Quantifying nanoscale order in amorphous materials: simulating fluctuation electron microscopy of amorphous silicon
Quantifying nanoscale order in amorphous materials: simulating fluctuation electron microscopy of amorphous silicon
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DOI：
10.1088/0953-8984/19/45/455204
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发表时间：
2007-11
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影响因子：
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通讯作者：
S. Bogle;P. Voyles;S. Khare;J. Abelson
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作者：
S. Bogle;P. Voyles;S. Khare;J. Abelson
涨落电子显微镜对非晶态材料中的三体和四体原子关联函数非常敏感；这足以证明纳米尺度上结构有序的存在，即使从衍射数据中提取的径向分布函数看起来完全是非晶态的。然而，将有限元数据转化为结构的定量模型仍然是一个艰巨的挑战。在这里，我们通过正演模拟一系列高质量原子模型的有限元数据来量化a-Si的有限元方法。利用改进的WWW方法，我们建立了非晶基质中含有10-40vol%的直径为1-3 nm的拓扑晶体颗粒的计算模型，并计算了由暗场像的统计方差V(K)作为散射矢量k的函数组成的有限元信号，我们证明了V(K)是非晶基质中有序区域的尺寸和体积分数的复函数。然而，作为k的函数的方差峰值的比率提供了有序区域的大小；而方差的大小提供了对体积分数的半定量测量。我们还比较了在有序区域中包含不同数量应变的模型。这一分析表明，现实模型中的应变量足以在高k处消除方差峰值。我们将模型结果与实验数据进行了比较。
Fluctuation electron microscopy (FEM) is explicitly sensitive to 3- and 4-body atomic correlation functions in amorphous materials; this is sufficient to establish the existence of structural order on the nanoscale, even when the radial distribution function extracted from diffraction data appears entirely amorphous. However, it remains a formidable challenge to invert the FEM data into a quantitative model of the structure. Here, we quantify the FEM method for a-Si by forward simulating the FEM data from a family of high quality atomistic models. Using a modified WWW method, we construct computational models that contain 10–40 vol% of topologically crystalline grains, 1–3 nm in diameter, in an amorphous matrix and calculate the FEM signal, which consists of the statistical variance V (k) of the dark-field image as a function of scattering vector k. We show that V (k) is a complex function of the size and volume fraction of the ordered regions present in the amorphous matrix. However, the ratio of the variance peaks as a function of k affords the size of the ordered regions; and the magnitude of the variance affords a semi-quantitative measure of the volume fraction. We have also compared models that contain various amounts of strain in the ordered regions. This analysis shows that the amount of strain in realistic models is sufficient to mute variance peaks at high k. We conclude with a comparison between the model results and experimental data.