3D nearest neighbor index model combined with Nano-CT to analyze SiC particles in ZrB2–SiC ceramics

Abstract

ZrB2–SiC nanocomposite ceramics are desirable for applications in the aeronautics and astronautics fileds. Analyzing SiC nanoparticles is important for developing ZrB2–SiC ceramics, but due to the limitations of existing methods and the performance of experimental equipment, few methods provide comprehensive three dimensional (3D) characterization and information mining. Therefore, we propose a 3D nearest neighbor index (NNI) model combined with large field of view (LFOV) X-ray nanoscale computed tomography (nano-CT). First, we drew conclusions about 3D NNI by simulating particles with different distribution patterns. We next designed an X-ray LFOV nano-CT experiment, then nondestructively reconstructed and visualized 3D tomographic images of ZrB2–SiC. Finally, we used the 3D NNI model and relevant conclusions to analyze the extracted nanoparticles in samples. The results showed that the 3D NNI model combined with LFOV nano-CT could be used to nondestructively, qualitatively and quantitatively characterize the distribution of SiC nanoparticles in an arbitrary 3D morphological region, and obtain multi-scale information about agglomerates.