The structural understanding of catalysts is essential for achieving efficient and selective polymerization. In this study, we designed a series of bifunctional catalysts based on squaramide, carboxylates, and alkali cations for the ring-opening polymerization (ROP) of lactide. These catalysts exhibited controlled polymerization behavior with narrow dispersity (Đ_M = 1.08–1.12). Kinetic evaluations revealed a linear relationship between the catalyst's chain length and activity for short CH₂ chains (X = 1–4). However, as the CH₂ segments lengthened, an “odd-even” effect on the kinetics was found, suggesting that the chain length alternately enhances or diminishes catalytic activity. The catalytic activity was significantly influenced by the counter cation (Li⁺, Na⁺, K⁺, and Cs⁺) of carboxylate, with larger radius cations showing higher rate constants (k_{obs Cs⁺} > k_{obs K⁺} > k_{obs Na⁺} > k_{obs Li⁺}). Computational studies demonstrated that this correlation resulted from varying binding energies. Moreover, the k_obs value of the catalyst can be tuned by adding different ratios of the crown ether. An interpretable machine learning method was introduced to link physical properties and activities, guiding the further design of effective catalysts for ROP.

中文翻译：

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可解释的机械加工学习有助于洞察双官能团方形酰胺催化的丙交酯开环聚合反应


对催化剂的结构理解对于实现高效的选择性聚合至关重要。在本研究中，我们设计了一系列基于方形酰胺、羧酸盐和碱阳离子的双功能催化剂，用于丙交酯的开环聚合 （ROP）。这些催化剂表现出受控的聚合行为和窄分散性 （Đ_M = 1.08–1.12）。动力学评估揭示了催化剂的链长与短 CH₂ 链 （X = 1–4） 的活性之间的线性关系。然而，随着 CH₂ 段的延长，发现对动力学的“奇偶”效应，表明链长交替增强或减少催化活性。羧酸盐的反阳离子（Li⁺、Na⁺、K⁺ 和 Cs⁺）对催化活性有显著影响，半径较大的阳离子表现出更高的速率常数（k_{obs Cs⁺} > k_{obs K⁺} > k_{obs Na⁺} > k_{obs Li⁺}）。计算研究表明，这种相关性是由不同的结合能引起的。此外，可以通过添加不同比例的冠醚来调整催化剂的 k_obs 值。引入了一种可解释的机器学习方法，将物理性质和活动联系起来，指导进一步设计有效的 ROP 催化剂。