ArticleScientific reports2025
Hybrid modeling for optimizing electrospun polyurethane nanofibrous membranes in air filtration applications.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed.
- Review
- Electrospun Conductive Composites with Anisotropic Microstructures and Tunable Mechanical Properties for Wearable Bioelectronics.Materials (Basel, Switzerland) · 2026Article
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Authors and funding
2 authors.
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Abstract
Nanofibers have gained recognition as promising materials for air filtration due to their high surface area-to-volume ratio, adjustable porosity, and exceptional mechanical properties. However, optimizing their structural characteristics to maximize filtration efficiency while minimizing pressure drop remains challenging due to the complexity of the electrospinning process. This study presents an artificial intelligence-based methodology to establish relationships between electrospinning parameters, nanofiber morphology, and filtration performance. An advanced statistical approach is used to systematically collect and analyze data, followed by modeling these relationships using artificial neural networks (ANN) and analytical formulas to enhance predictive accuracy. A genetic algorithm (GA) is subsequently utilized to refine electrospinning parameters, facilitating the production of nanofibers with enhanced filtration efficiency and optimized airflow resistance. The optimized nanofiber membranes are validated experimentally to assess their real-world performance. The findings demonstrate the potential of AI-driven design in fine-tuning nanofiber structures for advanced air filtration applications. The optimized sample achieved a filtration efficiency of 96%, a pressure drop of 110.23 Pa, and a quality factor of 0.0297. This study underscores the effectiveness of combining AI with electrospinning to develop high-performance air filtration materials.
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