Very large scale characterization of graphene mechanical devices using a colorimetry technique

TL;DR

This study introduces a scalable optical colorimetry technique to efficiently characterize over 21,000 graphene nanomechanical devices, revealing correlations between device geometry and mechanical stability, and measuring adhesion energy.

Contribution

The paper presents a novel, scalable optical method for large-scale characterization of graphene devices, enabling automated analysis and yield statistics.

Findings

Survival probability correlates with D^4/g^3 scaling parameter.

Median adhesion energy of 0.9 J/m^2 measured between graphene and SiO2.

Method allows parallel, automated image processing for device analysis.

Abstract

We use a scalable optical technique to characterize more than 21000 circular nanomechanical devices made out of suspended single- and double-layer graphene on cavities with different diameters ($D$) and depths ($g$). To maximize the contrast between suspended and broken membranes we used a model for selecting the optimal color filter. The method enables parallel and automatized image processing for yield statistics. We find the survival probability to be correlated to a structural mechanics scaling parameter given by $D^4/g^3$. Moreover, we extract a median adhesion energy of $\Gamma =$ 0.9 J/m$^2$ between the membrane and the native SiO$_2$ at the bottom of the cavities.