Atomistic Simulation of Olefin Polymerization Reaction by Organometallic Catalyst: Significant Role of Microscopic Structural Dynamics of (Pyridylamido)Hf(IV) Complex in Catalytic Reactivity

Kentaro Matsumoto^1*Nana Misawa¹Shuhei Kanesato¹Masataka Nagaoka^1,2,3,4*

• ¹Graduate School of Informatics, Nagoya University, Nagoya, Aichi, Japan
• ²Institute of Innovation for Future Society, Nagoya University, Nagoya, Aichi, Japan
• ³Elements Strategy Initiative for Catalysts and Batteries, Kyoto University, Katsura, Kyôto, Japan
• ⁴Core Research for Evolutional Science and Technology, Japan Science and Technology Agency (JST-CREST), Kawaguchi, Japan

Understanding the microscopic catalytic mechanism of the olefin polymerization reaction is crucial for the rational design of next-generation catalysts. However, the dynamic nature of the active species, including the fluctuations of the ion pair structure and the orientation of substituents, presents significant challenges for theoretical approaches. In this paper, we present an overview of our recent computational studies on the role of the structural dynamics of the active species of olefin polymerization catalyst in determining reactivity, especially focusing on a novel olefin polymerization catalyst (pyridylamido)Hf(IV) complex. Utilizing the molecular dynamics method and our Red Moon method, a novel methodology we have developed for atomistic simulation of complex chemical reaction systems, we elucidate how the dynamic features, including anion coordination and steric interaction, govern the reactivity in key steps such as ligand modification and propagation reactions. In addition, we demonstrate how machine learning techniques can be applied to extract chemically meaningful descriptors from the structural ensemble obtained from atomistic simulation data of complex chemical reaction systems, thereby identifying the substituents that play an important role in propagation reactions. Our studies highlight the importance of incorporating molecular-level dynamic features of catalysts into mechanistic models.