Applications of a L1-regularized linear regression to x-ray fluorescence holography data of functional materials
Applications of a L1-regularized linear regression to x-ray fluorescence holography data of functional materials
复制标题
L1-正则线性回归在功能材料 X 射线荧光全息数据中的应用
DOI：
10.1002/pssb.201800089
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发表时间：
2018
期刊：
影响因子：
--
通讯作者：
and T. Matsushita
中科院分区：
文献类型：
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作者：
S. Hosokawa;J. R. Stellhorn;K. Hayashi;and T. Matsushita
为了阐明材料的原子分辨结构特征，采用 X 射线荧光全息术 (XFH) 技术在发射荧光 X 射线的特定元素周围绘制三维 (3D) 原子图像。通过获取荧光 X 射线强度（全息图）的角度依赖性，原则上可以通过简单的傅里叶变换类方法获得周围原子的 3D 图像，无需特殊的原子模型。然而，实际上，需要无数个具有不同入射 X 射线能量的全息图才能在正确的位置再现无伪影的原子图像。相反，这里使用 L1 正则化线性回归的稀疏建模方法应用逆问题来解决这种小数据量的统计问题。该方法在一些功能材料的复杂晶体上取得了优异的结果，例如Mn掺杂Bi2Te3拓扑绝缘体、Fe65Ni35Invar合金和Fe硫族化物高温超导体。
To clarify atom‐resolved structural characterizations of materials, X‐ray fluorescence holography (XFH) technique is employed for drawing three‐dimensional (3D) atomic images around a specific element emitting fluorescent X‐rays. By taking the angle dependences of the fluorescent X‐ray intensity (hologram), 3D images of the surrounding atoms can be, in principle, obtained via simple Fourier transform‐like approaches with no special atomic models. In reality, however, an infinite number of the holograms with different incident X‐ray energies are necessary to reproduce the artifact‐less atomic images at the correct positions. Instead, here an inverse problem is applied using a sparse modeling approach of a L1‐regularized linear regression to solve such statistical problem of a small data size. The excellent results of this approach are presented on complex crystals of some functional materials, such as Mn doped Bi2Te3topological insulator, Fe65Ni35Invar alloy, and Fe chalcogenide high‐temperature superconductor.