Search Results (520)

The advancement of Internet of Things (IoT) technology has enabled battery-powered devices to be deployed across a wide range of applications; however, it also introduces challenges such as high energy consumption and security vulnerabilities. To address these issues, adiabatic logic circuits offer a promising solution for achieving energy efficiency and enhancing the security of IoT devices. Adiabatic logic circuits are well suited for energy harvesting systems, especially in applications such as sensor nodes, RFID tags, and other IoT implementations. In these systems, the harvested bipolar sinusoidal RF power is directly used as the power supply for the adiabatic logic circuit. However, adiabatic circuits require a peak detector to provide bulk biasing for pMOS transistors. To meet this requirement, a diode-connected MOS transistor-based voltage doubler circuit is used to convert the sinusoidal input into a usable DC signal. In this paper, we propose a novel adiabatic logic design that maintains low power consumption while optimizing energy and current fluctuations across various input transitions. By ensuring uniform and complementary current flow in each transition within the logic circuit’s functional blocks, the design reduces energy variation and enhances resistance against power analysis attacks. Evaluation under different clock frequencies and load capacitances demonstrates that the proposed adiabatic logic circuit exhibits lower fluctuation and improved security, particularly at load capacitances of 50 fF and 100 fF. The results show that the proposed circuit achieves lower power dissipation compared to conventional designs. As an application example, we implemented an ultrasonic transmitter circuit within a LoRaWAN network at the end-node sensor level, which serves as both a communication protocol and system architecture for long-range communication systems. Full article

Diabetic foot ulcers (DFUs) represent a critical global health issue, necessitating the development of advanced smart, flexible, and wearable sensors for continuous monitoring that are reimbursable within foot orthotics. This study presents the design and characterization of a pressure sensor implemented into a shoe insole to monitor diabetic wound pressures, emphasizing the need for a high sensitivity, durability under cyclic mechanical loading, and a rapid response time. This investigation focuses on the electrical and mechanical properties of carbon nanotube (CNT) composites utilizing Ecoflex and polydimethylsiloxane (PDMS). Morphological characterization was conducted using Transmission Electron Microscopy (TEM), Laser Confocal Microscopy, and Scanning Electron Microscopy (SEM). The electrical and mechanical properties of the CNT/Ecoflex- and the CNT/PDMS-based sensor composites were then investigated. CNT/Ecoflex was then further evaluated due to its lower variability performance between cycles at the same pressure, as well as its consistently higher capacitance values across all trials in comparison to CNT/PDMS. The CNT/Ecoflex composite sensor showed a high sensitivity (2.38 to 3.40 kPa⁻¹) over a pressure sensing range of 0 to 68.95 kPa. The sensor’s stability was further assessed under applied pressures simulating human weight. A custom insole prototype, incorporating 12 CNT/Ecoflex elastomeric matrix-based sensors (as an example) distributed across the metatarsal heads, midfoot, and heel regions, was developed and characterized. Capacitance measurements, ranging from 0.25 pF to 60 pF, were obtained across N = 3 feasibility trials, demonstrating the sensor’s response to varying pressure conditions linked to different body weights. These results highlight the potential of this flexible insole prototype for precise and real-time plantar surface monitoring, offering an approachable avenue for a challenging diabetic orthotics application. Full article

Sexing procedures and subsequent freezing still impact sperm cells, leading to decreased fertility of gender-ablated semen. This study aimed to enhance cryo-survivability and reduce the capacitation-like change rate of gender-ablated semen by adding 2 mg of cholesterol-loaded cyclodextrin (CLC) per mL of extended semen containing 67 × 10⁶ sperm cells. This marks the first use of CLC with gender-ablated semen. Semen from four Jersey bulls was used for this study. Viability, motility, and mitochondrial activity were evaluated and adjusted to account for the inactivation of undesired sex sperm cells during processing. Binding ability to oviduct cells, fertilizing ability, and acrosome status were also evaluated. Adding CLC did not increase sperm motility. The population with intact membranes and acrosomes was significantly increased (p < 0.05) from 28.9 ± 1.2% to 34.1 ± 1.2% in the CLC-treated group. Mitochondrial potential, capacitation status at the membrane, calcium levels, and binding ability to oviduct cells were maintained. CLC treatment did not delay capacitation while significantly improving fertilization rates after 8 and 12 h of co-incubation (77 ± 3% vs. 67 ± 3% and 82 ± 3% vs. 74 ± 3%, respectively; p < 0.05). In conclusion, CLC addition significantly improved gender-ablated post-thaw sperm viability, acrosome integrity, and fertilizing ability while preserving motility, capacitation progress, and binding ability to oviduct cells. Full article

Microbial Fuel Cell (MFC) is a novel bioelectrochemical system that catalyzes the oxidation of chemical energy in organic waste and converts it directly into electrical energy through the attachment and growth of electroactive microorganisms on the electrode surface. This technology realizes the synergistic effect of waste treatment and renewable energy production. A CF-NiO-PANI capacitor composite anode was prepared by loading polyaniline on a CF-NiO electrode to improve the capacitance of a CF electrode. The electrochemical characteristics of the composite anode were evaluated using cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS), and the electrode materials were analyzed comprehensively by scanning electron microscopy (SEM), energy diffusion spectrometer (EDS), and Fourier transform infrared spectroscopy (FTIR). MFC system based on CF-NiO-PANI composite anode showed excellent energy conversion efficiency in potato starch wastewater treatment, and its maximum power density increased to 0.4 W/m³, which was 300% higher than that of the traditional CF anode. In the standard charge–discharge test (C1000/D1000), the charge storage capacity of the composite anode reached 2607.06 C/m², which was higher than that of the CF anode (348.77 C/m²). Microbial community analysis revealed that the CF-NiO-PANI anode surface formed a highly efficient electroactive biofilm dominated by electrogenic bacteria (accounting for 47.01%), confirming its excellent electron transfer ability. The development of this innovative capacitance-catalytic dual-function anode material provides a new technical path for the synergistic optimization of wastewater treatment and energy recovery in MFC systems. Full article

Microbial fuel cells (MFCs) generate electricity through the microbial oxidation of organic waste. However, the inherent electrochemical performance of carbon felt (CF) electrodes is relatively poor and requires enhancement. In this study, nickel oxide (NiO) was successfully loaded onto CF to improve its electrode performance, thereby enhancing the electricity generation capacity of MFCs during the degradation of treated wastewater. Scanning electron microscopy (SEM), X-ray diffraction (XRD), and energy diffusion spectrometer (EDS) analyses confirmed the successful deposition of NiO on the CF surface. The modification enhanced both the conductivity and capacitance of the electrode and increased the number of microbial attachment sites on the carbon fiber filaments. The prepared CF–NiO electrode was employed as the anode in an MFC, and its electrochemical and energy storage performance were evaluated. The maximum power density of the MFC with the CF–NiO anode reached 0.22 W/m², compared to 0.08 W/m² for the unmodified CF anode. Under the C1000-D1000 condition, the charge storage capacity and total charge output of the CF–NiO anode were 1290.03 C/m² and 14,150.03 C/m², respectively, which are significantly higher than the 452.9 C/m² and 6742.67 C/m² observed for the CF anode. These results indicate notable improvements in both power generation and energy storage performance. High-throughput gene sequencing of the anodic biofilm following MFC acclimation revealed that the CF–NiO anode surface hosted a higher proportion of electroactive bacteria. This suggests that the NiO modification enhances the biodegradation of organic matter and improves electricity generation efficiency. Full article

Sustainability can be achieved through the widespread adoption of electrification across multiple sectors of activity, which would thereby enable increased operational efficiency and reduce the environmental impact. The attainment of this purpose relies on electrical circuits that convert electrical energy from renewable power plants into forms that are compatible with the specific requirements of the load. Failure of the aforementioned circuits, denominated as power converters, can lead to financial losses resulting from unexpected shutdowns and, in critical systems, can pose significant risks to human life. This article focuses on the topic of fault diagnosis in power converters. Some of the most vulnerable components of these converters are the capacitors used in the DC-link, whose failure evolves gradually. When the capacitor internal resistance (ESR) or the capacitor capacitance (C) exceeds a certain threshold value, it is advisable to propose a system shutdown, as soon as possible, to replace the capacitor. The solution presented in this article combines signal processing techniques (SPTs) with a machine learning (ML) algorithm to determine the optimal time for capacitor replacement. The ML algorithm employed herein was a logistic regression (LR) algorithm which classified the capacitor into one of two states: normal operation (0) or failure (1). To train and evaluate the LR model, two different datasets were created using various electrical quantities that can be measured non-invasively. The model demonstrated excellent performance, achieving an accuracy, precision, recall, and F1 score above 0.99. Full article

This paper introduces a novel neuromorphic-inspired hyper-heuristic framework (NeuHH) for solving the Capacitated Single-Allocation p-Hub Location Routing Problem (CSAp-HLRP), a challenging combinatorial optimization problem that jointly addresses hub location decisions, capacity constraints, and vehicle routing. The proposed framework employs Spiking Neural Networks (SNNs) as the decision-making core, leveraging their temporal dynamics and spike-timing-dependent plasticity (STDP) to guide the real-time selection and adaptation of low-level heuristics. Unlike conventional learning-based hyper-heuristics, NeuHH provides biologically plausible, event-driven learning with improved scalability and interpretability. Experimental results on benchmark instances demonstrate that NeuHH outperforms classical metaheuristics, Lagrangian relaxation methods, and reinforcement learning-based hyper-heuristics. Specifically, NeuHH achieves superior performance in total cost minimization (up to 13.6% reduction), load balance improvement (achieving a load balance factor of as low as 1.04), and heuristic adaptability (reflected by higher heuristic switching frequency). These results highlight the framework’s potential for real-time and energy-efficient logistics optimization in large-scale dynamic networks. Full article

This paper proposes an analysis of voltage stability under small disturbances following the integration of an offshore wind farm into a real power system, considering various load and generation scenarios under both normal and post-disturbance conditions. This study utilizes the southern region equivalent system, simulated with Anarede software version 11.7.2, an offshore wind farm with a maximum capacity of 2010 MW. This wind farm is modeled as a PQ bus, operating at partial (50%) and full (100%) generation levels. Three power factor scenarios are examined: resistive, capacitive, and inductive. Submodule 2.3 of the Brazilian National System Operator guidelines states that the base case operating conditions are considered voltage insecurity. Resistive and capacitive power factor operation improved voltage stability margins but resulted in overvoltage on several buses. Conversely, inductive power factor operation led to reduced stability margins and undervoltages at buses near the wind farm. Contingency analysis further revealed stability margins below security limits. Static Var Compensators were installed at critical buses to mitigate these effects, successfully eliminating the initial overvoltage and undervoltage. Modeling as PQ buses does not guarantee stability, making compensators essential for the safe integration of offshore wind generation in Brazilian test systems. Full article

This study introduces a novel and versatile application of neural networks (NNs) to enhance two distinct aspects of Wireless Power Transfer (WPT) systems. First, a compact NN architecture is presented for accurate distance estimation and automated impedance matching in a WPT system. Trained on either impedance measurements or scattering parameters acquired from the transmitter side, this NN effectively predicts the inter-coil distance and identifies optimal capacitance values for maximizing power transfer. Validation using both simulated and experimental data demonstrates consistently low prediction error rates. Second, a separate NN is employed to predict the optimal transmission frequency for minimizing the phase angle between voltage and current, thereby maximizing the power factor. This NN, validated on experimental data spanning various load conditions and inter-coil distances, achieves performance comparable to traditional PI control, but with significantly faster prediction speeds. This speed advantage is crucial for real-time applications and directly contributes to improved power efficiency. The results presented in this study, including the high accuracy of distance and capacitance prediction and the rapid determination of optimal frequencies for power factor maximization, showcase the significant potential of NNs for optimizing WPT systems. These findings open the way for more efficient, adaptable, and intelligent wireless energy transfer solutions, with potential applications ranging from dynamic charging of electric vehicles to real-time optimization of implantable medical devices. Full article

This paper presents a highly linear two-stage InGaP/GaAs power amplifier integrated circuit (PAIC) using a dynamic predistorter for 5G small-cell applications. The proposed predistorter, based on a diode-connected transistor, utilizes a supply voltage to accurately control the linearization characteristics by adjusting its dc current. It is connected in parallel with an inter-stage of the two-stage PAIC through a series configuration of a resistor and an inductor, and features a shunt capacitor at the base of the transistor. These passive components have been optimized to enhance the linearization performance by managing the RF signal’s coupling to the diode. Using these optimized components, the AM−AM and AM−PM nonlinearities arising from the nonlinear resistance and capacitance in the diode can be effectively used to significantly flatten the AM−AM and AM−PM characteristics of the PAIC. The proposed predistorter was applied to the 2.6 GHz two-stage InGaP/GaAs HBT PAIC. The IC was tested using a 5 × 5 mm² module package based on a four-layer laminate. The load network was implemented off-chip on the laminate. By employing a continuous-wave (CW) signal, the AM−AM and AM−PM characteristics at 2.55–2.65 GHz were improved by approximately 0.05 dB and 3°, respectively. When utilizing the new radio (NR) signal, based on OFDM cyclic prefix (CP) with a signal bandwidth of 100 MHz and a peak-to-average power ratio (PAPR) of 9.7 dB, the power-added efficiency (PAE) reached at least 11.8%, and the average output power was no less than 24 dBm, achieving an adjacent channel leakage power ratio (ACLR) of −40.0 dBc. Full article

Dynamic comparators play an important role in electronic systems, requiring high accuracy, low power consumption, and minimal offset voltage. This work proposes an accurate and low-complexity offset calibration design based on a capacitive load approach. It was designed using a 65 nm CMOS technology and comprehensively evaluated under Monte Carlo simulations and PVT variations. The proposed scheme was built using MIM capacitors and transistor-based capacitors, and it includes Verilog-based calibration algorithms. The proposed offset calibration is benchmarked, in terms of precision, calibration time, energy consumption, delay, and area, against prior calibration techniques: current injection via gate biasing by a charge pump circuit and current injection via parallel transistors. The evaluation of the offset calibration schemes relies on Analog/Mixed-Signal (AMS) simulations, ensuring accurate evaluation of digital and analog domains. The charge pump method achieved the best Energy-Delay Product (EDP) at the cost of lower long-term accuracy, mainly because of its capacitor leakage. The proposed scheme demonstrated superior performance in offset reduction, achieving a one-sigma offset of 0.223 mV while maintaining precise calibration. Among the calibration algorithms, the window algorithm performs better than the accelerated calibration. This is mainly because the window algorithm considers noise-induced output oscillations, ensuring consistent calibration across all designs. This work provides insights into the trade-offs between energy, precision, and area in dynamic comparator designs, offering strategies to enhance offset calibration. Full article

In this paper, we present a novel passive dual-tuned magnetic metasurface, which can enhance the field distribution produced by a closely placed radio-frequency coil for both ¹H and ²³Na 1.5 T MRI imaging. In particular, the proposed solution comprises a 5 × 5 capacitively loaded array, in which each unit-cell is composed of two concentric spiral coils. Specifically, the unit-cell internal spiral coil operates at the proton Larmor frequency (64 MHz), whereas the external is at the sodium one (17 MHz). Therefore, the paper aims to demonstrate the possibility of enhancing the magnetic field distribution in transmission and reception for 1.5 T MRI scanners by using the same metasurface configuration for imaging both nuclei, thus drastically simplifying the required instrumentation. We first describe the theoretical model used to design and synthetize the dual-tuned magnetic metasurface. Next, full-wave simulations are carried out to validate the approach. Finally, we report the experimental results acquired by testing the fabricated prototype at the workbench, observing a good agreement with the theoretical design and the numerical simulations. In particular, the metasurface increases the transmission efficiency T_x in presence of a biological phantom by a factor 3.5 at 17 MHz and by a factor 5 at 64 MHz, respectively. The proposed solution can pave the way for MRI multi-nuclei diagnostic technique with better images quality, simultaneously reducing the scanning time, the invasiveness on the patient and the overall costs. Full article

For high-power magnetic resonance imaging (MRI) radio frequency (RF) combiners operating in the frequency range from 60 MHz to 300 MHz, the primary challenges lie in achieving high-power transmission capability while minimizing the insertion loss (IL), reducing the physical dimensions, and meeting application bandwidth requirements. This paper presents a high-performance RF power combiner based on capacitor-loaded microstrip technology for 3.0T MRI radio frequency power amplifier (RFPA) systems. The proposed combiner features low loss, high integration, and miniaturization, and it comprises multiple branches, each employing microstrip lines and capacitors in a series–parallel arrangement to achieve an impedance transformation of 50 Ω to 100 Ω. Each branch was designed through theoretical analysis and electromagnetic simulations to achieve a line length 30% shorter than λ/4, a 6.2 mm line width, and 0.08 dB IL at the 3.0T MRI operation frequency band. A two-way to one-way combiner was further designed using this branch structure to achieve 0.2 dB IL through simulation optimization. A four-way to one-way combiner was then constructed by cascading two-way combiners and optimized via ADS-HFSS software(ADS2014 HFSS19) co-simulation. The fabricated combiner module uses an FR4 substrate and achieves a 0.4 dB insertion loss, −25 dB return loss, and 25 dB port isolation at 128 MHz ± 1 MHz, with compact dimensions (320 × 200 × 10 mm). To ensure high power capability, thermal analysis was performed to confirm that the module’s power-handling capacity exceeded 8 kW, and experimental validation with the 8 kW 3.0T RFPA demonstrated a stable temperature rise of approximately 2 °C. In this study, the innovative single-branch topology and the RF high-power four-to-one combiner for 3.0T MRI systems were used, resolving the trade-offs between power-handling capability, insertion loss, structural compactness, and operating bandwidth in MRI power combiners. The combiner was successfully integrated into the 3.0T MRI RFPA system, reducing the overall dimensions of the RFPA system and simplifying its installation, thereby enabling high-quality imaging validation. This solution demonstrates the scalable potential of the design for other high-field MRI systems operating in the MHz range (from tens to hundreds of MHz), including in 1.5T and 7.0T MRI systems. Full article

A full-bridge DC–DC converter with structure exchange is proposed to simulate battery charging based on an electronic load. The full-bridge phase-shift converter (FBPSC) uses an external resonant inductor and phase-shift control on the primary side to realize zero voltage switching (ZVS) above medium load. However, the energy of the resonant inductor is not enough to carry away the energy of the parasitic capacitance on the switch at light load, leading to the inability of ZVS as well as the circulating current problem due to the long duration of the primary-side circulating current. Consequently, in order to conquer such problems mentioned above, the structure exchange, with only the control strategy changed from the phase-shift control to the two-transistor forward control, is presented to increase the light-load efficiency remarkably. Furthermore, the number of inductors is reduced by using the center-tap structure on the secondary side compared to the current-doubler structure. In addition, the synchronous rectifier on the secondary side is used to further improve the overall efficiency of the converter. Full article

The advent of the Internet of Things has boosted portable and wearable miniature electronics, especially micro-supercapacitors (MSCs) with excellent integrated performance as well as high-power density and a long lifetime. However, the rational design of electrode material formulations and the construction of three-dimensional (3D) structured electrodes with scalable and cost-effective fabrication remains an arduous task for improving the energy density of MSCs to meet all industrial sector requirements, such as the mass-production of microscale structures, a lasting power supply, and safety. To address these challenges, combining the respective capacitance merits of MXenes and polyaniline (PANI), we propose a constructing strategy for the preparation of a 3D MXene@PANI hierarchical architecture consisting of one-dimensional (1D) PANI nanofibers grown on two-dimensional (2D) Ti₃C₂ MXene nanosheets via extrusion-based 3D printing. Such a 3D architecture not only achieves a high loading mass of MSC electrodes prior to conventional planar MSCs for abundant active site exposure, but it also overcomes the restacking of MXene nanosheets accounting for sluggish ionic kinetics. These features enable the resulting MSCs to deliver excellent electrochemical properties, including a high volumetric capacitance of 1638.3 mF/cm³ and volumetric energy density of 328.2 mWh/cm³. This power supply ability is further demonstrated by lighting up a blue bulb or powering an electronic thermometer. This study provides a promising design strategy of the architecture of MXene@PANI composites for high-performance MSCs with 3D printing technology. Full article