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封面介绍Machine learning bridges molecular structures and sur-factant performance. The advances in machine learning for predicting key surfactant properties (e.g., critical micelle concentration, surface tension, hydrophilic-lipo- philic balance, adsorption efficiency, and Krafft point) are systematically reviewed by Zhang, Ding, Guo, Li, and Xue on page 2310. Furthermore, preliminary applications and prospects of this technology in predicting environmental safety parameters such as biodegradability and ecotoxicity are examined. -
封面介绍The selective anion recognition of pyridinebisthiazola-mine-strapped calix[4]pyrrole 2 is reported by Yan, Huo and He on page 2442. This receptor strongly binds H2PO4- via simultaneous proton transfer between its thiazole units and H2PO4-. Relying on pH-responsive protonation-deprotonation of the bridging strap, the macrocycle serves as a pH-tunable molecular switch, selectively trapping H2PO4- under neutral conditions and switching its binding affinity to H2PO4- in acidic media. -
封面介绍The X—H (X=O, N, S) bond insertion reaction catalyzed by bismuth for diaryl diazomethanes is reported by Lü, Liu, Liu, Si, Li, Chen, and Liu on page 2409. This reaction is applicable to various compounds containing X—H bonds. This method has the characteristics of simple operation, mild conditions, and wide substrate range, providing an alternative solution for reactions involving transition metals and expanding the application of bismuth metal in carbene chemistry.
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