Electric Sensor Research Articles

Advances in the Fabrication of Nanoporous Anodic Aluminum Oxide and Its Applications to Sensors: A Review.

Nanoporous anodic aluminum oxide (AAO) is an important template for 1D nanomaterial synthesis. It is used as an etching template for nanopattern transfer in a variety of contexts, including nanostructured material synthesis, electrical sensors, optical sensors, photonic and electronic devices, photocatalysis, and hardness and anticorrosion improvement. In this review, we focus on various fabrication methods, pore geometry modification, and recent advances of AAO, as well as sensor applications linked to our environment, daily life, and safety. Pore geometry is concerned with the material composition, applied voltage mold, electrolyte type, temperature, and anodizing time during the fabrication of AAOs and for adjusting their pore size and profile. The applied voltage can be divided into four types: direct current anodization (DCA), reverse pulse anodization, pulse anodization (PA), and hybrid pulse anodization (HPA). Conventional AAOs are fabricated using DCA and mild anodization (MA) at a relatively low temperature (-5~15 °C) to reduce the Joule heating effect. Moreover, the issues of costly high-purity aluminum and a long processing time can be improved using HPA to diminish the Joule heating effect at relatively high temperatures of 20-30 °C with cheap low-purity (≤99%) aluminum. The AAO-based sensors discussed here are primarily divided into electrical sensors and optical sensors; the performance of both sensors is affected by the sensing material and pore geometry. The electrical sensor is usually used for humidity or gas measurement applications and has a thin metal film on the surface as an electrode. On the contrary, the AAO optical sensor is a well-known sensor for detecting various substances with four kinds of mechanisms: interference, photoluminescence, surface plasma resonance, and surface-enhanced Raman scattering (SERS). Especially for SERS mechanisms, AAO can be used either as a solid support for coating metal nanoparticles or a template for depositing the metal content through the nanopores to form the nanodots or nanowires for detecting substances. High-performance sensors will play a crucial role in our living environments and promote our quality of life in the future.

An Automated Wireless System for Monitoring Concrete Structures Based on Embedded Electrical Resistivity Sensors: Data Transmission and Effects on Concrete Properties.

Modern infrastructure heavily relies on robust concrete structures, underscoring the critical need for effective monitoring to ensure their safety and durability. This paper addresses this imperative issue by introducing an innovative automated and wireless system for continuous structural monitoring. By employing embedded electrical resistivity sensors coupled with a wireless-based data transmission mechanism, real-time data collection becomes feasible. We provide a general description of the system's architecture and its application in a pilot study covering the effects of the devices on concrete properties and data transmission. The dielectric properties of concrete specimens were investigated under natural and accelerated curing/degradation and the results were used in the final design of the antenna device. Furthermore, a pilot test comprising four reinforced concrete columns was used to investigate the range of data transmission from inside to outside of the concrete, the effects of the hardware device on the compressive strength and concrete distribution in the columns, and the data transmission quality in real time under realistic exposure conditions.

Machine Learning‐Aided Data Analysis in Single‐Protein Conductance Measurement with Electron Tunneling Probes†

Comprehensive SummaryThe electrical tunneling sensors have excellent potential in the next generation of single‐molecule measurement and sequencing technologies due to their high sensitivity and spatial resolution capabilities. Electrical tunneling signals that have been measured at a high sampling rate may provide detailed molecular information. Despite the extraordinarily large amount of data that has been gathered, it is still difficult to correlate signal transformations with molecular processes, which creates great obstacles for signal analysis. Machine learning is an effective tool for data analysis that is currently gaining more significance. It has demonstrated promising results when used to analyze data from single‐molecule electrical measurements. In order to extract meaningful information from raw measurement data, we have combined intelligent machine learning with tunneling electrical signals. For the purpose of analyzing tunneling electrical signals, we investigated the clustering approach, which is a classic algorithm in machine learning. A clustering model was built that combines the advantages of hierarchical clustering and Gaussian mixture model clustering. Additionally, customized statistical algorithms were designed. It has been proven to efficiently gather molecular information and enhance the effectiveness of data analysis.

On sombor indices of tetraphenylethylene, terpyridine rosettes and QSPR analysis on fluorescence properties of several aromatic hetero‐cyclic species

AbstractAromatic heterocyclic compounds have received a lot of interest due to their various important medicinal and biological applications. The broad synthetic investigation and functional usefulness of heterocyclic molecules is driving a surge in research interest. They are found in more than 90% of innovative medications and bridge the gap between biology and chemistry, where so much scientific discovery and application happens. Heterocycles are also useful in a variety of domains, including pharmaceutical chemistry, biochemistry, and others. In this article, quantitative structure‐property relationship (QSPR) models is developed using sombor indices to predict fluorescence properties of aromatic hetero‐cyclic species based on their structural features. This allows researchers to estimate the fluorescence behavior of new molecules without performing experimental measurements. As an application, we have computed the sombor indices for self‐assembled supramolecular graphs made of terpyridine (TPE) and tetraphenylethylene (TPY) molecules that are produced as rosette cycles. This form of rosettes graph is used in electrical sensors, light emitting diodes, bioimaging and photoelectric devices, and so on. Tetraphenylethylene can be used to make fluorescent probes for next‐generation sensing applications with typical induced aggregative emission behavior.

The Effect of Multiple Cycles of Surfactant-Alternating-Gas Process on Foam Transient Flow and Propagation in a Homogeneous Sandstone

Summary Years of laboratory studies and field tests show that there is still uncertainty about the ability of foam to propagate deep into a reservoir. Many factors have been identified as potential causes of nonpropagation, the most concerning being the lack of sufficient pressure gradient required to propagate foam at locations far from the point of injection. Most researchers that investigated foam propagation did so by coinjecting surfactant and gas. Coinjection offers limited information about transient foam processes due to limitations in the experimental methods needed to measure foam dynamics during transient flow. Foam injection by surfactant-alternating-gas (SAG) has proven to be more effective and common in field application. Repeated drainage and imbibition cycle offer a more favorable condition for the quick generation of foam. Foam can also be propagated at a lower pressure gradient in SAG mode. The objective of this study is to experimentally investigate how transient foam dynamics (trapping, mobilization, and bubble texture) change with multiple cycles of SAG and also with distance from the point of injection. A pair of X-ray source and receiver, differential pressure transducers, and electrical resistance sensors were placed along a 27-cm long, homogeneous, and high-permeability (KL = 70 md) Berea sandstone core. Foam was then generated in situ by SAG injection and allowed to propagate through the core sample under a capillary displacement by brine (brine injection rate = 0.5 cm3/min, Nca = 3×10-7). By use of a novel analytical method on coreflood data obtained from axial pressure and saturation sensors, we obtained trapped foam saturation, in-situ foam flow rates, apparent viscosities, and inferred qualitative foam texture at different core sections. We then observed the following: (i) Maximum trapped foam is uniform across the core sections, with saturation ranging from 47% to 52%. At the vicinity of foam injection, foam apparent viscosity is dominantly caused by gas trapping. At locations farther away, foam apparent viscosity is dominated by both gas trapping and refinement of foam texture. (ii) Cyclic injection of foam further enhances the refinement of foam texture. (iii) Textural refinement increases foam apparent viscosity as it propagates away from the point of injection. (iv) As the foam strength increases, the average gas flow rate in the core sample decreases from 0.5 cm3/min to 0.06 cm3/min. (v) There is no stagnation of foam as remobilization of trapped gas occurs during each cycle at an average flow rate of 0.002 cm3/min.

Perancangan Charger Station Dengan Pembayaran Uang Koin Beserta Analisa Potensi Bisnisnya

At this time, many electronic devices use battery technology such as laptops, cell phones, Bluetooth earphones (TWS), Bluetooth speakers and others. The device requires electrical energy from the battery to operate. It's normal for people with high mobility who often leave the room to run out of battery power. Because of that, how do you solve the problem of running out of battery energy / low battery on electronic devices, because of that a charger station tool was designed with coin payments where there is business potential in designing the device. This study uses the PZEM-004T module as an electrical energy sensor and multi coin acceptor to select coins that enter the charger station system, then the WeMos D1 mini will control the SSR and provide information via the 16x2 Alphanumeric LCD and the Blynk application because the WeMos D1 mini module supports the Internet. of Things (IoT). The information displayed on the Alphanumeric 16x2 LCD is the remaining kWh balance, voltage and load power of the charger station user, then the Blynk application displays information on the number of rupiah coins that have been entered, the remaining kWh balance, voltage, current, power factor and load power of the charger user. This charger station system uses a coin of Rp. 100, Rp. 200, Rp. 500 and Rp. 1000, where if the coins are inserted into the charger station system, the user will get a kWh electricity balance according to the calculation of the selling price. The author uses a profit margin of 300% of the cost of class B1 PLN electricity rates plus the cost of the charger station system electricity.

Development of certified reference materials of lithium chloride solution for water activity

Water activity (a) is used to assess the microbiological stability, shelf life, and safety of food. Water activity meters using electric humidity sensors can measure water activity conveniently. To calibrate water activity meters, certified reference materials (CRMs) of lithium chloride (LiCl) solution for water acidity were prepared by using the gravimetric method. Both the mass balance approach and potentiometric titration were combined to determine the purity of LiCl, and the molality (m) was calculated. The osmotic coefficient (ϕ) was calculated using m and the standard data for ϕ expressed as the Debye–Hückel equation. The certified value of a was calculated using an exponential function of the product of ϕ, m, and molecular mass of water. The certified values and uncertainty (U, k = 2) of two CRMs were 0.250 ± 0.006 and 0.500 ± 0.007, respectively. These two CRMs can be used to calibrate water activity meters and validate analytical methods.

Permanent Magnet with Direct Drive Synchronous Wind Turbine Generator System

This postulation illustrated a control framework for an immediate drive permanent magnet coordinated generator wind turbine system, with the goal of maximising the efficiency of this framework and capturing the maximum amount of wind energy. Additionally, in order to decrease the electric speed sensor installed on the rotor shaft of the PMSG (Permanent Magnet), as well as to reduce the complexity of the framework equipment and increase the stability of the framework, a sliding mode eyewitness-based PM rotor position and speed sensor less control calculation is shown here.The wind turbine and the permanent magnet combination machine with PMSG simulation models are first built in this proposal, and then largest force control calculations for this framework are presented. The best tip speed percentage based on the highest force point after control is used to achieve the strongest catch for the framework.

Sensor‐integrated brain‐on‐a‐chip platforms: Improving the predictive validity in neurodegenerative research

AbstractAffecting millions of individuals worldwide, neurodegenerative diseases (NDDs) pose a significant and growing health concern in people over the age of 60 years. Contributing to this trend are the steady increase in the aging population coupled with a persistent lack of disease‐altering treatment strategies targeting NDDs. The absence of efficient therapeutics can be attributed to high failure rates in clinical trials and the ineptness of animal models in preceding preclinical studies. To that end, in recent years, significant research effort has been dedicated to the development of human cell‐based preclinical disease models characterized by a higher degree of predictive validity. However, a key requirement of any in vitro model constitutes the precise knowledge and replication of the target tissues' (patho‐)physiological microenvironment. Herein, microphysiological systems have demonstrated superiority over conventional static 2D/3D in vitro cell culture systems, as they allow for the emulation and continuous monitoring of the onset, progression, and remission of disease‐associated phenotypes. This review provides an overview of recent advances in the field of NDD research using organ‐on‐a‐chip platforms. Specific focus is directed toward non‐invasive sensing strategies encompassing electrical, electrochemical, and optical sensors. Additionally, promising on‐ and integrable off‐chip sensing strategies targeting key analytes in NDDs will be presented and discussed in detail.

Application of fiber Bragg grating sensing technology and physical model in bridge detection

In order to understand the application of fiber Bragg grating sensing technology and physical models in bridge detection, the author proposes an application research based on fiber Bragg grating sensing technology and physical models in bridge detection. The author first introduced the principle of fiber optic sensors, then analyzed the technology of demodulating fiber optic gratings, and discussed the application of fiber optic sensing technology in bridge detection, effectively improving the monitoring effect and safety performance of bridges. Secondly, in response to the problem that electrical sensors are difficult to meet the long-term monitoring requirements of bridge structures, it is proposed to use fiber optic grating vibration sensors to monitor the vibration status of bridges, and the feasibility of the scheme is demonstrated through theoretical and experimental results. FBG sensor parameters: Select a cylindrical mass block with a diameter of 3 mm and a height of 4 mm, weighing 0.6 g, a fiber length of 65 mm, and a pre stretching amount of 1.3 mm. Fiber Bragg grating sensors not only meet the requirements of frequency measurement range and temperature adaptation range, but also have advantages such as resistance to electromagnetic interference, simple appearance structure, convenient deployment, and good long-term stability. They have good engineering application prospects.

A facile optical sensor: Plastic optical fiber voids as a liquid level presence sensor

Optical sensors use light to detect or monitor different phenomena. Plastic optical fibers (POFs) have larger core diameters and are more flexible and easier to handle than glass optical fibers, making them perfect for many sensing applications. This paper introduces a facile POF sensor to monitor the liquid level and the liquid/gas presence in a specific container by introducing a void in the POF's path. Multiple readings were gathered over two days to verify the sensor's consistent performance. The findings demonstrated that, when exposed to air, the sensor exhibited an average reading of 2.15 V, while its average reading increased to 2.56 V when submerged in water. Such a sensing system can be beneficial in dangerous and explosive environments where electrical sensors or signals are risk factors.

Application of graphene as sensors: a review

Graphene is a modern material which is currently also a topic in great demand. It has some special characteristics like being super thin, high conductivity, highly flexible, and more. These specialities made graphene a genuine material for developing new sensors. Although graphene is relatively rare in commercial use due to the lack of a wide-range and low-cost production method, many laboratory-based research and studies have already developed excellent sensors using graphene in many fields. After analysing masses of articles, this synthesised review concluded the application of graphene as electrical sensors, indicating the future. This paper finds that based on the physical character of graphene, it is also commonly made to be physical sensors in many perspectives, like measuring pressure, strain, temperature, humidity and even magnetic field strength (using the quantum Hall Effect) and many more. Those sensors are showing extraordinary performance; however, they lack stability under severe environments. Also, more compositive graphene material could be developed to expand the scope of electrochemical sensing. The flexibility of graphene is also under consideration which contains high potential in medical fields by designing wearable sensing systems.

Magneto-optical measurement of magnetic field and electrical current on a short pulse high energy pulsed power accelerator

We describe a direct magneto-optical approach to measuring the magnetic field driven by a narrow pulse width (<10 ns), 20 kA electrical current flow in the transmission line of a high energy pulsed power accelerator. The magnetic field and electrical current are among the most important operating parameters in a pulsed power accelerator and are critical to understanding the properties of the radiation output. However, accurately measuring these fields and electrical currents using conventional pulsed power diagnostics is difficult due to the strength of ionizing radiation and electromagnetic interference. Our approach uses a fiber coupled laser beam with a rare earth element sensing crystal sensor that is highly resistant to electromagnetic interference and does not require external calibration. Here, we focus on device theory, operating parameters, results from an experiment on a high energy pulsed power accelerator, and comparison to a conventional electrical current shunt sensor.

STM32 BASED WATER QUALITY MONITORING SYSTEM

Water is a precious and essential resource for all life on Earth. Ensuring the quality of water is vital for human health, environmental sustainability, and various industrial applications. This project introduces a novel STM32-based Water Quality Monitoring System designed to address the need for continuous and real-time monitoring of water parameters in various settings like pH and electrical conductivity sensors. The STM32-based Water Quality Monitoring System offers several advantages, including early detection of water pollution, enabling prompt action to mitigate environmental damage and health risks. It provides historical data for trend analysis, aiding in the identification of long-term water quality patterns and trends. Additionally, it reduces the need for manual sampling and laboratory testing, thus lowering operational costs for water treatment facilities. Furthermore, the system is highly adaptable and can be integrated into a variety of water management scenarios, including municipal water supplies, industrial processes, aquaculture, and environmental monitoring. It promotes sustainable water resource management by ensuring that water quality remains within safe and regulated standards In summary, this project presents an innovative STM32-Based Water Quality Monitoring System that leverages advanced microcontroller technology to address the critical issue of water quality monitoring. Key Words: water quality, stm32, pH sensor, conductivity sensor, aquaculture

Optical Properties of PVA Silicon Carbide Nano Composites Films Synthesized Via Laser Ablation

Background: Enhancing the optical characteristics of nano-silicon carbide and polyvinyl alcohol films is thought to be crucial for obtaining the semiconductor with the lowest energy gap for applications in electrical devices, digital displays, and sensors.
 Materials and Methods: Poly vinyl alcohol and silicon carbide's optical properties were examined. A pulsed laser with a 532 nm wavelength is used to create these nanoparticles into widespread nanoparticles in two environments (water and vinyl alcohol). Polyvinyl alcohol nanocomposite was created by spin coating silicon carbide particles with the weight fractions 0.90%, 0.91%, 0.93%, and 0.95%. Fourier spectroscopy was used to locate the functional groups based. Techniques FESEM were used to analyze the surface composition and nanoparticle dispersion on the membrane-surface of the nanocomposite. using spectroscopy UV-Vis used to record the absorbance spectrum in the range of (200-800) nm for ultraviolet radiation.
 Results: The direct energy gap (5.585, 5.310, 5.480, 4.986, 4.800) eV and the indirect (5.006, 4.880, 4.916, 4.683, 4.490) eV and Urbach energy (2.38, 2.45, 2.94, 2.74, 3.67) eV were calculated.for the samples by ratio, as shown in Table No. 1.
 Conclusion: By investigating the optical characteristics of nanoparticles, such as their extinction and absorption coefficients, direct and indirect optical energy gaps, and Urbach energies .increase in extinction and absorption coefficients Urbach energy when adding nano carbide to polyvinyl alcohol, results show narrowing of the direct and indirect energy gaps. This suggests that the nanocomposite's optical characteristics have improved.

Estimating electric power consumption of in-situ residential heat pump systems: A data-driven approach

International Energy Agency predicts that the global number of installed heat pumps (HP) will increase from 180 million in 2020 to approximately 600 million by 2030, covering 20% of buildings heating needs. Electric power consumption is one of the main key performance indicators for the heat pump systems from techno-economic perspective. However a common issue prevalent in many existing heat pumps is the lack of electric power measurement. The modern installations might be equipped with electric power measurement sensors but this comes at a higher system cost for the manufacturers and end-users. The primary objective of this work is to propose a virtual measurement for estimating power consumption, thereby eliminating the need for field measurement of power for heat pumps. To achieve the objective, a data-driven approach is proposed. Firstly, the in-situ data is preprocessed through data merging, cleaning, and normalization. Then, input features are pre-selected using Spearman correlation coefficients, and further refined by addressing multicollinearity problem. Following this, Extreme Gradient Boosting (XGBoost) models and polynomial models are developed by considering different features as inputs. All models are finally validated against the in-situ data from multi-units of ground source heat pump (GSHP) and air source heat pump (ASHP) installations. The results showed that the electric power consumption of GSHP can be estimated with high accuracy (99% for R2, 10 W for MAE, and 1% for MAPE) through generic data-driven models using only four easy-to-measure input features. Taking three input features as inputs for ASHP generic model, the accuracy can be reached to 83% for R2, 125 W for MAE, and 9% for MAPE. The method presented in this paper can be applied to estimate power consumption of millions of heat pumps and consequently add a significant value as well as provide different types of services, such as cost-saving benefits for manufacturers and end-users, flexibility services for aggregators and electricity grids.

Optical and electrical dual-mode tactile sensor with interlinked interfaces recording normal force and slip for closed-loop robotics

The rapid development of electronic skin will allow disabled people and intelligent robots to interact more effectively with their surroundings. Nevertheless, it remains challenging to simultaneously capture multi-dimensional personalized information (including pressure and slip sensation) through simple device structure design with high stability under complex mechanical conditions. Here, a tactile sensor with simple structure and reliable performance (withstand considerable stretching, twisting, bending, and vibration) is designed for pressure and slip sensing. It is implemented by optical and electrical dual-mode sensing mechanisms and high toughness interlinked interface strategy (interfacial toughness ∼ 33.69 Jm−2, nearly 5 times higher than control sample). This device is composed of a periodic microstructured piezoresistive layer and a triboelectrification-induced electroluminescent (TIEL) layer, both of which are based on the quasi-homogeneous PDMS (polydimethylsiloxane) composite. The whole device possesses the characteristics of lightness, flexibility, and light-transmitting. Besides, the device could automatically locate and track the slip motion while detecting the normal pressure in a large range (0–––1,000 kPa). As an application demonstration, the sensor is installed on a flexible manipulator and combined with the closed-loop control system. Compared to a single electrical mode, the optical and electrical dual-mode tactile sensor could more accurately monitor the sliding of the clamped object, adjust the clamping force instantly, and avoid object slipping. The unique performance of the device shows great potential in trajectory recognition, artificial limbs, intelligent robots, and human–machine interfaces.

Reflection performance of the Au/Cr asymmetrical grating under electric and magnetic fields

Symmetric grating is difficult to meet the requirements of optical communication, optical sensing, and solar cells, as the strictly integrating performance of the transmission or reflection efficiency, polarization, incident angle, and bandwidth. The asymmetrical grating is introduced to improve the performance of the optical devices. Here, the polarization properties, and spatial displacement of the P- and S- laser beams reflected from the Au/Cr asymmetrical grating under electric and magnetic fields are studied. The Goos-Hänchen (GH) shifts of the P-laser beam show dumbbell distribution. The GH shifts of the S-laser beam can be affected by the external direct current and magnetic field. The maximum GH and Imbert-Fedorov (IF) shifts of the P-laser beam are 15.75 µm and 35.10 µm, respectively. The maximum GH and IF shifts of the S-laser beam are 88.40 µm and 121.00 µm, respectively. The Au/Cr asymmetrical grating can be applied in polarization optics, magnetic sensors, electric sensors, and light manipulation.

Target recognition and detection system based on sensor and nonlinear machine vision fusion

Abstract In order to realize the automatic detection system of electric sensor, a method based on sensor and nonlinear machine vision is proposed. Aiming at complex scenes and dynamic changes in target recognition and detection in large-scale industrial field, a target recognition and detection system based on the fusion of vision sensor and nonlinear machine vision is proposed. The system introduces nonlinear features and uses deep neural network to realize multi-scale analysis and recognition of image data on the basis of traditional machine vision. The system uses C++ language development and has a good user interface. The photoelectric sensor weld image is collected by machine vision technology, the target area of the image is detected by Gaussian model, the feature points of the target area are extracted by combining Hessian matrix, the extracted feature points are input into the quantum gate neural network model, and the recognition results are obtained. The simulation results show that the author’s method has the highest value among the three test indicators, with the highest accuracy rate of 97%, the highest recall rate of 98%, and the highest F1 value of 94. The time consumed by the author’s method for automatic identification of photoelectric sensor welding is within 6 s, the time spent on the film wall recognition method for automatic identification of photoelectric sensor welding is within 20 s, and the time spent by the feature extraction and identification method for automatic identification of photoelectric sensor weld is within 22 s. It has been proven that the method based on the fusion of sensors and nonlinear machine vision can achieve an automatic recognition and detection system for electrical sensor welds. The object detection and recognition method proposed in this article can be applied to dynamic changes and complex scenes in various complex backgrounds and has a good application prospect. The system proposed in this article has some limitations, such as the algorithm in the calculation accuracy, real-time, and other aspects that have room for improvement.

Direct wireless readout of fiber Bragg grating sensors using radio-over-fiber.

Wireless readout of optical fiber sensors is of interest for a variety of applications. In the state of the art, the sensor data are digitized before the wireless transmission. We propose a wireless evaluation scheme for fiber Bragg gratings where the sensor signal is transmitted directly without any processing in a simplified sensor node. The underlying concept is explained in detail and validated experimentally. It is based on radio-over-fiber technology and evaluates not only the magnitude of the received analog electrical sensor signal but also the phase. Additionally, signal correction and signal processing schemes are discussed. A series of experimental measurements indicates not only advantages of the phase evaluation method over the magnitude evaluation method but also approves the general feasibility of the direct interrogation approach for wireless sensing applications. Future subjects of interest involve absolute accuracy considerations and maximum achievable sampling rates.