期刊
VIRTUAL AND PHYSICAL PROTOTYPING
卷 16, 期 3, 页码 291-305出版社
TAYLOR & FRANCIS LTD
DOI: 10.1080/17452759.2021.1930069
关键词
Additive manufacturing; large deformation response; helical architectures; breast tissue engineering
资金
- National Key Research and Development Program of China [2018YFA0703000]
- Key Research Project of Shaanxi Province [2020GXLH-Y-021]
- Guangdong Basic and Applied Basic Research Foundation [2020B1515130002]
- Youth Innovation Team of Shaanxi Universities
- Fundamental Research Funds for the Central Universities
This study focused on helical architectures for the additive manufacturing of flexible PCL scaffolds, which demonstrated the impact of design parameters on filament fusion and the benefits of interlaced helical structures. The use of mu CT-based finite element method effectively predicted deformation responses and confirmed the excellent shape recovery capability of the scaffolds under cyclical compression.
Helical architectures were designed for the additive manufacturing of highly flexible polycaprolactone (PCL) scaffolds for engineering soft tissues, which commonly require high flexibility and predominantly function under large deformation conditions. It was found that the design parameters like revolution and radius of helical architectures highly affected the filament fusion or bonding during the fabrication process. The bonding-induced interlaced helical architectures resulted in a more uniform deformation pattern and a lower modulus. mu CT-based finite element method was established to predict the large deformation responses of the scaffolds with helical architectures and patient-specific scaffold potentially for breast reconstruction, which showed well agreement with the experimental results. The fabricated scaffolds exhibited good shape recovery capability even under cyclical compression at a strain of about 20% for 10000 times. This exploration offers a promising way to predict the mechanical responses of flexible scaffolds with complex helical architectures under large deformation conditions.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据