Search Results (3,735)

Validated instruments assessing gender stereotype endorsement among adolescents are scarce and often overlook contemporary domains like digital privacy. To address this gap, this study developed and validated the Gender Stereotypes and Roles Adherence Battery for Adolescents (GAB-A) in a sample of 2955 Italian adolescents attending public secondary schools in Rome (56.4% male; mean age 14.3 years). The battery comprises three modules: the Gender Stereotyped Attitude Scale (GSAS), Gender Role Activities Scale (GRAS), and Gendered Traits Inventory (GTI). Psychometric analysis confirmed robust factor structures, notably identifying a distinct “Relational Control” factor within the GSAS that assesses beliefs normalizing partner surveillance. The results revealed a stark pattern of gender differentiation: males endorsed prescriptive attitudes (GSAS, d = 1.07) and roles (GRAS, d = 0.88) substantially more than females, particularly regarding violence myths. Conversely, essentialist trait beliefs (GTI) showed negligible gender differences (d = 0.11). Associations between stereotypes and psychological health were gender-moderated; within-group analyses indicated that endorsement predicted higher distress, hostility, and alexithymia in males, while being unrelated to well-being in females. Finally, gender-stratified normative data and operational cut-offs were established. The GAB-A provides a psychometrically sound tool for identifying elevated endorsement profiles and evaluating violence prevention interventions. Full article

Potassium-ion batteries hold great promise for large-scale energy storage, but their commercialization is hindered by the large ionic radius of potassium, which causes sluggish kinetics and severe volume expansion in anode materials. To address this, we present a scalable spray-drying strategy coupled with NaCl salt-templating to synthesize hierarchical porous carbon/vanadium sulfide microspheres (p-V₃S₄/C MS). In this structure, V₃S₄ nanoparticles are uniformly encapsulated within a dextrin-derived amorphous carbon matrix, and pores are formed via selective NaCl etching. This unique architecture accommodates volume fluctuations while providing rapid ion diffusion pathways. As a result, the p-V₃S₄/C MS anode exhibits outstanding electrochemical performance, maintaining a reversible capacity of 107 mA h g⁻¹ after 2000 cycles at 2.0 A g⁻¹, and achieves a high pseudocapacitive contribution of 93% at 2.0 mV s⁻¹. Furthermore, a full cell paired with a Prussian blue (PB) cathode demonstrates practical viability and robust reversibility. Our findings demonstrate that this structural engineering effectively mitigates internal resistance and structural degradation, offering a cost-effective route for mass-producing high-performance anodes for next-generation energy storage. Full article

Zinc-ion batteries have garnered significant research interest owing to their inherent safety, low cost, and environmental compatibility. Nevertheless, their widespread adoption is impeded by critical challenges including uncontrollable dendrite growth, parasitic side reactions stemming from active water molecules, and the corrosion of the zinc anode in conventional aqueous electrolytes. Herein, a hydrated deep eutectic solvent (HDES) electrolyte based on ZnSO₄, MnSO₄, and ethylene is proposed for high-performance zinc-ion batteries. This electrolyte demonstrates excellent stability and simultaneously enables the formation of a protective coating on the Zn anode surface. Spectroscopic analyses and theoretical simulations reveal that this electrolyte reconfigures the primary Zn²⁺ solvation shell by replacing water molecules with HDES components. This tailored solvation structure facilitates interfacial desolvation, elevates nucleation overpotential, and promotes uniform, dendrite-free zinc deposition. Simultaneously, a robust hydrogen bond network effectively sequesters free water, significantly suppressing the hydrogen evolution reaction and anode corrosion. Benefiting from these features, the HDES-based full cell delivers exceptional long-term stability, achieving over 2000 cycles at 3 mA cm⁻² with a capacity retention exceeding 95% and a Coulombic efficiency surpassing 85%. In sharp contrast, the traditional aqueous counterpart fails within only 200 cycles. This tenfold lifespan enhancement, coupled with cost-effectiveness and non-flammability, presents a promising strategy for advanced, grid-scale zinc-based energy storage. Full article

Electric vehicles (EVs) represent a key pathway toward reducing greenhouse gas emissions and fossil fuel dependence. Although significant advances have been achieved in energy storage technologies for EVs, a structured comparative assessment that jointly evaluates batteries, supercapacitors, and their hybridisation remains lacking. This review addresses that gap by systematically comparing lithium-ion, lead-acid, and nickel-based batteries with electrochemical double-layer capacitors (EDLCs), pseudocapacitors, and hybrid capacitors across ten performance and sustainability criteria. A literature-informed scoring framework, supplemented by sensitivity analysis under alternative weighting scenarios, is employed to rank the technologies. Particular attention is given to Hybrid Energy Storage Systems (HESS), which combine the high energy density of lithium-ion batteries with the high power density and long cycle life of supercapacitors. The review synthesises evidence that HESS can improve overall energy efficiency by up to 20% and extend battery lifetime by 30–50%, thereby reducing raw-material extraction, electronic waste, and lifecycle cost. Second-life pathways and circular-economy implications are discussed in depth. The findings demonstrate that neither batteries nor supercapacitors alone can satisfy the full spectrum of EV energy demands; instead, their integration within HESS offers the most balanced, sustainable, and economically viable solution. This work provides actionable insights for engineers, policymakers, and stakeholders engaged in next-generation sustainable mobility. Full article

The accelerating transition to low carbon energy systems has intensified the demand for nickel and cobalt from low-grade (<1.5 wt.%) refractory lateritic ores. These low-grade laterites are however not amenable to conventional beneficiation due to their complex mineralogy, eclectic physicochemical properties, and fine Ni–Co dissemination. This review examines recent advances made in the extraction of nickel and cobalt from complex low-grade lateritic ores, emphasizing the interplay between ore mineralogy, chemistry, beneficiation, pretreatment, and processing route selection. Developments in selective ore comminution–classification have led to the generation of Ni-rich fine fractions (undersize) and Co-rich coarse fractions (oversize), enabling differentiated extraction strategies that improve resource utilization, frugal energy use, and process efficiency. Mechanical activation via stirred media milling, thermal calcination-induced structural disorder, and dehydroxylate goethite products, are shown to significantly enhance Ni–Co leaching kinetics under both atmospheric and heap leaching conditions. A critical comparison of pyrometallurgical (rotary-kiln electric furnace) and hydrometallurgical (HPAL, EPAL, heap, atmospheric, bioleaching) routes demonstrates that ore-specific optimization is essential to balance recovery, acid consumption, and greenhouse gas emissions. The novel resin in moist mix (RIMM) process, which integrates ambient leaching and in situ ion exchange selective recovery, is shown to offer potential for sustainable values extraction from sub-economic resources. Furthermore, the review highlights the key innovation challenges and concomitant opportunities for enhanced critical battery metal recovery from complex laterite ores. Full article

With the continuous rise in the energy density of power batteries, battery heat generation has become an increasingly severe issue. Particularly under extreme conditions combining high summer temperatures and high discharge rates, battery thermal safety is facing tremendous challenges. To address this problem, this study proposes a honeycomb liquid cooling–PCM hybrid battery thermal management system (BTMS) based on fin–casing synergistic heat transfer enhancement. We analyzed the effects of the longitudinal fins and thermal conductive casing on the thermal characteristics of the system, further investigated the influence patterns of key factors including fin number, battery spacing and contact thermal resistance on the thermal performance of the honeycomb BTMS, and clarified the action mechanisms of each structure and parameter on battery temperature rise and temperature uniformity. The results show that the fin structure enhances longitudinal heat conduction, improves liquid cooling efficiency, and effectively reduces the maximum battery temperature, while the thermal conductive casing significantly improves battery temperature uniformity. The BTMS with fin–casing synergistic heat transfer enhancement can control the maximum battery temperature and temperature difference within 60 °C and 5 °C, respectively, under extreme operating conditions. Full article

The state of health (SOH) estimation of lithium-ion batteries faces significant challenges under complex operating conditions due to transient disturbances and distribution shifts. This paper proposes a deep learning framework named Conformer-KAN, which integrates a convolution-augmented Transformer (Conformer) with a Kolmogorov–Arnold Network (KAN). The method first constructs a unified input representation by fusing multi-view features including voltage, current, temperature, and incremental capacity. It then employs a Conformer encoder that combines gated local convolution units (GLCU) and multi-head self-attention (MHSA) to achieve joint modeling of local and global features. In addition, learnable spline-based activation functions are introduced within the KAN structure to enhance the model’s capacity for capturing complex nonlinear degradation behaviors. Cross-battery and cross-condition evaluations conducted on two public datasets demonstrate that the proposed method achieves root mean square errors (RMSE) of 0.006 ± 0.001 and 0.003 ± 0.001, and coefficients of determination (R²) of 0.987 ± 0.003 and 0.994 ± 0.002, respectively. These results show that Conformer-KAN significantly outperforms existing mainstream approaches in both robustness and generalization performance. Full article

Renewable Energy Communities (RECs) are recognized as effective collective models to accelerate decarbonization through shared renewable generation, consumption, and local flexibility provision. However, their large-scale deployment remains constrained by the temporal mismatch between variable renewable generation and strongly time-dependent demand, particularly in buildings where heating and cooling dominate final energy use. This state-of-the-art review provides an integrated and comparative assessment of Thermal Energy Storage (TES) and Battery Energy Storage Systems (BESS) within RECs, with explicit focus on power-to-heat (PtH) pathways and phase change material (PCM)-based cooling storage. Based on a structured analysis of the peer-reviewed literature published between 2015 and 2025, the review shows that TES represents a cost-effective and durable complement to electrochemical storage in heating- and cooling-dominated communities. Reported results indicate that TES integration can reduce peak electrical demand by 20–35%, increase local renewable self-consumption by 15–40%, and significantly lower required battery capacity in hybrid configurations. While BESS remains indispensable for short-term electrical balancing and fast-response grid services, TES offers lower costs per kWh stored, longer operational lifetimes (often exceeding 25–40 years), and lower lifecycle greenhouse gas emissions, typically 70–85% lower than those of BESS when thermal energy is used directly. Among TES technologies, PCM-based systems demonstrate particular effectiveness in cooling-dominated RECs, enabling peak cooling power reductions of up to 30% through diurnal load shifting. Across climatic contexts, the literature converges on hybrid TES–BESS architectures as the most robust storage solution, with reported reductions in grid imports and renewable curtailment of up to 35–40%. In addition, TES uniquely enables seasonal energy shifting, for which no cost-competitive electrochemical alternative currently exists. Despite these advantages, the review identifies persistent gaps related to the limited availability of long-term operational data and the need for empirical validation of hybrid control strategies. Future research should prioritize multi-year field demonstrations, advanced data-driven energy management, and policy frameworks that explicitly recognize thermal flexibility and sector coupling within Renewable Energy Communities. Full article

The integration of electric vehicles into microgrids demands advanced energy management to coordinate charging with renewable generation and storage resources. This study presents a cohesive and comprehensive evaluation of four distinct optimization strategies—genetic algorithm (GA), particle swarm optimization (PSO), ant colony optimization (ACO), and mixed-integer linear programming (MILP)—in coordinating EV charging and energy dispatch within a 55 MW grid-connected microgrid that includes photovoltaic, wind, battery energy storage (BESS), and bidirectional EV systems. Beyond numerical outcomes, this work emphasizes the behavioral and methodological characteristics of each optimization approach, assessing their structural advantages and resource utilization dynamics. A novel MILP solution algorithm is introduced, based on a hybrid branch-and-cut technique integrated with time decomposition, enabling the solver to capture long-horizon optimization dynamics with high precision. All four methods are applied over a year-long simulation with hourly resolution. While each strategy maintains operational feasibility and power balance, the MILP approach consistently achieves the highest economic benefit, delivering approximately $2.43 million in annual cost savings, representing roughly a 72.3% improvement over the best-performing heuristic strategy under the same deterministic operating conditions. GA, PSO, and ACO each capture moderate benefits but show limitations in foresight and storage cycling. The findings not only benchmark algorithmic performance but also provide insight into the internal logic and structural behavior of optimization techniques applied to dynamic energy systems, offering guidance for algorithm selection and design in microgrid EMS. Full article

High-speed solid particles ejected during battery thermal runaway pose severe safety threats, yet their velocity measurement is hindered by high density, microscopic size, and intense glare. This study proposes a non-intrusive velocimetry framework that integrates an enhanced single-stage object detector with a structural similarity matching algorithm. The detector incorporates specialized feature extraction modules and a high-resolution layer to identify microscopic targets in extreme environments, while the matching algorithm employs adaptive direction constraints to ensure precise trajectory tracking. Experimental validation demonstrates that the framework achieves a mean average precision of 92.7% and supports real-time processing. The method successfully quantifies a three-stage velocity evolution in battery failure events, identifying a peak particle speed exceeding 120 m/s. These findings provide critical kinematic data for optimizing battery safety structures and modeling fire propagation mechanisms. Full article

The future growth of alkali metal-based batteries requires an understanding of how ion size affects the exchange mechanisms. In this work, we present a direct, comparative electrochemical study of MXene-based electrodes mechanism vs. lithium (Li⁺), sodium (Na⁺), and potassium (K⁺) ions using the same electrochemical conditions. This controlled method enables an extensive investigation of the size-dependent interactions between the MXene structure and alkali metal ions. X-ray photoelectron spectroscopy and Raman analysis of TMAOH-treated Ti₃C₂T_x MXene electrodes show that delamination and cycling alter vibrational modes and the surface chemistry. Voltage profile study reveals diverse storage behaviors: Li⁺ has a prominent intercalation plateau, Na⁺ shows intermediate properties, and K⁺ displays sloping profiles, indicating surface-dominated adsorption. The significant correlation between ionic radius and electrochemical reversibility is shown by long-term cycling data over 300 cycles, which show greater capacity retention and stability for Li⁺ and progressively lower performance for Na⁺ and K⁺. These findings provide new mechanistic insights into MXene–ion interactions and build the foundation for developing MXene-based materials for specific alkali-ion chemistries in next-generation energy storage devices. Full article

This paper presents the design and experimental validation of a hardware-enforced charging profile selection framework for low-voltage electric all-terrain vehicles (ATVs), implemented on a programmable Delta battery charger operating within a voltage range of 0–120 V and a current range of 0–30 A. Unlike conventional programmable chargers that rely primarily on software-defined configuration or battery management system (BMS)-negotiated parameter setting, the proposed system enforces predefined constant-current–constant-voltage (CC–CV) charging profiles at the hardware execution layer. Vehicle identification is performed using CANopen-based identifiers, while relay-based selection, controlled via Modbus RTU, physically routes the charger output to fixed CC–CV control paths, thereby structurally reducing the risk of misconfiguration and unintended parameter changes. The system integrates layered control using embedded ESP32 nodes, a redPLC supervisory controller, and NodeRED-based orchestration, combined with real-time measurement, logging, and visualization using a time-series database and Grafana dashboards. Experimental validation is conducted using lithium-ion battery packs configured at four nominal voltage levels (24 V, 48 V, 60 V, and 72 V). The results confirm correct automatic profile selection, deterministic relay-based routing, and stable CC–CV charging behavior across repeated charging sessions. Rather than proposing a new charging algorithm, this work contributes a safety-by-design execution-layer charging architecture that complements higher-level smart charging and management protocols and is particularly suited for closed, heterogeneous fleet environments where deterministic behavior, robustness against configuration errors, and transparent verification of charging processes are critical. Full article

This study introduces and compares online rule-based and optimization-based energy management strategies for a mild hybrid electric vehicle, with their performance evaluated against an offline Dynamic Programming benchmark. A structured rule-based strategy is proposed to enforce engine operation along its optimal efficiency line, while the remaining power demand is balanced by the electric motor. To achieve charge-sustaining battery operation, a soft state of charge regulation mechanism is incorporated. An Equivalent Consumption Minimization Strategy (ECMS) is also developed using a precise formulation of battery equivalent fuel consumption computed from instantaneous engine and electric path efficiencies, instead of constant efficiencies used in the literature. DP, which provides a globally optimal solution over the entire driving cycle, is employed as a benchmark for assessing the rule-based and ECMS strategies. The control strategies are compared under charge-sustaining conditions, considering engine and motor operation characteristics, overall fuel consumption, and battery usage intensity. Furthermore, the influence of load shifting between the internal combustion engine and the electric motor on overall vehicle performance is analyzed. Fuel consumption decreases by 13.5% relative to the engine-only baseline with the proposed ECMS with precise equivalent fuel consumption, and DP yields an additional 1.6% benefit. Compared with the developed rule-based controller, ECMS nearly halves the battery usage intensity, and DP provides 3.1% further reduction relative to ECMS. Full article

To address the inherent limitations of Cu₂Se as a lithium-ion battery (LIB) anode, a Cu₂Se/MnSe@C composite was rationally designed and synthesized via selenization of a CuMn bimetallic metal–organic framework (MOF) precursor. This synthesis strategy integrates carbon composite engineering and heterogeneous structure construction, achieving in situ formation of Cu₂Se/MnSe heterogeneous nanoparticles anchored on amorphous carbon nanosheets. Structural characterizations confirm the successful construction of well-defined Cu₂Se/MnSe interfaces and uniform dispersion of selenide components, with Mn introduction inducing regulated electron transfer between Cu₂Se and MnSe. Electrochemical evaluations demonstrate that the Cu₂Se/MnSe@C composite exhibits a significantly enhanced lithium storage performance compared to single-component Cu₂Se@C, including higher specific capacity and superior rate capability. Mechanistic studies reveal that the synergistic effects of the carbon matrix (enhancing electrical conductivity and mitigating volume expansion) and the Cu₂Se/MnSe heterogeneous interface (lowering charge transfer resistance, accelerating Li⁺ diffusion, and boosting pseudocapacitive contribution) are responsible for the performance enhancement. Moreover, Cu₂Se/MnSe@C||LiFePO₄ full cells deliver a stable average operating voltage and reliable cycling stability, validating the composite’s practical application potential. Full article

Developing free-standing electrodes without the need of metal current collectors, binders, and conductive additives are essential for promoting the development of sodium-ion batteries (SIBs) to attain higher energy density. In this study, we developed and effectively synthesized a novel three-dimensional free-standing sodium-ion battery anode material with the composition of Bi@MoS₂@C carbon nanofibers by cleverly utilizing the energy storage advantages of each material. By growing MoS₂ nanospheres on Bi carbon nanofibers and coating them with a carbon layer, this free-standing system achieves both structural optimization and synergistic performance enhancement. Experimental results show that this composite electrode has a remarkably high initial specific capacity of 275.31 mA h g⁻¹ at a current density of 0.5 A g⁻¹, significantly exceeding that of Bi carbon nanofibers (150.6 mA h g⁻¹). Furthermore, it retains a capacity retention of 96.07% after 800 cycles, which significantly exceeds that of pristine MoS₂ (72.33 mA h g⁻¹) as a sodium-ion battery anode. The significant performance improvement originates from the free-standing structural design and synergistic effects of Bi carbon nanofibers, MoS₂ nanospheres and carbon layer, which not only provide 3D electron transport pathways and improved conductivity but also effectively accommodate volume changes during the charging and discharging processes. This work offers a promising and practical strategy for designing high-performance free-standing energy storage electrodes through hybrid mechanisms and synergistic effects. Full article