The selective transfer of patterned graphene

TL;DR

This paper introduces a novel femtosecond laser microfabrication technique for the precise, selective transfer of patterned microcleaving graphene onto specific targets, enhancing the fabrication of graphene-based heterostructures and devices.

Contribution

It presents a new method using bilayer-polymer and femtosecond laser fabrication for selective transfer of microcleaving graphene patterns.

Findings

Enables exact transfer of patterned graphene to targeted locations.

Leaves untransferred graphene flakes on the original substrate.

Facilitates fabrication of van der Waals heterostructures.

Abstract

Graphene is an emerging class of two-dimensional (2D) material with unique electrical properties and a wide range of potential practical applications. In addition, graphene hybrid structures combined with other 2D materials, metal microstructures, silicon photonic crystal cavities, and waveguides have more extensive applications in van der Waals heterostructures, hybrid graphene plasmonics, hybrid optoelectronic devices, and optical modulators. Based on well-developed transfer methods, graphene grown by chemical vapor deposition (CVD) is currently used in most of the graphene hybrid applications. Although mechanical exfoliation of highly oriented pyrolytic graphite provides the highest-quality graphene, the transfer of the desired microcleaving graphene (MG) to the structure at a specific position is a critical challenge, that limits the combination of MG with other structures. Herein, we report a new technique for the selective transfer of MG patterns and devices onto chosen targets using a bilayer-polymer structure and femtosecond laser microfabrication. This selective transfer technique, which exactly transfers the patterned graphene onto a chosen target, leaving the other flakes on the original substrate, provides an efficient route for the fabrication of MG-based microdevices. This method will facilitate the preparation of van der Waals heterostructures and enable the optimization of the performance of graphene hybrid devices.