Chemical Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, California, 94720-8226, USA.
Anal Chem. 2010 Oct 1;82(19):7906-14. doi: 10.1021/ac1012909.
We have developed an automated data analysis method for atmospheric particles using scanning transmission X-ray microscopy coupled with near edge X-ray fine structure spectroscopy (STXM/NEXAFS). This method is applied to complex internally mixed submicrometer particles containing organic and inorganic material. Several algorithms were developed to exploit NEXAFS spectral features in the energy range from 278 to 320 eV for quantitative mapping of the spatial distribution of elemental carbon, organic carbon, potassium, and noncarbonaceous elements in particles of mixed composition. This energy range encompasses the carbon K-edge and potassium L2 and L3 edges. STXM/NEXAFS maps of different chemical components were complemented with a subsequent analysis using elemental maps obtained by scanning electron microscopy coupled with energy dispersive X-ray analysis (SEM/EDX). We demonstrate the application of the automated mapping algorithms for data analysis and the statistical classification of particles.
我们开发了一种使用扫描透射 X 射线显微镜结合近边 X 射线精细结构光谱学（STXM/NEXAFS）分析大气粒子的自动化数据分析方法。该方法适用于含有有机和无机物质的复杂内部混合亚微米颗粒。我们开发了几种算法，以利用 NEXAFS 光谱特征在 278 到 320 eV 的能量范围内，对元素碳、有机碳、钾和非碳元素在混合成分颗粒中的空间分布进行定量映射。该能量范围包含碳 K 边缘和钾 L2 和 L3 边缘。不同化学组分的 STXM/NEXAFS 图谱与随后使用扫描电子显微镜结合能量色散 X 射线分析（SEM/EDX）获得的元素图谱的后续分析相补充。我们展示了自动化映射算法在数据分析和粒子统计分类中的应用。
