化学
动力学分辨率
催化作用
共聚物
动能
计算
环氧化物
分辨率(逻辑)
有机化学
对映选择合成
物理
算法
量子力学
人工智能
计算机科学
聚合物
作者
Bai‐Hao Ren,Sarah M. Severson,Sinuo Wang,Zheng‐Fei Liu,Lin-Di Zhang,Zi-Cong Wang,Ye Liu,Wei‐Min Ren,Geoffrey W. Coates,Xiao‐Bing Lu
摘要
The enantioselective resolution copolymerization of racemic terminal epoxides and CO2 is a powerful strategy for preparing isotactic polycarbonates. However, no catalytic system to date has enabled both high chemo- and stereoselectivity in this transformation. Herein, a computation-guided strategy was conducted to understand the key factors governing the activity, chemoselectivity, and stereoselectivity of chiral bimetallic cobalt complexes. Computational fine-tuning of bimetallic synergy allowed accelerated copolymerization, suppression of epoxide homopolymerization, and enhanced chiral induction. Ultimately, a privileged chiral bimetallic catalyst bearing 6,6-ditriflate substituents was computationally designed and experimentally synthesized, which exhibited unprecedented enantioselectivity (s-factor up to over 300) and high chemoselectivity (>95% carbonate units) for various racemic epoxides during resolution copolymerization with CO2. This study is expected to serve as a theoretical framework for broadly guiding the design of privileged chiral catalysts for asymmetric catalytic polymerizations.
科研通智能强力驱动
Strongly Powered by AbleSci AI