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Spectral Decomposition of X-ray Absorption Spectroscopy Datasets: Methods and Applications
Crystals ( IF 2.7 ) Pub Date : 2020-08-01 , DOI: 10.3390/cryst10080664 Andrea Martini , Elisa Borfecchia
Crystals ( IF 2.7 ) Pub Date : 2020-08-01 , DOI: 10.3390/cryst10080664 Andrea Martini , Elisa Borfecchia
X-ray absorption spectroscopy (XAS) today represents a widespread and powerful technique, able to monitor complex systems under in situ and operando conditions, while external variables, such us sampling time, sample temperature or even beam position over the analysed sample, are varied. X-ray absorption spectroscopy is an element-selective but bulk-averaging technique. Each measured XAS spectrum can be seen as an average signal arising from all the absorber-containing species/configurations present in the sample under study. The acquired XAS data are thus represented by a spectroscopic mixture composed of superimposed spectral profiles associated to well-defined components, characterised by concentration values evolving in the course of the experiment. The decomposition of an experimental XAS dataset in a set of pure spectral and concentration values is a typical example of an inverse problem and it goes, usually, under the name of multivariate curve resolution (MCR). In the present work, we present an overview on the major techniques developed to realize the MCR decomposition together with a selection of related results, with an emphasis on applications in catalysis. Therein, we will highlight the great potential of these methods which are imposing as an essential tool for quantitative analysis of large XAS datasets as well as the directions for further development in synergy with the continuous instrumental progresses at synchrotron sources.
中文翻译:
X射线吸收光谱数据集的光谱分解:方法和应用
今天的X射线吸收光谱(XAS)代表了一种广泛而强大的技术,能够在原位和操作条件下监视复杂的系统,而外部变量(例如采样时间,样品温度甚至被分析样品上的光束位置)都在变化。X射线吸收光谱法是一种元素选择性但体积平均的技术。每个测得的XAS光谱都可以看作是由研究样品中存在的所有含吸收剂的物种/构型产生的平均信号。因此,所获得的XAS数据由光谱混合物表示,该混合物由与明确定义的组分相关的叠加光谱图组成,其特征是在实验过程中不断变化的浓度值。一组纯XAS实验数据集的分解光谱和浓度值是反问题的典型示例,通常以多变量曲线分辨率(MCR)为名。在当前的工作中,我们将概述为实现MCR分解而开发的主要技术以及相关结果的选择,重点是催化的应用。其中,我们将重点介绍这些方法的巨大潜力,这些方法被用作定量分析大型XAS数据集的基本工具,以及与同步加速器源不断进行的仪器开发协同作用而进一步发展的方向。
更新日期:2020-08-01
中文翻译:
X射线吸收光谱数据集的光谱分解:方法和应用
今天的X射线吸收光谱(XAS)代表了一种广泛而强大的技术,能够在原位和操作条件下监视复杂的系统,而外部变量(例如采样时间,样品温度甚至被分析样品上的光束位置)都在变化。X射线吸收光谱法是一种元素选择性但体积平均的技术。每个测得的XAS光谱都可以看作是由研究样品中存在的所有含吸收剂的物种/构型产生的平均信号。因此,所获得的XAS数据由光谱混合物表示,该混合物由与明确定义的组分相关的叠加光谱图组成,其特征是在实验过程中不断变化的浓度值。一组纯XAS实验数据集的分解光谱和浓度值是反问题的典型示例,通常以多变量曲线分辨率(MCR)为名。在当前的工作中,我们将概述为实现MCR分解而开发的主要技术以及相关结果的选择,重点是催化的应用。其中,我们将重点介绍这些方法的巨大潜力,这些方法被用作定量分析大型XAS数据集的基本工具,以及与同步加速器源不断进行的仪器开发协同作用而进一步发展的方向。