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Sequential Self-Folding Structures by 3D Printed Digital Shape Memory Polymers
Folding is ubiquitous in nature with examples ranging from the formation of cellular components to winged insects. It finds technological applications including packaging of solar cells and space structures, deployable biomedical devices, and self-assembling robots and airbags. Here we demonstrate s...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4562068/ https://www.ncbi.nlm.nih.gov/pubmed/26346202 http://dx.doi.org/10.1038/srep13616 |
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author | Mao, Yiqi Yu, Kai Isakov, Michael S. Wu, Jiangtao Dunn, Martin L. Jerry Qi, H. |
author_facet | Mao, Yiqi Yu, Kai Isakov, Michael S. Wu, Jiangtao Dunn, Martin L. Jerry Qi, H. |
author_sort | Mao, Yiqi |
collection | PubMed |
description | Folding is ubiquitous in nature with examples ranging from the formation of cellular components to winged insects. It finds technological applications including packaging of solar cells and space structures, deployable biomedical devices, and self-assembling robots and airbags. Here we demonstrate sequential self-folding structures realized by thermal activation of spatially-variable patterns that are 3D printed with digital shape memory polymers, which are digital materials with different shape memory behaviors. The time-dependent behavior of each polymer allows the temporal sequencing of activation when the structure is subjected to a uniform temperature. This is demonstrated via a series of 3D printed structures that respond rapidly to a thermal stimulus, and self-fold to specified shapes in controlled shape changing sequences. Measurements of the spatial and temporal nature of self-folding structures are in good agreement with the companion finite element simulations. A simplified reduced-order model is also developed to rapidly and accurately describe the self-folding physics. An important aspect of self-folding is the management of self-collisions, where different portions of the folding structure contact and then block further folding. A metric is developed to predict collisions and is used together with the reduced-order model to design self-folding structures that lock themselves into stable desired configurations. |
format | Online Article Text |
id | pubmed-4562068 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-45620682015-09-15 Sequential Self-Folding Structures by 3D Printed Digital Shape Memory Polymers Mao, Yiqi Yu, Kai Isakov, Michael S. Wu, Jiangtao Dunn, Martin L. Jerry Qi, H. Sci Rep Article Folding is ubiquitous in nature with examples ranging from the formation of cellular components to winged insects. It finds technological applications including packaging of solar cells and space structures, deployable biomedical devices, and self-assembling robots and airbags. Here we demonstrate sequential self-folding structures realized by thermal activation of spatially-variable patterns that are 3D printed with digital shape memory polymers, which are digital materials with different shape memory behaviors. The time-dependent behavior of each polymer allows the temporal sequencing of activation when the structure is subjected to a uniform temperature. This is demonstrated via a series of 3D printed structures that respond rapidly to a thermal stimulus, and self-fold to specified shapes in controlled shape changing sequences. Measurements of the spatial and temporal nature of self-folding structures are in good agreement with the companion finite element simulations. A simplified reduced-order model is also developed to rapidly and accurately describe the self-folding physics. An important aspect of self-folding is the management of self-collisions, where different portions of the folding structure contact and then block further folding. A metric is developed to predict collisions and is used together with the reduced-order model to design self-folding structures that lock themselves into stable desired configurations. Nature Publishing Group 2015-09-08 /pmc/articles/PMC4562068/ /pubmed/26346202 http://dx.doi.org/10.1038/srep13616 Text en Copyright © 2015, 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 Mao, Yiqi Yu, Kai Isakov, Michael S. Wu, Jiangtao Dunn, Martin L. Jerry Qi, H. Sequential Self-Folding Structures by 3D Printed Digital Shape Memory Polymers |
title | Sequential Self-Folding Structures by 3D Printed Digital Shape Memory Polymers |
title_full | Sequential Self-Folding Structures by 3D Printed Digital Shape Memory Polymers |
title_fullStr | Sequential Self-Folding Structures by 3D Printed Digital Shape Memory Polymers |
title_full_unstemmed | Sequential Self-Folding Structures by 3D Printed Digital Shape Memory Polymers |
title_short | Sequential Self-Folding Structures by 3D Printed Digital Shape Memory Polymers |
title_sort | sequential self-folding structures by 3d printed digital shape memory polymers |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4562068/ https://www.ncbi.nlm.nih.gov/pubmed/26346202 http://dx.doi.org/10.1038/srep13616 |
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