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Unconventional Resistivity Scaling in Topological Semimetal CoSi

ORAL

Abstract

Nontrivial band topologies in semimetals lead to robust surface states that can contribute dominantly to the total conduction. This may result in reduced resistivity with decreasing feature size contrary to conventional metals, which may highly impact the semiconductor industry. Here we study the resistivity scaling of a representative topological semimetal CoSi using realistic band structures and Green’s function methods. We show that there exists a critical thickness dc dividing different scaling trends. Above dc, when the defect density is low such that surface conduction dominates, resistivity reduces with decreasing thickness; when the defect density is high such that bulk conduction dominates, resistivity increases as in conventional metals. Below dc, the persistent remnants of the surface states give rise to decreasing resistivity down to the ultrathin limit, unlike in topological insulators. The observed CoSi scaling can apply to broad classes of topological semimetals, providing guidelines for materials screening and engineering. Our study shows that topological semimetals bear the potential of overcoming the resistivity scaling challenges in back-end-of-line interconnect applications.

Publication: https://arxiv.org/abs/2209.06135

Presenters

  • Hsin Lin

    Academia Sinica

Authors

  • Hsin Lin

    Academia Sinica

  • Shang-Wei Lien

    National Cheng Kung University, Department of Physics, National Cheng Kung University, Tainan 701, Taiwan

  • Ion Garate

    Universite de Sherbrooke

  • Utkarsh Bajpai

    IBM Research, IBM Research, 257 Fuller Road, Albany, NY 12203, USA

  • Cheng-Yi Huang

    Northeastern University

  • Chuang-Han Hsu

    Natl Univ of Singapore

  • Yi-Hsin Tu

    National Cheng Kung University, Department of Physics, National Cheng Kung University, Tainan 701, Taiwan

  • Nicholas A Lanzillo

    IBM Research, IBM Research, 257 Fuller Road, Albany, NY 12203, USA

  • Arun Bansil

    Northeastern University, Northeastern University, Boston, USA

  • Tay-Rong Chang

    Natl Cheng Kung Univ, National Cheng Kung University

  • Gengchiau Liang

    National University of Singapore, Department of Electrical and Computer Engineering, College of Design and Engineering, National University of Singapore, Singapore

  • Ching-Tzu Chen

    IBM TJ Watson Research Center