Nietzold Tara, West Bradley M, Stuckelberger Michael, Lai Barry, Vogt Stefan, Bertoni Mariana I
School for Engineering of Matter, Transport, and Energy, Arizona State University.
School of Electrical, Computer, and Energy Engineering, Arizona State University.
J Vis Exp. 2018 Feb 17(132):56042. doi: 10.3791/56042.
The quantification of X-ray fluorescence (XRF) microscopy maps by fitting the raw spectra to a known standard is crucial for evaluating chemical composition and elemental distribution within a material. Synchrotron-based XRF has become an integral characterization technique for a variety of research topics, particularly due to its non-destructive nature and its high sensitivity. Today, synchrotrons can acquire fluorescence data at spatial resolutions well below a micron, allowing for the evaluation of compositional variations at the nanoscale. Through proper quantification, it is then possible to obtain an in-depth, high-resolution understanding of elemental segregation, stoichiometric relationships, and clustering behavior. This article explains how to use the MAPS fitting software developed by Argonne National Laboratory for the quantification of full 2-D XRF maps. We use as an example results from a Cu(In,Ga)Se2 solar cell, taken at the Advanced Photon Source beamline 2-ID-D at Argonne National Laboratory. We show the standard procedure for fitting raw data, demonstrate how to evaluate the quality of a fit and present the typical outputs generated by the program. In addition, we discuss in this manuscript certain software limitations and offer suggestions for how to further correct the data to be numerically accurate and representative of spatially resolved, elemental concentrations.
通过将原始光谱拟合到已知标准来对X射线荧光(XRF)显微镜图像进行定量分析,对于评估材料中的化学成分和元素分布至关重要。基于同步加速器的XRF已成为各种研究课题不可或缺的表征技术,特别是由于其无损性质和高灵敏度。如今,同步加速器能够以远低于微米的空间分辨率获取荧光数据,从而能够评估纳米尺度上的成分变化。通过适当的定量分析,进而有可能深入、高分辨率地了解元素偏析、化学计量关系和聚集行为。本文介绍了如何使用阿贡国家实验室开发的MAPS拟合软件对完整的二维XRF图像进行定量分析。我们以在阿贡国家实验室先进光子源2-ID-D光束线采集的铜铟镓硒(Cu(In,Ga)Se2)太阳能电池的结果为例。我们展示了拟合原始数据的标准程序,演示了如何评估拟合质量,并展示了该程序生成的典型输出。此外,我们在本手稿中讨论了某些软件限制,并就如何进一步校正数据以使其在数值上准确且能代表空间分辨的元素浓度提供了建议。