The role of stacking and strain in mean-field magnetic moments of multilayer graphene
András Balogh, Zoltán Tajkov, Péter Nemes-Incze, János Koltai
TL;DR
The paper addresses correlation-driven magnetism in ABC-stacked multilayer graphene and its dependence on stacking and mechanical distortions. It develops a tight-binding+$U$ framework with distance-dependent Slater-Koster interlayer hopping and a single universal Hubbard parameter, validated against hybrid-DFT results for 3–8 layer ABC and ABA systems. With a universal value of $U=5.84$ eV, the model reproduces layerwise antiferromagnetic order, where ABC moments grow with thickness while ABA moments peak at the center; mixed ABC-ABA stacks maintain region-specific patterns with boundary perturbations. The study also shows that uniaxial strain and interlayer spacing can tune magnetism in predictable ways, providing a computationally efficient path to explore correlation-driven magnetism across arbitrary graphite polytypes and suggesting experimental routes to realize buried flat-band magnetism.
Abstract
Rhombohedral or ABC stacked multilayer graphene hosts a correlated magnetic ground state at charge neutrality, making it one of the simplest systems to investigate strong electronic correlations. We investigate this ground state in multilayer graphene structures using the Hubbard model in a distance dependent Slater-Koster tight binding framework. We show that by using a universal Hubbard-$U$ term, we can accurately capture the spin polarization predicted by hybrid density functional theory calculations for both hexagonal (ABA) and rhombohedral (ABC) stackings. Using this $U$ value, we calculate the magnetic moments of 3-8 layers of ABC and ABA graphene multilayers. We demonstrate that the structure and magnitude of these magnetic moments are robust when heterostructures are built from varying numbers of ABC and ABA multilayers. By applying different types of mechanical distortions, we study the behaviour of the magnetism in graphene systems under uniaxial strain and pressure. Our results establish a computationally efficient framework to investigate correlation-driven magnetism across arbitrary stacking configurations of graphite polytypes.
