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Modeling the density gradient of 3D nanofiber scaffolds fabricated by divergence electrospinning
Advances in Manufacturing ( IF 4.2 ) Pub Date : 2020-06-13 , DOI: 10.1007/s40436-020-00307-0
Muhammad Adib Uz Zaman , Dilshan Sooriyaarachchi , Ying-Ge Zhou , George Z. Tan , Dong-Ping Du

Following recent insights on structure-cell-function interactions and the critical role of the extracellular matrix (ECM), the latest biofabrication approaches have increasingly focused on designing materials with biomimetic microarchitecture. Divergence electrospinning is a novel fabrication method for three-dimensional (3D) nanofiber scaffolds. It is introduced to produce 3D nanofiber mats that have numerous applications in regenerative medicine and tissue engineering. One of the most important characteristics of 3D nanofiber mats is the density gradient. This study provides a statistical analysis and response surface modeling framework based on experimental data to evaluate the manner by which the geometric designs of double-bevel collectors influence the fiber density gradient. Specifically, variance of analysis and sensitivity analysis were performed to identify parameters that had significant effects, and a response surface model embedded with seven location indicators was developed to predict the spatial distribution of fiber density for different collector designs. It was concluded that the collector height, bevel angle, and their interactions were significant factors influencing the density gradient. This study revealed the sensitivity of system configuration and provided an optimization tool for process controllability of microstructure gradients.



中文翻译:

模拟通过发散静电纺丝制造的3D纳米纤维支架的密度梯度

继对结构-细胞-功能相互作用和细胞外基质(ECM)的关键作用的最新见解之后,最新的生物制造方法越来越侧重于设计具有仿生微体系结构的材料。发散静电纺丝是一种用于三维(3D)纳米纤维支架的新颖制造方法。引入它来生产3D纳米纤维垫,这些垫在再生医学和组织工程中有许多应用。3D纳米纤维垫的最重要特征之一是密度梯度。这项研究提供了基于实验数据的统计分析和响应表面建模框架,以评估双斜面收集器的几何设计影响纤维密度梯度的方式。特别,进行了分析和灵敏度分析的方差,以确定具有显着影响的参数,并开发了嵌入七个位置指示器的响应面模型,以预测不同收集器设计的纤维密度的空间分布。结论是,收集器高度,斜角以及它们之间的相互作用是影响密度梯度的重要因素。这项研究揭示了系统配置的敏感性,并为微结构梯度的过程可控性提供了优化工具。它们之间的相互作用是影响密度梯度的重要因素。这项研究揭示了系统配置的敏感性,并为微结构梯度的过程可控性提供了优化工具。它们之间的相互作用是影响密度梯度的重要因素。这项研究揭示了系统配置的敏感性,并为微结构梯度的过程可控性提供了优化工具。

更新日期:2020-06-13
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