Volume 192

Traditionally, nickel-based catalysts (e.g., Raney Ni or Ni/Al₂O₃) have been used due to their low cost and high activity. However, Ni catalysts tend to yield excessive saturation and trans-fat isomers, which are undesirable for health. In recent years, intensive research has focused on new catalytic systems to improve selectivity, activity, and environmental performance. This review briefly surveys conventional catalysts and then focuses on two classes of novel catalysts: advanced supported metal catalysts (including noble metals and promoted Ni catalysts) and bimetallic or alloy catalysts. For each system, the article discusses the hydrogenation mechanism, observed activity and selectivity (particularly toward cis monoenes), catalyst stability and regeneration, as well as industrial scale-up potential and environmental impact (e.g., trans-fat formation, energy requirements). Emerging catalyst-free technologies (e.g., plasma hydrogenation) are also highlighted. The paper concludes with perspectives on designing catalysts that meet food-industry demands (high cis-selectivity, low trans content) while minimizing energy use and harmful by-products.

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With the widespread application of UAV technology in military, agricultural, logistics, and other fields, path planning, as a core technology of autonomous navigation, faces challenges from complex environmental constraints and multi-objective optimization. This paper systematically investigates the application of Particle Swarm Optimization (PSO) and its improved strategies in UAV 3D path planning. Secondly, by comparing five algorithms—traditional PSO, Variable social weight PSO, mutated particle PSO, hybrid strategy PSO, and neural network-assisted PSO—in complex terrains with varying numbers of peaks (N=5, 13, 20), their performance is evaluated. Simulation results indicate that the traditional PSO algorithm is simple and efficient but prone to premature convergence. The Variable social weight PSO excels in balancing exploration and exploitation capabilities, enhancing convergence speed. The mutated particle PSO and hybrid PSO effectively avoid local optima and demonstrate superior path quality in complex terrains. The neural network-assisted PSO incurs higher computational costs in high-dimensional complex environments and is susceptible to overfitting in simple environments. This study provides a theoretical basis for algorithm selection in different mission scenarios and proposes future directions for intelligent path planning technology development.

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With social development, the process of electrification has accelerated accordingly. However, performance degradation of lithium-ion batteries caused by heat generation remains a major problem that needs to be overcome at present. Because lithium batteries perform best at room temperature on battery thermal-management systems, especially upgrades to interfacial thermal-conductive materials, concerns the battery’s efficiency, lifespan, and even safety. This paper reviews heat-generation mechanisms and sorts out three categories of nano-upgraded interfacial thermal-conductive materials: metal-based, phase-change, and fluid-based. The literature indicates that using metal nanowires with special alignment within polymers can enhance interfacial thermal-conductive performance by roughly 100 times. Adding about 1% weight fraction graphene to the matrix can improve the efficiency of the heat-transfer network, while the sensible heat is slightly reduced at the same time. Adding magnetic Fe₃O₄ or CuO to a fluid to construct modules of alternating-magnetic-field nanofluids, forming dynamic heat-conduction chains, can significantly reduce battery-module temperatures. This paper focuses on a comprehensive analysis of four aspects of the experimental materials: thermal-conductivity efficiency, heat-buffering capacity, practicality, and manufacturability. It provides material-level design guidelines for battery cooling systems that are safer, longer-lived, and supportive of faster charging.

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