Reconstructed 3D Li-O2 Battery Electrodes

This data set includes a series of 3D battery electrodes reconstructed from NanoCT scans. Each 3D electrode model is derived from a detailed 2D slice with porosity between 0.729 and 0.906. All reconstructed electrodes have standardized dimensions of 300x300x300 voxels, with each voxel measuring 58.2 nm in resolution. The total sample size is 17.46X17.46X17.46 um3. The file names are indicative of the porosity levels of the electrodes, with the first three digits specifying the porosity; for example, a file name starting with 729 corresponds to a porosity of 0.729. Each data file records the (x, y, z) coordinates of the solid phase within the electrode structure, enabling precise spatial analysis. For optimal visualization, we recommend using ParaView, an open-source software for viewing complex 3D data sets. Additionally, the data set can be directly processed using programming languages and environments such as C, C++, Python, or Matlab, catering to a wide range of analytical and computational needs. Further details on the data reconstruction methodology and validation can be found in the paper: A Adam, F Wang, X Li, "Efficient reconstruction and validation of heterogeneous microstructures for energy applications," published in the International Journal of Energy Research, 46 (2022) 22757-22771. This publication provides an in-depth explanation of the techniques and processes employed in generating and validating this extensive data set. In addition, the pore and particle distributions of each digital electrodes are calculated using our customized ED-cPSD tool. The algorithm of this tool is described in detail in the following publication: A. Adam, H. Fang, G. Yang, X. Li, "cED-cPSD: Fast Phase-Size Distribution via Sequential Erosion-Dilation," SoftwareX, 31 (2025) 102211. This tool uses the Meijster algorithm instead of the traditional erosion-dilation algorithm and can be applied to both 2D and 3D geometries. It is approximately 280 times faster than the traditional erosion-dilation algorithm. The code, executable file, and supporting documents can be found at https://github.com/ElsevierSoftwareX/SOFTX-D-25-00235. Please utilize this data set under the instruction of the publication, and we welcome any collaborative efforts to enhance and expand upon this foundational work. Feel free to reach out for further information or clarification as needed. If you find our work useful, please recognize our publication and the GitHub repository in your research outputs or any related works. Thank you!