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Stochastic fitting of specular X‐ray reflectivity data using StochFit
Author(s) -
Danauskas Stephen M.,
Li Dongxu,
Meron Mati,
Lin Binhua,
Lee Ka Yee C.
Publication year - 2008
Publication title -
journal of applied crystallography
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.429
H-Index - 162
ISSN - 1600-5767
DOI - 10.1107/s0021889808032445
Subject(s) - specular reflection , electron density , x ray reflectivity , computer science , set (abstract data type) , software , interface (matter) , algorithm , probability density function , parameter space , reflectivity , optics , statistical physics , electron , computational physics , physics , mathematics , statistics , bubble , quantum mechanics , maximum bubble pressure method , parallel computing , programming language
Specular X‐ray reflectivity data provide detailed information on the electron density distribution at an interface. Typical modeling methods involve choosing a generic electron density distribution based on an initial speculation of the electron density profile from the physical parameters of the experimental system. This can lead to a biased set of solutions. StochFit provides stochastic model‐independent and model‐dependent methods for analyzing X‐ray reflectivities of thin films at an interface. StochFit divides an electron density profile into many small boxes and stochastically varies the electron density of these boxes to locate the best fit to a measured reflectivity. Additionally, it provides the ability to perform model‐dependent fitting with a stochastic search of the parameter space in order to locate the best possible fit. While model‐independent profile search algorithms have been described previously, they are difficult to implement because of the heavy computational requirements, and there is a dearth of software available to the general scientific public utilizing these techniques. Several cases that illustrate the usefulness of these techniques are presented, with a demonstration of how they can be used in tandem.

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