Introduction to Python Dynamic Diffraction Toolkit (PyDDT): structural refinement of single crystals via X-ray phase measurements

Rafaela F S Penacchio; Maurício B Estradiote; Cláudio M R Remédios; Guilherme A Calligaris; Milton S Torikachvili; Stefan W Kycia; Sérgio L Morelhão

doi:10.1107/S1600576723005800

Introduction to Python Dynamic Diffraction Toolkit (PyDDT): structural refinement of single crystals via X-ray phase measurements

J Appl Crystallogr. 2023 Aug 16;56(Pt 5):1574-1584. doi: 10.1107/S1600576723005800. eCollection 2023 Oct 1.

Authors

Rafaela F S Penacchio¹, Maurício B Estradiote¹, Cláudio M R Remédios², Guilherme A Calligaris³, Milton S Torikachvili⁴, Stefan W Kycia⁵, Sérgio L Morelhão¹

Affiliations

¹ Institute of Physics, University of São Paulo, São Paulo, SP, Brazil.
² Faculdade de Física, Universidade Federal do Pará, Belém, PA, Brazil.
³ Brazilian Synchrotron Light Laboratory - SIRIUS/CNPEM, Campinas, SP, Brazil.
⁴ Department of Physics, San Diego State University, San Diego, California, USA.
⁵ Department of Physics, University of Guelph, Guelph, Ontario, Canada.

Abstract

PyDDT is a free Python package of computer codes for exploiting X-ray dynamic multiple diffraction in single crystals. A wide range of tools are available for evaluating the usefulness of the method, planning feasible experiments, extracting phase information from experimental data and further improving model structures of known materials. Graphical tools are also useful in analytical methodologies related to the three-dimensional aspect of multiple diffraction. For general X-ray users, the PyDDT tutorials provide the insight needed to understand the principles of phase measurements and other related methodologies. Key points behind structure refinement using the current approach are presented, and the main features of PyDDT are illustrated for amino acid and filled skutterudite single crystals.

Keywords: Python code; X-ray dynamic diffraction; single crystals; triplet phase determination.

Grants and funding

The following funding is acknowledged: Fundação de Amparo à Pesquisa do Estado de São Paulo (scholarship No. 2021/01004-6 to Rafaela Penacchio; scholarship No. 2022/09531-8 to Mauricio Estradiote; grant No. 2019/01946-1 to Sergio Morelhao); Conselho Nacional de Desenvolvimento Científico e Tecnológico (scholarship No. 310432/2020-0 to Sergio Morelhao); Natural Sciences and Engineering Research Council of Canada (award to Stefan Kycia).