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Complementary Adsorption within Metal–Organic Frameworks for Ethylene Upgrading from Refinery Dry Gas
Molecule-specific adsorption offers an efficient approach for target molecule purification from complex mixtures that demand a series of energy-intensive separation units. However, existing separation mechanisms that discriminate molecular sizes or functional groups are generally unable to achieve molecule-specific adsorption due to insufficiently identified molecular information. We reveal the complementary adsorption mechanism that discriminates molecules through surface electrostatic potential and molecular shape, covering more comprehensive physical and chemical molecular properties, and realizing precise molecular recognition. The constructed novel porous material ZU-501, which exhibits electrostatic potential and shape complementarity toward ethylene, first realizes ethylene-specific adsorption from typical ethylene mixtures, including C1–C4 paraffins and olefins, and carbon dioxide. The practical use potential of ZU-501 for one-step ethylene recovery from a refinery dry gas is validated by scale-up breakthrough experiments and pressure swing adsorption modeling. This work paves an important avenue for the efficient utilization of low-concentration ethylene resources from diverse scenarios.
Heterointerface-Enabled Anti-Reverse-Current Electrodes for Alkaline Water Electrolyzers at 1000 mA cm–2
Achieving stable and efficient alkaline water electrolysis (AWE) under fluctuating renewable energy inputs is essential for large-scale green hydrogen production. However, frequent shutdown-induced reverse current (RC) effects pose significant challenges to electrode durability. Here, we introduce a gradient interlayer engineering strategy to develop robust AWE electrodes that intrinsically resist both electrochemical reconstruction and mechanical fatigue. By constructing a dense interlayer with Ni(112̅)/Ni3S2(1̅20) heterointerfaces, the electrode demonstrates high catalytic activity (1.79 V @1000 mA cm–2─meeting the U.S. DOE 2026 target), excellent operational stability (>1500 h at 1000 mA cm–2 in 30 wt % KOH at 80 °C), and exceptional RC resistance for 3600 accelerated startup/shutdown cycles. Mechanistic studies through cross-sectional characterizations and theoretical calculations reveal that the seamless interlayer at the catalyst–substrate interface enhances interfacial adhesion, mitigates lattice mismatch, and facilitates charge redistribution, ensuring robust stability and integrity even under operational strains and potential reversals. This work establishes interface crystallography as a design paradigm for durable electrodes, potentially overcoming the stability–activity dilemma toward industrially relevant electrolyzers coupled with fluctuating renewable energy sources.
Front Cover: Intelligent Generative Models for Quantum Neural Networks
The Hyperband-QNN algorithm achieves adaptive customization of quantum neural network structure by skilfully integrating the essence of neural networks and the Hyperband optimization algorithm, perfectly matching the needs of various specific tasks. This groundbreaking method not only opens up a new path for the design of quantum neural networks but also sets a model for the deep integration of quantum computing and traditional computing. More in article number 2400178, Zheng Shan and co-workers.
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科学插图
分子结构、细胞图像、实验装置
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分子动力学、过程演示、机制解释
教育培训课程
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科研图像规范与排版
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300
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300
PS+AIGC科研应用
300
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