Search Results (2,900)

A virtual power system stabilizer (PSS) adaptive damping control strategy based on a supercapacitor is used to suppress oscillations in a ship microgrid. The energy transmission path of the proposed strategy is to apply the equivalent damping power to the rotor by varying the electromagnetic power of the generator. Compared with conventional PSSs based on supercapacitors, storage devices not only enhance the capacity of damping power injected into the microgrid but also have more flexible configurations applicable to the size constraints of the ship microgrid. In addition, the adaptive control ensures that the DC bus voltage of the converter of the energy storage device is controlled within the neighborhood of the steady-state operating point, ensuring the asymptotic stability of the damping system. Finally, an experimental platform was built to verify the correctness and validity of the above theory. Full article

This paper focuses on power grid integration of wave energy converter (WEC) arrays that minimize added energy storage for maximizing power capture as well as smoothing the oscillatory power inputs into the grid. In particular, a linear right circular cylinder WEC array that implements complex conjugate control is compared and contrasted to a nonlinear WEC array that implements an hourglass buoy shape while both are integrated into the grid utilizing phase control (i.e., relative spacing of the WEC array) on the input powers to the grid. The Hamiltonians of the two WEC systems are derived, enabling a direct comparison of real and reactive power, with reactive power reflecting the utilization of stored energy. The control systems are simulated in MATLAB/Simulink under both regular wave conditions and irregular seas generated from a Bretschneider spectrum. For the linear right circular cylinder buoy, the proportional-derivative complex conjugate controller requires an external energy storage device to supply reactive power, whereas the nonlinear hourglass buoy inherently provides reactive power through its geometric design. This study demonstrates that: (i) The unique geometry of the hourglass buoy reduces the required energy storage size for the nonlinear system while simultaneously increasing power output. (ii) Phase control of the hexagonal hourglass array further enhances real power capture. Together, these effects substantially decrease the size and demand on the individual buoys and grid integration energy storage requirements. Full article

The field of electrochemical devices, encompassing energy storage, fuel cells, electrolysis, and sensing, is fundamentally reliant on the electrode materials that govern their performance, efficiency, and sustainability. Traditional materials, while foundational, often face limitations such as restricted reaction kinetics, structural deterioration, and dependence on costly or scarce elements, driving the need for continuous innovation. Emerging electrode materials are designed to overcome these challenges by delivering enhanced reaction activity, superior mechanical robustness, accelerated ion diffusion kinetics, and improved economic feasibility. In energy storage, for example, the shift from conventional graphite in lithium-ion batteries has led to the exploration of silicon-based anodes, offering a theoretical capacity more than tenfold higher despite the challenge of massive volume expansion, which is being mitigated through nanostructuring and carbon composites. Simultaneously, the rise of sodium-ion batteries, appealing due to sodium’s abundance, necessitates materials like hard carbon for the anode, as sodium’s larger ionic radius prevents efficient intercalation into graphite. In electrocatalysis, the high cost of platinum in fuel cells is being addressed by developing Platinum-Group-Metal-free (PGM-free) catalysts like metal–nitrogen–carbon (M-N-C) materials for the oxygen reduction reaction (ORR). Similarly, for the oxygen evolution reaction (OER) in water electrolysis, cost-effective alternatives such as nickel–iron hydroxides are replacing iridium and ruthenium oxides in alkaline environments. Furthermore, advancements in materials architecture, such as MXenes—two-dimensional transition metal carbides with metallic conductivity and high volumetric capacitance—and Single-Atom Catalysts (SACs)—which maximize metal utilization—are paving the way for significantly improved supercapacitor and catalytic performance. While significant progress has been made, challenges related to fundamental understanding, long-term stability, and the scalability of lab-based synthesis methods remain paramount for widespread commercial deployment. The future trajectory involves rational design leveraging advanced characterization, computational modeling, and machine learning to achieve holistic, system-level optimization for sustainable, next-generation electrochemical devices. Full article

With the fast development of the 5G technology and IoV, a vehicle has become a smart device with communication, computing, and storage capabilities. However, the limited on-board storage and computing resources often cause large latency for task processing and result in degradation of system QoS as well as user QoE. In the meantime, to build the environmentally harmonious transportation system and green city, the energy consumption of data processing has become a new concern in vehicles. Moreover, due to the fast movement of IoV, traditional GSI-based methods face the dilemma of information uncertainty and are no longer applicable. To address these challenges, we propose a T2VC model. To deal with information uncertainty and dynamic offloading due to the mobility of vehicles, we propose a MAB-based QEVA-UCB solution to minimize the system cost expressed as the sum of weighted latency and power consumption. QEVA-UCB takes into account several related factors such as the task property, task arrival queue, offloading decision as well as the vehicle mobility, and selects the optimal location for offloading tasks to minimize the system cost with latency energy awareness and conflict awareness. Extensive simulations verify that, compared with other benchmark methods, our approach can learn and make the task offloading decision faster and more accurately for both latency-sensitive and energy-sensitive vehicle users. Moreover, it has superior performance in terms of system cost and learning regret. Full article

Large-scale storage solutions play a critical role in the ongoing energy transition, with Underground Hydrogen Storage (UHS) emerging as a possible option. UHS can benefit from existing natural gas storage expertise; however, key differences in hydrogen’s behavior compared to CH₄ must be characterized at the pore scale to optimize the design and the management of these systems. This work investigates two-phase (gas–water) flow behavior using microfluidic devices mimicking reservoir rocks’ pore structure. Microfluidic tests provide a systematic side-by-side comparison of H₂–water and CH₄–water displacement under the same pore-network geometries, wettability, and flow conditions, focusing on the drainage phase. While all experiments fall within the transitional flow regime between capillary and viscous fingering, clear quantitative differences between H₂ and CH₄ emerge. Indeed, the results show that hydrogen’s lower viscosity enhances capillary fingering and snap-off events, while methane exhibits more stable viscous-dominated behavior. Both gases show rapid breakthrough; however, H₂’s flow instability—especially at low capillary numbers (Ca)—leads to spontaneous water imbibition, suggesting stronger capillary forces. Relative permeability endpoints are evaluated when steady state conditions are reached: they show dependence on Ca, not just saturation, aligning with recent scaling laws. Despite H₂ showing a different displacement regime, closer to capillary fingering, H₂ mobility remains comparable to CH₄. These findings highlight differences in flow behavior between H₂ and CH₄, emphasizing the need for tailored strategies for UHS to manage trapping and optimize recovery. Full article

Nanoparticle-mediated photothermal conversion exploits the unique light-to-heat transduction properties of engineered nanomaterials to address challenges in energy, water, and healthcare. This review first examines fundamental mechanisms—localized surface plasmon resonance (LSPR) in plasmonic metals and broadband interband transitions in semiconductors—demonstrating how tailored nanoparticle compositions can achieve >96% absorption across 250–2500 nm and photothermal efficiencies exceeding 98% under one-sun illumination (1000 W·m⁻², AM 1.5G). Next, we highlight advances in solar steam generation and desalination: floating photothermal receivers on carbonized wood or hydrogels reach >95% efficiency in solar-to-vapor conversion and >2 kg·m⁻²·h⁻¹ evaporation rates; three-dimensional architectures recapture diffuse flux and ambient heat; and full-spectrum nanofluids (LaB₆, Au colloids) extend photothermal harvesting into portable, scalable designs. We then survey photothermal-enhanced thermal energy storage: metal-oxide–paraffin composites, core–shell phase-change material (PCM) nanocapsules, and MXene– polyethylene glycol—PEG—aerogels deliver >85% solar charging efficiencies, reduce supercooling, and improve thermal conductivity. In biomedicine, gold nanoshells, nanorods, and transition-metal dichalcogenide (TMDC) nanosheets enable deep-tissue photothermal therapy (PTT) with imaging guidance, achieving >94% tumor ablation in preclinical and pilot clinical studies. Multifunctional constructs combine PTT with chemotherapy, immunotherapy, or gene regulation, yielding synergistic tumor eradication and durable immune responses. Finally, we explore emerging opto-thermal nanobiosystems—light-triggered gene silencing in microalgae and poly(N-isopropylacrylamide) (PNIPAM)–gold nanoparticle (AuNP) membranes for microfluidic photothermal filtration and control—demonstrating how nanoscale heating enables remote, reversible biological and fluidic functions. We conclude by discussing challenges in scalable nanoparticle synthesis, stability, and integration, and outline future directions: multicomponent high-entropy alloys, modular photothermal–PCM devices, and opto-thermal control in synthetic biology. These interdisciplinary innovations promise sustainable solutions for global energy, water, and healthcare demands. Full article

Rechargeable lithium-, sodium-, and potassium-ion batteries are utilized as essential energy storage devices for portable electronics, electric vehicles, and large-scale energy storage systems. In these systems, anode materials play a vital role in determining energy density, cycling stability, and safety of various batteries. However, the complex electrochemical reactions and dynamic changes that occur in anode materials during charge–discharge cycles generate major challenges for performance optimization and understanding failure mechanisms. In situ characterization techniques, capable of real-time tracking of microstructures, composition, and interface dynamics under operating conditions, provide critical insights that bridge macroscopic performance and microscopic mechanisms of anodes. This review systematically summarizes the applications of such techniques in studying anodes for lithium-, sodium-, and potassium-ion batteries, with a focus on their contributions across different anode types. It also indicates current challenges and future directions of these techniques, aiming to offer valuable references for relevant applications and the design of high-performance anodes. Full article

LoRaWAN is widely used for IoT environmental monitoring, but its lightweight security mechanisms leave the physical layer vulnerable to availability attacks such as jamming and battery-depletion. These risks are particularly critical in mission-critical environmental monitoring systems. This paper proposes a multi-attribute physical-layer authentication (PLA) framework that supports uplink legitimacy assessment by jointly exploiting radio, energy, and temporal attributes, specifically RSSI, altitude, battery_level, battery_drop_speed, event_step, and time_rank. Using publicly available Brno LoRaWAN traces, we construct a device-aware semi-synthetic dataset comprising 230,296 records from 1921 devices over 13.68 days, augmented with energy, spatial, and temporal attributes and injected with controlled jamming and battery-depletion anomalies. Five classifiers (Random Forest, Multi-Layer Perceptron, XGBoost, Logistic Regression, and K-Nearest Neighbours) are evaluated using accuracy, precision, recall, F1-score, and AUC-ROC. The Multi-Layer Perceptron achieves the strongest detection performance (F1-score = 0.8260, AUC-ROC = 0.8953), with Random Forest performing comparably. Deployment-oriented computational profiling shows that lightweight models such as Logistic Regression and the MLP achieve near-instantaneous prediction latency (below 2 µs per sample) with minimal CPU overhead, while tree-based models incur higher training and storage costs but remain feasible for Network Server-side deployment. Full article

With the rapid development of the Internet of Things (IoT), micro-energy storage devices face increasing demands for miniaturization, high energy density, and high power density. Owing to their excellent electrical conductivity and mechanical strength, TiN thin films are promising candidates for micro-supercapacitor electrodes. In this work, TiN thin films were prepared by direct current magnetron sputtering under different N₂/Ar flow ratios. The effects of the N₂/Ar flow ratio on the crystal structure, surface morphology, roughness, and electrochemical capacitive performance of TiN thin films were systematically investigated. The results show that at lower N₂/Ar flow ratios, the films consist of a mixture of TiN and Ti₂O₃ phases, while at higher N₂/Ar ratios, single-phase TiN with a preferred orientation along the (220) plane is detected in the obtained films. AFM measurements indicate that the root mean square roughness first increases and then decreases with increases in N₂/Ar flow ratios, and it reaches a maximum of around 15.9 nm when the N₂/Ar flow ratio is 5:15. XPS results show that the 5:15 sample contains the highest oxygen vacancy concentration, offering it the best conductivity, which is confirmed by four-probe measurements. Electrochemical tests demonstrate that the N₂/Ar flow ratio has a significant influence on the specific capacitance of TiN films, with the highest value of 3.29 mF/cm² achieved at a N₂/Ar flow ratio of 5:15, which is likely due to the rough and porous surface and much better conductivity of the as-deposited films. This study provides an important experimental basis for optimizing the performance of TiN thin-film electrodes. Full article

Tin selenide (SnSe) is a sustainable, lead-free IV–VI semiconductor whose layered orthorhombic crystal structure induces pronounced electronic and phononic anisotropy, enabling diverse energy-related functionalities. This review systematically summarizes recent progress in understanding the structure–property–processing relationships that govern SnSe performance in thermoelectric and optoelectronic applications. Key crystallographic characteristics are first discussed, including the temperature-driven Pnma–Cmcm phase transition, anisotropic band and valley structures, and phonon transport mechanisms that lead to intrinsically low lattice thermal conductivity below 0.5 W m⁻¹ K⁻¹ and tunable carrier transport. Subsequently, major synthesis strategies are critically compared, spanning Bridgman and vertical-gradient single-crystal growth, spark plasma sintering and hot pressing of polycrystals, as well as vapor- and solution-based thin-film fabrication, with emphasis on process windows, stoichiometry control, defect chemistry, and microstructure engineering. For thermoelectric applications, directional and temperature-dependent transport behaviors are analyzed, highlighting record thermoelectric performance in single-crystal SnSe at hi. We analyze directional and temperature-dependent transport, highlighting record thermoelectric figure of merit values exceeding 2.6 along the b-axis in single-crystal SnSe at ~900 K, as well as recent progress in polycrystalline and thin-film systems through alkali/coinage-metal doping (Ag, Na, Cu), isovalent and heterovalent substitution (Zn, S), and hierarchical microstructural design. For optoelectronic applications, optical properties, carrier dynamics, and photoresponse characteristics are summarized, underscoring high absorption coefficients exceeding 10⁴ cm⁻¹ and bandgap tunability across the visible to near-infrared range, together with interface engineering strategies for thin-film photovoltaics and broadband photodetectors. Emerging applications beyond energy conversion, including phase-change memory and electrochemical energy storage, are also reviewed. Finally, key challenges related to selenium volatility, performance reproducibility, long-term stability, and scalable manufacturing are identified. Overall, this review provides a process-oriented and application-driven framework to guide the rational design, synthesis optimization, and device integration of SnSe-based materials. Full article

With the increasing demand for high-energy-density energy storage systems in electric vehicles, smart grids, and portable electronic devices, the energy density of traditional lithium-ion batteries is approaching its theoretical limit. Lithium-sulfur (Li-S) batteries are regarded as strong candidates for next-generation high-performance energy storage systems due to their high theoretical energy density (2567 Wh kg⁻¹), low cost, and environmental friendliness. However, the commercialization of Li-S batteries still faces key challenges such as the shuttle effect, sluggish reaction kinetics, volume expansion, and lithium anode corrosion. To address these issues, researchers have developed various functional materials and structural design strategies, among which heterostructures and nanocage host materials show significant advantages. This review systematically summarizes the basic principles, key problems, and solving strategies of lithium-sulfur (Li-S) batteries, focusing on the role of nanocage heterostructures in enhancing polysulfide adsorption, catalytic conversion, and structural stability, and outlines their future development path in high-energy-density Li-S batteries. Full article

This paper reviews the research progress of supercapacitors (SCs), including the influence of electrode materials on energy storage mechanism and performance, and life prediction. Supercapacitors show application potential in many fields due to their high-power density, fast charge–discharge capability, long cycle life, and environmental protection characteristics. In this paper, the energy storage mechanism of the double-layer capacitor, pseudocapacitor, and asymmetric supercapacitor are discussed. New electrode materials, such as carbon-based materials, metal oxides, and conductive polymers, are reviewed based on the performance optimization measures that are involved in the microstructure design of electrode materials, and integrate the rule prediction of supercapacitors into comprehensive learning. When designing and using supercapacitors, we should not only pay attention to their life but also pay attention to their remaining service life in real time. The paper also mentions the progress of life prediction technology, which is of great significance to improve the reliability and maintenance efficiency of energy storage equipment, and ensure the long-term stable operation of energy storage systems. Future research directions include increasing energy density, extending life, adapting to extreme environments, developing flexible and wearable devices, intelligent management, and reducing costs. Full article

Aiming at multi-agent interest demands and environmental benefits, a distributionally robust game-theoretic optimization algorithm based on a green certificate–carbon trading mechanism is proposed for uncertain microgrids. At first, correlated wind–solar scenarios are generated using Kernel Density Estimation and copula theory and the probability distribution ambiguity set is constructed combining 1-norm and $\infty$-norm metrics. Subsequently, with gas turbines, renewable energy power producers, and an energy storage unit as game participants, a two-stage distributionally robust game-theoretic optimization scheduling model is established for microgrids considering wind and solar correlation. The algorithm is constructed by integrating a non-cooperative dynamic game with complete information and distributionally robust optimization. It minimizes a linear objective subject to linear matrix inequality (LMI) constraints and adopts the column and constraint generation (C&CG) algorithm to determine the optimal output for each device within the microgrid to enhance its overall system performance. This method ultimately yields a scheduling solution that achieves both equilibrium among multiple stakeholders’ interests and robustness. The simulation result verifies the effectiveness of the proposed method. Full article

The large-scale integration of doubly fed wind turbines reduces the inertia level of power systems and increases the risk of frequency instability. This paper analyzes the performance characteristics and application ranges of different types of energy storage technologies and addresses the limitations of conventional control methods, which cannot adjust energy storage power output in real time according to frequency variations and may hinder frequency recovery during the restoration stage. Based on a grid-forming doubly fed wind turbine model, this study adopts a hybrid ultracapacitor energy storage system as the auxiliary storage device. The hybrid configuration increases energy density and extends the effective support duration of the storage system, thereby meeting the requirements of longer-term frequency regulation. Furthermore, the paper proposes an adaptive inertia control strategy that combines an improved variable-K droop control with adaptive virtual inertia control to enhance the stability of doubly fed wind turbines under load fluctuations. Simulation studies conducted in MATLAB 2022/Simulink demonstrate that the proposed method significantly improves frequency stability in load disturbance scenarios. The strategy not only strengthens the frequency support capability of grid-connected wind turbine units but also accelerates frequency recovery, which plays an important role in maintaining power system frequency stability. Full article

The growing demand for energy-efficient memory systems in artificial intelligence (AI) accelerators has intensified research into novel device technologies and computing-in-memory (CIM) architectures. While conventional binary SRAM architectures using CMOS and FinFET devices have been widely explored, ternary-based designs offer potential benefits in terms of storage density and computational efficiency. This work presents a low-power analysis of a sense-amplifier embedded (SE) 9-transistor (9T) ternary SRAM architecture implemented using Carbon Nanotube Field-Effect Transistors (CNFETs) and Gate-All-Around Field-Effect Transistors (GAAFETs). The comparative results show a substantial reduction in total power consumption—from 109.2 $\mathsf{\mu }$W in FinFET to 26.73 $\mathsf{\mu }$W in GAAFET—and an ultra-low power of only 0.0004 $\mathsf{\mu }$W in CNFET, representing a 99% reduction compared to FinFET designs. Similarly, the total delay decreases from 0.01108 ns in FinFET to 0.004 ns in GAAFET, while the CNFET design shows a modest delay of 0.017 ns. Overall, GAAFET offers the best trade-off between power and delay, whereas CNFET achieves the lowest power consumption, making it highly suitable for ultra-low-power AI applications. These findings emphasize the superior energy efficiency and scalability potential of CNFET- and GAAFET-based designs over traditional FinFETs, offering a promising pathway toward next-generation ternary CIM-enabled SRAM architectures. Furthermore, fabrication challenges related to CNFET and GAAFET technologies are discussed, providing insights into their practical feasibility for large-scale integration. Full article