Solving molecular crystal structures from laboratory X-ray powder diffraction data with DASH: the state of the art and challenges

Florence, A.J. and Shankland, N. and Shankland, K. and David, W.I.F. and Pidcock, E. and Xu, X. and Johnston, A. and Kennedy, A.R. and Cox, P.J. and Evans, J.S.O. and Steele, G. and Cosgrove, S.D. and Frampton, C.S. (2005) Solving molecular crystal structures from laboratory X-ray powder diffraction data with DASH: the state of the art and challenges. Journal of Applied Crystallography, 38 (2). pp. 249-259. ISSN 0021-8898 (http://dx.doi.org/10.1107/S0021889804032662)

Full text not available in this repository.Request a copy

Abstract

The crystal structures of 35 molecular compounds have been redetermined from laboratory monochromatic capillary transmission X-ray powder diffraction data using the simulated-annealing approach embodied within the DASH structure solution package. The compounds represent industrially relevant areas (pharmaceuticals; metal coordination compounds; nonlinear optical materials; dyes) in which the research groups in this multi-centre study are active. The molecules were specifically selected to form a series within which the degree of structural complexity (i.e. degrees of freedom in the global optimization) increased systematically, the degrees of freedom increasing with increasing number of optimizable torsion angles in the structural model and with the inclusion of positional disorder or multiple fragments (counterions; crystallization solvent; Z' > 1). At the lower end of the complexity scale, the structure was solved with excellent reproducibility and high accuracy. At the opposite end of the scale, the more complex search space offered a significant challenge to the global optimization procedure and it was demonstrated that the inclusion of modal torsional constraints, derived from the Cambridge Structural Database, offered significant benefits in terms of increasing the frequency of successful structure solution by restricting the magnitude of the search space in the global optimization.

ORCID iDs

Florence, A.J. ORCID logoORCID: https://orcid.org/0000-0002-9706-8364, Shankland, N., Shankland, K., David, W.I.F., Pidcock, E., Xu, X., Johnston, A., Kennedy, A.R. ORCID logoORCID: https://orcid.org/0000-0003-3652-6015, Cox, P.J., Evans, J.S.O., Steele, G., Cosgrove, S.D. and Frampton, C.S.;