Data mining in organic crystallography
Springer Verlag, Volume 134, page 89--135 - 2009
Large data bases of crystal structures existing nowadays, give prospects of data mining. In this chapter we will demonstrate the derivation of an empirical force field from experimental data base and its application to the most challenging questions to be solved in structural organic crystallography, e.g. estimation of sublimation energy, crystal structure prediction, and crystal engineering. Another example of data mining given in chapter - the clustering of crystal structures. This approach allows to recognize similarities between crystals and to remove manifold entrances in virtual and experimental databases.
Références BibTex
@InBook{Hof09a,
author = {Hofmann, D.},
title = {Data mining in organic crystallography},
chapter = {Data Mining in Organic Crystallography},
series = {Structure and Bonding},
volume = {134},
pages = {89--135},
year = {2009},
publisher = {Springer Verlag},
address = {Heidelberg},
note = {isbn: ISBN: 978-3-642-04758-9 idxproject: ? editor: Detlef W. M. Hofmann and Liudmila N. Kuleshova},
type = {inbook},
keywords = {Data Mining, Organic Crystallography, Crystal structure prediction},
url = {https://publications.crs4.it/pubdocs/2009/Hof09a},
}