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

M. Scharber, D. Mühlbacher, M. Koppe et al.

Konstantinos Rogdakis, Georgios Psaltakis, Konstantinos Chatzimanolis et al.

Abstract The emulation of neuronal activity requires complex circuits that integrate multiple passive and active components, leading to a high circuit footprint. It is therefore apparent that developing a single device that can be used to emulate both synaptic and neuronal activity would allow less complexity and a much lower circuit footprint having significant impact on practical applications of neuromorphic systems. Herein, mixed halide perovskite‐based transistors are demonstrated to exhibit volatile memristive behavior that responds to both light and electric fields, opening the path for optoelectronic control of neuron‐like functions. Specifically, it is shown that by applying a low compliance current (ICC) during drain current–voltage (ID–VD) measurements, volatile memristive switching behavior is reported. A set of volatile ID–VD curves is presented under various gate biases, indicating a gate‐enabled shift of the low‐resistance state set voltage to higher values. The volatile nature of the device operated at low ICC allowed the demonstration of gate‐tunable neuronal functions, including amplitude‐ and frequency‐modulated spike firing. Furthermore, linear potentiation protocols and Leaky Integrate‐and‐Fire behavior is reported, while light pulses are shown to induce both photonic potentiation and graded optical neurons, opening the path for emulating neuron functions tunable by both light and electric fields.

Peng Xu, Yapeng Li, Tinghuan Chen et al.

Digital circuits representation learning has made remarkable progress in the electronic design automation domain, effectively supporting critical tasks such as testability analysis and logic reasoning. However, representation learning for analog circuits remains challenging due to their continuous electrical characteristics compared to the discrete states of digital circuits. This paper presents a direct current (DC) electrically equivalent-oriented analog representation learning framework, named \textbf{KCLNet}. It comprises an asynchronous graph neural network structure with electrically-simulated message passing and a representation learning method inspired by Kirchhoff's Current Law (KCL). This method maintains the orderliness of the circuit embedding space by enforcing the equality of the sum of outgoing and incoming current embeddings at each depth, which significantly enhances the generalization ability of circuit embeddings. KCLNet offers a novel and effective solution for analog circuit representation learning with electrical constraints preserved. Experimental results demonstrate that our method achieves significant performance in a variety of downstream tasks, e.g., analog circuit classification, subcircuit detection, and circuit edit distance prediction.

Qinghao Xu, Junhao Gong, Jiayi Chen et al.

Abstract In the rapidly advancing fields of artificial intelligence and the Internet of Things, there is a growing need for human‐computer interaction (HCI) solutions that are not only intuitive but also efficient and easy to use. Triboelectric nanogenerators present a promising approach to developing wireless human‐machine interfaces, offering advantages such as simple operating principles and flexible, adaptable designs. This study introduces an HCI system that leverages a contactless triboelectric detector (CTD) to classify complex motion patterns in 3D space. The CTD system consists of a contactless sensing panel, a silicone rubber finger sleeve, a signal acquisition circuit, and a mobile terminal, which together enable the seamless acquisition and classification of weak wireless signals. One of the key benefits of the system is its lack of active energy consumption, making it highly energy‐efficient. Additionally, its simple structure and ease of deployment make it an attractive option for various applications. Experimental results illustrate that the proposed system has significant potential for interactive perception in industrial environments. With a motion recognition accuracy of 99.33%—including for intricate motions such as spiral curves—this system demonstrates its potential as a next‐generation solution for wireless HCI systems.

Hanlin Wang, Haojie Li, Siqi Liu et al.

In recent years, high performance organic photovoltaics (OPVs) produced in ambient-air have shown extraordinary potential for commercialization. However, the presence of air components, represented by water and oxygen, makes it difficult to maintain the intrinsic stability of organic photovoltaic materials and the morphological stability of functional layers. Consequently, this phenomenon hinders the fabrication of high-performance devices. Herein, the key paths to realize high-performance air-prepared devices in recent research are reviewed through molecular design, device engineering, and process innovation. The roles of designing and synthesizing novel optoelectronic materials and device structure optimization in air-prepared high-performance OPVs are discussed. In addition, the optimization strategies for OPVs fabricated by printing process are discussed in depth, taking into account the synergistic nature of the printing process for the preparation of OPVs in an air environment. This provides theoretical guidance for high-throughput production of OPV modules.

U Jeong Yang, Sehyun Park, Woosung Choi et al.

Abstract As known, n‐type inorganic semiconductor nanoparticles such as zinc oxide nanoparticles have been explored in various sensing applications, which demand high‐density electronic elements placement for rapid operation. Herein, high‐resolution designs of conductive channels of noble metal‐doped zinc oxide nanoparticles is demonstrated using an engraving transfer printing process and silver metal doping approach. Such thin‐film transistors with reduced feature size to 2 µm fabricated exhibited significantly enhanced electron mobility up 3.46 × 10−2 cm2 V−1 s−1 and light sensitivity. Furthermore, the integration of this micropatterning technology and metal doping in thin‐film transistors is utilized for control of current–voltage characteristics under the ultraviolet radiation with high sensitivity. It is suggested that this approach to design of doped inorganic nanoparticle channels paves the way for high‐density thin‐film transistors suitable for optoelectronic circuit, UV photodetectors and neuromorphic computing systems.

Zhao-Fan Cai, Yang Li, Yu-Ran Zhang et al.

The non-Hermitian skin effect (NHSE), characterized by the accumulation of a macroscopic number of bulk states at system boundaries, is a hallmark of non-Hermitian physics. However, effective control of skin-mode localization in higher-dimensional systems remains a significant challenging. Here, we propose a versatile approach to manipulate the localization of skin modes in two-dimensional non-Hermitian lattices by combining disorder with a static electric field. While the electric field alone suppresses the NHSE in a clean system, the introduction of disorder induces transverse wave-packet transport perpendicular to the field. In nonreciprocal lattices, when the nonreciprocal hopping is misaligned with the electric field, the hopping component perpendicular to the field guides wave-packet propagation and produces boundary localization. By tuning the relative orientation between the electric field and the nonreciprocal hopping direction, the boundary localization position can be continuously and arbitrarily controlled. We further demonstrate distinct geometry-dependent manipulation of skin modes in reciprocal lattices, where controllable boundary localization emerges solely from the lattice geometry. These results establish a robust and tunable mechanism for engineering boundary accumulation and directed transport in non-Hermitian systems, offering new opportunities for applications in classical platforms and quantum materials.

Daniel O-Campa, Omar Pedraza, L. A. López et al.

This work focuses on the study of the spectral problem for Dirac materials immersed in position-dependent magnetic and electric fields. To achieve this, the system of differential equations satisfied by the eigenfunction components of the Hamiltonian has been decoupled, and the solutions for some specific cases have been analyzed using Heun functions, which provide us with a quantization relation and allow us to determine the solutions for the bound states.

Hongzhong Li, Yida He, Wanxin Fu et al.

Giovanni Pilato, Gianpaolo Vitale, G. Vassallo et al.

In this paper, a model for nonlinear ferrite power inductors based on the α\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\alpha $$\end{document}Net neural network is proposed. The model is able to reproduce the ferrite power inductors inductor behavior up to saturation, considering the core temperature. The α\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\alpha $$\end{document}Net neural network was used for its generalization capability considering a hybrid approach encompassing a classical weighted interpolation. The model’s effectiveness was experimentally verified by calculating the current flowing through two inductors in an electric circuit in different operating conditions, and has been compared with the two main models found in literature to show the improvement both in terms of the maximum value of the estimated current and the root mean square error. The modeling procedure can be easily extended to inductors with different sizes and core materials due to the features of the α\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\alpha $$\end{document}Net network and the hybrid approach to retrieve data.

Bayu Agung Prakoso, Unan Yusmaniar Oktiawati

Container menjadi alternatif virtualisasi infrastruktur layanan internet berkat efisiensi penggunaan sumber daya. Infrastruktur IT dapat terdiri dari beragam container, dengan Kubernetes berperan sebagai Container Orchestration. Container Network Interface (CNI) dipergunakan dalam skenario layanan pada Kubernetes untuk mengatur jaringan sehingga memudahkan terhubungnya layanan. Namun, masalah seperti kemampuan jaringan terbatas, kurangnya fleksibilitas, dan terbatasnya skalabilitas serta keamanan menjadi isu dalam penggunaan CNI plugin. Solusi atas persoalan tersebut adalah Multus CNI yang memungkinkan beragam antarmuka jaringan pada satu pod. Studi ini melakukan evaluasi kinerja antara Flannel dan Cilium sebagai plugin CNI dalam lingkungan Kubernetes Cluster dengan melibatkan Multus CNI. Metrik yang dianalisis mencakup latency, packet loss, throughput, dan CPU usage. Hasil penelitian akan menghasilkan pemahaman lebih baik mengenai kompromi yang harus dilakukan saat memilih antara Flannel dan Cilium sebagai plugin CNI dalam lingkungan Kubernetes Cluster.

Laimin Du, Leibin Ni, Xiong Liu et al.

Approximate computing is an emerging and effective method for reducing energy consumption in digital circuits, which is critical for energy-efficient performance improvement of edge-computing devices. In this paper, we propose a low-power DNN accelerator with novel signed approximate multiplier based on probability-optimized compressor and error compensation. The probability-optimized compressor is customized for partial product matrix (PPM) of signed operands, which gets the optimal logic circuit after probabilistic analysis and optimization. At the same time, we explored the PPM truncation method, found out the impact of different partial product (PP) truncation numbers on circuit benefit and error, and achieved a more ideal performance-error tradeoff through a reasonable error compensation method. In the optimal case of 8 bits, the proposed approximate multiplier saves 49.84&#x0025; power, 46.41&#x0025; area and 24.65&#x0025; delay compared to the exact multiplier. We employed the proposed approximate multiplier in the vector systolic array as the processing element (PE). Under the VGG-16 evaluation, the proposed accelerator achieves performance improvement of energy efficiency <inline-formula> <tex-math notation="LaTeX">$1.96\times $ </tex-math></inline-formula>, while the error loss was only 0.95&#x0025;.

Laishram Khumanleima Chanu, Samrat Chakraborty, Rajen Pudur

– The self-excited induction generator (SEIG) is well accepted for application in micro hydropower plants. However, in the edge-of-grid application it exhibits a limitation in its capacity to sustain the desired terminal voltage along with the frequency of variations in the prime mover's speed and load. Terminal voltage and frequency regulation are significant concerns for such schemes, and many such techniques are available to regulate the same. This paper presents a closed-loop control technique based on a generalized impedance controller (GIC) responsible for the impedance-controlled functioning of the pulse width variation voltage source converter (PWM-VSC) to regulate frequency and terminal voltage of machine with various loading conditions. A coupling transformer is connected between GIC and SEIG, and the ratings of GIC and transformer should be the same as SEIG, as GIC must compensate for the entire SEIG output. Three phase, 2.2 kW, 415 V, 4.8 A, 50 Hz SEIG, and a three IGBT-based voltage-sourced inverter with coupling transformer, are modelled in MATLAB environment. SEIG frequency and voltage effects in response to the GIC modulation index and phase angle are investigated in the real-time environment using the OPAL-RT (ver. OP4510) environment. The voltage and frequency are controlled using the proposed SEIG-GIC scheme, and the simulation results achieved from MATLAB/Simulink were validated with real-time observations.

Paul Tangney

I define the fields that describe electrical macrostructure, and their rates of change, in terms of the microscopic charge density, electric field, electric potential, and their rates of change. To deduce these definitions, I lay some new foundations of a theory of how observable macroscopic fields are related to spatial averages of their microscopic counterparts. I find that the relationships between macroscopic fields are identical in form to the relationships between their microscopic counterparts, meaning that the $\vec{P}$ and ${\vec{D}}$ fields do not appear in them. Without invoking quantum mechanics, I derive the expressions for polarization current established by the Modern Theory of Polarization. I prove that the bulk-average electric potential, or mean inner potential, vanishes in a macroscopically-uniform charge-neutral material, and I show that when a crystal lattice lacks inversion symmetry, it does not imply the existence of macroscopic $\vec{E}$ or $\vec{P}$ fields in the crystal's bulk. I point out that symmetry is scale-dependent. Therefore, if anisotropy of the microstructure does not manifest as anisotropy of the macrostructure, it cannot be the origin of a macroscopic vector field. The macroscopic charge density vanishes in a material's bulk. Therefore, regardless of the microstructure, a macroscopic $\vec{E}$ field cannot emanate from the bulk. I find that all relationships between observable macroscopic fields can be expressed mathematically without introducing the polarization ($\vec{P}$) and electric displacement ($\vec{D}$) fields, neither of which is observable. I also show that most `quantum mechanical' aspects of the existing microscopic theory of electricity in materials are compatible with, or required features of, a statistical theory of classical particles whose charges and masses are comparable to those of electrons and nuclei.

Chaoxi Cui, Run-Wu Zhang, Yilin Han et al.

Exploring new Hall effect is always a fascinating research topic. The ordinary Hall effect and the quantum Hall effect, initially discovered in two-dimensional (2D) non-magnetic systems, are the phenomena that a transverse current is generated when a system carrying an electron current is placed in a magnetic field perpendicular to the currents. In this work, we propose the electric counterparts of these two Hall effects, termed as electric Hall effect (EHE) and quantum electric Hall effect (QEHE). The EHE and QEHE emerge in 2D magnetic systems, where the transverse current is generated by applying an electric gate-field instead of a magnetic field. We present a symmetry requirement for intrinsic EHE and QEHE. With a weak gate-field, we establish an analytical expression of the intrinsic EHE coefficient. We show that it is determined by intrinsic band geometric quantities: Berry curvature and its polarizability which consists of both intraband and interband layer polarization. Via first-principles calculations, we investigate the EHE in the monolayer Ca(FeN)$_2$, where significant EHE coefficient is observed around band crossings. Furthermore, we demonstrate that the QEHE can appear in the semiconductor monolayer $\rm BaMn_2S_3$, of which the Hall conductivity exhibits steps that take on the quantized values $0$ and $\pm1$ in the unit of $e^2/h$ by varying the gate-field within the experimentally achievable range. Due to the great tunability of the electric gate-field, the EHE and QEHE proposed here can be easily controlled and should have more potential applications.

H. Eskandari, H. Kaimori, T. Matsuo

In this article, a second-order approximation is proposed for nonlinear eddy-current (EC) problems via parametric Cauer ladder network (CLN) method. Through the CLN method, an orthogonal sequence of electric and magnetic modes along with the equivalent circuit parameters are generated by magnetostatic finite element analysis. When there are nonlinear materials in the medium, the modes and their corresponding values in equivalent circuit may vary according to the core’s saturation level. This article introduces new algorithms to generate second-order CLN (SO-CLN) based on intensity of the first and second magnetic modes. Additionally proper handling of circuit equations is also included. Numerical tests are carried out over a 2-D nonlinear inductor with bulk type conductive-magnetic core to show the accuracy of the proposed method.

K. Du, Pai Lu

The high-power and high-frequency response characteristics of supercapacitors have enabled their promising application in fasting charging/discharging scenarios such as power grid stabilization and Internet of Things (IoT). The widespread use of portable electronic devices and the evolution of the IoT have underscored the growing demand for the ongoing miniaturization and enhanced energy autonomy of existing circuit components [1]. Micro-supercapacitors (MSCs) have surfaced as a promising solution to meet these demands, offering superior power density and cycle life compared to similar battery products [2]. However, integrating MSCs with electronic circuits presents significant challenges, often serving as a roadblock to comprehensive system miniaturization. To cater to the requirements of practical application scenarios, particularly in System-in-Package (SiP) and System-on-Chip (SoC) contexts, the fabrication of MSCs requires the use of silicon-based semiconductors or Micro-Electro-Mechanical Systems (MEMS) technology [3]. This strategic approach not only enhances performance but also ensures shorter interconnection distances, more compact dimensions, and increased energy and power density across all components. Emphasizing high power density, elevated energy density, and responsive high-frequency behavior is crucial for the optimal characteristics of MSCs in future applications. As for electrode materials, carbon, which is abundant and cost-effective, has spurred extensive research into various nanostructured carbon-based materials for Electric Double-Layer (EDL) MSCs, including activated carbon, carbon nanotubes (CNTs), carbide-derived carbon, and onion-like carbon [4]. Additionally, transition metal oxides such as ruthenium oxide and manganese oxide, along with conductive polymers like polypyrrole and polyaniline, have proven useful as materials for pseudocapacitive micro supercapacitors [5]. Notably, CNTs fabricated through Chemical Vapor Deposition (CVD) are unequivocally compatible with MEMS microfabrication technology. In the context of EDL MSCs, a dense CNT network structure boosts energy density but impedes ion transport, thereby reducing power density. Conversely, a sparse CNT network structure facilitates ion transport but compromises high-frequency response due to fewer charge transfer paths. Therefore, the development of CNT-based MSCs tailored to practical application needs a more thorough investigation into CNT network structures and their current collector designs. Here, we report the fabrication of on-chip MSCs that are fully compatible with Silicon-based MEMS technology. Figure 1 illustrates the fabrication and characterization process of on-chip MSCs utilizing silicon-based MEMS technology, showing distinct surface morphologies of b-Si nanostructures after CNT growth and Au layer deposition. Figure 2 presents the electrochemical performance of the on-chip MSCs. The CV curves exhibit an ideal rectangular shape at a scan rate of 1 V/s. Even at a high scan rate of 100 V/s, the CV curve maintains a quasi-rectangular shape with minimal distortion, confirming the ultrafast response performance (Fig. 2 (a-b)). The phase angles of the on-chip MSCs are measured to be -68.9° and -66.2° in 1.0 M Na2SO4, and -64.1° and -70.8° in 0.5 M H2SO4 at 120 Hz (Fig. 2 (c)). The absence of a prominent semicircle in the Nyquist plots at high frequencies region implies fast electron transfer and ion diffusion within CNT/Au nanocomposite electrodes. Furthermore, the equivalent series resistances (ESR) are 0.604 Ω·cm2, 0.201 Ω·cm2, 0.504 Ω·cm2, and 0.126 Ω·cm2 for Si-CNT-20 and Si-CNT-20-Au MSCs (Fig. 2 (d)), indicating excellent interfacial contact between the CNT layer and Au current collector and good electrode conductivity. Fig. 2(e) shows that the MSCs deliver a specific capacitance (CA ) of 0.049 mF/cm2, 1.041 mF/cm2, 0.101 mF/cm2, and 1.368 mF/cm2 in 1.0 M Na2SO4 and 0.5 M H2SO4 at 120 Hz, respectively. The relaxation time constant (τ0 ) is calculated to be as short as 1.65 ms for the MSCs (Si-CNT-20-Au), underscoring rapid ion diffusion within electrodes in 0.5 M H2SO4 electrolyte (Fig. 2 (e)). In conclusion, we have successfully used b-Si as the scaffold structure and 3D CNT/Au nanocomposites as the active material for on-chip MSCs application. Significantly, the incorporation of this silicon-based 3D CNT/Au nanocomposite electrode presents promising prospects for the application of MSCs in varied domains, including wearable electronics, IoT devices, and sensor networks. References [1] M. Beidaghi, C. Wang, Adv. Funct. Mater., (2012), 22, 4501. [2] G. S. Gund, J. H. Park, R. Harpalsinh, M. Kota, J. H. Shin, T. I. Kim, Y. Gogotsi, H. S. Park, Joule, (2019), 3, 164. [3] C. Lethien, J. Le Bideau, T. Brousse. Energy Environ. Sci., (2019),12, 96-115. [4] Z. Fan, N. Islam, and S. B. Bayne, Nano Energy, (2017), 39, 306-320. [5] J. Wei, X. Li, H. Xue, J. Shao, R. Zhu, H. Pang, Adv. Mater. Interfaces., (2018), 5(9), 1701509. Acknowledgement Financial support from the Innovation Norway through an EEA Grant under Grant No. 2021/336905, is acknowledged. Figure 1

Zepeng Zhou, Wenqing Li, J. Qian et al.

With the emergence of fifth-generation (5G) cellular networks, millimeter-wave (mmW) and terahertz (THz) frequencies have attracted ever-growing interest for advanced wireless applications. The traditional printed circuit board materials have become uncompetitive at such high frequencies due to their high dielectric loss and large water absorption rates. As a promising high-frequency alternative, liquid crystal polymers (LCPs) have been widely investigated for use in circuit devices, chip integration, and module packaging over the last decade due to their low loss tangent up to 1.8 THz and good hermeticity. The previous review articles have summarized the chemical properties of LCP films, flexible LCP antennas, and LCP-based antenna-in-package and system-in-package technologies for 5G applications, although these articles did not discuss synthetic LCP technologies. In addition to wireless applications, the attractive mechanical, chemical, and thermal properties of LCP films enable interesting applications in micro-electro-mechanical systems (MEMS), biomedical electronics, and microfluidics, which have not been summarized to date. Here, a comprehensive review of flexible LCP technologies covering electric circuits, antennas, integration and packaging technologies, front-end modules, MEMS, biomedical devices, and microfluidics from microwave to THz frequencies is presented for the first time, which gives a broad introduction for those outside or just entering the field and provides perspective and breadth for those who are well established in the field.

Prabhat Kumar Maiti

The transformer is the most critical apparatus in the electric power network. Reliable operation of it is of foremost concern for a proficient power supply. Therefore, it is vital to safeguard the transformer so that it functions at its highest capacity. In order to achieve it, an improvement in the insulation system is necessary, as the majority of faults in transformers are due to the malfunctioning of the insulation system. Petroleum-based oils are extensively used as insulating liquids in transformers. The latterly evolved field of nanotechnology has encouraged studies on Nanofluids (NFs), which are suitable as liquid insulators. In spite of the advantages of NFs in electrical and thermal behavior compared to their base fluids, further studies are needed to establish their long-standing performances as liquid insulators. In this study, three mineral oil samples, new, mid-aged, and extensively aged, were taken. Nanofluids of 0.02% Al2O3 and 0.02% SiO2 of these oils were prepared. The base fluids and nanofluids were characterized by interfacial tension, acidity, dielectric dissipation factor, resistivity, and electric strength. The nanofluids prepared were subjected to laboratory thermal ageing in the presence of copper and kraft paper for 64 hours at 150 °C. The unaged and laboratory-aged nanofluids were characterized for acidity, Interfacial Tension (IFT), Specific Resistance (SR), Tan Delta (TD), and Dielectric Strength (BDV). It was found through this work that the addition of nanoparticles upgraded the properties of oil samples. The long-term applicability and permanence of nanofluids might depend on catalytic effects. These catalytic effects are derived from the internal assembly materials of the transformer.