Probing the effective diffusion coefficient and filtration performance of micro/nanofibrous composite layered filters

Diffusion is an important filtration mechanism of fibrous filters for removing fine particles from gas streams. An analytical model is proposed in this work, based on fractal theory, to quantify the effective diffusion coefficient (EDC) across micro/nanofibrous filters with a layered structure. To show the influence of macroscopic parameters of fibrous filters on EDC, the present models are expressed in terms of fiber diameter. Polyacrylonitrile (PAN) nanofibers were prepared by electrospinning on melt-blown polypropylene (PP) microfiber filter materials to form micro/nanofibrous filters. To validate this model, a three-dimensional (3D) fiber model with physical parameters of the samples was reconstructed using the GeoDict code, and the Brownian movement of nanoparticles was simulated to calculate the EDC. Two kinds of pore size distributions for the layer-structured fibrous filters have been identified, which also shows the internal heterogeneity of the filter media. With decreasing fiber diameter, the tortuosity of the pore channel increases, while the EDC decreases. Compared with the numerical simulation and the experimental data reported in the literature, the current model gives a better theoretical prediction. In addition, the diffusion mechanism in classical filtration theory was modified to reduce the deviation between theoretical prediction and experimental results.