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

Meysam Akbari, Zahra Hashemi, Erika Covi et al.

This work introduces an enhanced operational amplifier architecture in which four flipped voltage follower (FVF) cells act as adaptive tail current sources to improve the performance of a conventional current mirror (CM)-based design. The FVF cells dynamically boost the differential pair current beyond the nominal bias level during the slewing interval, enabling a significantly higher slew rate and reduced settling time. By employing both n-channel and p-channel input stages driving cascode loads, the proposed dual FVF-controlled tail sources improve efficiency for both small- and large-signal operations. Additionally, the use of supplementary input devices increases the overall transconductance, thereby achieving higher DC gain and extended gain&#x2013;bandwidth product. The amplifier was implemented in TSMC 0.18-<inline-formula> <tex-math notation="LaTeX">$\mu $ </tex-math></inline-formula>m CMOS technology and validated through measurements, demonstrating a DC gain of 73.3 dB, a unity-gain bandwidth of 98.4 MHz, and a slew rate of 102.7 V/<inline-formula> <tex-math notation="LaTeX">$\mu $ </tex-math></inline-formula>s. The circuit operates from a 1.8-V supply, driving a 16-pF capacitive load, with a power consumption of <inline-formula> <tex-math notation="LaTeX">$642~\mu $ </tex-math></inline-formula>W.

Xiao Wen, Xiaopeng Liu, Jianping Meng

Diagnosing diseases through the detection of biomarker levels in exhaled breath samples represents a new frontier in medical diagnostics, as it offers a non-invasive and low-cost method for disease diagnosis. The emergence of two-dimensional (2D) materials, with their unique physicochemical properties and structural diversity, has greatly advanced the development of gas sensors, providing broader prospects for their application in disease diagnosis. 2D material gas sensors are typically sensitive even at very low concentrations of gases at room temperature, with the added advantages of low power consumption and ease of integration. This review aims to introduce the main types of 2D materials and their characteristics, discuss gas biomarkers representing different diseases and the corresponding 2D material gas sensor. Then, we identify technological gaps hindering the application of 2D material gas sensor and explore methods for improving them. The goal is to guide future research and development efforts and identify the best strategies for overcoming these obstacles. Finally, we provide an outlook on the integration of various 2D material gas sensors and the realization of simultaneous detection of multiple gas biomarkers.

Sumit Pratap Singh, Mostafa Jafari Nokandi, Timo Rahkonen et al.

This work presents a sliding-IF mixer-first IQ receiver front-end, in 130 nm SiGe BiCMOS technology with <inline-formula> <tex-math notation="LaTeX">${f_{t}}/{f_{\mathrm { max}}}$ </tex-math></inline-formula> of 300 GHz/450 GHz, operating in 300 GHz band. For near-<inline-formula> <tex-math notation="LaTeX">$f_{\mathrm { max}}$ </tex-math></inline-formula> operation, the sliding-IF architecture eliminates the need for the local oscillator (LO) frequency to be the same as the carrier frequency. Consequently, the power consumption of the LO chain is significantly reduced with carefully optimized multiplier chain. Signal amplification is performed at the IF stage. LO frequency at two thirds and one third of the carrier frequency is generated, from an external 50 GHz LO signal using on-chip frequency doublers for RF and I/Q mixers, respectively. The receiver provides 15.2 dB of conversion gain, input-referred compression point of &#x2013;17 dBm and single sideband noise figure of 29.5 dB at 310 GHz. The 3-dB RF and BB bandwidths are measured to be 26 GHz and 10 GHz, respectively. Despite operating at 0.69x<inline-formula> <tex-math notation="LaTeX">$f_{\mathrm { max}}$ </tex-math></inline-formula>, the receiver front-end operates with 16-quadrature amplitude modulation (QAM) modulation with 4 GHz, 64-QAM with 2 GHz and 256-QAM with 0.5 GHz wide modulated signal centered at low-baseband frequency with 8.2%, 5.5%, and 2.7% error vector magnitude (EVM), respectively. In low gain mode, the receiver offers a 10 dB improvement in the dynamic range with a 30% reduction in power consumption in the signal chain, which makes it one of the most energy efficient receiver front-ends in its class.

Nikolai Hofmann, Vanessa Wirth, Johanna Braunig et al.

Near-field multiple-input multiple-output (MIMO) radar systems allow for high-resolution spatial imaging by leveraging multiple antennas to transmit and receive signals across multiple perspectives. This capability is particularly advantageous in challenging environments, where optical imaging techniques struggle. We present a novel approach to inverse rendering for near-field MIMO radar systems, aimed at reconstructing material properties such as surface roughness, dielectric constants, and conductivity from radar and ground-truth mesh data, for example obtained from multi-view stereo. Drawing inspiration from physically based rendering techniques in computer graphics, we formalize an advanced inverse rendering algorithm that integrates electromagnetic wave propagation models directly into the optimization process. To avoid bias from conventional radar image reconstruction algorithms in the optimization process, we directly derive gradients from raw radar outputs, resulting in more accurate material characterization. We validate our approach through extensive experiments on both synthetic and real radar datasets, demonstrating its effectiveness in a multitude of scenarios.

Artem Boriskin, Massinissa Ziane, Mariem Mafamane et al.

The increasing use of the upper part of the microwave spectrum for wireless communications requires appropriate methods and instrumentation for user exposure assessment. In this context, the IEC TC106 is developing a new international standard for user exposure compliance testing of the next generation 5G/6G wireless devices operating above 6&#x2009;GHz. As a part of this initiative, the development of a universal reference skin model (RSM) is fundamental for definition of reference data to be included in specifications for body phantom design. In this study, we systematically analyze the impact of the human body near-surface tissue structure on the electromagnetic field (EMF) reflection from the skin surface in the 6&#x2013;100&#x2009;GHz range. A conventional multi-layer model is used to calculate skin reflectance as a function of the tissue thickness for the range of thicknesses corresponding to that of typical human skin and near-surface body tissues at four body sites concerned by the 5G/6G wireless use-case scenarios, namely: head, torso, forearm, and palm. The dominant contribution from the epidermis/dermis (ED) layer to the skin reflectance is demonstrated for all body sites in the considered frequency range. A high variation in the reflectance of the palm skin at frequencies above 20&#x2009;GHz is demonstrated and explained by the matching layer effect associated with a thick stratum corneum (SC). The dry skin model, represented by a semi-infinite homogeneous medium with complex permittivity equivalent to that of the ED tissue, is shown to be an appropriate RSM both for the experimental and numerical evaluation of the absorbed power density (APD) in the 6&#x2013;100&#x2009;GHz range. The reference data for the antenna loading and APD at the skin surface are provided for standard reference feeds at 10&#x2009;GHz, 30&#x2009;GHz, 60&#x2009;GHz, and 90&#x2009;GHz.

Y. Sun, M. Alzate Banguero, P. Salev et al.

Abstract The ramp‐reversal memory (RRM) effect in metal–insulator transition metal oxides (TMOs), a non‐volatile resistance change induced by repeated temperature cycling, has attracted considerable interest in neuromorphic computing and non‐volatile memory devices. Our previous defect motion model successfully explained RRM in vanadium dioxide (VO2), capturing observed critical temperature shifts and memory accumulation throughout the sample. However, this approach lacked interactions between metallic and insulating domains. Here, we extend our model by combining a correlated Random Field Ising Model with defect diffusion‐segregation, enabling accurate hysteresis modeling while predicting the relationship between RRM and domain interactions. Our simulations demonstrate that the maximum RRM occurs when the turnaround temperature approaches the inflection point. This peak in RRM vs. turnaround temperature is consistent with prior transport measurements, as well as our own optical measurements reported here. Significantly, we find that increasing nearest‐neighbor interactions enhances the maximum memory effect, thus providing a clear mechanism for optimizing RRM performance. Since our model employs minimal assumptions, we predict that RRM should be a widespread phenomenon in materials exhibiting patterned phase coexistence of electronic domains. This work not only advances fundamental understanding of memory behavior in TMOs but also establishes a much‐needed theoretical framework for optimizing device applications.

Hangkai Fan, Alexey Proskurin, Mingzhao Song et al.

Second-harmonic generation (SHG) is a fundamental nonlinear optical process widely used in photonics; however, it is strictly forbidden in the bulk of centrosymmetric materials due to their inversion symmetry. Nevertheless, applying an external electric field breaks this inversion symmetry. It induces an effective second-order nonlinear response known as the electric-field-induced second-harmonic generation (EFISH) effect. This mechanism enables SHG even in centrosymmetric media and provides a powerful tool for dynamic and electrically tunable nonlinear nanophotonics. This review presents a comprehensive overview of the EFISH effect, covering the fundamentals, various material platforms (including bulk semiconductor crystals, ferroelectrics, van der Waals materials, and polymers), as well as diverse strategies for electric field engineering. It further distinguishs EFISH from related effects such as current-induced SHG and the quantum-confined Stark effect, and highlight emerging applications of EFISH in tunable photonic devices, carrier dynamics probing, and nonlinear optical modulation across optical, electronic, and THz regimes. Finally, key challenges and perspectives for the future development of electrically controlled nonlinear optical systems are outlined.

Surat Layek, Mahesh A. Hingankar, Ayshi Mukherjee et al.

Two-dimensional materials are a fertile ground for exploring quantum geometric phenomena, with Berry curvature and its first moment, the Berry curvature dipole, playing a central role in their electronic response. These geometric properties influence electronic transport and result in the anomalous and nonlinear Hall effects, and are typically controlled using static electric fields or strain. However, the possibility of modulating quantum geometric quantities in real-time remains unexplored. Here, we demonstrate the dynamic modulation of Berry curvature and its moments, as well as the generation of a pseudo-electric field using time-dependent strain. By placing heterostructures on a membrane, we introduce oscillatory strain together with an in-plane AC electric field and measure Hall signals that are modulated at linear combinations of the frequencies of strain and electric field. Our measurements reveal modulation of Berry curvature and its first moment. Notably, we provide direct experimental evidence of pseudo-electric field that results in an unusual dynamic strain-induced Hall response. This approach opens up a new pathway for controlling quantum geometry on demand, moving beyond conventional static perturbations. The pseudo-electric field provides a framework for external electric field-free anomalous Hall response and opens new avenues for probing the topological properties.

Sergiy Mankovsky, Svitlana Polesya, Jan Minar et al.

We present an approach for first principles investigations on the spin driven electric polarization in type II multiferroics. We propose a parametrization of the polarization with the parameters calculated using the Korringa-Kohn-Rostoker Green function (KKR-GF) formalism. Within this approach the induced electric polarization of a unit cell is represented in terms of three-site parameters. Those antisymmetric with respect to spin permutation are seen as an ab-initio based counter-part to the phenomenological parameters used within the inverse-Dzyaloshinskii-Moriya-interaction (DMI) model. Due to their relativistic origin, these parameters are responsible for the electric polarization induced in the presence of a non-collinear spin alignment in materials with a centrosymmetric crystal structure. Beyond to this, our approach gives direct access to the element- or site-resolved electric polarization. To demonstrate the capability of the approach, we consider several examples of the so-called type II multiferroics, for which the magneto-electric effect is observed either as a consequence of an applied magnetic field (we use Cr$_2$O$_3$ as a prototype), or as a result of a phase transition to a spin-spiral magnetic state, as for instance in MnI$_2$, CuCrO$_2$ and AgCrO$_2$.

Mlungisi Ntombela, Kabeya Musasa, Katleho Moloi

Electric vehicles (EVs) are gaining more and more traction as a viable option in the automotive sector. This mode of transportation is currently on track, according to current trends, to totally replace internal combustion engine (ICE) cars in the not-too-distant future. The economic system, the energy infrastructure, and the environment are just a few of the areas where electric vehicles could have a major impact. The transportation industry produces the second-most carbon dioxide gas from the combustion of fossil fuels, making it the second-highest contributor to global warming. A lot of people are looking to EVs, or electric vehicles, as a possible game-changing answer to this problem. Since an electric motor drives the electric vehicle’s propeller instead of an internal combustion engine, electric vehicles can reduce their carbon dioxide (CO2) emissions compared to traditional automobiles. If coupled with renewable energy sources, EVs might theoretically become emission-free automobiles. In this paper, we will examine the various EV drive circuit types, including their construction and the benefits and drawbacks of employing each. This article discusses the current state of battery technology with an emphasis on EV batteries. This article discusses the best electric motor for EVs in terms of efficiency, power density, fault tolerance, dependability, cost, and more. Next, we conduct in-depth research into the difficulties and potential rewards of EV adoption in the future. While improvements in areas like charging times and battery performance are encouraging, government regulation of EVs remains a big non-technical barrier.

Massimo Vatalaro, Raffaele De Rose, Marco Lanuzza et al.

Physically unclonable functions (PUFs) represent emerging cryptographic primitives that exploit the uncertainty of the CMOS manufacturing process as an entropy source for generating unique, random and stable keys. These devices can be potentially used in a wide variety of applications ranging from secret key generation, anti-counterfeiting, and low-cost authentications to advanced protocols such as oblivious transfer and key exchange. Unfortunately, guaranteeing adequate PUF stability is still challenging, thus often requiring post-silicon stability enhancement techniques. The latter help to contrast the raw sensitivity to on-chip noise and variations in the environmental conditions (i.e., voltage and temperature variations), but their area and energy costs are not always feasible for IoT devices that operate with constrained budgets. This pushes the demand for ever more stable, area- and energy-efficient solutions at design time. This review aims to provide an overview of several weak PUF solutions implemented in CMOS technology, discussing their performance and suitability for being employed in security applications.

Arturo Barjola, Roberto Herráiz, Andrea Amaro et al.

Abstract MXenes, a promising family of 2D transition metal carbides/nitrides, are renowned for their exceptional electronic conductivity and mechanical stability, establishing them as highly desirable candidates for advanced electromagnetic interference (EMI) shielding material. Despite these advantages, challenges persist in optimizing MXene synthesis methods and improving their oxidation resistance. Surface defects on MXenes significantly impact their electronic properties, impeding charge transport and catalyzing the oxidation process. In this study, a novel synthesis protocol derived from the conventional, minimally invasive layer delamination (MILD) method, is presented. Two additional steps are introduced aiming at enhancing process yield, addressing a crucial issue as conventional methods often yield high‐quality individual MXene flakes but struggle to generate sufficient quantities for bulk material production. This approach successfully yields Ti3C2Tx films with excellent conductivity (3973.72 ±121.31 Scm−1) and an average EMI shielding effectiveness (SE) of 56.09 ± 1.60 dB within the 1.5 to 10 GHz frequency range at 35% relative humidity (RH). Furthermore, this investigation delves into the long‐term oxidation stability of these films under varying RH conditions. These findings underscore the effectiveness of this innovative synthesis approach in elevating both the conductivity and EMI shielding capabilities of MXene materials. This advancement represents a significant step toward harnessing MXenes for practical applications requiring robust EMI shielding solutions. Additionally, insights into long‐term stability offer critical considerations for implementing MXenes in real‐world environments.

Hyunho Seok, Dongho Lee, Sihoon Son et al.

Abstract Brain‐inspired parallel computing is increasingly considered a solution to overcome memory bottlenecks, driven by the surge in data volume. Extensive research has focused on developing memristor arrays, energy‐efficient computing strategies, and varied operational mechanisms for synaptic devices to enable this. However, to realize truly biologically plausible neuromorphic computing, it is essential to consider temporal and spatial aspects of input signals, particularly for systems based on the leaky integrate‐and‐fire model. This review highlights the significance of neuromorphic computing and outlines the fundamental components of hardware‐based neural networks. Traditionally, neuromorphic computing has relied on two‐terminal devices such as artificial synapses. However, these suffer from significant drawbacks, such as current leakage and the lack of a third terminal for precise synaptic weight adjustment. As alternatives, three‐terminal synaptic devices, including memtransistors, ferroelectric, floating‐gate, and charge‐trapped synaptic devices, as well as optoelectronic options, are explored. For an accurate replication of biological neural networks, it is vital to integrate artificial neurons and synapses, implement neurobiological functions in hardware, and develop sensory neuromorphic computing systems. This study delves into the operational mechanisms of these artificial components and discusses the integration process necessary for realizing biologically plausible neuromorphic computing, paving the way for future brain‐inspired electronic systems.

Nisha C. Rani, N. Amuthan

This study proposes a novel solution to address harmonic issues in a Renewable Energy Resource System (RES) connected to the grid, using a Voltage Source Inverter (VSI) controlled by a QRCC based on Zero Voltage Transition and Zero Current Transition (ZVT-ZCT). We enhance system performance by integrating Harris Hawks Optimization (HHO) with the VSI. Key outcomes include evaluating the system's effectiveness in terms of voltage drop, current drop, real power, active power, and total harmonic distortion (THD). Notably, settling times for various converters are highlighted: 0.01 s for SEPIC, 0.008 s for CUK, 0.005 s for ZETA, and an impressive 0.0001 s for the Cascade converter. Under different operational conditions, open-loop operation yields a THD of 18.45%, reduced to 7.843% in closed-loop with PI controller. Optimization techniques further improve the system, achieving a low THD of 0.0549%. We emphasize the significance of MPPT-based INC-IR for cascade converters, resulting in a minimal switching loss of 0.38W, showcasing the system's efficiency in energy conversion.

Samuel Talkington, Rahul Gupta, Richard Asiamah et al.

Despite their wide-scale deployment and ability to make accurate high-frequency voltage measurements, communication network limitations have largely precluded the use of smart meters for real-time monitoring purposes in electric distribution systems. Although smart meter communication networks have limited bandwidth available per meter, they also have the ability to dedicate higher bandwidth to varying subsets of meters. Using this capability to enable real-time monitoring from smart meters, this paper proposes an online bandwidth-constrained sensor sampling algorithm that takes advantage of the graphical structure inherent in the power flow equations. The key idea is to use a spectral bandit framework where the estimated parameters are the graph Fourier transform coefficients of the nodal voltages. The structure provided by this framework promotes a sampling policy that strategically accounts for electrical distance. Maxima of sub-Gaussian random variables model the policy rewards, which relaxes distributional assumptions common in prior work. The scheme is implemented on a synthetic electrical network to dynamically identify meters exposing violations of voltage magnitude limits, illustrating the effectiveness of the proposed method.

Chiara Ceriani, Mattia Scagliotti, Tommaso Losi et al.

Abstract Conjugated semiconducting polymers are key active materials for printable electronics, sensors and biosensors, organic photovoltaics, organic light emitting devices, and more. The research in the field developed very efficient materials and sound structure property relationships, thus making a case for a transition from laboratory to industrial environment. At this critical juncture, sustainability, and ease of scaling up are at least as important as performances, to the point that efficient materials on a lab scale could become unpractical for the industry. The development of more efficient synthetic protocols and the complete removal of all organic solvents from both the synthesis and the processing of semiconducting polymers can help tremendously to improve sustainability and reduce costs. It is shown that the use of an aqueous dispersion of the food grade surfactant lecithin as the medium, enables the synthesis and processing of the representative semiconducting alternating copolymer poly (9,9‐dioctylfluorene‐alt‐bithiophene) (PF8T2) in high yield and high quality and with transistor performances comparable with those obtained with reference materials synthetized and processed from volatile organic solvents.

Firas Saadallah Raheem, Noorulden Basil

As voltage and power issues across automation intelligence photovoltaic system, the efficient of Fractional Order Proportional Integral Derivative (FOPID) controller can be the primary approach to preventing unstable the current and voltage sensors, and this strategy is considered as an automation intelligent computing, in providing an automated intelligent photovoltaic computing system solution to select the appropriate FOPID gains for the most cases with four cases, many challenges are bound to be faced: (1) design an automated intelligent photovoltaic system including scalability and precision toward voltage and power issues for prioritizing current and voltage sensors, and (2) technical measured and simulated including the gap between convergences and an accurate matching amongst four cases considering all FOPID gains. Based on previous studies, no study had provided a solution for automation intelligent photovoltaic system during these gains settings issues. This study aimed to propose a novel automation intelligence photovoltaic system for voltage and power issues across current and voltage sensors based on Black Hole Optimization (BHO) algorithm to provide an efficient automation intelligence system using FOPID gains. The batteries, including three thermal model for three batteries have met the importance intelligent batteries in the automated intelligence PV system, must be augmented to develop system. Four cases for voltage and power issues conclude for the three PV panels. In the first case, a new automated intelligent PVs Panels between lowest and upper bounds is generated on the basis of the automated system with select fifteen gains for tuning and different bounds for other cases acquired via intelligent BHO algorithm. The execution of automated intelligent system possesses the precision and scalability presentation within tuned BHO algorithm. The objective validation results which indicate that the case 1 is a better case.

Genjie Yang, Jiyu Li, Mengge Wu et al.

Abstract Flexible photodetectors (FPDs), which provide excellent advantages such as great wearability, portability, even implantability, have attracted tremendous interest in wearable healthcare monitoring, bendable imaging sensors, portable optical communication, etc. Recently, organic and perovskite‐based photoactive materials have been considered promising candidates for FPDs due to their superior optoelectronic performance, appealing mechanical flexibility, low‐temperature solution processability, and cost‐effectiveness. In this review, the milestone progress of organic, perovskite, and organic‐perovskite hybrid‐based FPDs and their applications in artificial intelligence are summarized. First, a brief introduction of device configurations, working principles, and key parameters for FPDs are presented. Subsequently, functional materials in FPDs, especially flexible photoactive materials of organic, perovskite, and organic‐perovskite hybrids, are summarized and analyzed. More importantly, representative applications of FPDs are summarized, including wearable healthcare monitoring, imaging sensors, and optical communication. The outlook and challenges for the field are proposed at the end. The purpose of this review is to not only elaborate on the fundamental design principles of FPDs, but also serve as a roadmap for next‐generation artificial intelligence sensing technologies.

Kiran Bala, Ramakant Upadhyay, Syed Rashid Anwar et al.

Intelligent Transportation System (ITS) heavily relies on the unique mobile ad-hoc network (MANET) known as the vehicular ad-hoc network (VANET). The convenience that the Location Based Service (LBS), security issues arising from VANETs' great portability. Among the most widely used privacy-preserving techniques, distributed k-anonymity does not consider users' reliability, which results in hostile vehicle tracking. Therefore, Blockchain-enabled, Trust and Location dependent-Privacy Preserving (BTLB-PP) authentication system in VANET to overcome issues. Trust Management (TM) based on Dirichlet distribution, client and member will only collaborate with vehicles they confide by explicitly examining various prerequisites of claimed vehicle and collaborative vehicle during construction of unidentified obfuscation region and integrating attributes of these two functions. Using blockchain, a data structure has been proposed to promptly register trust of vehicles on publicly available blocks, allowing any vehicle to retrieve. In the trials, tests on various datasets have been run. Suggested system is resistant to multiple trust model threats, improving the security of vehicles' confidentiality and privacy. The performance evaluation metrics are precision, recall, f-measure and false positive rate (FPR) are used to evaluate the proposed system. Results from the simulation show that the proposed method is efficient and practical in reality. The suggested method was tested in a simulated traffic situation to verify its effectiveness.

Fulvia Del Duca, Lukas Hiendlmeier, Reem Al Fata et al.

Abstract Thin film electronic devices based on flexible biocompatible substrates are desired in various fields such as implants, soft robotics, and wearables, where stretchability is often necessary. Structure‐enabled stretchability in flexible thin films can be achieved by introducing origami‐inspired folds, thereby storing excess material in the out‐of‐plane direction to unfold upon stress. When using vapor‐deposited substrates such as parylene‐C, folds can be introduced prefabrication using molds patterned in repeated grooves and ridges. Here, this work reports the fabrication and parametrization of 10‐µm‐thick stretchable origami parylene‐C electrodes using 3D printed molds. The molds are printed with a sinusoidal pattern and tunable amplitude and slope, with accurate printing results up to 60° steepness. A 160‐nm‐thick gold layer on top of the folded parylene is patterned via laser ablation following the 3D mold shape. Depending on the design parameters, the resulting electrodes maintain functionality until 40%–100% strain. By 3D printing the molds, this technique can fabricate electrodes with complete control of the designed directions of stretchability in a rapid prototyping approach.