Statistical Reconstruction of 3D Paper Structure Using Simulated Annealing Algorithm Based on 2D Scanning Electron Microscopy Image

The microstructure of fibrous paper plays an important role in its property investigation. In this study, an approach is proposed to extrapolate a 2D image into a virtual 3D microstructure. Five types of handsheets made of different pulps were prepared. Then, a hybrid function of two-point correlation and lineal-path function (S-2&L-2) and co-occurrence correlation functions (CCFs) was used in the simulated annealing reconstruction method. Thus, microstructures of two-phase fiber-pore handsheets were reconstructed using 2D scanning electron microscopy images. Finally, penetration simulations and calculations of the absolute permeability of handsheets were conducted. The statistical values of two-point correlation function (S-2) and lineal-path function (L-2) extracted from the reconstructed images were used to characterize the reconstruction accuracy, and the comparisons of reconstruction accuracy and time were made. The study results showed that the 3D microstructures of fibrous handsheets could be reconstructed effectively by S-2&L-2 and CCFs, identifying with the targets. The accuracies were around 10(-)(5), and the reconstruction times by CCFs were shortened by 30-60% compared with S-2&L-2. Moreover, the visual permeability simulation results could reflect the structural difference of handsheets, according to the calculated absolute permeability. These findings provide a guidance for 3D reconstruction of natural fiber paper.

Automated summary

This study proposes an approach to extrapolate a 2D image into a virtual 3D microstructure and verifies its effectiveness through experiments. The method can be used for 3D reconstruction of fibrous paper and provides information about the paper's properties.