硬x射线纳米xanes和实现多模态化学成像的深度学习工具

A. Pattammattel, R. Tappero, Y. Chu, M. Ge, D. Gavrilov, Xiaojing Huang, Hanfei Yan
{"title":"硬x射线纳米xanes和实现多模态化学成像的深度学习工具","authors":"A. Pattammattel, R. Tappero, Y. Chu, M. Ge, D. Gavrilov, Xiaojing Huang, Hanfei Yan","doi":"10.1117/12.2599526","DOIUrl":null,"url":null,"abstract":"Spectromicroscopy techniques allow the study of local chemical states along with morphology information. At the hard X-ray nanoprobe (HXN) beamline at NSLS-II, we developed nanoscale chemical imaging with high chemical state sensitivity and micron-scale penetration depth. In addition to the chemical images, XRF and phase-contrast images collected simultaneously offer multi-modal, correlative image analysis. We also developed a highly interactive, python-based graphical user interface (NSLS-II MIDAS) that allows multi-modal analysis of nano-XANES and XRF images. Advanced supervised and unsupervised learning algorithms enable users to explore the traditional XANES analysis along with standard machine-learning tools","PeriodicalId":289295,"journal":{"name":"X-Ray Nanoimaging: Instruments and Methods V","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Hard x-ray nano-XANES and implementation deep learning tools for multi-modal chemical imaging\",\"authors\":\"A. Pattammattel, R. Tappero, Y. Chu, M. Ge, D. Gavrilov, Xiaojing Huang, Hanfei Yan\",\"doi\":\"10.1117/12.2599526\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Spectromicroscopy techniques allow the study of local chemical states along with morphology information. At the hard X-ray nanoprobe (HXN) beamline at NSLS-II, we developed nanoscale chemical imaging with high chemical state sensitivity and micron-scale penetration depth. In addition to the chemical images, XRF and phase-contrast images collected simultaneously offer multi-modal, correlative image analysis. We also developed a highly interactive, python-based graphical user interface (NSLS-II MIDAS) that allows multi-modal analysis of nano-XANES and XRF images. Advanced supervised and unsupervised learning algorithms enable users to explore the traditional XANES analysis along with standard machine-learning tools\",\"PeriodicalId\":289295,\"journal\":{\"name\":\"X-Ray Nanoimaging: Instruments and Methods V\",\"volume\":\"4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"X-Ray Nanoimaging: Instruments and Methods V\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1117/12.2599526\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"X-Ray Nanoimaging: Instruments and Methods V","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1117/12.2599526","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

光谱显微镜技术允许研究局部化学状态以及形态信息。在NSLS-II的硬x射线纳米探针(HXN)光束线上,我们开发了具有高化学状态灵敏度和微米级穿透深度的纳米级化学成像。除了化学图像,同时收集的XRF和相衬图像提供了多模态,相关的图像分析。我们还开发了一个高度交互式的、基于python的图形用户界面(NSLS-II MIDAS),允许对纳米xanes和XRF图像进行多模态分析。先进的监督和无监督学习算法使用户能够与标准的机器学习工具一起探索传统的XANES分析
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Hard x-ray nano-XANES and implementation deep learning tools for multi-modal chemical imaging
Spectromicroscopy techniques allow the study of local chemical states along with morphology information. At the hard X-ray nanoprobe (HXN) beamline at NSLS-II, we developed nanoscale chemical imaging with high chemical state sensitivity and micron-scale penetration depth. In addition to the chemical images, XRF and phase-contrast images collected simultaneously offer multi-modal, correlative image analysis. We also developed a highly interactive, python-based graphical user interface (NSLS-II MIDAS) that allows multi-modal analysis of nano-XANES and XRF images. Advanced supervised and unsupervised learning algorithms enable users to explore the traditional XANES analysis along with standard machine-learning tools
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信
小红书