期刊论文详细信息
JOURNAL OF BIOMECHANICS 卷:117
Numerical-experimental analysis of the permeability-porosity relationship in triply periodic minimal surfaces scaffolds
Article
Pires, Tiago1  Santos, Jorge1  Ruben, Rui B.2  Gouveia, Barbara P.1  Castro, Andre P. G.1  Fernandes, Paulo R.1 
[1] Univ Lisbon, Inst Super Tecn, IDMEC, Lisbon, Portugal
[2] Polytech Inst Leiria, CDRSP, ESTG, Leiria, Portugal
关键词: Bone tissue engineering;    Scaffolds;    Permeability;    Triply periodic minimal surfaces;    Computational fluid dynamics;   
DOI  :  10.1016/j.jbiomech.2021.110263
来源: Elsevier
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【 摘 要 】

Bone Tissue Engineering has been focusing on improving the current methods for bone repair, being the use of scaffolds presented as an upgrade to traditional surgery techniques. Scaffolds are artificially porous matrices, meant to promote cell seeding and proliferation, being these properties influenced by the permeability of the structure. This work employed experimental pressure drop tests and Computational Fluid Dynamics models to assess permeability (and fluid streamlines) within different triply periodic minimal surfaces scaffold geometries (Schwarz D, Gyroid and Schwarz P). The pressure outputs from the computational analysis presented a good correlation with the experimental results, with R2 equal to 0.903; they have also shown that a lower porosity may not mean a lower permeability if the geometry is altered, such as the difference between 60% porous Gyroid scaffolds (8.1*10-9 mm2) and 70% porous Schwarz D scaffolds (7.1*10-9 mm2). Fluid streamlines revealed how the Gyroid geometries are the most appropriate design for most bone tissue engineering applications, due to their consistent fluid permeation, followed by Schwarz D. The Schwarz P geometries have shown flat streamlines and significant variation of the permeability with the porosity (an increase of 10% in their porosity lead to an increase in the permeability from 5.1*10-9 mm2 to 11.7*10-9 mm2), which would imply a poor environment for cell seeding and proliferation. (c) 2021 Elsevier Ltd. All rights reserved.

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