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Extraction of domain structure information from small-angle scattering patterns of bulk materials

机译:从散装材料的小角度散射图案中提取域结构信息

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摘要

A method is presented that permits the extraction and visualization of topological domain structure information contained in small-angle scattering (SAS) patterns without complex pretreatment. Multi-dimensional noisy raw data can be processed. Such data are, for instance, accumulated in the field of materials research from short-exposure-time in situ small-angle X-ray scattering (SAXS) experiments wit synchrotron radiation. The result is a multidimensional intersect or chord distribution, which is defined as the Laplacian of the correlation function. Moreover, it is equivalent to the autocorrelation of the gradient of the electron density. The procedure is, in particular, adapted to the analysis of the nanoscale structure of samples with fibre symmetry, such as polymer fibres or strained elastomers. Multi-dimensional relations among morphological components become apparent in real space and help to elucidate the nature of the processes governing formation And change of structure on the nanometre scale. Utilizing digital signal processing tools, the algorithm is based on spatial frequency filtering of the raw data. The background to be subtracted from the small-angle scattering pattern is formed from its own low spatial frequencies. Noise may be removed by suppressing high spatial frequencies. In the frequency band between these low and high spatial frequencies, the domain structure information of the studied nanocomposite appears. [References: 34]
机译:提出了一种无需复杂的预处理就可以提取和可视化包含在小角度散射(SAS)模式中的拓扑域结构信息的方法。可以处理多维嘈杂的原始数据。例如,这些数据是在材料研究领域中通过同步辐射辐射的短时原位小角X射线散射(SAXS)实验获得的。结果是多维相交或和弦分布,其定义为相关函数的拉普拉斯算子。此外,它等效于电子密度梯度的自相关。该程序尤其适合于分析具有纤维对称性的样品(例如聚合物纤维或应变弹性体)的纳米级结构。形态成分之间的多维关系在现实空间中变得显而易见,并有助于阐明在纳米尺度上控制形成和结构变化的过程的性质。利用数字信号处理工具,该算法基于原始数据的空间频率滤波。从小角度散射图案减去的背景由其自身的低空间频率形成。可以通过抑制高空间频率来消除噪声。在这些低空间频率和高空间频率之间的频带中,出现了所研究的纳米复合材料的畴结构信息。 [参考:34]

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