SGK-SSCr PhD prize 2019 for Luzia Germann

Dr. Luzia Germann was awarded for the SGK-SSCr PhD prize 2019 for her outstanding work entitled "Investigation of Solid State Reactions of Molecular Functional Materials by in situ X-ray Powder diffraction". The award was established by the Swiss Society for Crystallography (SGK-SSCr) for the best PhD thesis in crystallography. The prize is open to students of either Swiss nationality, students who earned a PhD from a Swiss University or carried out significant part of the PhD at a Swiss Research Institution. The award ceremony takes place at the annual SGK-SSCr meeting on 4th of September 2019 in Sion, Switzerland, including an invited 30 minutes oral presentation about the PhD work.

The ability to monitor solid-state reactions in real-time is of particular interest, as it allows to elucidate reaction mechanism in addition to study the properties and behavior of reactants and reaction products. This is necessary for a better understanding of material properties. Different methods are commonly used to investigate the in situ solid-state transformations. Most of them are based on spectroscopic, microscopic, or diffraction techniques. XRPD is the method of choice for the characterization of bulk reaction products, phase quantification, refinement of crystal structures for microcrystalline materials, and monitoring of bulk solid-state reactions. During her PhD, Luzia Germann derived crystal structural models ab initio from in situ and ex situ XRPD analysis in combination with solid-state NMR spectroscopy (NMR crystallography) [1]. Furthermore, thermal transformations and decomposition pathways of coordination compounds [2], as well as mechanochemical formation of metal-organic frameworks and a library of pharmaceutical cocrystals was also studied to elucidate their reaction mechanism and kinetics [3].

(a) Time resolved 2D XRPD plot of the mechanochemical formation of a pharmaceutical cocrystal with calculated XRPD patterns of the individual phases above and below the 2D plot. (b) Result of the sequential Rietveld analysis.

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