Ionisation of atoms determined by kappa refinement against 3D electron diffraction data

Ashwin Suresh, Emre Yörük, Małgorzata K. Cabaj, Petr Brázda, Karel Výborný, Ondřej Sedláček, Christian Müller, Hrushikesh Chintakindi, Václav Eigner and Lukáš Palatinus ()
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Ashwin Suresh: Institute of Physics of the Czech Academy of Sciences
Emre Yörük: Institute of Physics of the Czech Academy of Sciences
Małgorzata K. Cabaj: Institute of Physics of the Czech Academy of Sciences
Petr Brázda: Institute of Physics of the Czech Academy of Sciences
Karel Výborný: Institute of Physics of the Czech Academy of Sciences
Ondřej Sedláček: Institute of Physics of the Czech Academy of Sciences
Christian Müller: Institute of Physics of the Czech Academy of Sciences
Hrushikesh Chintakindi: Institute of Physics of the Czech Academy of Sciences
Václav Eigner: Institute of Physics of the Czech Academy of Sciences
Lukáš Palatinus: Institute of Physics of the Czech Academy of Sciences

Nature Communications, 2024, vol. 15, issue 1, 1-17

Abstract: Abstract Conventional refinement strategies used for three-dimensional electron diffraction (3D ED) data disregard the bonding effects between the atoms in a molecule by assuming a pure spherical model called the Independent Atom model (IAM) and may lead to an inaccurate or biased structure. Here we show that it is possible to perform a refinement going beyond the IAM with electron diffraction data. We perform kappa refinement which models charge transfers between atoms while assuming a spherical model. We demonstrate the procedure by analysing five inorganic samples; quartz, natrolite, borane, lutecium aluminium garnet, and caesium lead bromide. Implementation of kappa refinement improved the structure model obtained over conventional IAM refinements and provided information on the ionisation of atoms. The results were validated against periodic DFT calculations. The work presents an extension of the conventional refinement of 3D ED data for a more accurate structure model which enables charge density information to be extracted.

Date: 2024
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DOI: 10.1038/s41467-024-53448-2

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