Search Results (1,570)

Fast charging accelerates lithium-ion battery operation but increases the risk of lithium (Li) plating—a process that undermines efficiency, longevity, and safety. Here, we introduce a predictive modeling framework that captures the onset and severity of Li plating under practical fast-charging conditions. By integrating an empirically parameterized SOC threshold model with time-dependent kinetic simulations and Arrhenius based thermal analysis, we delineate operating regimes prone to irreversible Li accumulation. The framework distinguishes reversible and irreversible plating fractions, quantifies energy losses, and identifies a critical activation energy (0.25 eV) associated with surface-limited deposition. Visualizations in the form of severity maps and voltage-zone risk classifications enable direct application to battery management systems. This approach bridges electrochemical degradation modeling with real-time charge protocol design, offering a practical tool for safe, high-performance battery operation. Full article

Future $e^{+}{e}^{-}$ colliders are expected to play a fundamental role in measuring Standard Model (SM) parameters with unprecedented precision and in probing physics beyond the SM (BSM). This study investigates two-particle angular correlation distributions involving final-state SM charged hadrons. Unexpected correlation structures in these distributions is considered to be a hint for new physics perturbing the QCD partonic cascade and thereby modifying azimuthal and (pseudo)rapidity correlations. Using Pythia8 Monte Carlo generator and fast simulation, including selection cuts and detector effects, we study potential structures in the two-particle angular correlation function. We adopt the QCD-like Hidden Valley (HV) scenario as implemented in Pythia8 generator, with relatively light HV v-quarks (below about 100 GeV), to illustrate the potential of this method. Full article

In recent years, 3D pixel sensors have been a topic of increasing interest within the High Energy Physics community. Due to their inherent radiation hardness, demonstrated up to a fluence of $3\times {10}^{16}$ 1 MeV equivalent neutrons per square centimeter, 3D pixel sensors have been used to equip the innermost tracking layers of the ATLAS and CMS detector upgrades at the High-Luminosity Large Hadron Collider. Additionally, the next generation of vertex detectors calls for precise measurement of charged particle timing at the pixel level. Owing to their fast response times, 3D sensors present themselves as a viable technology for these challenging applications. Nevertheless, both radiation hardness and fast timing require 3D sensors to be operated with high bias voltages on the order of ∼150 V and beyond. Special attention should therefore be devoted to avoiding problems that could cause premature electrical breakdown, which could limit sensor performance. In this paper, TCAD simulations are used to gain deep insight into the impact of surface isolation layers (i.e., p-stop and p-spray) used by different vendors on the high-voltage tolerance of small-pitch 3D sensors. Results relevant to different geometrical configurations and irradiation scenarios are presented. The advantages and disadvantages of the available technologies are discussed, offering guidance for design optimization. Experimentalmeasurements from existing samples based on both isolation techniques show good agreement with simulated breakdown voltages, thereby validating the simulation approach. Full article

A four-vector potential of an external test electromagnetic field in a Schwarzschild background is described in terms of a combination of dipole and quadrupole magnetic fields. This combination is an interior solution of the source-free Maxwell equations. Such external test magnetic fields cause the dynamics of charged particles around the black hole to be nonintegrable, and are mainly responsible for chaotic dynamics of charged particles. In addition to the external magnetic fields, some circumstances should be required for the onset of chaos. The effect of the magnetic fields on chaos is shown clearly through an explicit symplectic integrator and a fast Lyapunov indicator. The inclusion of the quadrupole magnetic fields easily induces chaos, compared with that of the dipole magnetic fields. This result is because the Lorentz forces from the quadrupole magnetic fields are larger than those from the dipole magnetic fields. In addition, the Lorentz forces act as attractive forces, which are helpful for bringing the occurrence of chaos in the nonintegrable case. Full article

We present a brief overview of the field of charge density waves (CDW) in condensed systems with focus set to the underlying mechanisms behind the CDW ground state. Our intention in this short review is not to count all related facts from the vast volume of literature about this decades-old and still developing field, but rather to pinpoint the most important, mostly theoretical ones, presenting the development of the field. Starting from the “early days”, mainly based on weakly coupled, chain-like quasi-1D systems and Peierls instability, in which the Fermi surface nesting has been the predominant and practically paradigmatic mechanism of the CDW ground state stabilisation, we track the change in paradigms while entering the field of layered quasi-2D systems, with Fermi surface far away from the nesting regime, in which rather strong, essentially momentum-dependent interactions and particular reconstructions of the Fermi surface become essential. Examples of real quasi-1D materials, such as organic and inorganic conductors like Bechgaard salts or transition metal trichalcogenides and bronzes, in which experiment and theory have been extremely successful in providing detailed understanding, are contrasted to layered quasi-2D materials, such as ${\mathrm{high-T}}_c$ superconducting cuprates, intercalated graphite compounds or transition metal dichalcogenides, for which the theory explaining an onset of the CDWs constitutes a frontier of this fast-evolving field, strongly boosted by development of modern ab initio calculation methods. Full article

Aggregation of tau protein is a hallmark feature of tauopathies such as Alzheimer’s disease. The microtubule-binding domain of tau plays a crucial role in the tau aggregation process. In this study, we investigated the dual effects of membrane interactions of tau_298–317, a fragment peptide from the microtubule-binding domain, on peptide-induced membrane disruption and membrane-mediated peptide self-assembly. Our results show that neither wild-type tau_298–317 nor its P301L or Ser305-phosphorylated mutants aggregate in the presence of zwitterionic POPC vesicles or cause lipid vesicle leakage, indicating weak peptide–membrane interactions. In contrast, tau_298–317 strongly interacts with negatively charged POPG liposomes, leading to a rapid transition of the peptide conformation from random coils to α-helical intermediate conformation upon membrane adsorption, which may further promote peptide self-association to form oligomers and β-sheet-rich fibrillar structures. Tau_298–317-induced rapid POPG membrane leakage indicates a synergistic process of the peptide self-assembly at the membrane interface and the aggregation-induced membrane disruption. Notably, phosphorylation at Ser305 disrupts favorable electrostatic interactions between the peptide and POPG membrane surface, thus preventing peptide aggregation and membrane leakage. In contrast, the P301L mutation significantly enhances membrane-mediated peptide aggregation and peptide-induced membrane disruption, likely due to alleviation of local conformational constraints and enhancement of local hydrophobicity, which facilitates fast conformational conversion to β-sheet structures. These findings provide mechanistic insights into the molecular mechanisms underlying membrane-mediated aggregation of crucial regions of tau and peptide-induced membrane damage, indicating potential strategies to prevent tau aggregation and membrane rupture by targeting critical electrostatic interactions between membranes and key local regions of tau. Full article

Titanium dioxide (TiO₂) is a benchmark photocatalyst for environmental applications, but its limited visible-light activity due to a wide band gap and fast charge recombination restricts its practical efficiency. This study presents the development of heterostructured Ag (Au)/MoS₂-TiO₂ inverse opal (IO) films that synergistically integrate photonic, plasmonic, and semiconducting functionalities to overcome these limitations. The materials were synthesized via a one-step evaporation-induced co-assembly approach, embedding MoS₂ nanosheets and plasmonic nanoparticles (Ag or Au) within a nanocrystalline TiO₂ photonic framework. The inverse opal architecture enhances light harvesting through slow-photon effects, while MoS₂ and plasmonic nanoparticles improve visible-light absorption and charge separation. By tuning the template sphere size, the photonic band gap was aligned with the TiO₂-MoS₂ absorption edge and the localized surface plasmon resonance of Ag, enabling optimal spectral overlap. The corresponding Ag/MoS₂-TiO₂ photonic films exhibited superior photocatalytic and photoelectrocatalytic degradation of tetracycline under visible light. Ultraviolet photoelectron spectroscopy and Mott–Schottky analysis confirmed favorable band alignment and Fermi level shifts that facilitate interfacial charge transfer. These results highlight the potential of integrated photonic–plasmonic-semiconductor architectures for efficient solar-driven water treatment. Full article

Organic nonvolatile transistor memories (ONVMs) using a hybrid spiro [fluorene-9,7′-dibenzo [c, h] acridine]-5′-one (SFDBAO)/polystyrene (PS) film as bulk-heterojunction-like tunneling and trapping elements were fabricated. From the characterization of the 10% SFDBAO/PS based on ONVM, a sterically hindered small-molecule SFDBAO with rigid orthogonal configuration and a donor–acceptor (D-A) structure as a molecular-scale charge storage element demonstrated significantly higher charge trapping ability than other small-molecule materials such as C₆₀ and Alq₃. The ONVM based on 10% SFDBAO/PS presents ambipolar memory behaviors with a wide memory window (146 V), a fast-switching speed (20 ms), an excellent retention time (over 5 × 10⁴ s), and stable reversibility (36 cycles without any noticeable decay). By applying different gate voltages, the above ONVM shows reliable four-level data storage characteristics. The investigation demonstrates that the strategical bulk-heterojunction-like tunneling and trapping elements composed of small-molecule materials and polymers exhibit promising potential for high-performance ambipolar ONVMs. Full article

In this paper, a detailed review of electric vehicle (EV) charging station architectures is first presented, and then an optimal architecture suitable for a large MW-scale EV fast-charging station (EVFS) with multiple fast chargers is proposed and evaluated. The study examines various EVFS architectures, including those currently deployed in commercial sites. Most EVFS implementations use either a common AC-bus or a common DC-bus configuration, with DC-bus architectures being slightly more predominant. The paper analyzes the EV charging and battery energy storage system (BESS) requirements for future large-scale EVFSs and identifies key implementation challenges associated with the full adoption of the common DC-bus approach. To overcome these limitations, a novel multi-zone EVFS architecture is proposed that employs an optimal combination of isolated and non-isolated DC-DC converter topologies while maintaining galvanic isolation for EVs. The system efficiency and total power converter capacity requirements of the proposed architecture are evaluated and compared with those of other EVFS models. A major feature of the proposed design is its multi-zone division and zonal isolation capabilities, which are not present in conventional EVFS architectures. These advantages are demonstrated through a scaled-up model consisting of 156 EV fast chargers. The analysis highlights the superior performance of the proposed multi-zone EVFS architecture in terms of efficiency, total power converter requirements, fault tolerance, and reduced grid impacts, making it the best solution for reliable and scalable MW-scale commercial EVFS systems of the future. Full article

To address the challenges of prolonged current isolation times and high dependency on varistors in traditional flexible short-circuit fault isolation schemes for DC systems, this paper proposes a rapid fault isolation circuit design based on an adaptive solid-state circuit breaker (SSCB). By introducing an adaptive current-limiting branch topology, the proposed solution reduces the risk of system oscillations induced by current-limiting inductors during normal operation and minimizes steady-state losses in the breaker. Upon fault occurrence, the current-limiting inductor is automatically activated to effectively suppress the transient current rise rate. An energy dissipation circuit (EDC) featuring a resistor as the primary energy absorber and an auxiliary varistor (MOV) for voltage clamping, alongside a snubber circuit, provides an independent path for inductor energy release after faults. This design significantly alleviates the impact of MOV capacity constraints on the fault isolation process compared to traditional schemes where the MOV is the primary energy sink. The proposed topology employs a symmetrical bridge structure compatible with both pole-to-pole and pole-to-ground fault scenarios. Parameter optimization ensures the IGBT voltage withstand capability and energy dissipation efficiency. Simulation and experimental results demonstrate that this scheme achieves fault isolation within 0.1 ms, reduces the maximum fault current-to-rated current ratio to 5.8, and exhibits significantly shorter isolation times compared to conventional approaches. This provides an effective solution for segment switches and tie switches in millisecond-level self-healing systems for both low-voltage (LVDC, e.g., 750 V/1500 V DC) and medium-voltage (MVDC, e.g., 10–35 kV DC) smart DC distribution grids, particularly in applications demanding ultra-fast fault isolation such as data centers, electric vehicle (EV) fast-charging parks, and shipboard power systems. Full article

A scheme of load frequency control (LFC) is proposed based on the deep deterministic policy gradient (DDPG) and active disturbance rejection control (ADRC) for multi-region interconnected power systems considering the renewable energy sources (RESs) and energy storage (ES). The dynamic models of multi-region interconnected power systems are analyzed, which provides a basis for the subsequent RES access. Superconducting magnetic energy storage (SMES) and capacitor energy storage (CES) are adopted due to their rapid response capabilities and fast charge–discharge characteristics. To stabilize the frequency fluctuation, a first-order ADRC is designed, utilizing the anti-perturbation estimation capability of the first-order ADRC to achieve effective control. In addition, the system states are estimated using a linear expansion state observer. Based on the output of the observer, the appropriate feedback control law is selected. The DDPG-ADRC parameter optimization model is constructed to adaptively adjust the control parameters of ADRC based on the target frequency deviation and power deviation. The actor and critic networks are continuously updated according to the actual system response to ensure stable system operation. Finally, the experiment demonstrated that the proposed method outperforms traditional methods across all performance indicators, particularly excelling in reducing adjustment time (45.8% decrease) and overshoot (60% reduction). Full article

The electric vehicle (EV) business model integrates advanced battery technology, dynamic power train architectures, and intelligent energy management systems with ecosystem strategies and digital services. It incorporates environmental sustainability through lifecycle analysis and renewable energy integration. China, with 9.49 million EV sales in 2023 (33% market share), faces infrastructure gaps constraining further growth. China is strategically mitigating CO₂ emissions while fostering economic expansion, notwithstanding constraints such as suboptimal battery technology advancements, elevated production expenditure, and enduring ecological impacts. This Political, Economic, Social, Technological, Legal, Environmental (PESTLE) assessment, operationalized through a survey of 800 stakeholders and Statistical Package for the Social Sciences IBM SPSS SPSS (Version 28) quantitative analysis (factor loading = 0.73 for Technology; eigenvalue = 4.12), identifies infrastructure gaps as the dominant barrier (72% of stakeholders). Political factors (β = 0.82) emerged as the strongest adoption predictor, outweighing economic subsidies in significance. The adoption of EVs in China presents a significant prospect for reducing CO₂ emissions and advancing technology. However, economic barriers, market dynamics, inadequate infrastructure, regulatory uncertainty, and social acceptance issues are addressed in the assessment. The study recommends prioritizing infrastructure investment (e.g., 500 K fast-charging stations by 2027) and policy stability to overcome adoption barriers. This study provides three key advances: (1) quantification of PESTLE factor weights via factor analysis, revealing technological (infrastructure) and political factors as dominant; (2) identification of infrastructure gaps, not subsidies, as the primary adoption barrier; and (3) demonstration of infrastructure’s persistence post-subsidy cuts. These insights redefine EV adoption priorities in China. Full article

This paper presents a hybrid fast charging strategy for static wireless power transfer (WPT) systems that synergistically combines pulsed current and multi-stage current (MCM) modes to enable rapid yet battery-health-conscious electric vehicle (EV) charging, thereby promoting sustainable transportation. The proposed approach employs a memetic algorithm (MA) to dynamically optimize the charging parameters, achieving an optimal balance between speed and battery longevity while maintaining 90.78% system efficiency at the SAE J2954-standard 85 kHz operating frequency. A neural-network-based state of charge (SOC) estimator provides accurate real-time monitoring, complemented by MA-tuned PI control for enhanced resonance stability and adaptive pulsed current–MCM profiles for the optimal energy transfer. Simulations and experimental validation demonstrate faster charging compared to that using the conventional constant current–constant voltage (CC-CV) methods while effectively preserving the battery’s state of health (SOH)—a critical advantage that reduces the environmental impact of frequent battery replacements and minimizes the carbon footprint associated with raw material extraction and battery manufacturing. By addressing both the technical challenges of high-power WPT systems and the ecological imperative of battery preservation, this research bridges the gap between fast charging requirements and sustainable EV adoption, offering a practical solution that aligns with global decarbonization goals through optimized resource utilization and an extended battery service life. Full article

Lithium-polymer (LiPo) batteries are valued for their high energy density, stable voltage output, low self-discharge, and strong reliability, making them a popular choice for high-performance and portable applications. Despite these advantages, the charging behavior of LiPo batteries—especially during rapid charging—remains an area with limited understanding. This research examines the electro-thermal characteristics of VARTA LiPo batteries when subjected to high charging currents (2C, 3C, and 4C rates). A temperature-sensitive charging model is developed to address safety and efficiency concerns during fast charging. Experimental data indicate that charging at 45 °C yields the best performance, achieving 80% state of charge (SoC) within 25 min. However, charging at temperatures above or below this level (such as 25 °C) reduces efficiency due to increased internal resistance and accelerated battery aging. The model, validated across a range of temperatures (25 °C, 35 °C, 45 °C, and 60 °C), shows that longer constant-current (CC) charging phases at higher temperatures are associated with lower internal resistance. These results highlight the importance of effective thermal management for optimizing both safety and performance in LiPo battery applications. Full article

California’s SB 1014 (Clean Miles Standard) mandates ridehailing fleet electrification to reduce emissions from vehicle miles traveled, posing financial and infrastructure challenges for drivers. This study employs a mixed-methods approach, including expert interviews (n = 10), group discussions (n = 8), and a survey of full- and part-time drivers (n = 436), to examine electric vehicle (EV) adoption attitudes and policy preferences. Access to home charging and prior EV experience emerged as the most statistically significant predictors of EV acquisition. Socio-demographic variables, particularly income and age, could also influence the EV choice and sensitivity to policy design. Full-time drivers, though confident in the EV range, were concerned about income loss from the charging downtime and access to urban fast chargers. They showed a greater interest in EVs than part-time drivers and favored an income-based instant rebate at the point of sale. In contrast, part-time drivers showed greater hesitancy and were more responsive to vehicle purchase discounts (price reductions or instant rebates at the point of sale available to all customers) and charging credits (monetary incentive or prepaid allowance to offset the cost of EV charging equipment). Policymakers might target low-income full-time drivers with greater price reductions and offer charging credits (USD 500 to USD 1500) to part-time drivers needing operational and infrastructure support. Full article