Kohlbrecher Joachim, Breßler Ingo
Laboratory for Neutron Scattering and Imaging, Paul Scherrer Institut, 5232 Villigen PSI, Switzerland.
BAM Federal Institute for Materials Research and Testing, 12205 Berlin, Germany.
J Appl Crystallogr. 2022 Nov 21;55(Pt 6):1677-1688. doi: 10.1107/S1600576722009037. eCollection 2022 Dec 1.
Small-angle scattering is an increasingly common method for characterizing particle ensembles in a wide variety of sample types and for diverse areas of application. has been one of the most comprehensive and flexible curve-fitting programs for decades, with many specialized tools for various fields. Here, a selection of enhancements and additions to the program are presented that may be of great benefit to interested and advanced users alike: () further development of the technical basis of the program, such as new numerical algorithms currently in use, a continuous integration practice for automated building and packaging of the software, and upgrades on the plug-in system for easier adoption by third-party developers; () a selection of new form factors for anisotropic scattering patterns and updates to existing form factors to account for multiple scattering effects; () a new type of a very flexible distribution called metalog [Keelin (2016). , 243-277], and regularization techniques such as the expectation-maximization method [Dempster (1977). , , 1-22; Richardson (1972) , 55; Lucy (1974). , 745; Lucy (1994). , 983-994], which is compared with fits of analytical size distributions via the non-linear least-squares method; and () new structure factors, especially for ordered nano- and meso-scaled material systems, as well as the Ornstein-Zernike solver for numerical determination of particle interactions and the resulting structure factor when no analytical solution is available, with the aim of incorporating its effects into the small-angle scattering intensity model used for fitting with .
小角散射是一种越来越常见的方法，用于表征各种样品类型中的粒子集合体，并应用于不同领域。几十年来，它一直是最全面、最灵活的曲线拟合程序之一，拥有许多适用于各个领域的专业工具。本文介绍了该程序的一系列增强功能和新增内容，这些内容可能对感兴趣的高级用户都大有裨益：（1）程序技术基础的进一步发展，例如当前正在使用的新数值算法、软件自动构建和打包的持续集成实践，以及插件系统的升级，以便第三方开发者更易于采用；（2）为各向异性散射图案选择了新的形状因子，并对现有形状因子进行了更新，以考虑多重散射效应；（3）一种新型的非常灵活的分布，称为超对数分布[基林（2016年）。《统计软件杂志》，243 - 277页]，以及正则化技术，如期望最大化方法[邓普斯特等人（1977年）。《皇家统计学会学报B辑（方法学）》，39卷，1 - 22页；理查森（1972年）。《皇家统计学会学报B辑（方法学）》，34卷，55页；露西（1974年）。《天文学杂志》，79卷，745页；露西（1994年）。《皇家统计学会学报B辑（方法学）》，56卷，983 - 994页]，并通过非线性最小二乘法将其与解析尺寸分布的拟合结果进行比较；以及（4）新的结构因子，特别是用于有序纳米和介观尺度材料系统的结构因子，以及用于在没有解析解时数值确定粒子相互作用和由此产生的结构因子的奥恩斯坦 - 泽尔尼克求解器，目的是将其效应纳入用于与该程序拟合的小角散射强度模型中。
