Data-science-based reconstruction of 3-D membrane pore structure using a single 2-D micrograph
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 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.
© This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/
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| Work Title | Data-science-based reconstruction of 3-D membrane pore structure using a single 2-D micrograph |
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| License | CC BY-NC-ND 4.0 (Attribution-NonCommercial-NoDerivatives) |
| Work Type | Article |
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| Publication Date | April 24, 2023 |
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| Deposited | July 24, 2023 |
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