A review is presented of recent advancements in characterization and automation and how this has led to a new generation of automated serial-sectioning facilities, which has allowed for the analysis of larger 3D datasets with thousands of objects of interest at high resolution. A case study is presented in which the Robotic Serial Sectioning System for 3D (RS^3D) is used to analyze the correlation of the initialization of new grain orientations and defects within additively manufactured 316L steel. Finally, we provide a brief discussion of new technologies including new microscopy methods, machine learning, and sparse sampling that could potentially reduce the effort and cost of collecting and analyzing 3D microstructural data in the near future.

本文介绍了表征和自动化方面的最新进展，以及这如何导致了新一代自动串行切片设备的发展，该设备可以高分辨率分析具有数千个感兴趣对象的大型3D数据集。提出了一个案例研究，其中使用3D机器人连续切片系统（RS ^3D）分析了增材制造316L钢中新晶粒取向的初始化与缺陷的相关性。最后，我们简要讨论了新技术，包括新的显微技术，机器学习和稀疏采样，这些技术有可能在不久的将来减少收集和分析3D微观结构数据的工作量和成本。