Spinning round : High-Performance Computing für maßgeschneiderte Materialien für die Informationstechnologie

Kratzer, Peter GND

Mit Hilfe der Dichtefunktionaltheorie sind wir in der Lage, den Zusammenhang zwischen der atomaren Struktur und den Eigenschaften eines Materials zu erforschen, ohne dass empirisch gewonnene Kenntnisse als Ausgangspunkt benötigt werden. Der Einsatz von High-Performance Computing ermöglicht es uns, diesen parameterfreien wissenschaftlichen Zugang sogar auf komplexe Systeme, zum Beispiel Grenzflächen zwischen zwei Materialien, auszudehnen.

Density functional theory puts us in position to investigate the relationship structure-propertty in materials without having to rely on empirical input. The usage of high performance computing enables us to extend this parameter-free approach to complex atomic structures that are encountered for instance at interfaces between two materials. We are thus in position to carry out computeraided explorative studies of diverse materials combinations, and to tailor the materials properties to specific envisaged applications. Several such applications from the field of spintronics have been presented: For the spin transistor, a magnetic material compatible with silicon is sought for, and we managed to identify manganese silicide as one candidate. For the spin valve and for thermal spin injection, we explored ferromagnetic half metals and identified double layer structures of Heusler alloys as promising. As a future goal, we aim at enhancing the predictive power of our approach by including dynamical materials properties into our modelling. Examples are oscillations of the atoms around their equilibrium positions as well as spin waves in magnetic materials, both of which have an impact on the temperature dependence of the electrical resistivity.



Citation style:
Kratzer, P., 2017. Spinning round: High-Performance Computing für maßgeschneiderte Materialien für die Informationstechnologie. Natur-, Ingenieur- und Wirtschaftswissenschaften - High-Performance und Cloud Computing. https://doi.org/10.17185/duepublico/70375
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