Data-science-based reconstruction of 3-D membrane pore structure using a single 2-D micrograph

Hooman Chamani

doi:10.1016/j.memsci.2023.121673

Data-science-based reconstruction of 3-D membrane pore structure using a single 2-D micrograph

2023-07-01

8

OA

AI

Jason Hattrick‐Simpers *

J

Jay R. Werber *

DOI：10.1016/j.memsci.2023.121673

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Abstract

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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 in-formation 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 al-gorithm could dramatically improve the ability of the membrane community to characterize membranes, accelerating the design and synthesis of membranes with desired structural and transport properties.

Keywords:

Data science

3-D reconstruction

Membrane microstructure

Electron microscopy

Pore analysis

Data-science-based reconstruction of 3-D membrane pore structure using a single 2-D micrograph

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