Numerical Study of the Filtration Performance for Electrospun Nanofiber Membranes
Source abstract
Abstract
To solve the limitations of these models for submicron materials like electrospun nanofiber membranes, a numerical simulation was used to construct a three-dimensional model closer to the actual structure to explore the filtration resistance and efficiency of these membranes. Based on the actual polydisperse electrospun nanofiber filter, the three-dimensional structure (fiber diameter 280 nm–1300 nm, thickness 0.0150 mm–0.0240 mm, and solid volume fraction 11.3–17.7%) was reconstructed by GeoDict software. The filtration resistance was simulated with the FlowDict module (surface velocity 6.89 cm/s, 20 °C), and the filtration efficiency was calculated with the FilterDict module (2.5 μm particles, tracking 20,000). The results are compared with the experimental values, Davids empirical formula, Happel model, and Kuwabara model. The results show that the simulated values of filtration resistance are generally higher than the experimental values (deviation ≤ 20%), among which the simulation and experiment have the highest consistency, followed by the Davids formula (such as the relative error of 41.62% at 9% spinning solution concentration), and the Kuwabara model has the largest error (59.86%). The simulated value of filtration efficiency is higher than the experimental value (deviation ≤ 7%), because the model assumes that the particles adhere directly after contacting the fiber, and the actual sliding off is not considered. This study confirms that numerical simulation can efficiently predict the filtration performance of electrospun nanofiber membranes. Therefore, it provides a basis for optimizing material structure by adjusting spinning parameters and promoting the engineering application of submicron filter materials.
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Research context
OpenAlex topics: Electrospun Nanofibers in Biomedical Applications · Aerosol Filtration and Electrostatic Precipitation · Advanced Sensor and Energy Harvesting Materials
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Energy and Environment, Anhui University of Technology, Ma’anshan 243032, China
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