{"title":"QSAR-driven digital catalyst models: high-throughput design of polyolefin elastomers","authors":"Bing Yan, Shijia Wang, Xiao Gui, Xinpeng Xing, Qishun Guo, Chengang Cao, Jian Li, Tao Jiang","doi":"10.1016/j.jcat.2025.116447","DOIUrl":null,"url":null,"abstract":"<div><div>Metallocene catalysts are pivotal in enabling the high-temperature solution polymerization of ethylene/1-octene to produce polyolefin elastomers. Among these, bridged metallocene catalysts are particularly valuable commercially owing to their exceptional thermal stability and high catalytic activity. However, their diverse and complex structural characteristics pose major challenges in the precise and controllable design and synthesis of catalysts that simultaneously exhibit high activity, superior copolymerization performance, and the ability to produce high-molecular-weight polymers. Herein, the quantitative structure–activity relationships (QSARs) of <em>C</em><sub>1</sub>-symmetric bridged metallocene catalysts for ethylene/1-octene copolymerization were investigated through a combined experimental and density functional theory approach. In contrast to most studies that focus solely on the catalyst structure, our findings emphasize the importance of analyzing catalyst performance based on the transition state species formed during the reaction. Specifically, the ∠C<sub>Cp</sub>–M−C<sub>Flu</sub> and the ∠M–C<sub>α</sub>–H<sub>α</sub> of ethylene π-complexes in [Cp(R<sub>1</sub>)Ind(R<sub>2</sub>)<sub>2</sub>Si(R)<sub>2</sub>M(<em>i</em>Bu)]<sup>+</sup> were identified as important influencing factor of catalytic activity. Additionally, the M–C<sub>α</sub> bond length in [Cp(R<sub>1</sub>)Ind(R<sub>2</sub>)<sub>2</sub>Si(R)<sub>2</sub>MC<sub>4</sub>H<sub>8</sub>(<em>i</em>Bu)<sup>+</sup>…C<sub>2</sub>H<sub>4</sub>] <sup>‡</sup> was found to influence copolymerization performance, while the C<sub>α</sub>–M−C<sub>1</sub>−C<sub>2</sub> twist angle in [Cp(R<sub>1</sub>)Ind(R<sub>2</sub>)<sub>2</sub>Si(R)<sub>2</sub>MC<sub>2</sub>H<sub>4</sub>(<em>i</em>Bu)<sup>+</sup>…C<sub>2</sub>H<sub>4</sub>]<sup>‡</sup> directly affected the molecular weight of the polymerization product. These QSARs were further validated through machine learning and experimental verification. Based on these insights, a novel high-performance catalyst was designed and synthesized. Finally, a universally applicable digital catalyst model with high-throughput screening capabilities was developed, leveraging the obtained QSARs.</div></div>","PeriodicalId":346,"journal":{"name":"Journal of Catalysis","volume":"452 ","pages":"Article 116447"},"PeriodicalIF":6.5000,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Catalysis","FirstCategoryId":"92","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0021951725005135","RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CHEMISTRY, PHYSICAL","Score":null,"Total":0}
引用次数: 0
Abstract
Metallocene catalysts are pivotal in enabling the high-temperature solution polymerization of ethylene/1-octene to produce polyolefin elastomers. Among these, bridged metallocene catalysts are particularly valuable commercially owing to their exceptional thermal stability and high catalytic activity. However, their diverse and complex structural characteristics pose major challenges in the precise and controllable design and synthesis of catalysts that simultaneously exhibit high activity, superior copolymerization performance, and the ability to produce high-molecular-weight polymers. Herein, the quantitative structure–activity relationships (QSARs) of C1-symmetric bridged metallocene catalysts for ethylene/1-octene copolymerization were investigated through a combined experimental and density functional theory approach. In contrast to most studies that focus solely on the catalyst structure, our findings emphasize the importance of analyzing catalyst performance based on the transition state species formed during the reaction. Specifically, the ∠CCp–M−CFlu and the ∠M–Cα–Hα of ethylene π-complexes in [Cp(R1)Ind(R2)2Si(R)2M(iBu)]+ were identified as important influencing factor of catalytic activity. Additionally, the M–Cα bond length in [Cp(R1)Ind(R2)2Si(R)2MC4H8(iBu)+…C2H4] ‡ was found to influence copolymerization performance, while the Cα–M−C1−C2 twist angle in [Cp(R1)Ind(R2)2Si(R)2MC2H4(iBu)+…C2H4]‡ directly affected the molecular weight of the polymerization product. These QSARs were further validated through machine learning and experimental verification. Based on these insights, a novel high-performance catalyst was designed and synthesized. Finally, a universally applicable digital catalyst model with high-throughput screening capabilities was developed, leveraging the obtained QSARs.
期刊介绍:
The Journal of Catalysis publishes scholarly articles on both heterogeneous and homogeneous catalysis, covering a wide range of chemical transformations. These include various types of catalysis, such as those mediated by photons, plasmons, and electrons. The focus of the studies is to understand the relationship between catalytic function and the underlying chemical properties of surfaces and metal complexes.
The articles in the journal offer innovative concepts and explore the synthesis and kinetics of inorganic solids and homogeneous complexes. Furthermore, they discuss spectroscopic techniques for characterizing catalysts, investigate the interaction of probes and reacting species with catalysts, and employ theoretical methods.
The research presented in the journal should have direct relevance to the field of catalytic processes, addressing either fundamental aspects or applications of catalysis.