In this study, a state-of-the-art high-throughput experimentation (HTE) workflow for catalytic olefin polymerization, covering an unprecedented wide part of the polymer knowledge and value chains from catalytic synthesis all the way down to “engineering” microrheology, was thoroughly assessed with respect to its ability to prepare new materials and produce large and accurate databases for the investigation of quantitative structure–property relationships (QSPRs). Olefin blocks copolymers (OBCs) produced under chain-shuttling polymerization conditions were used as a demonstration case. The results of a thorough microstructural, structural, mechanical, morphological, and rheological characterization of OBC replicas prepared with the HTE synthetic platform and a commercial sample, chosen as a benchmark, demonstrate the robustness of the approach. The proposed workflow can become a paradigm for the high-throughput synthesis and investigation of novel materials, thus reducing the time to market of new products. In our opinion, this opens the door to integrated HTE and artificial intelligence approaches to QSPR problem solving in the numerous cases for which a thorough understanding of the theory is not sufficient to deterministically unravel the complexity of practical applications.

中文翻译：

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将高通量实验 (HTE) 方法扩展到催化烯烃聚合：从催化剂到材料

在这项研究中，用于催化烯烃聚合的最先进的高通量实验 (HTE) 工作流程，涵盖了从催化合成一直到“工程”微流变学的聚合物知识和价值链的前所未有的广泛部分，对其制备新材料和生成用于研究定量结构-性能关系 (QSPR) 的大型准确数据库的能力进行了全面评估。在链穿梭聚合条件下生产的烯烃嵌段共聚物 (OBC) 被用作示范案例。对使用 HTE 合成平台和商业样品制备的 OBC 复制品进行彻底的微观结构、结构、机械、形态和流变学表征的结果证明了该方法的稳健性。所提出的工作流程可以成为高通量合成和研究新材料的范例，从而缩短新产品的上市时间。我们认为，这为在大量案例中集成 HTE 和人工智能方法来解决 QSPR 问题打开了大门，在这些案例中，对理论的透彻理解不足以确定性地揭示实际应用的复杂性。