Topology Classification using Chiral Symmetry and Spin Correlations in Graphene Nanoribbons.

Jiang, Jingwei; Louie, Steven G · Nano Lett · 2021

basic_science · Level V

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Abstract

We apply the topological classification theory using chiral symmetry to graphene nanoribbons (GNRs). This approach eliminates the requirement of time-reversal and spatial symmetry in previous <i>Z</i><sub>2</sub> topology theory, resulting in a <i>Z</i> classification with the conventional <i>Z</i> index in a new vector-formed expression called "chiral phase index" (CPI). Our approach is applicable to GNRs of arbitrary terminations and any quasi one-dimensional chiral structures, including magnetism. It naturally solves a recent experimental puzzle of junction states at a class of asymmetric GNR junctions. We moreover derive a simple analytic formula for the CPI of armchair GNRs. Since this approach enables access to electron spin behavior, based on the CPI, we design a novel GNR with periodic localized moments and strong spin-spin exchange coupling.