Role of a nanoparticle network in polymer mechanical reinforcement: insights from molecular dynamics simulations

文献情報

出版日 2021-08-28

DOI 10.1039/D1CP03153H

インパクトファクター 3.676

著者

Xiu Li, Ziwei Li, Jianxiang Shen, Zijian Zheng, Jun Liu

原文を見る

要旨

Fully understanding the mechanism by which nanoparticles (NPs) strengthen polymer matrices is crucial for fabricating high-performance polymer nanocomposites (PNCs). Herein, coarse-grained molecular dynamics simulations were adopted to explicitly investigate the reinforcing effect of a NP network. Our results revealed that increasing the NP–NP interactions induced the self-assembly of NPs into a three-dimensional (3D) network that reinforced the polymer matrix. The reinforcing mechanism of NP–NP interactions was quite different from that of NP–polymer interactions. The latter promoted the orientation of polymer chains to transfer the external stress, while the former distributed the stress throughout the NP network. This work revealed the mechanism by which the NP network reinforced the polymer matrix at the molecular level and also provided guidelines for developing high performance PNCs via interfacial modification.

掲載誌

Physical Chemistry Chemical Physics

CiteScore: 5.5

自己引用率: 10.3%

年間論文数: 3036

Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions. The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.