Fabrication of Graphene/Cu Composite by Chemical Vapor Deposition and Effects of Graphene Layers on Resultant Electrical Conductivity

Graphene(Gr)has unique properties including high electrical conductivity;Thus,graphene/copper(Gr/Cu)composites have attracted increasing attention to replace traditional Cu for electrical applications. However,the problem of how to control graphene to form desired Gr/Cu composite is not well solved. This paper aims at exploring the best parameters for preparing graphene with different layers on Cu foil by chemical vapor deposition(CVD)method and studying the effects of different layers graphene on Gr/Cu composite’s electrical conductivity. Graphene grown on single-sided and double-sided copper was prepared for Gr/Cu and Gr/Cu/Gr composites. The resultant electrical conductivity of Gr/Cu composites increased with decreasing graphene layers and increasing graphene volume fraction. The Gr/Cu/Gr composite with monolayer graphene owns volume fraction of less than 0.002%,producing the best electrical conductivity up to59.8 ×10^(6)S/m,equivalent to 104.5% IACS and 105.3% pure Cu foil.

Exploring the synergy of the eyebrain connection:neuromodulation approaches for neurodegenerative disorders through transcorneal electrical stimulation

The connection and interaction between the eye and the brain are crucial to understanding brain disorders(Marchesi et al.,2021).Both the eye and the brain have a limited regenerative capacity as there are few progenitor cells,and nerve cells do not replicate.Hence,neurodegeneration implicates irreversible damage to the central nervous system,as observed in several neurodegenerative diseases(Marchesi et al.,2021).

Review of Techniques for Integrating Security in Software Development Lifecycle

Software-related security aspects are a growing and legitimate concern,especially with 5G data available just at our palms.To conduct research in this field,periodic comparative analysis is needed with the new techniques coming up rapidly.The purpose of this study is to review the recent developments in the field of security integration in the software development lifecycle(SDLC)by analyzing the articles published in the last two decades and to propose a way forward.This review follows Kitchenham’s review protocol.The review has been divided into three main stages including planning,execution,and analysis.From the selected 100 articles,it becomes evident that need of a collaborative approach is necessary for addressing critical software security risks(CSSRs)through effective risk management/estimation techniques.Quantifying risks using a numeric scale enables a comprehensive understanding of their severity,facilitating focused resource allocation and mitigation efforts.Through a comprehensive understanding of potential vulnerabilities and proactive mitigation efforts facilitated by protection poker,organizations can prioritize resources effectively to ensure the successful outcome of projects and initiatives in today’s dynamic threat landscape.The review reveals that threat analysis and security testing are needed to develop automated tools for the future.Accurate estimation of effort required to prioritize potential security risks is a big challenge in software security.The accuracy of effort estimation can be further improved by exploring new techniques,particularly those involving deep learning.It is also imperative to validate these effort estimation methods to ensure all potential security threats are addressed.Another challenge is selecting the right model for each specific security threat.To achieve a comprehensive evaluation,researchers should use well-known benchmark checklists.

A Study of Lateralized Cognitive Processes in Upper-Division Electrical Engineering Students’: Correlating Written Language Functions with Analytical Reasoning in Microelectronics

The human brain is asymmetrical in function, with each of its two hemispheres being somewhat responsible for distinct cognitive and motor tasks, to include writing. It stands to reason that engineering students who have established entrance into their upper-division programs will have demonstrated cognitive proficiency in math and logical operations, abstract and analytical reasoning and language usage, to include writing. In this study the question was asked: is there a correlation between an upper-division electrical engineering students’ analytical reasoning ability and their descriptive writing ability? Descriptive writing is taken here to mean a students’ ability to identify key physical aspects of a mathematical model and to express—in words—a concise and well-balanced description that demonstrates a deep conceptual understanding of the model. This includes more than a description of the variables or the particular application to an engineering problem;it includes a demonstrated recognition of the basic physics that govern the model, certain limitations (idealizations) inherent in the model, and an understanding of how to make practical experimental measurements to verify the governing physics in the model. A student at this level may demonstrate proficiency in their analytical reasoning skills and hence be capable of correctly solving a given problem. However, this does not guarantee that the same student is skilled in associating equations with their physical meaning on a deep conceptual level or in understanding physical limitations of the equation. Consequently, such a student may demonstrate difficulty in mapping their comprehension of the model into written language that demonstrates a sound conceptual understanding of the governing physics. The findings represent a sample of two independent class sections of Electrical and Computer Engineering junior’s first course in Microe-lectronic Devices and Circuits during fall semesters 2012 and 2013 at a private mid-size university in NW Oregon. A total of three exams were administered to each of the 2012/2013 groups. Correlations between exam scores that students achieved on their descriptive writing of microelectronics phenomena and their analytical problem-solving abilities were examined and found to be quite significant.

Characteristic evaluation of Al_2O_3/CNTs hybrid materials for micro-electrical discharge machining

The characteristic evaluation of aluminum oxide （A1203）/carbon nanotubes （CNTs） hybrid composites for micro-electrical discharge machining （EDM） was described. Alumina matrix composites reinforced with CNTs were fabricated by a catalytic chemical vapor deposition method. A1203 composites with different CNT concentrations were synthesized. The electrical characteristic of A1203/CNTs composites was examined. These composites were machined by the EDM process according to the various EDM parameters, and the characteristics of machining were analyzed using field emission scanning electron microscope （FESEM）. The electrical conductivity has a increasing tendency as the CNTs content is increased and has a critical point at 5% A1203 （volume fraction）. In the machining accuracy, many tangles of CNT in A1203/CNTs composites cause violent spark. Thus, it causes the poor dimensional accuracy and circularity. The results show that conductivity of the materials and homogeneous distribution of CNTs in the matrix are important factors for micro-EDM of A1203/CNTs hybrid composites.

A Systemic Approach to Integrated E-maintenance of Large Engineering Plants

Large engineering plants （LEPs） have certain unique features that necessitate a maintenance strategy that is a combination of both time and condition based maintenance. Although this requirement is appreciated to varying degrees by asset owners, applied research leading to a systematic development of such a maintenance strategy is the need of the day. Such a strategy should also adopt a wholesome ＂systemic＂ approach so that the realization of the overall objectives of maintenance is maximized. E-maintenance has several potential benefits for large engineering plants. In this paper, a three pronged strategy is suggested for the successful implementation of e-maintenance for LEPs. Firstly, an integrated condition and time based maintenance framework is proposed for LEPs. Secondly, reference is drawn to models for condition and time based maintenance at systemic levels. As a part of the ab initio development of a condition monitoring system for a LEP, one of the characteristics of the condition monitoring system, namely, predictability, is discussed in detail as a sample for a systemic study. Thirdly, emphasis is laid on the information and expertise available in the domain of plant design, operation and maintenance and the same is tapped for incorporation in maintenance decision making.

Tailored PEDOT:PSS hole transport layer for higher performance in perovskite solar cells: Enhancement of electrical and optical properties with improved morphology

Precise control over the charge carrier dynamics throughout the device can result in outstanding performance of perovskite solar cells(PSCs).Poly(3,4-ethylenedioxythiophene):poly(styrene sulfonate)(PEDOT:PSS)is the most actively studied hole transport material in p-i-n structured PSCs.However,charge transport in the PEDOT:PSS is limited and inefficient because of its low conductivity with the presence of the weak ionic conductor PSS.In addition,morphology of the underlying PEDOT:PSS layer in PSCs plays a crucial role in determining the optoelectronic quality of the active perovskite absorber layer.This work is focused on realization of a non-wetting conductive surface of hole transport layer suitable for the growth of larger perovskite crystalline domains.This is accomplished by employing a facile solventengineered(ethylene glycol and methanol)approach resulting in removal of the predominant PSS in PEDOT:PSS.The consequence of acquiring larger perovskite crystalline domains was observed in the charge carrier dynamics studies,with the achievement of higher charge carrier lifetime,lower charge transport time and lower transfer impedance in the solvent-engineered PEDOT:PSS-based PSCs.Use of this solventengineered treatment for the fabrication of MAPbI3 PSCs greatly increased the device stability witnessing a power conversion efficiency of 18.18%,which corresponds to^37%improvement compared to the untreated PEDOT:PSS based devices.

Comparative study on discharge conditions in micro-hole electrical discharge machining of tungsten carbide (WC-Co) material

WC-Co is used widely in die and mold industries due to its unique combination of hardness, strength and wear-resistance. For machining difficult-to-cut materials, such as tungsten carbide, micro-electrical discharge machining(EDM) is one of the most effective methods for making holes because the hardness is not a dominant parameter in EDM. This paper describes the characteristics of the discharge conditions for micro-hole EDM of tungsten carbide with a WC grain size of 0.5 μm and Co content of 12%. The EDM process was conducted by varying the condenser and resistance values. A R-C discharge EDM device using arc erosion for micro-hole machining was suggested. Furthermore, the characteristics of the developed micro-EDM were analyzed in terms of the electro-optical observation using an oscilloscope and field emission scanning electron microscope.

Nanopowder production by gas-embedded electrical explosion of wire

A small electrical explosion of wire （EEW） setup for nanopowder production is constructed. It consists of a low inductance capacitor bank of 2 μF–4 μF typically charged to 8 kV–30 kV, a triggered gas switch, and a production chamber housing the exploding wire load and ambient gas. With the EEW device, nanosize powders of titanium oxides, titanium nitrides, copper oxides, and zinc oxides are successfully synthesized. The average particle size of synthesized powders under different experimental conditions is in a range of 20nm–80nm. The pressure of ambient gas or wire vapor can strongly affect the average particle size. The lower the pressure, the smaller the particle size is. For wire material with relatively high resistivity, such as titanium, whose deposited energy Wd is often less than sublimation energy W s due to the flashover breakdown along the wire prematurely ending the Joule heating process, the synthesized particle size of titanium oxides or titanium nitrides increases with overheat coefficient k （k = W d /Ws ） increasing.

Enabling electrically tunable radio frequency components with advanced microfabrication and thin film techniques

Multi-function,multiband,cost-effective,miniaturized reconfigurable radio frequency(RF)components are highly demanded in modern and future wireless communication systems.This paper discusses the needs and implementation of multiband reconfigurable RF components with microfabrication techniques and advanced materials.RF applications of fabrication methods such as surface and bulk micromachining techniques are reviewed,especially on the development of RF microelectromechanical systems(MEMS)and other tunable components.Works on the application of ferroelectric and ferromagnetic materials are investigated,which enables RF components with continuous tunability,reduced size,and enhanced performance.Methods and strategies with nano-patterning to improve high frequency characteristics of ferromagnetic thin film(e.g.,ferromagnetic resonance frequency and losses)and their applications on the development of fully electrically tunable RF components are fully demonstrated.

Improvement of the electrical resistivity of epoxy resin at elevated temperature by adding a positive temperature coefficient BaTiO3-based compound

The DC electrical resistivity-temperature characteristic is an important property for insulating materials to operate at a high stress level.In order to improve the DC electrical resistivity at elevated temperature in a targeted way,a positive temperature coefficient(PTC)material(Ba Ti O3-based compound(BT60))was selected as the filler in this paper,whose electrical resistivity has a PTC effect when the temperature exceeds its Curie temperature.The BT60 was treated with hydrogen peroxide and(3-Aminopropyl)triethoxysilane.Epoxy composites with different loadings of BT60 fillers(0 wt%,0.5 wt%,and 2 wt%of epoxy)were prepared,denoted as EP-0,EP-0.5,and EP-2.It was shown that BT60 was able to maintain the DC breakdown strength when its loading was less than 2 wt%of epoxy.As the temperature exceeds 60°C,BT60 will compensate for the negative temperature coefficient effect of epoxy resin to some extent.The electrical resistivity of EP-2 was improved by 55%compared with that of neat epoxy at 90°C.It was found that the potential barrier at the grain boundary of BT60 and the deep traps in the interface between BT60 and the epoxy resin hinder the migration of carriers and thus increase the electrical resistivity of epoxy composite.

Research at Tsinghua University on electrical explosions of wires

Electrical explosion of a wire(EEW)has been investigated for more than ten years at Tsinghua University,and the main results are reviewed in this paper.Based onEEWin vacuum,an X-pinch was used as an x-ray source for phase-contrast imaging of small insects such as mosquitoes and ants in which it was possible to observe clearly their detailed internal structures,which can never be seen with conventional x-ray radiography.Electrical explosion of a wire array(EEWA)in vacuum is the initial stage in the formation of a wire-array Z-pinch.The evolution ofEEWAwas observed with x-ray backlighting using two X-pinches as x-ray sources.It was found that each wire in an EEWA exhibits a core–corona structure instead of forming a fully vaporized metallic vapor.This structure is detrimental to the plasma implosion of a Z-pinch.By inserting an insulator as a flashover switch into the cathode,formation of a core–corona structure was suppressed and core-freeEEWAwas realized.EEWin gases was used for nanopowder production.Three parameters(vaporization rate,gas pressure,and energy deposited in the exploding plasma)were found to influence the nanoparticle size.EEWin water was used for shock-wave generation.The shock wave generated by melting could be recorded with a piezoelectric gauge only in underheat EEW.ForEEW with a given stored energy but different energy-storage capacitor banks,the small capacitor bank produced a rapidly rising current that deposited more energy into the wire and generated a stronger shock wave.

Health Monitoring of Induction Motor Using Electrical Signature Analysis

Induction motors have been widely used across industry,particularly with smaller loads and fixed speed services.Existing works focus on fault detection of induction motors without considering the shutdown time and production in industry.Therefore,this work aims to monitor the health conditions of the induction motor continuously through electrical signature analysis(ESA).The proposed technique is capable of predicting different kinds of faults,i.e.,rotor faults,stator phase imbalances,and supply cable faults at early stages.Moreover,ESA in real time is implemented.Thereafter,these current spectra were analyzed in frequency domain and compared with healthy current spectra.Performance evaluation is implemented by observing these spectra under different faulty conditions.A comparative study is made and analyzed through MATLAB simulations.

Laser‑Induced and MOF‑Derived Metal Oxide/Carbon Composite for Synergistically Improved Ethanol Sensing at Room temperature

Advancements in sensor technology have significantly enhanced atmospheric monitoring.Notably,metal oxide and carbon(MO_(x)/C)hybrids have gained attention for their exceptional sensitivity and room-temperature sensing performance.However,previous methods of synthesizing MO_(x)/C composites suffer from problems,including inhomogeneity,aggregation,and challenges in micropatterning.Herein,we introduce a refined method that employs a metal–organic framework(MOF)as a precursor combined with direct laser writing.The inherent structure of MOFs ensures a uniform distribution of metal ions and organic linkers,yielding homogeneous MO_(x)/C structures.The laser processing facilitates precise micropatterning(<2μm,comparable to typical photolithography)of the MO_(x)/C crystals.The optimized MOF-derived MO_(x)/C sensor rapidly detected ethanol gas even at room temperature(105 and 18 s for response and recovery,respectively),with a broad range of sensing performance from 170 to 3,400 ppm and a high response value of up to 3,500%.Additionally,this sensor exhibited enhanced stability and thermal resilience compared to previous MOF-based counterparts.This research opens up promising avenues for practical applications in MOF-derived sensing devices.

Five-phase Synchronous Reluctance Machines Equipped with a Novel Type of Fractional Slot Winding

Multi-phase machines are so attractive for electrical machine designers because of their valuable advantages such as high reliability and fault tolerant ability.Meanwhile,fractional slot concentrated windings(FSCW)are well known because of short end winding length,simple structure,field weakening sufficiency,fault tolerant capability and higher slot fill factor.The five-phase machines equipped with FSCW,are very good candidates for the purpose of designing motors for high reliable applications,like electric cars,major transporting buses,high speed trains and massive trucks.But,in comparison to the general distributed windings,the FSCWs contain high magnetomotive force(MMF)space harmonic contents,which cause unwanted effects on the machine ability,such as localized iron saturation and core losses.This manuscript introduces several new five-phase fractional slot winding layouts,by the means of slot shifting concept in order to design the new types of synchronous reluctance motors(SynRels).In order to examine the proposed winding’s performances,three sample machines are designed as case studies,and analytical study and finite element analysis(FEA)is used for validation.

Coupling Analysis of Multiple Machine Learning Models for Human Activity Recognition

Artificial intelligence(AI)technology has become integral in the realm of medicine and healthcare,particularly in human activity recognition(HAR)applications such as fitness and rehabilitation tracking.This study introduces a robust coupling analysis framework that integrates four AI-enabled models,combining both machine learning(ML)and deep learning(DL)approaches to evaluate their effectiveness in HAR.The analytical dataset comprises 561 features sourced from the UCI-HAR database,forming the foundation for training the models.Additionally,the MHEALTH database is employed to replicate the modeling process for comparative purposes,while inclusion of the WISDM database,renowned for its challenging features,supports the framework’s resilience and adaptability.The ML-based models employ the methodologies including adaptive neuro-fuzzy inference system(ANFIS),support vector machine(SVM),and random forest(RF),for data training.In contrast,a DL-based model utilizes one-dimensional convolution neural network(1dCNN)to automate feature extraction.Furthermore,the recursive feature elimination(RFE)algorithm,which drives an ML-based estimator to eliminate low-participation features,helps identify the optimal features for enhancing model performance.The best accuracies of the ANFIS,SVM,RF,and 1dCNN models with meticulous featuring process achieve around 90%,96%,91%,and 93%,respectively.Comparative analysis using the MHEALTH dataset showcases the 1dCNN model’s remarkable perfect accuracy(100%),while the RF,SVM,and ANFIS models equipped with selected features achieve accuracies of 99.8%,99.7%,and 96.5%,respectively.Finally,when applied to the WISDM dataset,the DL-based and ML-based models attain accuracies of 91.4%and 87.3%,respectively,aligning with prior research findings.In conclusion,the proposed framework yields HAR models with commendable performance metrics,exhibiting its suitability for integration into the healthcare services system through AI-driven applications.

Electrical and Optical Characteristics of Electrodeless Lamp

In order to study the methods to enhance the efficacy of electrodeless lamp,volt-ampere characteristics,illuminance and emission spectrum have been investigated in home-built electrodeless lamp experimental system with an electrodeless lamp in shape like QL 85 lamp.The results show that lamp current increases as lamp voltage increases in non-discharge,the current decreases first and then increases as the voltage increases in discharge.The illuminance of electrodeless lamp increases linearly with discharge power increasing,and it decreases linearly with power decreasing.The emission spectrum is different for different bulb and lighting time.The spectrum of Ar 811.5 nm,76.5 nm,750.4 nm and Hg 313.2 nm decrease with lighting time.While the intensity of Hg 407.8 nm increases with lighting time.

A comparative study of data-driven battery capacity estimation based on partial charging curves

With its generality and practicality, the combination of partial charging curves and machine learning(ML) for battery capacity estimation has attracted widespread attention. However, a clear classification,fair comparison, and performance rationalization of these methods are lacking, due to the scattered existing studies. To address these issues, we develop 20 capacity estimation methods from three perspectives:charging sequence construction, input forms, and ML models. 22,582 charging curves are generated from 44 cells with different battery chemistry and operating conditions to validate the performance. Through comprehensive and unbiased comparison, the long short-term memory(LSTM) based neural network exhibits the best accuracy and robustness. Across all 6503 tested samples, the mean absolute percentage error(MAPE) for capacity estimation using LSTM is 0.61%, with a maximum error of only 3.94%. Even with the addition of 3 m V voltage noise or the extension of sampling intervals to 60 s, the average MAPE remains below 2%. Furthermore, the charging sequences are provided with physical explanations related to battery degradation to enhance confidence in their application. Recommendations for using other competitive methods are also presented. This work provides valuable insights and guidance for estimating battery capacity based on partial charging curves.

Applying Improved Electrical Breakdown Model to Study Insulating Property of c-C_4F_8/N_2 Gas Mixture

Perfluorocyclobutane(c-C4F8) has been recently considered as a potential alternative to SF6,because of its high electro-negativity and extremely low environmental effect.However,due to its high boiling point,c-C4F8 should mixed with buffer gases such as N2 or CO2 in order to avoid the liquefaction at low temperature.This paper investigates insulating properties of c-C4F8/N2 gas mixtures from two aspects including electrical strength,and Global Warming Potential(GWP).Moreover,improved electrical breakdown model of gas mixtures is founded.Breakdown temperature and breakdown electrical field in gas mixtures can be obtained from rigorous Townsend criterion expression according to gas mixtures ratio and cross section data of gas mixtures in this model.Under the condition of different gas pressure(0.1~0.4 MPa),gas mixtures ratio(0～30%),and electrode gap(2~10 mm),breakdown voltages of gas mixtures are calculated by using of this model.Insulation strength of SF6/N2 mixed gas is compared with c-C4F8/N2 mixed gas in the same conditions.Research results show that theoretical computation corresponds with experiment.If the content of c-C4F8 or SF6 in mixtures is less than 30%,insulation strength between c-C4F8/N2 and SF6/N2 is very close.Considering two indexes(breakdown voltage,GWP),it is suitable for c-C4F8 content being 15%～20% in c-C4F8/N2 gas

Design and Power Flow Analysis of Electrical System Using Electrical Transient and Program Software

Power flow analysis is a numerical way of study of behavior of flow of electric power in an interconnected system. In order to meet the growing demands of electrical energy in an optimum way, there is a need to upgrade existing systems or to install new systems. Therefore, planning of new installations and determination of best operating conditions of existing systems need power flow analysis. In this way, cost/benefit ratio for both suppliers and customers is maintained. This research involves the design and power flow analysis of IEEE-14 bus system. Newton Raphson method is applied for better efficiency and reduced computational time. Simulation analysis is conducted in ETAP software because of its excessive used in real life systems.