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Extracting the differential inverse inelastic mean free path and differential surface excitation probability of Tungsten from X-ray photoelectron spectra and electron energy loss spectra

机译:从X射线光电子能谱和电子能量损失谱中提取钨的微分逆非弹性平均自由程和微分表面激发概率

摘要

Precise knowledge of the differential inverse inelastic mean free path (DIIMFP) and differential surface excitation probability (DSEP) of Tungsten is essential for many fields of material science. In this paper, a fitting algorithm is applied for extracting DIIMFP and DSEP from X-ray photoelectron spectra and electron energy loss spectra. The algorithm uses the partial intensity approach as a forward model, in which a spectrum is given as a weighted sum of cross-convolved DIIMFPs and DSEPs. The weights are obtained as solutions of the Riccati and Lyapunov equations derived from the invariant imbedding principle. The inversion algorithm utilizes the parametrization of DIIMFPs and DSEPs on the base of a classical Lorentz oscillator. Unknown parameters of the model are found by using the fitting procedure, which minimizes the residual between measured spectra and forward simulations. It is found that the surface layer of Tungsten contains several sublayers with corresponding Langmuir resonances. The thicknesses of these sublayers are proportional to the periods of corresponding Langmuir oscillations, as predicted by the theory of R.H. Ritchie.
机译:精确了解钨的差分逆无弹性平均自由程(DIIMFP)和差分表面激发概率(DSEP)对于材料科学的许多领域都是必不可少的。本文应用拟合算法从X射线光电子能谱和电子能量损失谱中提取DIIMFP和DSEP。该算法使用部分强度方法作为正向模型,其中频谱是交叉卷积的DIIMFP和DSEP的加权和。获得的权重是从不变嵌入原理导出的Riccati和Lyapunov方程的解。该反演算法在传统的洛伦兹振荡器的基础上利用DIIMFP和DSEP的参数化。通过使用拟合过程可以找到模型的未知参数,该过程可以最大程度地减少实测光谱和正向模拟之间的残差。发现钨的表面层包含具有相应的朗缪尔共振的几个亚层。如R.H.Ritchie的理论所预言的,这些子层的厚度与相应的Langmuir振荡的周期成比例。

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