Data science approaches for microstructure quantification and feature identification in porous membranes

摘要: Rigorous quantification of porous microstructures exhibiting a wide variety pore shapes, sizes, and their spatial distributions presents significant challenge. In this work, novel data science approaches are used to characterize the complex in membranes, extract salient features at pore-scale. Towards goal, microstructure generator is developed utilized create large ensemble structures covering substantial range measures such as stretched shapes (geometrical anisotropy), porosity, specific surface, sizes. Additionally, morphology real membranes obtained experimentally by high resolution X-ray tomography. The statistical representations for simulated membrane calculated compared rigorously using that based on principal component analyses 2-point correlations. This approach allows an objective measure difference between any two selected microstructures. versatility benefits demonstrated paper.