在SasView中实现数值汉高变换对SESANS数据的分析

IF 16.4 1区 化学 Q1 CHEMISTRY, MULTIDISCIPLINARY Accounts of Chemical Research Pub Date : 2020-04-02 DOI:10.3233/jnr-200154
Jurrian Bakker, Adam L. Washington, S. Parnell, A. A. van Well, C. Pappas, W. Bouwman
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引用次数: 4

摘要

SESANS数据分析已在SasView软件包中实现,允许使用各向同性小角度散射(SAS)模型的数值Hankel变换来分析SESANS实验。数值近似的误差比典型的实验误差低三个数量级。SasView的所有高级数据拟合功能(多模型拟合、批量拟合和同时/约束拟合)现在也可用于SESANS,SAS模型拟合SESANS测量的示例证明了这一点。
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Analysis of SESANS data by numerical Hankel transform implementation in SasView
SESANS data analysis has been implemented in the SasView software package, allowing SESANS experiments to be analyzed using a numerical Hankel transformation of isotropic small-angle scattering (SAS) models. The error of the numerical approximation is three orders of magnitude below typical experimental errors. All advanced data fitting features of SasView (multi-model fitting, batch fitting, and simultaneous/constrained fitting) are now also available for SESANS and this is demonstrated by examples of fitting SAS models to SESANS measurements.
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来源期刊
Accounts of Chemical Research
Accounts of Chemical Research 化学-化学综合
CiteScore
31.40
自引率
1.10%
发文量
312
审稿时长
2 months
期刊介绍: Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance. Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.
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