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Mechanochemistry provides polymorphs that are difficult to obtain by conventional solution-based methods. Based on the nicotinamide and pimelic acid cocrystal, we demonstrated that the ball size, frequency, and temperature are essential parameters. Our results indicate that fine-tuning the energy input during a mechanochemical reaction can provide control over polymorphism.
The stability of materials is a very important property for materials discovery. In recent years, we have explored several approaches for advancing the prediction of the stability of crystals (e.g., classical chemical heuristics and machine-learned interatomic potentials). For example, we have assessed a famous chemical heuristic – the Pauling rules – regarding their usefulness for structure prediction. They are only of limited predictive power, i.e. the rules 2 to 5 only work for 13 % of all tested oxides. Furthermore, we have shown that machine-learned interatomic potentials can be used to predict phonon properties of a range of silicon allotropes accurately and, therefore, they can also be used to assess the dynamic stability of materials. To do so, we have developed new schemes to build reference databases for machine learned interatomic potentials.
Ein drastisch hoher Polyethylene Massenanteil wurde bei der Analytik der Umweltproben im Vergleich zu weiteren Polymeren festgestellt. Zu einem Überbefund des Polyethylene können strukturell verwandte Verbindungen wie z.B. Fette durch Signalüberlagerung führen. Mithilfe von beschleunigter Lösemittelextraktion soll die störende Komponente entfernt werden.