Moir\'e patterns generated by stacked 2D lattices: a general algorithm to identify primitive coincidence cells

TL;DR

This paper introduces a general algorithm to identify minimal superlattice cells in stacked 2D materials, enabling efficient simulation of complex moiré patterns with large periodicities.

Contribution

The authors present a novel, general procedure to determine the primitive coincidence cells for arbitrary 2D lattice stacks, improving simulation efficiency and accuracy.

Findings

Validated on twisted graphene bilayers with analytic solutions

Successfully applied to graphene on Ni surfaces with experimental agreement

Produces small coincidence cells for complex moiré superstructures

Abstract

Two-dimensional materials on metallic surfaces or stacked one on top of the other can form a variety of moir\'e superstructures depending on the possible parameter and symmetry mismatch and misorientation angle. In most cases, such as incommensurate lattices or identical lattices but with a small twist angle, the common periodicity may be very large, thus making numerical simulations prohibitive. We propose here a general procedure to determine the minimal simulation cell which approximates, within a certain tolerance and a certain size, the primitive cell of the common superlattice, given the two interfacing lattices and the relative orientation angle. As case studies to validate our procedure, we report two applications of particular interest: the case of misaligned hexagonal/hexagonal identical lattices, describing a twisted graphene bilayer or a graphene monolayer grown on Ni(111), and the case of hexagonal/square lattices, describing for instance a graphene monolayer grown on Ni(100) surface. The first one, which has also analytic solutions, constitutes a solid benchmark for the algorithm; the second one shows that a very nice description of the experimental observations can be obtained also using the resulting relatively small coincidence cells.