Regensburg 2025 – wissenschaftliches Programm
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KFM: Fachverband Kristalline Festkörper und deren Mikrostruktur
KFM 8: (Multi)ferroic States: From Fundamentals to Applications (III)
KFM 8.7: Vortrag
Dienstag, 18. März 2025, 11:15–11:30, H9
Ferroelectric and piezoelectric molecular crystals: From database mining to computational design — •Kristian Berland1, Elin D. Sødahl1, Seyedmojtaba Seyedraofi1, Carl H Gørbitz2, Ola Nilsen2, Manjunath Balagopalan2, Maxi Litterst3, Martijn Kemerink3, Jesus Carrete4, Georg K. H. Madsen4, Graeme Day5, and Julian Walker6 — 1NMBU, Ås, Norway — 2U. Oslo, Norway — 3Heidelberg University, Heidelberg, Germany — 4TU Wien, Vienna, Austria — 5U. Southampton, UK — 6NTNU, Trondheim, Norway
Molecular crystals offer great potential for piezoelectric and ferroelectric devices due to their vast chemical tuneability. Plastic (ionic) crystals hosts malleable orientationally disordered mesophases and their rotational freedom can yield high shear piezoelectric response[CrystGrowthDes. 2023, 23, 729]. Proton-transfer Making new crystals with desired properties, however, is not straightforward. We devised new tools to screen the Cambridge Structural Database (CSD), identifying 60 new potential ferroelectrics[PhysRevMaterials 8, 054413, 2024; CrystGrowthDes 2023, 23, 8607], 5 of which we have experimentally confirmed. Crystal structure prediction (CSP) was used to design additional ones [arXiv:2410.20481]. Finally, machine-learning force fields (MLFFs) can provide insight into dynamical properties of mesopphases [arXiv:2410.15746]. With these examples, I will argue how computational methods can be pivotal in advancing the field of small-molecule ferroic crystals.
Keywords: Machine learning force fields; Cambridge crystallographic database; Crystal structure prediction; Ferroelectricity; Piezoelectricity