Surface analysis insight note: Multivariate curve resolution of an X‐ray photoelectron spectroscopy image

IF 1.6 4区 化学 Q4 CHEMISTRY, PHYSICAL
Behnam Moeini, Neal Gallagher, Matthew R. Linford
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引用次数: 1

Abstract

This Insight Note follows a series of three previous insight notes on X‐ray photoelectron spectroscopy image analysis that focused on the importance of analyzing the raw data, the use of summary statistics, and principal component analysis (PCA). The same X‐ray photoelectron spectroscopy image data set was analyzed in all three notes. We now show an analysis of this same data set using multivariate curve resolution (MCR). MCR is a widely used exploratory data analysis method. Because of MCR's nonnegativity constraints, it has the important advantage of producing factors that look like real spectra. That is, both its scores and loadings are positive, so its results are often more interpretable than those from PCA. The requirements for preprocessing data are also, in general, lower for MCR compared with PCA. To help determine the number of factors that best describe the data set, a series of MCR models with different numbers of factors was created. Based on the chemical reasonableness of its factors, a two‐factor model was selected. Scores plots/images show the regions of the image that correspond to these two factors.
表面分析洞察注:X射线光电子能谱图像的多变量曲线分辨率
这篇见解笔记是继之前关于X射线光电子能谱图像分析的一系列三个见解笔记之后,重点是分析原始数据、使用汇总统计和主成分分析(PCA)的重要性。在所有三个笔记中分析了相同的X射线光电子能谱图像数据集。我们现在展示了使用多变量曲线分辨率(MCR)对同一数据集的分析。MCR是一种广泛应用的探索性数据分析方法。由于MCR的非负性约束,它有一个重要的优势,即产生看起来像真实光谱的因子。也就是说,它的分数和负载都是正的,所以它的结果通常比PCA的结果更可解释。一般来说,与PCA相比,MCR对预处理数据的要求也较低。为了帮助确定最能描述数据集的因素数量,我们创建了一系列具有不同数量因素的MCR模型。基于各因素的化学合理性,选择了双因素模型。分数图/图像显示了图像中与这两个因素相对应的区域。
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来源期刊
Surface and Interface Analysis
Surface and Interface Analysis 化学-物理化学
CiteScore
3.30
自引率
5.90%
发文量
130
审稿时长
4.4 months
期刊介绍: Surface and Interface Analysis is devoted to the publication of papers dealing with the development and application of techniques for the characterization of surfaces, interfaces and thin films. Papers dealing with standardization and quantification are particularly welcome, and also those which deal with the application of these techniques to industrial problems. Papers dealing with the purely theoretical aspects of the technique will also be considered. Review articles will be published; prior consultation with one of the Editors is advised in these cases. Papers must clearly be of scientific value in the field and will be submitted to two independent referees. Contributions must be in English and must not have been published elsewhere, and authors must agree not to communicate the same material for publication to any other journal. Authors are invited to submit their papers for publication to John Watts (UK only), Jose Sanz (Rest of Europe), John T. Grant (all non-European countries, except Japan) or R. Shimizu (Japan only).
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