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Applications of Topological Data Analysis (TDA) for Studying Structural Motifs in Amorphous Bi<sub>2</sub>Se<sub>3</sub>

ORAL

Abstract

Topological materials host unique surface properties that are robust to deformations, thus making them excellent candidates for next-generation computer chips and quantum computing hardware components. In topological crystalline materials, periodicity provides the framework to derive topological invariants. However, in amorphous topological materials, this long range order is not present. In this work, we study the application of topological data analysis (TDA), specifically persistent homology, to amorphous Bi2Se3. We show that persistent homology can be used to extract representative structural motifs. We apply persistent homology to an experimentally characterized Bi2Se3 slab and MD-simulated Bi2Se3 structures compared to reference crystalline Bi2Se3 structures to quantify the amount of disorder present. Finally, we determine the relationship between these representative structural motifs and the emergent electronic and topological properties, such as the structural spillage, a topological indicator developed for amorphous systems.

Presenters

  • Elyssa F Hofgard

    Massachusetts Institute of Technology

Authors

  • Elyssa F Hofgard

    Massachusetts Institute of Technology

  • Dmitriy Morozov

    Lawrence Berkeley National Laboratory

  • Musa A Hussien

    Lawrence Berkeley National Laboratory

  • Temuujin Bayaraa

    Lawrence Berkeley National Laboratory

  • Sinead M Griffin

    Lawrence Berkeley National Laboratory, Materials Sciences Division and Molecular Foundry, LBNL, Materials Sciences Division and Molecular Foundry, Berkeley Lab, Lawrence Berkeley National Lab

  • Tess E Smidt

    Massachusetts Institute of Technology