Universally optimizable strategy for magnetic gaps towards high-temperature quantum anomalous Hall states via magnetic-insulator/topological-insulator building-blocks

TL;DR

This paper reveals a universal principle for optimizing magnetic gaps in ferromagnetic-insulator/topological-insulator systems, crucial for achieving high-temperature quantum anomalous Hall states, by balancing hybridization strength and stacking order.

Contribution

It uncovers the nonmonotonic relationship between hybridization strength and magnetic gap, and proposes stacking order modification as a practical tuning method.

Findings

Optimal hybridization balances magnetic gap enhancement and TSS delocalization.

Stacking order modification enables tuning of Chern numbers and global gaps.

Universal principle guides experimental optimization of magnetic gaps in QAH systems.

Abstract

Optimizing the magnetic Zeeman-splitting term, specifically the magnetic gap of the topological surface states (TSSs), is a crucial issue and central challenge in advancing higher-temperature quantum anomalous Hall (QAH) states. In this work, we demonstrate a counterintuitive, nonmonotonic relationship between the magnetic gap and the hybridization strength in ferromagnetic-insulator (FMI)/topological-insulator (TI) sandwich structures. Concretely, insufficient hybridization strength fails to induce a substantial magnetic gap; while excessive hybridization incandesces the competition between kinetic and Coulomb exchange interactions, thereby reducing the gap. Strong hybridization strength also spatially delocalizes the TSSs, diminishing the effective orbital coupling between TSS-based p and magnetic d orbitals, which further weakens kinetic and Coulomb exchange interaction strength. Moreover, modifying the stacking order offers an experimentally viable approach to optimizing magnetic gaps, enabling the tunability of Chern numbers, chirality and maximizing global gaps. These findings unveil a universal guiding principle for optimizing magnetic gaps in FMI-TI proximity-based QAH systems, offering valuable insights for advancing experimental implementations in this field.