  Conventional 2-D scanning electron microscopy (SEM) is commonly used to
rapidly and qualitatively evaluate membrane pore structure. Quantitative 2-D
analyses of pore sizes can be extracted from SEM, but without information about
3-D spatial arrangement and connectivity, which are crucial to the
understanding of membrane pore structure. Meanwhile, experimental 3-D
reconstruction via tomography is complex, expensive, and not easily accessible.
Here, we employ data-science tools to demonstrate a proof-of-principle
reconstruction of the 3-D structure of a membrane using a single 2-D image
pulled from a 3-D tomographic data set. The reconstructed and experimental 3-D
structures were then directly compared, with important properties such as mean
pore radius, mean throat radius, coordination number and tortuosity differing
by less than 15%. The developed algorithm will dramatically improve the ability
of the membrane community to characterize membranes, accelerating the design
and synthesis of membranes with desired structural and transport properties.
