A mesoscopic model of nanoclusters self-assembly on a graphene Moir\'e

TL;DR

This paper introduces a continuum mesoscopic model for the self-assembly of metal nanoclusters on twisted bilayer graphene, analyzing steady states, dynamics, and effects of temperature and adsorption potential, with extensions to related systems.

Contribution

It presents a novel mesoscopic model for nanocluster self-assembly on Moiré-patterned graphene, including analytical and dynamic analyses, and explores effects of various parameters and system extensions.

Findings

Nanoclusters self-assemble at Moiré cell centers.

Self-assembly efficiency varies with metal type and temperature.

Adsorption potential accelerates self-assembly and influences morphology.

Abstract

A continuum, post-deposition mesoscopic model of a Moir\'e-regulated self-assembly of metal nanoclusters on a twisted bilayer graphene is presented. Quasi-two-dimensional nanocluster-like steady states at a low adsorbate coverage are analytically determined for Pt, Ni, and Pb adsorbates, pointing that nanoclusters self-assemble at the Moir\'e cells centers. This is followed by the computations of nanoclusters self-assembly dynamics. Differences in the self-assembly efficiency for three chosen metals are highlighted across three typical values of an initial submonolayer coverage and for three temperature regimes. Accounting for the adsorption potential of metal atoms onto graphene leads to a significantly faster nanoclusters self-assembly and has a transient impact on the nanoclusters morphologies. A model extensions to the cases of nanoclusters self-assembly on a Moir\'e formed by a monolayer graphene over a metal substrate, and the electromigration-guided self-assembly on such Moir\'e are proposed.