Search Results (2,546)

In this report, a thickness-driven, aggregation–structure–transport optimum in sonicated poly(3-hexylthiophene) (P3HT) FETs was investigated. Mobility peaks at ~10–20 nm, coincident with a minimum in the photoluminescence (PL) vibronic ratio I₀₋₀/I₀₋₁ (strong H-aggregate interchain coupling) and X-ray diffraction sharpening of the (100) lamellar peak with slightly reduced d-spacing, indicate tighter π–π stacking and larger crystalline coherence. Absorption analysis (Spano model) is consistent with this enhanced interchain order. The mobility maximum arises from an optimal balance: J-aggregate–like intrachain planarity supports along-chain transport, while H-aggregates provide interchain connectivity for efficient hopping. Below this thickness, insufficient interchain coupling limits transport; above it, over-aggregation and disorder introduce traps and weaken gate control. The sharp rise in threshold voltage beyond the critical thickness indicates more trap states or fixed charges forming within the film bulk. As a result, a larger gate bias is needed to deplete the channel (remove excess holes) and switch the device off. These results show that electrical gating can be tuned via solution processing (sonication) and film thickness—guiding the design of P3HT devices for photovoltaics and sensing. Full article

As Battery Management Systems (BMSs) continue to expand in both scale and capacity, conventional state-of-charge (SOC) estimation methods—such as Coulomb counting and model-based observers—face increasing challenges in meeting the requirements for cell-level precision, scalability, and adaptability under aging and operating variability. To address these limitations, this study integrates a Deep Neural Network (DNN)–based estimation framework into a node-level BMS architecture, enabling edge-side computation at each individual battery cell. The proposed architecture adopts a decentralized node-level structure with distributed parameter synchronization, in which each BMS node independently performs SOC estimation using shared model parameters. Global battery characteristics are learned through offline training and subsequently synchronized to all nodes, ensuring estimation consistency across large battery arrays while avoiding centralized online computation. This design enhances system scalability and deployment flexibility, particularly in high-voltage battery strings with isolated measurement requirements. The proposed DNN framework consists of two identical functional modules: an offline training module and a real-time estimation module. The training module operates on high-performance computing platforms—such as in-vehicle microcontrollers during idle periods or charging-station servers—using historical charge–discharge data to extract and update battery characteristic parameters. These parameters are then transferred to the real-time estimation chip for adaptive SOC inference. The decentralized BMS node chip integrates preprocessing circuits, a momentum-based optimizer, a first-derivative sigmoid unit, and a weight update module. The design is implemented using the TSMC 40 nm CMOS process and verified on a Xilinx Virtex-5 FPGA. Experimental results using real BMW i3 battery data demonstrate a Root Mean Square Error (RMSE) of 1.853%, with an estimation error range of [4.324%, −4.346%]. Full article

This work examines resistance drift in FPGA I/O paths subjected to combined electrical and thermal stress, using a Xilinx Spartan-6 device as a representative platform. A multiplexed measurement approach was employed, in which multiple I/O pins were externally shorted and sequentially activated, enabling precise tracking of voltage, current, and effective series resistance over time, under controlled bias conditions. Two accelerated stress modes were investigated: high-temperature dwell in the range of 80–120 °C and thermal cycling between 80 and 140 °C. Both stress modes exhibited similar sub-linear (power-law) time dependence on resistance change, indicating cumulative degradation behavior. However, Arrhenius analysis revealed a strong contrast in effective activation energy: approximately 0.62 eV for high-temperature dwell and approximately 1.3 eV for thermal cycling. This divergence indicates that distinct physical mechanisms dominate under each stress regime. The lower activation energy is consistent with electrically and thermally driven on-die degradation within the FPGA I/O macro, including bias-related aging of output drivers and pad-level structures. In contrast, the higher activation energy observed under thermal cycling is characteristic of diffusion- and creep-dominated thermo-mechanical damage in package-level interconnects, such as solder joints. These findings demonstrate that resistance-based monitoring of FPGA I/O paths can discriminate between device-dominated and package-dominated aging mechanisms, providing a practical foundation for reliability assessment and self-monitoring methodologies in complex electronic systems. Full article

The construction of ultra-high voltage transmission lines puts extremely high demands on the high-altitude operation of heavy-load unmanned aerial vehicles (UAV). Air density and temperature at high altitudes have a great influence on the efficiency and stability of the UAV power system. Traditional regulation methods based on parameters pre-set or simple look-up tables cannot achieve the best adaptability. In this paper, we presents an intelligent method for the high-altitude adaptability control of heavy-load UAV power systems using a deep neural network. The proposed method collects real-time, multi-dimensional environmental parameters, including altitude, temperature, and air pressure, using a barometric altimeter and GPS receiver, constructs a High-Altitude Adaptive Regulation Network (HAARN), and intelligently learns complex nonlinear relationships to predict the optimal motor speed, propeller pitch angle, and current limit under the current environmental conditions so as to dynamically adjust power output. The HAARN model was trained on a dataset of 12,000 synchronized samples collected from both controlled environmental-chamber experiments (temperature range: −10 $°\mathrm{C}$ to 20 $°\mathrm{C}$; pressure range: 100–50 kPa, corresponding approximately to 0–5500 m) and multi-point plateau flight trials conducted at 2000 m, 3000 m, 4000 m, and 4500 m. This combined dataset was used for feature engineering, exhaustive-label generation, and model validation to ensure robust generalization across realistic high-altitude operating conditions. Experimental results show that, compared with traditional PID control and lookup-table approaches, the proposed method reduces thrust attenuation by about 12.5% and improves energy efficiency by 8.3% at the altitude of 4000 m. In addition, HAARN demonstrates consistent improvements across the tested altitude range (0–4500 m). Full article

To address active power fluctuations in power grids induced by high renewable energy penetration and overcome the limitations of existing probabilistic power flow (PPF) methods that ignore generator frequency regulation constraints, this paper proposes a segmented stochastic power flow modeling method and an efficient analytical framework that incorporates the actions and capacity constraints of regulation units. Firstly, a dual dynamic piecewise linear power injection model is established based on “frequency deviation interval stratification and unit limit-reaching sequence ordering,” clarifying the hierarchical activation sequence of “loads first, followed by conventional units, and finally automatic generation control (AGC) units” along with the coupled adjustment logic upon reaching limits, thereby accurately reflecting the actual frequency regulation process. Subsequently, this model is integrated with the State-Independent Linearized Power Flow (DLPF) model to develop a segmented stochastic power flow framework. For the first time, a deep integration of unscented transformation (UT) and regulation-aware power allocation is achieved, coupled with the Nataf transformation to handle correlations among random variables, forming an analytical framework that balances accuracy and computational efficiency. Case studies on the New England 39-bus system demonstrate that the proposed method yields results highly consistent with those of Monte Carlo simulations while significantly enhancing computational efficiency. The DLPF model is validated to be applicable under scenarios where voltage remains within 0.95–1.05 p.u., and line transmission power does not exceed 85% of rated capacity, exhibiting strong robustness against parameter fluctuations and capacity variations. Furthermore, the method reveals voltage distribution patterns in wind-integrated power systems, providing reliable support for operational risk assessment in grids with high shares of renewable energy. Full article

The widespread adoption of low-power devices and microelectronic systems has intensified the need for efficient energy harvesting solutions. While cantilever-beam piezoelectric energy harvesters (PEHs) are popular for their simplicity, their performance is often limited by conventional mass block designs. This study addresses this by proposing a comprehensive structural optimization framework for a triangular cantilever PEH to significantly enhance its electromechanical conversion efficiency. The methodology involved a multi-stage approach: first, an embedded coupling design was introduced to connect the mass block and cantilever beam, improving space utilization and strain distribution. Subsequently, the mass block’s shape was optimized. Furthermore, a negative Poisson’s ratio (NPR) honeycomb structure was integrated into the cantilever beam substrate to induce biaxial strain in the piezoelectric layer. Finally, a variable-density mass block was implemented. The synergistic combination of all optimizations—embedded coupling, NPR substrate, and variable-density mass block—culminated in a total performance enhancement of 69.07% (17.76 V) in voltage output and a 44.34% (28.01 Hz) reduction in resonant frequency. Through experimental testing, the output performance of the prototype machine showed good consistency with the simulation results, successfully verifying the effectiveness of the structural optimization method proposed in this study. These findings conclusively show that strategic morphological reconfiguration of key components is highly effective in developing high-performance, low-frequency adaptive piezoelectric energy harvesting systems. Full article

The sustained growth of electricity demand and the global transition toward low-carbon energy systems have intensified the need for efficient, flexible, and reliable operation of electrical distribution networks. In this context, the coordinated integration of distributed renewable energy resources and demand-side flexibility has emerged as a key strategy to improve technical performance and economic efficiency. This work proposes an integrated optimization framework for active power supply in a radial, distribution-like network through the optimal siting and sizing of photovoltaic (PV) units and wind turbines (WTs), combined with a real-time pricing (RTP)-based demand-side response (DSR) program. The problem is formulated using the branch-flow (DistFlow) model, which explicitly represents voltage drops, branch power flows, and thermal limits in radial feeders. A multiobjective function is defined to jointly minimize annual operating costs, active power losses, and voltage deviations, subject to network operating constraints and inverter capability limits. Uncertainty associated with solar irradiance, wind speed, ambient temperature, load demand, and electricity prices is captured through probabilistic modeling and scenario-based analysis. To solve the resulting nonlinear and constrained optimization problem, an Improved Whale Optimization Algorithm (I-WaOA) is employed. The proposed algorithm enhances the classical Whale Optimization Algorithm by incorporating diversification and feasibility-oriented mechanisms, including Cauchy mutation, Fitness–Distance Balance (FDB), quasi-oppositional-based learning (QOBL), and quadratic penalty functions for constraint handling. These features promote robust convergence toward admissible solutions under stochastic operating conditions. The methodology is validated on a large-scale radialized network derived from the IEEE 118-bus benchmark, enabling a DistFlow-consistent assessment of technical and economic performance under realistic operating scenarios. The results demonstrate that the coordinated integration of PV, WT, and RTP-driven demand response leads to a reduction in feeder losses, an improvement in voltage profiles, and an enhanced voltage stability margin, as quantified through standard voltage deviation and fast voltage stability indices. Overall, the proposed framework provides a practical and scalable tool for supporting planning and operational decisions in modern power distribution networks with high renewable penetration and demand flexibility. Full article

This study addresses the lack of transparent methods for calculating the energy requirements of pulsed electric field (PEF) pretreatments in biogas research. Two detailed approaches are proposed and evaluated to quantify the energy consumed during the pretreatment of lignocellulosic harvest residues (corn, soybean, and sunflower) using a low-frequency electric field. The first approach is based on previously measured capacitor parameters, including resistance (R_s, R_p), inductance (L_s), capacitance (C_p), and loss factor (D), which were interpolated to 50 Hz from measurements performed over the frequency range of 100 Hz to 10 kHz. The second approach relies on direct measurements of the effective voltage and current waveforms across the capacitor, followed by calculation of the power factor (cos φ). Both methods enable reliable estimation of energy consumption and differ primarily in the type of input data required: Method 1 is based on capacitor characteristics determined before and after pretreatment, while Method 2 uses real-time treatment data. Despite these differences, the two approaches yielded highly consistent results, confirming their robustness and applicability. The calculated energy values were subsequently incorporated into a net energy balance by comparing the energy consumed during pretreatment with the methane energy output from anaerobic digestion. For all three investigated lignocellulosic substrates, PEF pretreatment resulted in a positive energy balance under the applied process conditions. Full article

Electric field-assisted local functionalization of materials is a resist-free technique generally applied at the nanoscale, which has been understood within the paradigm of the water meniscus. Using a home-made prototype the authors applied this technique at scales compatible with the biosensor industry (tens of microns). However, interpreting these results requires a different paradigm. The expansion of the oxidized region over time in two-dimensional materials under a localized electric field is modeled from first physical principles. Boltzmann statistics is applied to the oxyanion incorporation at the perimeter of the oxidized zone, and a new general relation between oxide radius and time is formulated. It includes the reduction in the energy barrier due to the field effect and its dependence on the oxide radius. To gain insight into this dependence whatever the layers structure, 2D material involved, or electrical operating conditions, simple structures based on multilayer stacks representing the main constituents are proposed, where the Poisson equation is solved using finite element calculations. This enables to derive energy barriers for oxyanion incorporation at varying spot radii which are consistent with those resulting from fitting experimental data. The reasonable agreement obtained provides researchers with a new tool to predict the evolution of local functionalization of 2D layers as a function of the following fabrication parameters: time, applied voltage, and relative humidity, solely based on materials properties. Full article

Bi₂Se₃ thin films with different thicknesses are deposited on prepatterned n-Si substrates by the vapor–solid deposition method, demonstrating photodetector performances in the visible and near-infrared range up to the telecommunication wavelength 1550 nm and showing response times as low as 126 ns. The current voltage characteristics measured in the temperature range 77–300 K indicate the formation of Schottky junctions at the interface between the two materials. The nature of the junctions is discussed considering the effect of disorder at the interface induced by the Bi₂Se₃ film granularity. The temperature dependence of the ideality factors and the Schottky barrier heights is consistent with a thermionic field effect mechanism governing the electron motion through the interface, which is responsible for the fast response of the photodetectors. Full article

A stripline-type circulator is essential for the initial low-power characterization of vacuum electron devices such as magnetrons, enabling accurate measurements of startup behavior, oscillation frequency, and mode structure while minimizing reflections and protecting diagnostic equipment. In this study, two broadband S-band stripline circulator prototypes operating in the 2–4 GHz and 3–4 GHz bands were designed, fabricated, and experimentally characterized. A unified design methodology was implemented by using the same ferrite material and coupling angle in both structures, providing procurement simplicity, cost reduction, and technological standardization. This approach also enabled a direct assessment of how bandwidth variations influence circulator behavior. The design goals targeted a transmission efficiency above 90%, isolation exceeding 15 dB, and a voltage standing-wave ratio (VSWR) of 1.2:1. Experimental evaluations, including magnetic field mapping, low-power S-parameter measurements, and high-power tests, confirmed that both prototypes satisfy these specifications, consistently achieving at least 90% transmission across their respective operating bands. Additionally, a comparative analysis between a locally fabricated ferrite and a commercial ferrite sample was conducted, revealing the influence of material properties on transmission stability and high-power behavior. The results demonstrate that broadband stripline circulators employing a common ferrite material can be adapted to different S-band applications, offering a practical, cost-effective, and reliable solution for RF systems. Full article

This paper introduces an enhanced bandgap reference (BGR) design, addressing the shortcomings of traditional circuits, such as significant temperature drift, limited power-supply rejection, and inadequate load-driving capacity. The proposed design incorporates a symmetric folded common-emitter–common-base BJT amplifier with MOS-assisted biasing, employed in the proposed BGR, enforcing branch voltage symmetry to effectively suppress intrinsic offset caused by structural mismatch. By reducing the amplifier input offset, the circuit achieves improved reference voltage stability, a lower temperature coefficient (TC), and an enhanced power-supply rejection ratio (PSRR). Additionally, a negative-feedback adaptive current-adjustment driver is implemented to dynamically adjust the output current in response to real-time load changes. This method bolsters the load-driving capability and maintains a stable reference output across varying load conditions. The circuit was simulated using a 0.18 μm BCD process, revealing that with a 3.3 V supply voltage, the BGR produces a stable output voltage of 2.5 V, with a TC of $2.372\times {10}^{-6}$ °C⁻¹. The simulated PSRR is −114.2 dB at DC and −62.07 dB at 1 kHz. Moreover, under a 3.3 V supply, sweeping the load capacitance from 0.1 μF to 100 μF demonstrates that the reference voltage remains consistently regulated at 2.5 V, confirming its excellent load tolerance and output stability. Full article

The surface morphology of lithium metal electrodes evolves markedly during cycling, modulating interfacial kinetics and increasing the risk of dendrite-driven internal short circuits. Here, we infer this morphological evolution from direct-current (DC) signals by analyzing open-circuit voltage (OCV) transients after constant current interruptions. The OCV exhibits a rapid initial decay followed by a transition to a slower long-time decay. With repeated plating, this transition shifts to earlier times, thereby increasing the contribution of long-term relaxation. We quantitatively analyze this behavior using an equivalent circuit with a transmission-line model (TLM) representing the electrolyte-accessible interfacial region of the electrode, discretized into ten depth-direction segments. Tracking segment-wise changes in resistances and capacitances with cycling enables morphology estimation. Repeated plating strongly increases the double-layer area near the current collector, while the charge-transfer-active surface shifts toward the separator side, showing progressively smaller and eventually negative changes toward the current-collector side. Together with the segment-resolved time constants, these trends indicate that lithium deposition becomes increasingly localized near the separator-facing surface, while the interior becomes more tortuous, consistent with post-mortem observations. Overall, the results demonstrate that DC voltage-relaxation analysis combined with a TLM framework provides a practical route to track lithium metal electrode surface evolution in Li-metal-based cells. Full article

A reflective all-fiber optical current transformer based on a spatial non-reciprocal phase modulation technique is investigated by theoretical analysis and experimental measurement. The modulation unit, composed of a phase delay wave plate (LiNbO₃) and two Faraday rotators, achieves flexible frequency adjustment by converting modulation from the time domain to the spatial domain. Therefore, the avoidance of the impact caused by delay coils is achieved in principle. The absence of intrinsic frequency limitations eliminates the demand for precise timing control in demodulation, thereby simplifying the demodulation circuit and reducing the cost and size of the transformer. In previous studies, redundancies were identified in the optical path coupling devices. The half-wave voltage of the modulator is excessively high, and its size is considerable due to constraints inherent in the manufacturing process. The measurement range is within 1800 A. The scheme simplifies some optical path components. By optimizing the phase delay wave plate, the half-wave voltage of the modulator is significantly reduced by a factor of 150. Experimental results demonstrate that the current transformer exhibits excellent detection consistency within the rated current range of 30–3600 A (1–120%), the response time is within 3 ms, and the measurement error and peak error reach 0.052% and 0.127%. This configuration provides a novel option for the design and practical application of all-fiber optical current transformers. Full article

High penetration of renewable energy sources complicates static voltage stability assessment, as conventional line-based indices are typically derived under restrictive assumptions, such as neglecting voltage-angle differences or decoupling active and reactive power effects, which may lead to inaccurate proximity signals under RES-rich operating conditions. The proposed research study develops an enhanced voltage stability index (EVSI) from a two-port π line model that explicitly retains line impedance, active and reactive power terms, and voltage-angle difference between the sending and receiving ends; secure system operation satisfies EVSI < 1. Unlike classical indices, EVSI preserves the coupled physical interactions most relevant to voltage collapse while maintaining a closed-form structure suitable for online monitoring. EVSI is evaluated in a coupled transmission–distribution setting with solar photovoltaic-based distributed generation under varying penetration levels and loadings, using PV-curve nose points as collapse references, and benchmarked against classical indices. Across scenarios, EVSI remains closest to unity at the nose point, accurately tracing the collapse boundary and consistently identifying weak buses, whereas the traditional indices exhibit dispersed values and sensitivity to operating assumptions. The proposed results indicate that EVSI offers a reliable and computationally convenient indicator for online assessment and early warning of voltage instability in renewable-integrated, coupled transmission–distribution networks. Full article