電子背散射衍射的研究進展
我們介紹了電子背散射衍射(EBSD)領(lǐng)域的一些最新進展。 我們強調(diào)如何使用開源算法和開放數(shù)據(jù)格式來快速開發(fā)材料的微觀結(jié)構(gòu)洞察力。 我們將 AstroEBSD 用于基于單像素的 EBSD mapping和常規(guī)的取向mapping; 其次是使用主成分分析和多變量統(tǒng)計結(jié)合精細模板匹配方法的無監(jiān)督機器學習方法,以高精度快速索引取向數(shù)據(jù)。 接下來,我們將使用直接電子探測器捕獲的衍射圖案與動態(tài)模擬進行比較,并將其投影以創(chuàng)建高質(zhì)量的實驗“參考衍射球”。 最后,我們使用帶有轉(zhuǎn)移學習和卷積神經(jīng)網(wǎng)絡的監(jiān)督機器學習對階段進行分類。
Advances in electron backscatter diffraction
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 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.
原文鏈接:
文中使用的直接電子探測器是選用的捷克Advacam公司的Minipix電子,離子、質(zhì)子及X射線多功能探測器(點擊了解詳情)。