A TPMS-based method for modeling porous scaffolds for bionic bone tissue engineering

Abstract In the field of bone defect repair, gradient porous scaffolds have received increased attention because they provide a better environment for promoting tissue regeneration. In this study, we propose an effective method to generate bionic porous scaffolds based on the TPMS (triply periodic m...

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Autores principales: Jianping Shi, Liya Zhu, Lan Li, Zongan Li, Jiquan Yang, Xingsong Wang
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Lenguaje:EN
Publicado: Nature Portfolio 2018
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Acceso en línea:https://doaj.org/article/953f0873e8754530b05e140499afd954
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spelling oai:doaj.org-article:953f0873e8754530b05e140499afd9542021-12-02T16:08:01ZA TPMS-based method for modeling porous scaffolds for bionic bone tissue engineering10.1038/s41598-018-25750-92045-2322https://doaj.org/article/953f0873e8754530b05e140499afd9542018-05-01T00:00:00Zhttps://doi.org/10.1038/s41598-018-25750-9https://doaj.org/toc/2045-2322Abstract In the field of bone defect repair, gradient porous scaffolds have received increased attention because they provide a better environment for promoting tissue regeneration. In this study, we propose an effective method to generate bionic porous scaffolds based on the TPMS (triply periodic minimal surface) and SF (sigmoid function) methods. First, cortical bone morphological features (e.g., pore size and distribution) were determined for several regions of a rabbit femoral bone by analyzing CT-scans. A finite element method was used to evaluate the mechanical properties of the bone at these respective areas. These results were used to place different TPMS substructures into one scaffold domain with smooth transitions. The geometrical parameters of the scaffolds were optimized to match the elastic properties of a human bone. With this proposed method, a functional gradient porous scaffold could be designed and produced by an additive manufacturing method.Jianping ShiLiya ZhuLan LiZongan LiJiquan YangXingsong WangNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 8, Iss 1, Pp 1-10 (2018)
institution DOAJ
collection DOAJ
language EN
topic Medicine
R
Science
Q
spellingShingle Medicine
R
Science
Q
Jianping Shi
Liya Zhu
Lan Li
Zongan Li
Jiquan Yang
Xingsong Wang
A TPMS-based method for modeling porous scaffolds for bionic bone tissue engineering
description Abstract In the field of bone defect repair, gradient porous scaffolds have received increased attention because they provide a better environment for promoting tissue regeneration. In this study, we propose an effective method to generate bionic porous scaffolds based on the TPMS (triply periodic minimal surface) and SF (sigmoid function) methods. First, cortical bone morphological features (e.g., pore size and distribution) were determined for several regions of a rabbit femoral bone by analyzing CT-scans. A finite element method was used to evaluate the mechanical properties of the bone at these respective areas. These results were used to place different TPMS substructures into one scaffold domain with smooth transitions. The geometrical parameters of the scaffolds were optimized to match the elastic properties of a human bone. With this proposed method, a functional gradient porous scaffold could be designed and produced by an additive manufacturing method.
format article
author Jianping Shi
Liya Zhu
Lan Li
Zongan Li
Jiquan Yang
Xingsong Wang
author_facet Jianping Shi
Liya Zhu
Lan Li
Zongan Li
Jiquan Yang
Xingsong Wang
author_sort Jianping Shi
title A TPMS-based method for modeling porous scaffolds for bionic bone tissue engineering
title_short A TPMS-based method for modeling porous scaffolds for bionic bone tissue engineering
title_full A TPMS-based method for modeling porous scaffolds for bionic bone tissue engineering
title_fullStr A TPMS-based method for modeling porous scaffolds for bionic bone tissue engineering
title_full_unstemmed A TPMS-based method for modeling porous scaffolds for bionic bone tissue engineering
title_sort tpms-based method for modeling porous scaffolds for bionic bone tissue engineering
publisher Nature Portfolio
publishDate 2018
url https://doaj.org/article/953f0873e8754530b05e140499afd954
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