Hasil untuk "Electric apparatus and materials. Electric circuits. Electric networks"

Minwoo Park, Jungkyun Im, Minkwan Shin et al.

Shubhradip Guchait, Diego R. Hinojosa, Nathan James Pataki et al.

Abstract This study demonstrates the possibility to enhance thermoelectric properties of n‐type benzodifuranone‐based copolymers using a combination of polymer orientation (using high temperature rubbing) and sequential doping with the dopant N‐DMBI‐H. It focuses on the impact of the side chain length and the chemical nature of the comonomer (thiophene vs furan) on the efficacy of this methodology that preserves the facile solution‐processability of this polymer family and enables effective sequential doping without a thermal activation step. The combination of high temperature rubbing and thermal annealing helps reach a high orientation of the copolymers with the thiophene comonomer regardless of the length of the side chains whereas the furan‐based polymer is marginally aligned. The high orientation of thiophene‐based copolymers results in a strong improvement of electrical conductivity and power factors reaching up to 9.8 ± 1.6 S cm−1 and 8 ± 3 µW m−1.K2, respectively.

Carlos Orlando Enrique Da Silva, Rajesh Akula, C. Amon

This expert view article reviews the latest developments, challenges, and opportunities in hierarchical modeling of electric vehicle (EV) battery systems across multiple length scales from battery electrodes to cells, modules, and packs. Special emphasis has been placed on thermal modeling developments over the past six years. The article starts with an overview of lithium-ion battery-powered EVs, adoption barriers, and the fundamentals of battery heat generation, temperature effects, and battery thermal management systems (BTMS). This article provides a comprehensive insight into the latest electrode-to-pack modeling methodologies and the complex multiphysics phenomena impacting BTMS across hierarchical length scales. At the electrode level, this article reviews atomistic modeling methods with density functional theory, molecular dynamics, and machine learning algorithms, as well as how these methods have revealed novel two-dimensional materials and heterostructures as promising nanostructured electrode materials for next-generation batteries. At the cell level, the article focuses on form-factor dependent cell performance, characterization of anisotropic thermophysical properties and distributed heat generation, and high-fidelity battery cell thermal models coupled with electrochemical and equivalent circuit models. At the module and pack (system) levels, the article highlights the challenges of scaling up high-fidelity electrochemical-thermal coupled models to the system level, the advantages of reduced-order lumped-parameter thermal and electrical network models, and the opportunities presented by surrogate modeling methodologies, including data-driven and physics-informed machine learning approaches. This expert view concludes with a perspective on the role of digital twins for battery systems.

Jialei Wu, Ruqin Ma, Xin Ge et al.

Moisture-enabled electric generators (MEGs) harvest environmental moisture for energy generation and environmental monitoring, showing promise in wearable electronics. Electrospinning nanofiber membranes, favored for their large surface area, micro-nano channel networks, material versatility, and facile fabrication, serve as ideal platforms for MEGs. Although sodium alginate (SA), a natural polymer rich in hydrophilic groups, is suitable for humidity-driven energy harvesting, challenges persist in its direct electrospinnability and in balancing sustained hygroscopic power output with structural stability under humid conditions. This work designed an antibacterial bilayer nanofiber membrane with a distinct hydrophilic hierarchical structure using polyvinyl alcohol (PVA), SA, and silver nanoparticles (AgNPs), cross-linked with glutaraldehyde (GA) to enhance durability. The bilayer structure, with an upper layer of PVA/SA/AgNPs and a lower layer of PVA/AgNPs, both cross-linked with 2 wt.% GA, achieved a 0.415 V open-circuit voltage, retaining 93.2% performance after 25 cycles. It exhibited 99.83% and 99.57% inhibition against S. aureus and E. coli, respectively, ensuring biostability in humid environments. These MEGs enable multifunctional integration for real-time moisture detection, respiratory health monitoring, activity tracking, and energy harvesting in self-powered wearable systems.

Yachong Zhu, Lishi Wei, Shanshan Song et al.

Hydrogels are characterized by their exceptional hydrophilic properties, rendering them optimal active materials for moist-electric generator (MEG). Nonetheless, insufficient protonation and ionic diffusion compromise the electrical properties of hydrogels, thereby limiting their practical applications. In this study, an ionic conductive hydrogel based on the combination of functionalized nanocellulose (FCNF) and polyacrylamide (PAM) was developed by UV-initiated polymerization and solvent substitution. The FCH hydrogel has good stretchability (250 %) and high conductivity (17.3S m-1). In addition, the MEG was constructed using FCH hydrogel. The MEG device has excellent electrical output performance, with open circuit voltage, short circuit current density and maximum power density of 1 V, 1.38 μA cm-2 and 63 nW cm-2, respectively. At the same time, the MEG also has stable environmental adaptability, and can maintain stable output in a wide humidity range (15-98 %RH) and low temperature (-20 °C). Notably, MEG exhibits scalability through series/parallel configuration, achieving current and voltage outputs of 4.0 V (five series units) and 5.4 μA (five parallel units), and can also be directly used as a power supply to power capacitors and LED light. This work presents a novel approach for developing simple, environmentally friendly, and efficient MEGs for portable self-powered flexible devices.

Zdzislaw Trzaska

Farzin Asadi

Zhongsheng Yang, Songyu Wang, Rongtian Cao et al.

Partially recrystallized precipitation-hardened high entropy alloys have shown excellent mechanical properties with yield strength up to 2 ​GPa. However, the recrystallization kinetics of precipitation-hardened high entropy alloys are not adequately revealed due to the complex interactions between precipitation and recrystallization. Here, we report an abnormal recrystallization behavior of precipitation-hardened high-entropy alloys that the recrystallization kinetics at 600 ​°C are faster than those at 800 ​°C. Moreover, the recrystallization period at 800 ​°C is significantly shorter than that at 600 ​°C. Through comparative analysis, we attributed the abnormal recrystallization kinetics to the delayed pinning effect caused by slow precipitation kinetics at 600 ​°C while the shortened recrystallization period to the high recrystallization nucleation rate by particle-stimulated nucleation at 800 ​°C.

Wonryeol Lee, Taeyong Jeong, Daju Lee et al.

This paper presents the design and performance evaluation of a fully integrated digital phased array-based nonlinear radar system. The proposed system employs a bi-static structure, where the transmitter and receiver are physically separated. The transmitter operates at 3–3.2 GHz, while the receiver is designed to capture the second harmonic responses at 6–6.4 GHz. The system consists of 64 channels for both transmission and reception, enabling electronic beam steering through phase shift control. To enhance the beamforming accuracy, a novel transmitter calibration method utilizing an oscilloscope instead of a network analyzer was implemented. The method simplifies synchronization requirements while maintaining precise phase alignment. Performance evaluation of the radar system was conducted through experimental validation in both free-space and concealed conditions, using arbitrary commercial electronic devices as targets. The experimental validation results demonstrated an average range error of 32.3 cm with a range resolution of 37.5 cm. Additionally, multi-target detection was performed using beamforming techniques. In free-space conditions, the radar achieved accurate target localization with angular errors below 1°. In concealed conditions, nonlinear reflections introduced minor localization errors due to clutter. Despite these challenges, the system successfully detected multiple targets by employing a clustering method. To the best of our knowledge, the system presented here is the first demonstration of a fully integrated digital phased array-based nonlinear radar in the open literature.

Hadjira BELAIDI, Anis ZARA, Yasmine SAIDI et al.

This work focuses on developing an advanced robotic hand to assist individuals who have lost a hand. This robotic hand is designed to replicate the functionality and dexterity of a natural hand. Key features include wireless connectivity enabled by the ESP32 module, intuitive control through electromyography (EMG) sensors, and voice recognition capabilities. An accompanying Android application gathers health-related data and provides real-time notifications to healthcare providers.

Jie Gao, Guodong Yang, Wanwen Huang et al.

By forming alloys with Li ions, silicon (Si) can possess an energy capacity ten times that of graphite anodes, making it a promising candidate for the next generation anode materials for lithium-ion batteries. However, the large volumetric changes of Si during the lithiation/delithiation process result in unstable electrochemical cycling performance, and the deficiencies in electrical and ionic conductivity limit its rate performance, thereby constraining the large-scale application of Si-based anode. Due to its strong interaction with Si particles and its convenience in constructing doped carbon layers and carbon layers with special structures, polymers are regarded as low-cost (for example, the price of lignin is as low as 200–600 $/ton) and effective carbon sources to prepare core-shell structured Si@C composite materials and optimize the shortcomings of Si-based anodes.In this review, we first discuss surface modification methods for Si particles aimed at enhancing the adhesion to polymers and effectively improving the dispersibility of Si nanoparticles in polymers. Subsequently, the roles and methods for improving the electronic/ionic conductivity and structural stability of carbon layers, including doping and the construction of various special structures, are summarized and compared. These advancements position Si@C composites as viable candidates for next-generation high-energy batteries. Finally, the prospects for Si anodes coated with polymer-derived carbon layers are proposed.

Pengfei Tang, Kun Yang, Chaoming Xie et al.

Silver‐based printed circuits have demonstrated significant potential in the field of flexible electronics, particularly for applications such as wearable devices, owing to their high conductivity, low cost, and ease of mass production. However, their structural and performance degradation under continuous mechanical and electrical loads during service poses a major challenge to achieving long‐term stable functionality. Herein, this study investigates the performance and microstructural evolution of silver‐based printed circuits under electromechanical coupling loads and unveils the underlying material degradation mechanisms. Resistance change curves reveal that, under identical bending loads, lower current density (208.3 A/cm2) accelerates circuit degradation more significantly than higher current density (1164.7 A/cm2). By analysing the thermal characteristics, conductive phase structure, and conductive network of printed circuits under mechanical loading, electric field stimulation, and electromechanical coupling, it is evident that heat plays a critical role in determining resistance changes in silver‐based printed circuits. At lower temperatures, heat‐induced oxidation of nanosilver to nonconductive silver oxide emerges as the primary driver of resistance increase. Conversely, at higher temperatures, heat‐induced sintering of silver forms new conductive pathways that offset the resistance increase caused by the oxidation of silver nanoparticles. These findings not only elucidate the fatigue degradation mechanisms of silver‐based printed circuits but also offer theoretical guidance for the development of high‐performance silver‐based printed circuits.

Konstantin K. Kim, Irina M. Karpova, Nikolay S. Kuznechenkov et al.

The research purpose is to ensure the required duration of continuous monitoring of the electrified railway transport overhead catenary system. This monitoring is carried out by using electric helicopter-type unmanned aerial aircrafts. To achieve this purpose the method was used for recharging the onboard battery pack by the energy of the electromagnetic field generated by traction currents flowing through the contact wire or suspension wire during the flight of the aircraft in close proximity to the overhead catenary system. To implement this method, an inductive way of transferring electromagnetic energy from the overhead catenary system to the apparatus onboard system is used. An electric winding is used as the receiver of this energy. This winding is a part of the onboard charging device and is installed on the aircraft. The subject of the research was the 25 kV AC chain-type catenary suspension. A finite element model of the circuit was developed. The monitoring device was represented by the Freefly Alta 8 hexacopter with an Alta Flight Battery Pack from Freefly. The following results and recommendations can be made: using the mathematical modeling methods utilizing the COMSOL Multiphysics® 6.0 program, one can prove the possibility of recharging by the electromagnetic field of the current in the catenary wire, at the lateral displacement of the aircraft from the longitudinal axis of the catenary wire. The thermal calculation results for the battery pack showed that at negative ambient temperatures, the use of thermal containers is an effective and efficient measure for maintaining the optimal temperature regime for the battery pack for an extended period with an acceptable increase in takeoff weight in terms of the maximum takeoff weight.

Dina A. Naser, M. Essai, A. Mahmoud et al.

Comprehending and predicting the fluctuations in the energy storage functionality of ferroelectric-based apparatuses throughout a broad range of temperatures is crucial. To achieve this, we developed and simulated a Function Fitting ANN model using MATLAB. The model was trained using the back-propagation algorithm, effectively capturing the relationship between the applied electric field, and resulting polarization through experimental data. The model demonstrates excellent performance with two hidden layers consisting of 37 neurons in each and three input layers. Extensive experimentation confirms the model's impressive accuracy in predicting energy storage performance, particularly at different temperature conditions around Curie temperature Tc. The experimental part of the study was done in the temperature range (43-95 ᵒC) which seems to be limited. However, it justifies temperature-induced changes around the Curie temperature (T C ). Above curie temperature (T > T C ), the material becomes paraelectric and loses its spontaneous polarization resulting in more decrease in recoverable energy-storage density and efficiency. The remarkable predictive performance of the model is attributed to its remarkably low mean square error of 3.68×10 -5 . This result emphasizes the model's precision and reliability in accurately forecasting energy storage parameters. Finally, BCZT ceramic samples were selected for the present work for being a very famous ferroelectric material and has well-known ferroelectric properties.

M. Fetene, Dereje Arijamo Dolla, Chin-Cheng Wang et al.

Electric vehicles equipped with lithium ion batteries (LIB) face safety concerns, primarily related to thermal effects. One critical component of LIB is the separator, which serves the purpose of preventing direct contact between the positive and negative electrodes while enabling the movement of lithium-ions. Any damage to the separator can result in short circuits and battery explosions. The properties of cellulose are compared to those of polyolefin through differential scanning calorimetry (DSC), thermogravimetric analysis (TGA), weight loss measurements, and heat flow properties. These parameters play a vital role in determining the suitability of the material for LIB separators. The results obtained from the analysis are highly encouraging, as banana peel cellulose (BPC) exhibits a higher DSC value of 323.18°C, a moderate heat flow of 231.22J/g, a TGA result of 235°C, a weight loss of 59.37 percent, which is considered favorable, and a differential thermal analysis (DTA) result of 330.23°C. These findings position BPC as an excellent alternative material for separators in comparison to the existing polyolefin materials. Furthermore, an artificial neural network is employed to predict the performance of BPC material, with a binary classification system of 0 and 1, where 0 represents failure and 1 represents success. The model is trained using the input data, and it has been observed that the training process is successful, achieving an accuracy rate of 97.58%.

Kang Yao

With the rapid development of the e-commerce industry, enterprises need to effectively manage and analyze various operational data to support decision making and optimize business processes. Sensor technology is widely used in e-commerce environment, which can collect a lot of voice data and extract valuable information through data mining technology. The study presents the current background and trends of the e-commerce industry, with a focus on the importance and challenges of operational data analytics. A sensor-based voice data mining framework is proposed. Sensors are first used to collect voice data and turn it into a digital signal that can be used for analysis. Then the data mining algorithm is used to process and analyze the voice data, and a series of results about e-commerce operation are obtained. Analyze voice data to help companies develop effective marketing strategies, improve product quality, and optimize supply chain management. This study proves the role of sensor-based voice data mining in e-commerce operational data analysis. By harnessing the full potential of voice data, businesses can better understand and meet customer needs, improve competitiveness and performance. This research result has practical significance for the development of e-commerce industry, and provides guidance and reference for the research and practice in related fields.

MengJuan Han

Traditional financial risk detection methods are mainly based on statistical models and market data, in which sensor network has a wide application prospect. The research can improve the accuracy and efficiency of financial risk detection by using the data and information of sensor network. By making full use of the data collection capabilities of sensor networks to obtain more comprehensive and accurate financial data, it helps to identify potential risk factors more accurately. This paper introduces DTW (Dynamic Time warping) algorithm as the main financial risk detection method, which can effectively capture the similarity between time series data and apply it to the financial data obtained by sensor network. Through regularization and matching of time series data, abnormal changes and abnormal patterns can be identified, so as to timely warn and control financial risks. By comparing the data of sensor network with that of traditional methods, we found that the financial risk detection method based on DTW algorithm and sensor network has higher accuracy and efficiency, and can identify potential risk factors more accurately.

Caiyuan Xiao

In recent years, China's technological level has undergone rapid development, and technologies such as wireless local area networks and wireless sensor networks have also undergone rapid development in this situation. Under the influence of developed networks, many high-tech items are applied in our daily lives, such as intelligent transportation, remote control and monitoring, intelligent household appliances, and so on. In this environment, internet technology is rapidly developing and widely applied in various fields, making huge contributions to positioning technology and monitoring technology. The demand for high-precision, low-cost, strong applicability, and simple operation scientific technology in various industries is constantly increasing. Ultra wideband technology has played a significant role in the field of indoor positioning due to its unique advantages. However, in complex environments, the propagation of broadband signals is easily affected by obstacles, which weakens the signal received and seriously affects indoor positioning accuracy. As people gradually move into cities, the increase in population has caused increasingly serious traffic congestion. In order to solve the positioning problem of urban people, positioning industries that serve people have gradually emerged in the public's career, which has led to an increasing demand for accurate positioning. The complex environment of cities and the complex environment where people live can have a serious impact on positioning technology, leading to continuous deterioration of positioning accuracy. Non-Line of Sight (NLOS) is an important factor affecting positioning accuracy. So, this article conducts a thorough study on wireless local area networks and wireless sensor networks, fully improving the development of wireless positioning, and conducting a thorough study on the algorithm of NLOS- anchor.

Yasser Damine, Ahmed Chaouki Megherbi, Salim Sbaa et al.

The detection of faults in induction machines (IMs) is crucial for maintaining their optimal performance and extending their lifespan. Bearing faults, in particular, can have a significant impact on the efficiency and reliability of these machines. Ensemble Empirical Mode Decomposition (EEMD) is an appropriate technique for monitoring bearing health in IMs. This work is to evaluate the effectiveness of EEMD. The aim is to see in which level this technique can enhance the efficiency of bearing fault diagnosis. Our experimental findings indicate that EEMD exhibits greater effectiveness than VMD.