Moisture Effect on Particulate Matter Filtration Performance using Electro-Spun Nanofibers including Density Functional Theory Analysis.

In this study, we use density functional theory (DFT) calculations to investigate the effect of moisture on the performance of three types of nanofiber (NF)-based air-filter media prepared by electrospinning polyvinyl alcohol, polyvinylidene fluoride, and polyacrylonitrile (PAN). Based on the DFT calculations of the intermolecular interactions between the NF-based filter media and water molecules, the PAN-NF filter is expected to exhibit the best performance in the wet state. Experiment studies also successfully demonstrate that the PAN-NF filter medium has better performance in the filtration of particulate matter (PM) than a commercial semi-high efficiency particulate air filter under wet conditions, and these results are in good agreement with the DFT calculation. The PAN-NF filter shows better performance because of its hydrophilic nature and the relatively low thickness the filter medium that allowed fast recovery of its PM-filtration performance.