Tino Matthew Peres, Suderman Robert, Abukhdeir Nasser Mohieddin
Department of Chemical Engineering, University of Waterloo, Waterloo, Ontario, Canada.
Google Research, 1600 Amphitheatre Parkway, Mountain View, CA, United States of America.
Nanotechnology. 2024 Feb 2;35(16). doi: 10.1088/1361-6528/ad1df4.
Structure-property relations are of fundamental importance for continued progress in materials research. Determining these relationships for nanomaterials introduces additional challenges, especially when nanostructure is present, either through self-assembly or nano-lithographic processes. Recent advances have been made for quantification of nanostructured surfaces, for which many robust experimental imaging methods exist. One promising approach is based on the use offor image analysis, which may be used as a reduced basis for surface pattern structure resulting from a broad range of phenomena (e.g. self-assembly). These shapelet-based methods enable automated quantification of nanostructured images, guided by the user/researcher, providing pixel-level information of local order without requiring detailed knowledge of order symmetries. In this work, enhancements to the existing shapelet-basedare developed which enable further analysis of local order, including quantification ofand identification of. The presented shapelet-based methods are applied to a representative set of images of self-assembled surfaces from experimental characterization techniques including scanning electron microscopy, atomic force microscopy, and transmission electron microscopy. These methods are shown to be complementary in implementation and, importantly, provide researchers with a robust and generalized computational approach to comprehensively quantify nanostructure order, including local orientation and boundaries within well-aligned grains.
结构-性能关系对于材料研究的持续进展至关重要。确定纳米材料的这些关系带来了额外的挑战，特别是当存在纳米结构时，无论是通过自组装还是纳米光刻工艺。在纳米结构表面的量化方面已经取得了最新进展，为此存在许多强大的实验成像方法。一种有前途的方法是基于使用用于图像分析，它可以用作由广泛现象（例如自组装）产生的表面图案结构的简化基础。这些基于小波的方法能够在用户/研究人员的指导下对纳米结构图像进行自动量化，提供局部有序的像素级信息，而无需详细了解有序对称性。在这项工作中，对现有的基于小波的方法进行了改进，从而能够进一步分析局部有序，包括对……的量化和对……的识别。所提出的基于小波的方法应用于来自实验表征技术（包括扫描电子显微镜、原子力显微镜和透射电子显微镜）的自组装表面的一组代表性图像。这些方法在实施中被证明是互补的，重要的是，为研究人员提供了一种强大且通用的计算方法，以全面量化纳米结构有序，包括排列良好的晶粒内的局部取向和边界。
