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Revealing the morphological architecture of a shape memory polyurethane by simulation
The lack of specific knowledge of the network structure in shape memory polymers (SMPs) has prevented us from gaining an in-depth understanding of their mechanisms and limited the potential for materials innovation. This paper firstly reveals the unit-cell nanoscale morphological architecture of SMP...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4931583/ https://www.ncbi.nlm.nih.gov/pubmed/27373495 http://dx.doi.org/10.1038/srep29180 |
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author | Hu, Jinlian Zhang, Cuili Ji, Fenglong Li, Xun Han, Jianping Wu, You |
author_facet | Hu, Jinlian Zhang, Cuili Ji, Fenglong Li, Xun Han, Jianping Wu, You |
author_sort | Hu, Jinlian |
collection | PubMed |
description | The lack of specific knowledge of the network structure in shape memory polymers (SMPs) has prevented us from gaining an in-depth understanding of their mechanisms and limited the potential for materials innovation. This paper firstly reveals the unit-cell nanoscale morphological architecture of SMPs by simulation. The phase separated architecture of a segmented shape memory polyurethane (SMPU) with a 30 wt% hard segment content (HSC, 4,4’-diphenylmethane diisocyanate (MDI) and 1,4-butanediol (BDO)) showing good shape memory properties was investigated by dissipative particle dynamics (DPD) simulations. A linked-spherical netpoint-frame phase of MDI, a matrix-switch phase of polycaprolactone (PCL) and a connected-spider-like interphase for BDO were obtained for this SMPU. The BDO interphase can reinforce the MDI network. Based on these simulation results, a three-dimensional (3D) overall morphological architectural model of the SMPU can be established. This theoretical study has verified, enriched and integrated two existing schematic models: one being the morphological model deduced from experiments and the other the frame model for SMPs reported before. It can serve as a theoretical guide for smart polymeric materials design. This method for the simulation of polymer structure at the nanoscale can be extended to many areas such as photonic crystals where nanoscale self-assembly plays a vital role. |
format | Online Article Text |
id | pubmed-4931583 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-49315832016-07-06 Revealing the morphological architecture of a shape memory polyurethane by simulation Hu, Jinlian Zhang, Cuili Ji, Fenglong Li, Xun Han, Jianping Wu, You Sci Rep Article The lack of specific knowledge of the network structure in shape memory polymers (SMPs) has prevented us from gaining an in-depth understanding of their mechanisms and limited the potential for materials innovation. This paper firstly reveals the unit-cell nanoscale morphological architecture of SMPs by simulation. The phase separated architecture of a segmented shape memory polyurethane (SMPU) with a 30 wt% hard segment content (HSC, 4,4’-diphenylmethane diisocyanate (MDI) and 1,4-butanediol (BDO)) showing good shape memory properties was investigated by dissipative particle dynamics (DPD) simulations. A linked-spherical netpoint-frame phase of MDI, a matrix-switch phase of polycaprolactone (PCL) and a connected-spider-like interphase for BDO were obtained for this SMPU. The BDO interphase can reinforce the MDI network. Based on these simulation results, a three-dimensional (3D) overall morphological architectural model of the SMPU can be established. This theoretical study has verified, enriched and integrated two existing schematic models: one being the morphological model deduced from experiments and the other the frame model for SMPs reported before. It can serve as a theoretical guide for smart polymeric materials design. This method for the simulation of polymer structure at the nanoscale can be extended to many areas such as photonic crystals where nanoscale self-assembly plays a vital role. Nature Publishing Group 2016-07-04 /pmc/articles/PMC4931583/ /pubmed/27373495 http://dx.doi.org/10.1038/srep29180 Text en Copyright © 2016, Macmillan Publishers Limited http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Hu, Jinlian Zhang, Cuili Ji, Fenglong Li, Xun Han, Jianping Wu, You Revealing the morphological architecture of a shape memory polyurethane by simulation |
title | Revealing the morphological architecture of a shape memory polyurethane by simulation |
title_full | Revealing the morphological architecture of a shape memory polyurethane by simulation |
title_fullStr | Revealing the morphological architecture of a shape memory polyurethane by simulation |
title_full_unstemmed | Revealing the morphological architecture of a shape memory polyurethane by simulation |
title_short | Revealing the morphological architecture of a shape memory polyurethane by simulation |
title_sort | revealing the morphological architecture of a shape memory polyurethane by simulation |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4931583/ https://www.ncbi.nlm.nih.gov/pubmed/27373495 http://dx.doi.org/10.1038/srep29180 |
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