Bayesian inference of nanoparticle-broadened x-ray line profiles

2019-08-14 06:46:54

distribution size experimental bayesian ray

责任者: Armstrong, Nicholas;Kalceff, Walter;Cline, James P.;Bonevich, John E. 单位: University of Technology Sydney, Broadway, NSW 2007, Australia 来源出处: Journal of Research of the National Institute of Standards and Technology,2004,109(1):155-178 摘要: A single-step, self-contained method for determining the crystallite-size distribution and shape from experimental x-ray line profile data is presented. It is shown that the crystallite-size distribution can be determined without invoking a functional form for the size distribution, determining instead the size distribution with the least assumptions by applying the Bayesian/MaxEnt method. The Bayesian/MaxEnt method is tested using both simulated and experimental CeO2 data, the results comparing favourably with experimental CeO2 data from TEM measurements. 关键词: Nanostructured materials;Crystalline materials;Fuzzy control;X ray analysis;Entropy;Particle size analysis;Data acquisition;Microstructure;Inverse problems;Parameter estimation;Functions;Boundary conditions;Bayesian;Fuzzy pixel;Instrumental broadening;Maximum entropy;X-ray line profiles;Nanoparticles;Size broadening;Size distribution