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Due to their unique structural features, electrospun membranes have gained considerable attention for use in applications where quality of depth filtration is a dominant performance factor. To elucidate the depth filtration phenomena it is important to quantify the intrinsic structural properties independent from the dynamics of transport media. Several methods have been proposed for structural characterization of such membranes. However, these methods do not meet the requirement for the quantification of intrinsic structural properties in depth filtration. This may be due to the complex influence of transport media dynamics and structural elements in the depth filtration process. In addition, the different morphological architectures of electrospun membranes present obstacles to precise quantification. This paper seeks to quantify the structural characteristics of electrospun membranes by introducing a robust image analysis technique and exploiting it to evaluate the permeation-filtration mechanism. To this end, a nanostructured fibrous network was simulated as an ideal membrane using adaptive local criteria in the image analysis. The reliability of the proposed approach was validated with measurements and comparison of structural characteristics in different morphological conditions. The results were found to be well compatible with empirical observations of perfect membrane structures. This approach, based on optimization of electrospinning parameters, may pave the way for producing optimal membrane structures for boosting the performance of electrospun membranes in end-use applications. </p

Simulation of Structural Characteristics and Depth Filtration Elements in Interconnected Nanofibrous Membrane Based on Adaptive Image Analysis