Development of cat-GRRM/MC/MD method for the simulation of cross-linked network structure formation with molecular autocatalysis

自催化 环氧树脂 催化作用 分子动力学 活化能 分子 反应机理 固化(化学) 聚合物 化学反应 化学 材料科学 计算化学 反应速率 化学物理 物理化学 高分子化学 有机化学
作者
Yingxiao Xi,H. Fukuzawa,Shoji Fukunaga,Gota Kikugawa,Yinbo Zhao,Yoshiaki Kawagoe,Tomonaga Okabe,Naoki Kishimoto
出处
期刊:Molecular Catalysis [Elsevier]
卷期号:552: 113680-113680 被引量:2
标识
DOI:10.1016/j.mcat.2023.113680
摘要

Epoxy resins, which are common matrices in carbon fibre-reinforced plastics, are derived from the curing of epoxy amines. Molecular dynamics (MD) simulations are commonly used to model the physical properties of such network polymers, but they do not account for chemical reactions. Quantum chemical (QC) calculations can elucidate reaction mechanisms and energies but are not suitable for models with thousands of atoms. To address these limitations, in this study, we developed a new method, cat-GRRM/MC/MD, that combines QC calculations in the Global Reaction Route Mapping (GRRM) program with reaction simulations involved in MD simulation methods. This approach allows the simulation of reaction pathways in which proton donor molecules such as alcohols and amines act as molecular catalysts (autocatalysis), and the reaction kinetics are realised in a Monte Carlo (MC) manner. Our results show that autocatalysis significantly reduces the activation energy of the epoxy resin reaction, bringing the calculated data closer to the experimental results. When these quantum chemical calculations were incorporated into MD simulations, it was found that the activation energy influenced the crosslinking results. Models including catalysis led to network polymers with larger carbon skeletons, and physical properties such as the Young's modulus and glass transition temperature become closer to experimental results. This study not only deepens our understanding of the mechanism of the self-catalytic reaction of epoxy resins but also provides a new tool for accurately simulating the performance of epoxy resins, thus enabling more precise control of their properties.

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