Numerical Study of the Filtration Performance for Electrospun Nanofiber Membranes

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 pol...

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Main Authors: Wenyuan Hu, Fuping Qian, Simin Cheng, Lumin Chen, Xiao Ma, Huaiyu Zhong
Format: Article
Language:English
Published: MDPI AG 2025-08-01
Series:Applied Sciences
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Online Access:https://www.mdpi.com/2076-3417/15/15/8667
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author Wenyuan Hu
Fuping Qian
Simin Cheng
Lumin Chen
Xiao Ma
Huaiyu Zhong
author_facet Wenyuan Hu
Fuping Qian
Simin Cheng
Lumin Chen
Xiao Ma
Huaiyu Zhong
author_sort Wenyuan Hu
collection DOAJ
description 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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spelling doaj-art-5f9b9874ef034862b9f9629c51fee3402025-08-20T03:35:58ZengMDPI AGApplied Sciences2076-34172025-08-011515866710.3390/app15158667Numerical Study of the Filtration Performance for Electrospun Nanofiber MembranesWenyuan Hu0Fuping Qian1Simin Cheng2Lumin Chen3Xiao Ma4Huaiyu Zhong5School of Energy and Environment, Anhui University of Technology, Ma’anshan 243032, ChinaSchool of Energy and Environment, Anhui University of Technology, Ma’anshan 243032, ChinaSchool of Energy and Environment, Anhui University of Technology, Ma’anshan 243032, ChinaSchool of Energy and Environment, Anhui University of Technology, Ma’anshan 243032, ChinaSchool of Energy and Environment, Anhui University of Technology, Ma’anshan 243032, ChinaSchool of Energy and Environment, Anhui University of Technology, Ma’anshan 243032, ChinaTo 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.https://www.mdpi.com/2076-3417/15/15/8667electrospinningnanofibermembranesfiltration performancenumerical simulation
spellingShingle Wenyuan Hu
Fuping Qian
Simin Cheng
Lumin Chen
Xiao Ma
Huaiyu Zhong
Numerical Study of the Filtration Performance for Electrospun Nanofiber Membranes
Applied Sciences
electrospinning
nanofibermembranes
filtration performance
numerical simulation
title Numerical Study of the Filtration Performance for Electrospun Nanofiber Membranes
title_full Numerical Study of the Filtration Performance for Electrospun Nanofiber Membranes
title_fullStr Numerical Study of the Filtration Performance for Electrospun Nanofiber Membranes
title_full_unstemmed Numerical Study of the Filtration Performance for Electrospun Nanofiber Membranes
title_short Numerical Study of the Filtration Performance for Electrospun Nanofiber Membranes
title_sort numerical study of the filtration performance for electrospun nanofiber membranes
topic electrospinning
nanofibermembranes
filtration performance
numerical simulation
url https://www.mdpi.com/2076-3417/15/15/8667
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