Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/80644
Title: High-throughput 3D reconstruction of stochastic heterogeneous microstructures in energy storage materials
Authors: Zhang, Y
Yan, M
Wan, Y
Jiao, Z
Chen, Y
Chen, F
Xia, C
Ni, M 
Issue Date: 2019
Publisher: Nature Publishing Group
Source: NPJ computational materials, 2019, v. 5, no. 1, 11 How to cite?
Journal: NPJ computational materials 
Abstract: Stochastic heterogeneous microstructures are widely applied in structural and functional materials, playing a crucial role in determining their performance. X-ray tomography and focused ion beam serial sectioning are frequently used methods to reconstruct three-dimensional (3D) microstructures, yet are demanding techniques and are resolution-limited. Here, a high-throughput multi-stage 3D reconstruction method via distance correlation functions is developed using a single representatively large-sized 2D micrograph for stochastic microstructures, and verified by X-ray micro-tomography datasets of isotropic and anisotropic solid oxide fuel cell electrodes. This method provides an economic, easy-to-use and high-throughput approach for reconstructing stochastic heterogeneous microstructures for energy conversion and storage devices, and can readily be extended to other materials.
URI: http://hdl.handle.net/10397/80644
EISSN: 2057-3960
DOI: 10.1038/s41524-019-0149-4
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