3D characterization of electrospun fiber felts based on a voxelized-dynamic contact coupled model
Year: 2025
Type: article
Abstract: Electrospun fiber mats, as a class of high-performance nonwoven materials, are widely applied in textiles, filtration, medical, and other fields. However, the precise three-dimensional characterization of their microstructure and quantification of volume fraction face challenges such as low resolution, poor computational efficiency, and reliance on expensive experimental imaging. This study aims to develop a computer modeling method independent of experiments, achieving high-precision reconstruction and performance prediction of fiber mats. Methodologically, by simulating the electrospinning deposition process, a parameterized deposition model is constructed, and a solvent-orientation coupled dynamic contact model is proposed, which integrates solvent residual concentration with von Mises orientation distribution and quantifies fiber cross-penetration behavior through adhesion offset equations. The main work includes developing an efficient voxelization algorithm that analyzes fiber-voxel interactions via multi-level detection (center point-corner point-ray penetration) and tolerance compensation mechanisms, enabling rapid calculation of volume fraction. Experimental results demonstrate that the error rate of this method is below 2%, and it remains robust in high fiber density scenarios. This model not only provides a high-precision tool for studying the relationship between microstructure and performance of electrospun materials but can also be extended to multi-process parameter optimization and multi-scale performance prediction, thereby promoting the intelligent design and application of nonwoven materials.
Authors: Yexin Liu, Gaoming Jiang, Bingxian Li, Haisang Liu, Hui Xu, Shukai Tang
Institution: Jiangnan University
Language: English
Subfield: Biomaterials
Field: Materials Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $1,590
Award: G7048165096
OpenAlex ID: W4416598753
