization.

Many researchers have limited access to fully equipped laboratory-scale batch bioreactors and chemostats due to their relatively high cost. This becomes particularly prohibitive when multiple replicas of the same experiment are required, but not enough bioreactors are available to operate simultaneously. Additionally, experiments using shaken flasks are common but show significant limitations in terms of maintaining homogeneous conditions in liquid cultures or installing instrumentation for monitoring. Here, we proposed to tackle this significant hurdle by providing a route to make available the manufacture of low-cost, milliliter-scale bioreactors. This approach seems plausible for enabling proof-of-concept experiments before moving to a larger scale without significant investments. The conceptually designed systems were based on external-loop bioreactors due to their flexibility, simplicity, and ease of assembling and testing. Designs were initially evaluated in silico with the aid of COMSOL Multiphysics. The successfully evaluated systems were then constructed via additive manufacturing and assembled for hydrodynamics testing via tracer methods. This was enabled by a newly home-made optical absorbance sensor (OAS) for in-line and real-time measurements. Both the in silico and experimental results indicated close to ideal mixing conditions and low shear stress. Cell growth curves were prepared by culturing Escherichia coli and following its cell density in real-time. Our cell growth rate and maximum cell density were similar to those previously obtained in closely related systems. Therefore, the proposed bioreactors are an affordable alternative for batch and continuous cell growth studies rapidly and inexpensively.

On the Detection of Spectral Emissions of Iron Oxides in Combustion Experiments of Pyrite Concentrates.

In this paper, we report on the spectral detection of wustite, Fe(II) oxide (FeO), and magnetite, Fe(II, III) oxide (Fe3O4), molecular emissions during the combustion of pyrite (FeS2), in a laboratory-scale furnace operating at high temperatures. These species are typically generated by reactions occurring during the combustion (oxidation) of this iron sulfide mineral. Two detection schemes are addressed: the first consisting of measurements with a built-in developed spectrometer with a high sensitivity and a high spectral resolution. The second one consisting of spectra measured with a low spectral resolution and a low sensitivity commercial spectrometer, but enhanced and analyzed with post signal processing and multivariate data analysis such as principal component analysis (PCA) and a multivariate curve resolution - the alternating least squares method (MCR-ALS). A non-linear model is also proposed to reconstruct spectral signals measured during pyrite combustion. Different combustion conditions were studied to evaluate the capacity of the detection schemes to follow the spectral emissions of iron oxides. The results show a direct correlation between FeO and Fe3O4 spectral features intensity, and non-linear relations with key combustion variables such as flame temperature, and the combusted sulfide mineral particle size.

Tailored Algorithm for Sensitivity Enhancement of Gas Concentration Sensors Based on Tunable Laser Absorption Spectroscopy.

In this work, a novel tailored algorithm to enhance the overall sensitivity of gas concentration sensors based on the Direct Absorption Tunable Laser Absorption Spectroscopy (DA-ATLAS) method is presented. By using this algorithm, the sensor sensitivity can be custom-designed to be quasi constant over a much larger dynamic range compared with that obtained by typical methods based on a single statistics feature of the sensor signal output (peak amplitude, area under the curve, mean or RMS). Additionally, it is shown that with our algorithm, an optimal function can be tailored to get a quasi linear relationship between the concentration and some specific statistics features over a wider dynamic range. In order to test the viability of our algorithm, a basic C 2 H 2 sensor based on DA-ATLAS was implemented, and its experimental measurements support the simulated results provided by our algorithm.

Flash Smelting Copper Concentrates Spectral Emission Measurements.

In this paper, we report on spectral features emitted by a reaction shaft occurring in flash smelting of copper concentrates containing sulfide copper minerals such as chalcopyrite (CuFeS2), bornite (Cu5FeS4) and pyrite (FeS2). Different combustion conditions are addressed, such as sulfur-copper ratio and oxygen excess. Temperature and spectral emissivity features are estimated for each case by using the two wavelength method and radiometric models. The most relevant results have shown an increasing intensity behavior for higher sulfur-copper ratios and oxygen contents, where emissivity is almost constant along the visible spectrum range for all cases, which validates the gray body assumption. CuO and FeO emission line features along the visible spectrum appear to be a sensing alternative for describing the combustion reactions.

Tooth decay detection using a fiber optic sensor / Detección de caries dental usando un sensor de fibra óptica

ABSTRACT Introduction: tooth decay has become one of the most prevalent diseases worldwide, but ironically it is one of the most neglected. Currently, adequate and effective caries treatment is based on early diagnosis and procedures such as sealants, crowns, and root canal treatment. Methods: This study examined the behavior of carious and non-carious areas of critical dental units (premolars and molars) subjecting them to a wavelength of 830 nm in adult humans who agreed to a dental exam and had at least one tooth affected by dental caries. Underage persons and patients in medical treatment were excluded. After finding a behavior that helped differentiate decayed tissue from healthy areas, the used experimental system was characterized and tested in volunteers. The implemented system contains a fiber optic sensor comprised of a trifurcated fiber and a photodetector to perform optical power measurements. Results: This sensor detected 100% of dental caries samples on premolar and molar occlusal surfaces. It also showed the ability to diagnose buccal cavities. Conclusions: The results showed that caries can be identified in dental units by means of a fiber optic sensor and infrared light at 830 nm.

RESUMEN. Introducción: la caries se ha manifestado como una de las enfermedades con mayor prevalencia mundial, pero paradójicamente es una de las más desatendidas. En la actualidad, el tratamiento adecuado y eficaz contra la caries se basa en el diagnóstico temprano y en procedimientos como obturaciones, coronas y tratamiento de conductos. Métodos: esta investigación se centró en examinar el comportamiento de zonas cariadas y no cariadas de piezas dentales vitales (premolares y molares) al someterlas a una longitud de onda de 830 nm en seres humanos mayores de edad que aceptasen una revisión odontológica y que presentaran al menos un caso de caries dental. Fueron excluidos menores de edad y personas bajo tratamientos médicos. Tras encontrar un comportamiento que permitió diferenciar entre zonas cariadas y sanas, se caracterizó el sistema experimental usado y se probó en voluntarios. El sistema implementado se basa en un sensor de fibra óptica compuesto por una fibra trifurcada y un fotodetector para realizar mediciones de potencia óptica. Resultados: este sensor detectó el 100% de las muestras de caries dental en superficies oclusales de premolares y molares. Asimismo, exhibió indicios de la capacidad de diagnosticar caries vestibulares. Conclusiones: los resultados mostraron que se puede establecer la presencia de caries en piezas dentales mediante la implementación de un sensor de fibra óptica y luz infrarroja de 830 nm.

Theoretical study of chromophores for biological sensing: Understanding the mechanism of rhodol based multi-chromophoric systems.

Development of two-photon fluorescent probes can aid in visualizing the cellular environment. Multi-chromophore systems display complex manifolds of electronic transitions, enabling their use for optical sensing applications. Time-Dependent Density Functional Theory (TDDFT) methods allow for accurate predictions of the optical properties. These properties are related to the electronic transitions in the molecules, which include two-photon absorption cross-sections. Here we use TDDFT to understand the mechanism of aza-crown based fluorescent probes for metals sensing applications. Our findings suggest changes in local excitation in the rhodol chromophore between unbound form and when bound to the metal analyte. These changes are caused by a charge transfer from the aza-crown group and pyrazol units toward the rhodol unit. Understanding this mechanism leads to an optimized design with higher two-photon excited fluorescence to be used in medical applications.

Fluorescent and Colorimetric Electrospun Nanofibers for Heavy-Metal Sensing.

The accumulation of heavy metals in the human body and/or in the environment can be highly deleterious for mankind, and currently, considerable efforts have been made to develop reliable and sensitive techniques for their detection. Among the detection methods, chemical sensors appear as a promising technology, with emphasis on systems employing optically active nanofibers. Such nanofibers can be obtained by the electrospinning technique, and further functionalized with optically active chromophores such as dyes, conjugated polymers, carbon-based nanomaterials and nanoparticles, in order to produce fluorescent and colorimetric nanofibers. In this review we survey recent investigations reporting the use of optically active electrospun nanofibers in sensors aiming at the specific detection of heavy metals using colorimetry and fluorescence methods. The examples given in this review article provide sufficient evidence of the potential of optically electrospun nanofibers as a valid approach to fabricate highly selective and sensitive optical sensors for fast and low-cost detection of heavy metals.

Classification of Flying Insects with high performance using improved DTW algorithm based on hidden Markov model

ABSTRACT Insects play significant role in the human life. And insects pollinate major food crops consumed in the world. Insect pests consume and destroy major crops in the world. Hence to have control over the disease and pests, researches are going on in the area of entomology using chemical, biological and mechanical approaches. The data relevant to the flying insects often changes over time, and classification of such data is a central issue. And such time series mining tasks along with classification is critical nowadays. Most time series data mining algorithms use similarity search and hence time taken for similarity search is the bottleneck and it does not produce accurate results and also produces very poor performance. In this paper, a novel classification method that is based on the dynamic time warping (DTW) algorithm is proposed. The dynamic time warping algorithm is deterministic and lacks in modeling stochastic signals. The dynamic time warping (DTW) algorithm is improved by implementing a nonlinear median filtering (NMF). Recognition accuracy of conventional DTW algorithms is less than that of the hidden Markov model (HMM) by same voice activity detection (VAD) and noise-reduction. With running spectrum filtering (RSF) and dynamic range adjustment (DRA). NMF seek the median distance of every reference of time series data and the recognition accuracy is much improved. In this research work, optical sensors are used to record the sound of insect flight, with invariance to interference from ambient sounds. The implementation of our tool includes two parts, an optical sensor to record the "sound" of insect flight, and a software that leverages on the sensor information, to automatically detect and identify flying insects.