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钕铁硼磁体纳米级X射线光谱显微镜研究中的无监督数据挖掘

Unsupervised Data Mining in nanoscale X-ray Spectro-Microscopic Study of NdFeB Magnet.

作者信息

Duan Xiaoyue, Yang Feifei, Antono Erin, Yang Wenge, Pianetta Piero, Ermon Stefano, Mehta Apurva, Liu Yijin

机构信息

School of computer, Wuhan University, Wuhan, Hubei 430072, China.

Division of Biomaterials and Bioengineering, Department of Preventive and Restorative Dental Sciences, UCSF, San Francisco, CA 94143-0758, USA.

出版信息

Sci Rep. 2016 Sep 29;6:34406. doi: 10.1038/srep34406.

DOI:10.1038/srep34406
PMID:27680388
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5041149/
Abstract

Novel developments in X-ray based spectro-microscopic characterization techniques have increased the rate of acquisition of spatially resolved spectroscopic data by several orders of magnitude over what was possible a few years ago. This accelerated data acquisition, with high spatial resolution at nanoscale and sensitivity to subtle differences in chemistry and atomic structure, provides a unique opportunity to investigate hierarchically complex and structurally heterogeneous systems found in functional devices and materials systems. However, handling and analyzing the large volume data generated poses significant challenges. Here we apply an unsupervised data-mining algorithm known as DBSCAN to study a rare-earth element based permanent magnet material, NdFeB. We are able to reduce a large spectro-microscopic dataset of over 300,000 spectra to 3, preserving much of the underlying information. Scientists can easily and quickly analyze in detail three characteristic spectra. Our approach can rapidly provide a concise representation of a large and complex dataset to materials scientists and chemists. For example, it shows that the surface of common NdFeB magnet is chemically and structurally very different from the bulk, suggesting a possible surface alteration effect possibly due to the corrosion, which could affect the material's overall properties.

摘要

基于X射线的光谱显微镜表征技术的新进展,使得空间分辨光谱数据的采集速度比几年前提高了几个数量级。这种加速的数据采集,具有纳米级的高空间分辨率以及对化学和原子结构细微差异的敏感性,为研究功能器件和材料系统中存在的层次复杂且结构异质的系统提供了独特的机会。然而,处理和分析所生成的大量数据带来了重大挑战。在此,我们应用一种名为DBSCAN的无监督数据挖掘算法来研究一种基于稀土元素的永磁材料钕铁硼。我们能够将一个超过300,000个光谱的大型光谱显微镜数据集精简至3个,同时保留了大部分基础信息。科学家们能够轻松快速地详细分析这三个特征光谱。我们的方法能够迅速为材料科学家和化学家提供一个大型复杂数据集的简洁表示。例如,它表明常见钕铁硼磁体的表面在化学和结构上与主体有很大不同,这表明可能存在由于腐蚀导致的表面改变效应,而这可能会影响材料的整体性能。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f51c/5041149/f1b809cf506d/srep34406-f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f51c/5041149/98dc5e098bee/srep34406-f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f51c/5041149/8dac093a9ae3/srep34406-f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f51c/5041149/62dc659f64f3/srep34406-f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f51c/5041149/f1b809cf506d/srep34406-f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f51c/5041149/98dc5e098bee/srep34406-f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f51c/5041149/8dac093a9ae3/srep34406-f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f51c/5041149/62dc659f64f3/srep34406-f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f51c/5041149/f1b809cf506d/srep34406-f4.jpg

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