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Solving Crystal Structures from Powder Data. III. The Use of the Probability Distributions for Estimating the | F |'s
Author(s) -
Carrozzini B.,
Giacovazzo C.,
Guagliardi A.,
Rizzi R.,
Burla M. C.,
Polidori G.
Publication year - 1997
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/s0021889896010382
Subject(s) - probabilistic logic , decomposition , amplitude , moduli , crystal structure , invariant (physics) , crystal (programming language) , distribution (mathematics) , marginal distribution , probability distribution , computer science , mathematics , materials science , algorithm , statistical physics , statistics , physics , mathematical analysis , chemistry , crystallography , optics , quantum mechanics , programming language , organic chemistry , random variable , mathematical physics
Decomposition programs of powder patterns play a basic role for crystal structure solution from powder data. Indeed, they provide the structure‐factor amplitudes to which direct or Patterson methods can be applied. The decomposition process is not always satisfactory: large errors in the estimates frequently frustrate any attempt to solve crystal structures. This paper describes a probabilistic method that, integrated with the Le Bail algorithm, is able to improve amplitude estimates. The method uses triplet‐invariant distribution functions, from which marginal distributions estimating structure‐factor moduli were derived.