Molecular Dynamics Simulation of Polymer Nanocomposites with Supramolecular Network Constructed via Functionalized Polymer End-Grafted Nanoparticles
Since the proposal of self-healing materials, numerous researchers have focused on exploring their potential applications in flexible sensors, bionic robots, satellites, etc. However, there have been few studies on the relationship between the morphology of the dynamic crosslink network and the comp...
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MDPI AG
2023-07-01
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Series: | Polymers |
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Online Access: | https://www.mdpi.com/2073-4360/15/15/3259 |
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author | Guanyi Hou Runhan Ren Wei Shang Yunxuan Weng Jun Liu |
author_facet | Guanyi Hou Runhan Ren Wei Shang Yunxuan Weng Jun Liu |
author_sort | Guanyi Hou |
collection | DOAJ |
description | Since the proposal of self-healing materials, numerous researchers have focused on exploring their potential applications in flexible sensors, bionic robots, satellites, etc. However, there have been few studies on the relationship between the morphology of the dynamic crosslink network and the comprehensive properties of self-healing polymer nanocomposites (PNCs). In this study, we designed a series of modified nanoparticles with different sphericity (η) to establish a supramolecular network, which provide the self-healing ability to PNCs. We analyzed the relationship between the morphology of the supramolecular network and the mechanical performance and self-healing behavior. We observed that as η increased, the distribution of the supramolecular network became more uniform in most cases. Examination of the segment dynamics of polymer chains showed that the completeness of the supramolecular network significantly hindered the mobility of polymer matrix chains. The mechanical performance and self-healing behavior of the PNCs showed that the supramolecular network mainly contributed to the mechanical performance, while the self-healing efficiency was dominated by the variation of η. We observed that appropriate grafting density is the proper way to effectively enhance the mechanical and self-healing performance of PNCs. This study provides a unique guideline for designing and fabricating self-healing PNCs with modified Nanoparticles (NPs). |
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issn | 2073-4360 |
language | English |
last_indexed | 2024-03-11T00:18:38Z |
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spelling | doaj.art-9df4f85906c64b4bbae2e46fef92fb4b2023-11-18T23:28:42ZengMDPI AGPolymers2073-43602023-07-011515325910.3390/polym15153259Molecular Dynamics Simulation of Polymer Nanocomposites with Supramolecular Network Constructed via Functionalized Polymer End-Grafted NanoparticlesGuanyi Hou0Runhan Ren1Wei Shang2Yunxuan Weng3Jun Liu4College of Chemistry and Materials Engineering, Beijing Technology and Business University, Beijing 100048, ChinaCollege of Chemistry and Materials Engineering, Beijing Technology and Business University, Beijing 100048, ChinaCollege of Chemistry and Materials Engineering, Beijing Technology and Business University, Beijing 100048, ChinaCollege of Chemistry and Materials Engineering, Beijing Technology and Business University, Beijing 100048, ChinaCenter of Advanced Elastomer Materials, Beijing University of Chemical Technology, Beijing 100029, ChinaSince the proposal of self-healing materials, numerous researchers have focused on exploring their potential applications in flexible sensors, bionic robots, satellites, etc. However, there have been few studies on the relationship between the morphology of the dynamic crosslink network and the comprehensive properties of self-healing polymer nanocomposites (PNCs). In this study, we designed a series of modified nanoparticles with different sphericity (η) to establish a supramolecular network, which provide the self-healing ability to PNCs. We analyzed the relationship between the morphology of the supramolecular network and the mechanical performance and self-healing behavior. We observed that as η increased, the distribution of the supramolecular network became more uniform in most cases. Examination of the segment dynamics of polymer chains showed that the completeness of the supramolecular network significantly hindered the mobility of polymer matrix chains. The mechanical performance and self-healing behavior of the PNCs showed that the supramolecular network mainly contributed to the mechanical performance, while the self-healing efficiency was dominated by the variation of η. We observed that appropriate grafting density is the proper way to effectively enhance the mechanical and self-healing performance of PNCs. This study provides a unique guideline for designing and fabricating self-healing PNCs with modified Nanoparticles (NPs).https://www.mdpi.com/2073-4360/15/15/3259self-healing materialssupramolecular crosslink networkmolecular dynamic simulation |
spellingShingle | Guanyi Hou Runhan Ren Wei Shang Yunxuan Weng Jun Liu Molecular Dynamics Simulation of Polymer Nanocomposites with Supramolecular Network Constructed via Functionalized Polymer End-Grafted Nanoparticles Polymers self-healing materials supramolecular crosslink network molecular dynamic simulation |
title | Molecular Dynamics Simulation of Polymer Nanocomposites with Supramolecular Network Constructed via Functionalized Polymer End-Grafted Nanoparticles |
title_full | Molecular Dynamics Simulation of Polymer Nanocomposites with Supramolecular Network Constructed via Functionalized Polymer End-Grafted Nanoparticles |
title_fullStr | Molecular Dynamics Simulation of Polymer Nanocomposites with Supramolecular Network Constructed via Functionalized Polymer End-Grafted Nanoparticles |
title_full_unstemmed | Molecular Dynamics Simulation of Polymer Nanocomposites with Supramolecular Network Constructed via Functionalized Polymer End-Grafted Nanoparticles |
title_short | Molecular Dynamics Simulation of Polymer Nanocomposites with Supramolecular Network Constructed via Functionalized Polymer End-Grafted Nanoparticles |
title_sort | molecular dynamics simulation of polymer nanocomposites with supramolecular network constructed via functionalized polymer end grafted nanoparticles |
topic | self-healing materials supramolecular crosslink network molecular dynamic simulation |
url | https://www.mdpi.com/2073-4360/15/15/3259 |
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