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As a result of the high safety, low cost, and environmental benignity, aqueous zinc-ion batteries are regarded as one of the most promising candidates for next-generation large-scale energy storage systems. However, their further development is constrained by performance bottlenecks in existing cathode materials, including capacity, cycle life, and reaction kinetics. In this study, a high-entropy design strategy is employed to synthesize the metal oxide (FeNiMnMgCuCo)3O4 with a cubic spinel structure, and its electrochemical performance as a cathode for zinc-ion batteries is systematically evaluated. The prepared (FeNiMnMgCuCo)3O4 high-entropy cathode exhibits high reversible capacity (341.3 mA h g−1 at 0.1 A g−1) and remarkable long-term cycling stability (76.1% retention after 1000 cycles at 3 A g−1). This work not only demonstrates a high-entropy cathode material with practical potential but also provides new research insights for optimizing zinc-ion storage performance through composition design and entropy regulation.

As a result of the high safety, low cost, and environmental benignity, aqueous zinc-ion batteries are regarded as one of the most promising candidates for next-generation large-scale energy storage systems. However, their further development is constrained by performance bottlenecks in existing cathode materials, including capacity, cycle life, and reaction kinetics. In this study, a high-entropy design strategy is employed to synthesize the metal oxide (FeNiMnMgCuCo) O with a cubic spinel structure, and its electrochemical performance as a cathode for zinc-ion batteries is systematically evaluated. The prepared (FeNiMnMgCuCo) O high-entropy cathode exhibits high reversible capacity (341.3 mA h g at 0.1 A g ) and remarkable long-term cycling stability (76.1% retention after 1000 cycles at 3 A g ). This work not only demonstrates a high-entropy cathode material with practical potential but also provides new research insights for optimizing zinc-ion storage performance through composition design and entropy regulation.

What are the main findings? * A novel high-entropy cathode (FeNiMnMgCuCo)[sub.3]O[sub.4] is designed and synthesized for aqueous zinc-ion batteries. * The material exhibits a high reversible capacity of 341.3 mA h g[sup.−1] at 0.1 A g[sup.−1]. * The material possesses excellent cycling stability (76.1% retention after 1000 cycles at 3 A g[sup.−1]). * Multi-element coexistence in mixed valence states and high configurational entropy ( 1.78 R) enhance stability. * The high-entropy design effectively promotes Zn[sup.2+] diffusion and redox kinetics while suppressing structural degradation during cycling. A novel high-entropy cathode (FeNiMnMgCuCo)[sub.3]O[sub.4] is designed and synthesized for aqueous zinc-ion batteries. The material exhibits a high reversible capacity of 341.3 mA h g[sup.−1] at 0.1 A g[sup.−1]. The material possesses excellent cycling stability (76.1% retention after 1000 cycles at 3 A g[sup.−1]). Multi-element coexistence in mixed valence states and high configurational entropy ( 1.78 R) enhance stability. The high-entropy design effectively promotes Zn[sup.2+] diffusion and redox kinetics while suppressing structural degradation during cycling. What are the implications of the main findings? * This work demonstrates a high-entropy cathode material with practical potential. * This work provides new research insights for optimizing zinc-ion storage performance through composition design and entropy regulation. * This work will be of significant interest to researchers in the fields of electrochemistry and energy storage. This work demonstrates a high-entropy cathode material with practical potential. This work provides new research insights for optimizing zinc-ion storage performance through composition design and entropy regulation. This work will be of significant interest to researchers in the fields of electrochemistry and energy storage. As a result of the high safety, low cost, and environmental benignity, aqueous zinc-ion batteries are regarded as one of the most promising candidates for next-generation large-scale energy storage systems. However, their further development is constrained by performance bottlenecks in existing cathode materials, including capacity, cycle life, and reaction kinetics. In this study, a high-entropy design strategy is employed to synthesize the metal oxide (FeNiMnMgCuCo)[sub.3]O[sub.4] with a cubic spinel structure, and its electrochemical performance as a cathode for zinc-ion batteries is systematically evaluated. The prepared (FeNiMnMgCuCo)[sub.3]O[sub.4] high-entropy cathode exhibits high reversible capacity (341.3 mA h g[sup.−1] at 0.1 A g[sup.−1]) and remarkable long-term cycling stability (76.1% retention after 1000 cycles at 3 A g[sup.−1]). This work not only demonstrates a high-entropy cathode material with practical potential but also provides new research insights for optimizing zinc-ion storage performance through composition design and entropy regulation.

In this paper, the mesoporous silica MCM-41 supporting nano zero valent iron (MSNZVI) composite was synthesized in a facile way and characterized by XRD, FT-IR, TEM and N 2 adsorption–desorption. The catalytic activity of the as-prepared MSNZVI composite as a catalyst was evaluated on the p -nitrophenol reduction in the presence of excess NaBH 4 . And the rate constant is 4.89 × 10 −3  s −1 when the mole ratio of NaBH 4 to p -nitrophenol is 500. MSNZVI composite can be reused for at least five cycles with stable catalytic activity. Moreover, a possible catalytic mechanism of MSNZVI was proposed to explain the reduction of p -nitrophenol by NaBH 4 .

Most marine gas hydrate systems follow a vertical pattern with hydrate overlying free gas. Here we document the discovery of a gas to hydrate system in a horizontal sand layer in the Qiongdongnan Basin of the South China Sea. Eight wells were drilled by the Guangzhou Marine Geological Survey in 2021–2022 to investigate the occurrence and mechanisms responsible for the formation of the system. We describe a free gas‐bearing sand reservoir at the center of the system sustained by advecting hot fluids and gas; away from the advecting zone, the cooler, surrounding sand reservoir is filled with hydrate. Observations at this site show that advective heat has a large control on hydrate formation in sands and may be a key mechanism which allows gas migration within the hydrate stability zone and the formation of high‐saturation hydrate in sand layers. Plain Language Summary Natural gas hydrate, an ice‐like substance composed of water and gas, is commonly found in sediments under the ocean. Most marine hydrate systems follow a vertical pattern where hydrate‐bearing sediments overlie free gas‐bearing sediments; in addition, most hydrate is hosted in marine muds at low concentration. Here we document a horizontal system that transitions from high concentrations of free gas to high concentrations of hydrate in a horizontal sand layer in the northern South China Sea. Two recent drilling expeditions are conducted to explore this unique system. Seismic and logging data suggests that multiple processes including focused fluid flow, capillary sealing and heat transfer control the formation of the system. Key Points We discover a gas hydrate system where gas transitions to hydrate in a flat‐lying sand layer in the northern South China Sea Capillary sealing occurs at the sand‐clay interface, preventing upward fluid advection and causes fluids to migrate laterally Advecting warm fluids and gas are the primary control on the hydrate and free gas system in this sand layer

Nuclear energy is a cornerstone of the global energy mix, delivering reliable, low-carbon power essential for sustainable energy systems. However, the safety of nuclear reactors is critical to maintaining operational reliability and public trust, particularly during accidents like a Loss of Coolant Accident (LOCA) or a Steam Line Break Inside Containment (SLBIC). This study introduces a Bayesian Network (BN) framework used to enhance nuclear energy safety by predicting accident severity and identifying key factors that ensure energy production stability. With the integration of simulation data and physical knowledge, the BN enables dynamic inference and remains robust under missing-data conditions—common in real-time energy monitoring. Its hierarchical structure organizes variables across layers, capturing initial conditions, intermediate dynamics, and system responses vital to energy safety management. Conditional Probability Tables (CPTs), trained via Maximum Likelihood Estimation, ensure accurate modeling of relationships. The model’s resilience to missing data, achieved through marginalization, sustains predictive reliability when critical energy system variables are unavailable. Achieving R2 values of 0.98 and 0.96 for the LOCA and SLBIC, respectively, the BN demonstrates high accuracy, directly supporting safer nuclear energy production. Sensitivity analysis using mutual information pinpointed critical variables—such as high-pressure injection flow (WHPI) and pressurizer level (LVPZ)—that influence accident outcomes and energy system resilience. These findings offer actionable insights for the optimization of monitoring and intervention in nuclear power plants. This study positions Bayesian Networks as a robust tool for real-time energy safety assessment, advancing the reliability and sustainability of nuclear energy production.

Keloid scars (keloids), a prototypical form of aberrant scar tissue formation, continue to pose a significant therapeutic challenge within dermatology and plastic surgery due to suboptimal treatment outcomes. Gelatinases are a subgroup of matrix metalloproteinases (MMPs), a family of enzymes that play an important role in the degradation and remodeling of the ECM (a pivotal factor for keloids development). Gelatinases include gelatinase A (MMP-2) and gelatinase B (MMP-9). Since accumulating evidence has shown that gelatinases played a crucial role in the process of keloid formation, we summarized the current knowledge on the association between MMP-2 and MMP-9 expression and the pathological process of keloids through a comprehensive review. This review demonstrated that the interplay between MMP-2, MMP-9, and their regulators, such as TGF-β1/Smad, PI3K/AKT, and LncRNA-ZNF252P-AS1/miR-15b-5p/BTF3 signaling cascades, involved in the intricate balance governing ECM homeostasis, collectively driving the excessive collagen deposition and altered tissue architecture observed in keloids. In summary, this review consolidates the current understanding of MMP-2 and MMP-9 in keloid pathogenesis, shedding light on their intricate involvement in the dysregulated keloids processes. The potential for targeted therapeutic interventions presents promising opportunities for advancing keloid management strategies.

User preference learning is an important process in automated negotiation, because only when the negotiating agents are able to fully grasp the user preference information can the negotiation strategy play its due role. However, in most automated negotiation systems, user preference is assumed to be complete and correct, which is quite different from the reality. In real life, user preference is often complex and incomplete, which hinders the application of automated negotiation research in practice. To this end, this paper focuses on the learning method of user preference in negotiation. Since CP-nets can intuitively express the interdependence among negotiation issues, which have good interpretability and expansibility, they have become one of most important representations of user preference in automated negotiation. Therefore, we propose a CP-nets-based user preference learning module in negotiation framework, which consists of both passive learning and active learning methods. In passive learning, we propose an algorithm to construct complete CP-nets with incomplete user preference information. In active learning, we innovatively propose the structural query method, which improves the accuracy of preference learning represented by CP-nets with less query cost. The experimental results show that the module is effective for negotiation framework and can help users reach better agreements in negotiation.

According to the engineering phenomenon of the galloping of ice-coated transmission lines at certain wind speeds, this paper proposes a novel type of energy harvester based on the galloping of a flexible structure. It uses the tension generated by the galloping structure to cause periodic strain on the piezoelectric cantilever beam, which is highly efficient for converting wind energy into electricity. On this basis, a physical model of fluid–structure interaction is established, and the Reynolds-averaged Navier–Stokes equation and SST K -ω turbulent model based on ANSYS Fluent are used to carry out a two-dimensional steady computational fluid dynamics (CFD) numerical simulation. First, the CFD technology under different grid densities and time steps is verified. CFD numerical simulation technology is used to simulate the physical model of the energy harvester, and the effect of wind speed on the lateral displacement and aerodynamic force of the flexible structure is analyzed. In addition, this paper also carries out a parameterized study on the influence of the harvester’s behavior, through the wind tunnel test, focusing on the voltage and electric power output efficiency. The harvester has a maximum output power of 119.7 μW/mm3 at the optimal resistance value of 200 KΩ at a wind speed of 10 m/s. The research results provide certain guidance for the design of a high-efficiency harvester with a square aerodynamic shape and a flexible bluff body.