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

ABSTRACT

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 (S₂&L₂) 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 (S₂) and lineal-path function (L₂) 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 S₂&L₂ 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 S₂&L₂. 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.

摘要

本研究提出了一种由纸张的2D扫描电子显微镜 (SEM) 图像重建其3D微结构的方法。制备了5种纤维的手抄纸, 分别采用两点相关和复合线性路径函数 (S₂&L₂) 以及共现相关函数(CCFs) 的模拟退火方法,基于SEM图像, 重构了纸张的3D微观结构, 并用图像的S₂和L₂函数来表征重建精度, 最后进行了纸张渗透性能的模拟。结果表明, S₂&L₂和CCFs可以有效重建纸张3D微观结构, 重建精度约为10⁻⁵; CCFs的重建时间比S₂&L₂缩短30%-60%;渗透模拟结果与计算的绝对渗透率保持一致。.

KEYWORDS:

• Microstructure
• three-dimensional reconstruction
• paper sheets
• simulated annealing reconstruction
• simulation
• permeability

Acknowledgments

The authors appreciate the support provided by the Joint Research for International Cooperation on Scientific and Technological Innovation by MOST (2017YFE0184900) and the National Natural Science Foundation of Guangdong Province, China (2021A1515010327).

Disclosure statement

No potential conflict of interest was reported by the author(s).

Ethical approval

We confirm that all the research meets ethical guidelines and adheres to the legal requirements of the study country. The research does not involve any human or animal welfare-related issues.

Supplementary material

Supplemental data for this article can be accessed online at https://doi.org/10.1080/15440478.2022.2107141

Additional information

Funding

This research was supported by the [Joint Research for International Cooperation on Scientific and Technological Innovation] under Grant [number 2017YFE0184900]; and [National Natural Science Foundation of Guangdong Province, China] under Grant [number 2021A1515010327].