电子背散射衍射研究进展
Advances in electron backscatter diffraction
摘要：
本文介绍了电子背散射衍射（EBSD）领域的一些最新进展。我们强调如何使用开源算法和开放数据格式来快速开发材料的微观结构洞察力。我们包括使用AstroEBSD基于单像素的EBSD映射和传统的方向映射;其次是无监督的机器学习方法，使用主成分分析和多变量统计，结合精细的模板匹配方法，快速索引方向数据，具有高精度。接下来，我们将使用直接电子探测器捕获的衍射图案与动态模拟进行比较，并将其投影以创建高质量的实验“参考衍射球”。最后，我们使用具有迁移学习和卷积神经网络的监督机器学习对阶段进行分类。
英文摘要：
We present a few recent developments in the field of electron backscatter diffraction (EBSD). We highlight how open source algorithms and open data formats can be used to rapidly to develop microstructural insight of materials. We include use of AstroEBSD for single pixel based EBSD mapping and conventional orientation mapping; followed by an unsupervised machine learning approach using principal component analysis and multivariate statistics combined with a refined template matching method to rapidly index orientation data with high precision. Next, we compare a diffraction pattern captured using direct electron detector with a dynamical simulation and project this to create a high quality experimental "reference diffraction sphere". Finally, we classify phases using supervised machine learning with transfer learning and a convolutional neural network.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
