Search Results (205)

Given the increases in renewable energy penetration, appropriately allocating transmission costs is important in generation and transmission investment decisions. This study examines how a generator-side transmission charge affects investment decisions by power generation companies (PC) and the transmission system operator (TSO) under two frameworks differing in who decides investment timing. We compare two frameworks: (1) TSO determines investment timing and the PC determines capacity (TL framework); (2) PC determines investment timing and capacity (GL framework). We examine how variations in generator-side charges and demand uncertainty affect the optimal investment timing, capacity, and social surplus. Regarding investment timing, increases in the generator-side charge led to earlier investment in the TL framework but delayed investment in the GL framework. Concerning investment capacity, the TL framework yielded greater capacity with low uncertainty, while the GL framework supported greater capacity with high uncertainty. The magnitude of the relative social surplus of the two frameworks was reversed according to the generator-side charge and uncertainty. Specifically, the GL framework became increasingly superior to the TL framework as uncertainty increased, and this advantage was amplified by a higher generator-side charge. Policymakers should consider uncertainty and calibrate the level of generator-side charge and the allocation of decision-making authority. Full article

Glancing Angle Deposition (GLAD) has emerged as a versatile and powerful nanofabrication technique for developing next-generation gas sensors by enabling precise control over nanostructure geometry, porosity, and material composition. Through dynamic substrate tilting and rotation, GLAD facilitates the fabrication of highly porous, anisotropic nanostructures, such as aligned, tilted, zigzag, helical, and multilayered nanorods, with tunable surface area and diffusion pathways optimized for gas detection. This review provides a comprehensive synthesis of recent advances in GLAD-based gas sensor design, focusing on how structural engineering and material integration converge to enhance sensor performance. Key materials strategies include the construction of heterojunctions and core–shell architectures, controlled doping, and nanoparticle decoration using noble metals or metal oxides to amplify charge transfer, catalytic activity, and redox responsiveness. GLAD-fabricated nanostructures have been effectively deployed across multiple gas sensing modalities, including resistive, capacitive, piezoelectric, and optical platforms, where their high aspect ratios, tailored porosity, and defect-rich surfaces facilitate enhanced gas adsorption kinetics and efficient signal transduction. These devices exhibit high sensitivity and selectivity toward a range of analytes, including NO₂, CO, H₂S, and volatile organic compounds (VOCs), with detection limits often reaching the parts-per-billion level. Emerging innovations, such as photo-assisted sensing and integration with artificial intelligence for data analysis and pattern recognition, further extend the capabilities of GLAD-based systems for multifunctional, real-time, and adaptive sensing. Finally, current challenges and future research directions are discussed, emphasizing the promise of GLAD as a scalable platform for next-generation gas sensing technologies. Full article

A battery charger for solid-state lithium battery packs was developed and implemented. The power stage used a phase-shifted full-bridge converter integrated with a current-doubler rectifier and synchronous rectification. Dual voltage and current control loops were employed to enable constant-voltage and constant-current charging modes. To improve the lifespan of the output filter capacitor, the current-doubler rectifier was adopted to effectively reduce output current ripple. During the initial start-up phase, as the charger transitions from constant-voltage to constant-current output mode, the use of proportional–integral control in the voltage and current loop error amplifiers may cause current overshoot during the step-rising phase, primarily due to the integral action. Therefore, this study incorporated fuzzy control, proportional control, and proportional–integral control strategies into the current-loop error amplifier. This approach effectively reduced the current overshoot during the step-rising phase, preventing the charger from mistakenly triggering the overcurrent protection mode. The analysis and design considerations of the proposed circuit topology and control loop are presented. Experimental results agree with theoretical predictions, thereby confirming the validity of the proposed approach. Full article

This paper presents a low-power data acquisition (DAQ) chip tailored for impulsive charge sensing, featuring a comparator-gated dynamic acquisition (CG-DAQ) architecture. A dynamic comparator triggers both the gain stage and a 12-bit successive-approximation register (SAR) analog-to-digital converter (ADC) through a shared timing path, enabling event-driven amplification and digitization. Programmable conversion gain ranging from 5 to 40 mV/pC is achieved by switching the sampling capacitance. Fabricated in TSMC 65 nm CMOS, the chip detects input charges from 0.01 to 36 pC, supports a signal bandwidth of 10 kHz to 100 kHz, and enables sampling rates up to 1 MS/s. It achieves an input-referred noise of 5.5 fC_rms and a peak signal-to-noise ratio (SNR) of 67 dB, all within a 54 μW power envelope and a compact 0.03 mm² core area. The proposed architecture facilitates accurate and energy-efficient charge-domain sensing for capacitive and piezoelectric sensor applications. Full article

In high-precision Hemispherical Resonator Gyroscope (HRG) control systems, readout circuit noise critically determines resonator displacement detection precision. Addressing noise issues, this paper compares the noise characteristics and contribution mechanisms of the Transimpedance Amplifier (TIA) and Charge-Sensitive Amplifier (CSA). By establishing a noise model and analyzing circuit bandwidth, the dominant role of feedback resistor thermal noise in the TIA is revealed. These analyses further demonstrate the significant suppression of high-frequency noise by the CSA capacitive feedback network. Simulation and experimental results demonstrate that the measured noise of the TIA and CSA is consistent with the theoretical model. The TIA output noise is 25.8 $\mathsf{\mu }{V}_{\mathrm{rms}}$, with feedback resistor thermal noise accounting for 99.8%, while CSA output noise is reduced to 13.2 $\mathsf{\mu }{V}_{\mathrm{rms}}$, a reduction of 48.8%. Near resonant frequency, the equivalent displacement noise of the CSA is $1.69\times {10}^{-14}\mathrm{m}/\sqrt{\mathrm{Hz}}$, a reduction of 86.7% compared to the TIA’s $1.27\times {10}^{-13}\mathrm{m}/\sqrt{\mathrm{Hz}}$, indicating the CSA is more suitable for high-precision applications. This research provides theoretical guidance and technical references for the topological selection and parameter design of HRG readout circuits. Full article

Memristive elements, known as memristors, memcapacitors and meminductors, have become an important topic of research in the electronics world in recent years. As there is still no efficient way to manufacture two-terminal memristive elements, many researchers have focused their efforts on designing emulator circuits that mimic these devices. In this study, a memcapacitor emulator circuit using Current Derivative Buffered Amplifier (CDBA) is proposed, which has significant advantages such as wide dynamic range, differential structure at the input port, high sloping rate and wide bandwidth. The main advantages of the emulator are that it is floating without grounding constraint, it is electronically adjustable, it has charge-controlled incremental and decremental modes and it has a simpler circuit structure since it does not contain a memristor. To ensure the integrity of the circuit theory, the results of the mathematical model and the simulation of the memcapacitor are given together. In addition, the characteristics of the experimentally investigated memcapacitor emulator are in good agreement with the simulation results. To provide an illustration of the performance of the proposed emulator, firstly the second-order active low-pass filter circuit and subsequently the amoeba learning circuit are selected as the working environment. The results show that the filtering performance of the proposed emulator at a value after the cut-off frequency in the filter circuit is $25\%$ more efficient than a standard capacitor and in terms of power consumption, it consumes $27.93\%$ less power than a standard capacitor. Moreover, the emulator successfully accomplishes the learning and data storage tasks in the amoeba learning circuit. Full article

In this paper, a high-voltage chopper and ping-pong auto-zeroing operational amplifier was designed for industrial and automotive applications. Based on chopper stabilization, the proposed circuit introduces a novel chopper switch control signal that varies with the input common-mode voltage. This scheme effectively suppresses the reference offset caused by the chopper switches and prevents transistor breakdown under high-voltage conditions. Additionally, the ping-pong auto-zero structure was optimized by employing a six-channel parallel first-stage amplifier, which further reduced the charge injection and ripple introduced by the chopper switches. The amplifier was implemented using an SMIC (Semiconductor Manufacturing International Corporation) 180 nm 1P5M BCD (Bipolar-CMOS-DMOS) process with a chip area of 4.211 mm². The post-layout simulation results show that, under a 55 V supply, the amplifier achieves an input-referred noise Power Spectral Density (PSD) of 6.2 $\mathrm{nV}/\sqrt{\mathrm{Hz}}$ and an input offset voltage of 32 $\mu \mathrm{V}$, while the output voltage swings from 0.2 V to 53.4 V with a unity gain bandwidth of 3.2 MHz, which meets the requirements for high-voltage, high-resolution signal processing. Full article

Food spoilage caused by microbial contamination remains a global challenge, driving demand for sustainable antibacterial packaging. Conventional photocatalytic materials suffer from limited spectral response, rapid charge recombination, and insufficient reactive oxygen species (ROS) generation under visible light. Here, a Z-scheme heterojunction was constructed by coupling zeolitic imidazolate framework-8 (ZIF-8) with Ag₃PO₄, achieving dual-spectral absorption and spatial charge separation. The directional electron transfer from Ag₃PO₄’s conduction band to ZIF-8 effectively suppresses electron-hole recombination, prolonging carrier lifetimes and amplifying ROS production (·O₂⁻/·OH). Synergy with Ag⁺ release further enhances bactericidal efficacy. Incorporated into a cellulose acetate matrix (CAM), the ZIF-8/Ag₃PO₄/CAM film demonstrates 99.06% antibacterial efficiency against meat surface microbiota under simulated sunlight, alongside high transparency. This study proposes a Z-scheme heterojunction strategy to maximize ROS generation efficiency and demonstrates a scalable fabrication approach for active food packaging materials, effectively targeting microbial contamination control and shelf-life prolongation. Full article

The paper explores the pressing issue of energy consumption in machine learning (ML) models and their environmental footprint. As ML technologies, especially large-scale models, continue to surge in popularity, their escalating energy demands and corresponding CO₂ emissions are drawing critical attention. The article dives into innovative strategies to curb energy use in ML applications without compromising—and often even enhancing—model performance. Key techniques, such as model compression, pruning, quantization, and cutting-edge hardware design, take center stage in the discussion. Beyond operational energy use, the paper spotlights a pivotal yet often overlooked factor: the substantial emissions tied to the production of ML hardware. In many cases, these emissions eclipse those from operational activities, underscoring the immense potential of optimizing manufacturing processes to drive meaningful environmental impact. The narrative reinforces the urgency of relentless advancements in energy efficiency across the IT sector, with machine learning and data science leading the charge. Furthermore, deploying ML to streamline energy use in other domains like industry and transportation amplifies these benefits, creating a ripple effect of positive environmental outcomes. The paper culminates in a compelling call to action: adopt a dual-pronged strategy that tackles both operational energy efficiency and the carbon intensity of hardware production. By embracing this holistic approach, the artificial intelligence (AI) sector can play a transformative role in global sustainability efforts, slashing its carbon footprint and driving momentum toward a greener future. Full article

Maritime safety is crucial as vessels underpin global trade, but engine room explosions threaten crew safety, the environment, and assets. With modern ship designs growing more complex, numerical simulation has become vital for analyzing and preventing such events. This study examines safety risks from alternative fuel explosions in ship engine rooms, using the Trinitrotoluene (TNT)-equivalent method. A finite element model of a double-layer cabin explosion is developed, and simulations using blastFOAM in OpenFOAM v9 analyze shock wave propagation and stress distribution. Four explosion locations and five scales were tested, revealing that explosion scale is the most influential factor on shock wave intensity and structural stress, followed by equipment layout, with location having the least—though still notable—impact. Near the control room, an initial explosion caused a peak overpressure of 2.4 × 10⁶ Pa. Increasing the charge mass from 10 kg to 50 kg raised overpressure to 3.9 × 10⁶ Pa, showing strong dependence of blast intensity on explosive mass. Equipment absorbs and reflects shock waves, amplifying localized stresses. The findings aid in optimizing engine room layouts and improving explosion resistance, particularly for alternative fuels like liquefied natural gas (LNG), enhancing maritime safety and sustainability. Full article

The growing deployment of photovoltaic (PV) and energy storage systems (ESSs) in power grids has amplified concerns over component degradation, which undermines efficiency, increases costs, and shortens system lifespan. This paper proposes a quantum-enhanced optimization framework to mitigate degradation impacts in PV–storage systems through real-time adaptive energy dispatch. The framework combines quantum-assisted Monte Carlo simulation, quantum annealing, and reinforcement learning to model and optimize degradation pathways. A predictive maintenance module proactively adjusts charge–discharge cycles based on probabilistic forecasts of degradation states, improving resilience and operational efficiency. A hierarchical structure enables real-time degradation assessment, hourly dispatch optimization, and weekly long-term adjustments. The model is validated on a 5 MW PV array with a 2.5 MWh lithium-ion battery using real degradation profiles. Results demonstrate that the proposed framework reduces battery wear by 25% and extends PV module lifespan by approximately 2.5 years compared to classical methods. The hybrid quantum–classical implementation achieves scalable optimization under uncertainty, enabling faster convergence across high-dimensional solution spaces. This study introduces a novel paradigm in degradation-aware energy management, highlighting the potential of quantum computing to enhance both the sustainability and real-time control of renewable energy systems. Full article

In the N$\nu$DEx collaboration, a high-pressure gas TPC is being developed to search for the neutrinoless double beta decay. The use of electronegative ⁸²SeF₆ gas mandates an ion-TPC. The reconstruction of the z coordinate is to be realized by exploiting the feature of multiple species of charge carriers. As the initial stage of the development, we studied the properties of the ${\mathrm{SF}}_6$ gas, which is non-toxic and has a similar molecular structure to ${\mathrm{SeF}}_6$. In the paper, we present the measurement of drift velocities and mobilities of the majority and minority negative charge carriers found in ${\mathrm{SF}}_6$ at a pressure of 750 Torr, slightly higher than the local atmospheric pressure. The reduced fields range between 3.0 and 5.5 Td. This was performed using a laser beam to ionize the gas inside a small TPC, with a drift length of 3.7 cm. A customized charge-sensitive amplifier was developed to read out the anode signals induced by the slowly drifting ions. The closure test of the reconstruction of the z coordinate using the difference in the velocities of the two carriers was also demonstrated. Full article

Pd-WO₃ coatings on porous silicon (PSi) substrates are engineered to enhance interfacial charge transfer and surface reactivity through atomic-scale structural tailoring. This study combines first-principles calculations and experimental characterization to elucidate how Pd nanoparticles (NPs) optimize the coating’s electronic structure and environmental stability. The hierarchical PSi framework with uniform nanopores (200–500 nm) serves as a robust substrate for WO₃ nanorod growth (50–100 nm diameter), while Pd decoration (15%–20% surface coverage) strengthens Pd–O–W interfacial bonds, amplifying electron density at the Fermi level by 2.22-fold. Systematic computational analysis reveals that Pd-induced d-p orbital hybridization near the Fermi level (−2 to +1 eV) enhances charge delocalization, optimizing interfacial charge transfer. Experimentally, these modifications enhance the coating’s response to environmental degradation, showing less than 3% performance decay over 30 days under cyclic humidity (45 ± 3% RH). Although designed for gas sensing, the coating’s high surface-to-volume ratio and delocalized charge transport channels demonstrate broader applicability in catalytic and high-stress environments. This work provides a paradigm for designing multifunctional coatings through synergistic interface engineering. Full article

Timing measurements are critical for the detectors at the future HL-LHC, to resolve reconstruction ambiguity when the number of simultaneous interactions reaches up to 200 per bunch crossing. The ATLAS collaboration therefore builds a new High-Granularity Timing detector for the forward region. A customized ASIC, called ALTIROC, has been developed, to read out fast signals from low-gain avalanche detectors (LGADs), which has 50 ps time-resolution for signals from minimum-ionizing particles. To meet these requirements, a custom-designed pre-amplifier, a discriminator, and TDC circuits with minimal jitter have been implemented in a series of prototype ASICs. The latest version, ALTIROC3, is designed to contain full functionality. Hybrid assemblies with ALTIROC3 ASICs and LGAD sensors have been characterized with charged-particle beams at CERN-SPS and with laser-light injection. The time-jitter contributions of the sensor, pre-amplifier, discriminator, TDC, and digital readout are evaluated. Full article

In this study, we demonstrate that the Sn₂Se₂P₄ monolayer exhibits intrinsic anisotropic electronic characteristics with the strain-synergistic modulation of carrier transport and optoelectronic properties, as revealed by various levels of density functional theory calculations combined with the non-equilibrium Green’s function method. The calculations reveal that a-axis uniaxial compression of the Sn₂Se₂P₄ monolayer induces an indirect-to-direct bandgap transition (from 1.73 eV to 0.97 eV, as calculated by HSE06), reduces the hole effective mass by ≥70%, and amplifies current density by 684%. Conversely, a-axis uniaxial expansion (+8%) boosts ballistic transport (a/b-axis current ratio > 10⁵), rivaling black phosphorus. Notably, a striking negative differential conductance arises with the maximum I_peak/I_valley in the order of 10⁵ under the 2% uniaxial compression along the b-axis of the Sn₂Se₂P₄ monolayer. Visible-range anisotropic absorption coefficients (~10⁵ cm⁻¹) are achieved, where −4% a-axis strain elevates the photocurrent density (6.27 μA mm⁻² at 2.45 eV) and external quantum efficiency (39.2%) beyond many 2D materials benchmarks. Non-monotonic strain-dependent photocurrent density peaks at 2.00 eV correlate with hole effective mass reduction patterns, confirming the carrier mobility of the Sn₂Se₂P₄ monolayer as the governing parameter for photogenerated charge separation. These results establish Sn₂Se₂P₄ as a multifunctional material enabling strain-tailored anisotropy for logic transistors, negative differential resistors, and photovoltaic devices, while guiding future investigations on environmental stabilization and heterostructure integration toward practical applications. Full article