Pauw Brian R, Pedersen Jan Skov, Tardif Samuel, Takata Masaki, Iversen Bo B
Centre for Materials Crystallography, Department of Chemistry and iNANO, Aarhus University, DK-8000 Aarhus, Denmark ; Structural Materials Science Laboratory, RIKEN SPring-8 Centre, Hyogo 679-5148, Japan ; International Centre for Young Scientists, National Institute of Materials Science, Tsukuba 305-0047, Japan.
J Appl Crystallogr. 2013 Apr 1;46(Pt 2):365-371. doi: 10.1107/S0021889813001295. Epub 2013 Feb 14.
Monte Carlo (MC) methods, based on random updates and the trial-and-error principle, are well suited to retrieve form-free particle size distributions from small-angle scattering patterns of non-interacting low-concentration scatterers such as particles in solution or precipitates in metals. Improvements are presented to existing MC methods, such as a non-ambiguous convergence criterion, nonlinear scaling of contributions to match their observability in a scattering measurement, and a method for estimating the minimum visibility threshold and uncertainties on the resulting size distributions.
基于随机更新和试错原理的蒙特卡罗（MC）方法，非常适合从非相互作用低浓度散射体（如溶液中的颗粒或金属中的沉淀物）的小角散射图案中获取无形式的粒度分布。本文提出了对现有MC方法的改进，例如明确的收敛标准、贡献的非线性缩放以匹配其在散射测量中的可观测性，以及一种估计最小可见度阈值和所得粒度分布不确定性的方法。
