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HL: Fachverband Halbleiterphysik
HL 21: Graphene: Electronic Structure and Excitations (joint session O/HL)
HL 21.4: Vortrag
Dienstag, 18. März 2025, 11:15–11:30, H6
Accelerated Exploration of Defective Graphene Superstructures — •Benedict Saunders1, Lukas Hörmann1,2, and Reinhard Maurer1,2 — 1Department of Chemistry, University of Warwick, Coventry — 2Department of Physics, University of Warwick, Coventry
Graphene has been meticulously studied due to its remarkable mechanical, electrical, and thermal properties. It is well documented that introducing various dopants and defects to the lattice can be used to tune the material’s properties for a specific application, such as in electronics, sensors, or catalysis. In order to design graphene with specific properties, one must achieve precise control over the composition and concentration of defects. This requires a fundamental understanding of the stability of defects and their interaction in a given superstructure. We present a comprehensive method for exploring the configurational space of defective 2D superstructures. We have extended the SAMPLE structure search code to defects in 2D materials. SAMPLE uses Bayesian learning based on sparse Density Functional Theory data for structure exploration. We show the capabilities of our approach for a proof-of-principle application on free-standing graphene with heteroatom defects. Finally, we use the SAMPLE code to gain physical insight into the interactions between these defects, paving the way for effective and rational growth models of topologically designed defective graphene.
Keywords: Thermodynamics; Bayesian Machine learning; Configuration space; Topological Design; Defect Superstructures