A method to estimate statistical errors of properties derived from charge‐density modelling. Issue 3 (3rd May 2018)

• Record Type: Journal Article
• Authors: Fournier, Bertrand; Guillot, Benoît; Lecomte, Claude; Escudero-Adán, Eduardo C.; Jelsch, Christian
• Is Part Of: Acta crystallographica. Volume 74:Issue 3(2018:May)
• Page Start: 170
• Page End: 183
• Publication Date: 2018-05-03
• Subjects: Monte Carlo methods -- electron density -- uncertainty -- topology -- intermolecular interactions; Crystallography -- Periodicals; Condensed matter -- Periodicals; 548
• DOI: 10.1107/S2053273318004308
• Languages: English
• ISSNs: 2053-2733

Abstract

Abstract : Errors on molecular properties including the topology of electron density and electrostatics are estimated from a sample of deviating models generated using the variance–covariance matrix issued at the end of the charge‐density refinement. Abstract : Estimating uncertainties of property values derived from a charge‐density model is not straightforward. A methodology, based on calculation of sample standard deviations (SSD) of properties using randomly deviating charge‐density models, is proposed with the MoPro software. The parameter shifts applied in the deviating models are generated in order to respect the variance–covariance matrix issued from the least‐squares refinement. This `SSD methodology' procedure can be applied to estimate uncertainties of any property related to a charge‐density model obtained by least‐squares fitting. This includes topological properties such as critical point coordinates, electron density, Laplacian and ellipticity at critical points and charges integrated over atomic basins. Errors on electrostatic potentials and interaction energies are also available now through this procedure. The method is exemplified with the charge density of compound ( E )‐5‐phenylpent‐1‐enylboronic acid, refined at 0.45 Å resolution. The procedure is implemented in the freely available MoPro program dedicated to charge‐density refinement and modelling.