High-throughput 3D reconstruction of stochastic heterogeneous microstructures in energy storage materials

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作者
Yanxiang Zhang
Mufu Yan
Yanhong Wan
Zhenjun Jiao
Yu Chen
Fanglin Chen
Changrong Xia
Meng Ni
机构
[1] Harbin Institute of Technology,National Key Laboratory for Precision Hot Processing of Metals, MIIT Key Laboratory of Advanced Structure
[2] University of Science and Technology of China,Function Integrated Materials and Green Manufacturing Technology, School of Materials Science and Engineering
[3] Harbin Institute of Technology,CAS Key Laboratory of Materials for Energy Conversion, Department of Materials Science and Engineering
[4] Georgia Institute of Technology,College of Science
[5] University of South Carolina,Center for Innovative Fuel Cell and Battery Technologies, School of Materials Science and Engineering
[6] The Hong Kong Polytechnic University,Department of Mechanical Engineering
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摘要
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.
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