Statistical reconstruction of heterogeneous microstructures based on 2D images
Statistical reconstruction of heterogeneous microstructures based on 2D images
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基于二维图像的异质微观结构统计重建
DOI：
10.1117/12.2658951
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发表时间：
2023
期刊：
影响因子：
--
通讯作者：
Wang, Long
中科院分区：
文献类型：
--
作者：
Kessenich, Nathaniel K.;Wang, Long
聚合物纳米复合材料通常具有异质微观结构，显着影响这些材料系统的结构-性能关系。各种显微成像技术，例如光学显微镜、扫描电子显微镜 (SEM) 和 X 射线显微镜，对于表征纳米复合材料系统至关重要，并提供了微观结构特征的信息丰富的见解。然而，当需要大量微观结构数据时，通过实验进行显微成像可能会很昂贵。解决成像限制并更有效地生成大型微观结构数据集的一种有前景的方法是从单个原始输入图像统计重建相似图像。用于生成统计等效图像的常用方法是模拟退火优化算法。然而，由于与模拟退火算法中使用的随机搜索路径相关的高计算成本，以高度一致性重建图像可能具有挑战性。因此，在本研究中，通过操纵搜索路径域和可用的统计信息来优化模拟退火算法，开发了一种新颖且更有效的图像重建方法。实施优化技术来重建几个示例二维 (2D) 图像以评估其功能。
Polymer nanocomposites typically possess heterogeneous microstructures that significantly affect structure-property relationships of these material systems. Various microscopic imaging techniques, such as optical microscopy, scanning electron microscopy (SEM), and X-ray microscopy, are essential for characterizing nanocomposite material systems and have provided informative insights of microstructural features. However, microscopic imaging through experiments can be expensive when large amounts of microstructural data are needed. One promising approach to address the imaging limitation and more efficiently generate large microstructural dataset is to statistically reconstruct similar images from a single original input image. A common method used to generate statistically equivalent images is the simulated annealing optimization algorithm. However, due to the high computational cost associated with the stochastic search path used in the simulated annealing algorithm, it can be challenging to reconstruct images with a high degree of agreement. Thus, in this study, a novel and more efficient image reconstruction method was developed by optimizing the simulated annealing algorithm through the manipulation of search path domain and available statistical information. The optimization technique was implemented to reconstruct several example two-dimensional (2D) images to evaluate its capabilities.