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

Yanxiang Zhang, Mufu Yan, Yanhong Wan, Zhenjun Jiao, Yu Chen, Fanglin Chen, Changrong Xia, Meng Ni

Research output: Journal article publicationJournal articleAcademic researchpeer-review

11 Citations (Scopus)

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.

Original languageEnglish
Article number11
Journalnpj Computational Materials
Volume5
Issue number1
DOIs
Publication statusPublished - 1 Dec 2019

ASJC Scopus subject areas

  • Modelling and Simulation
  • Materials Science(all)
  • Mechanics of Materials
  • Computer Science Applications

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