Large-Area High-Throughput Identification and Quality Control of Graphene and Few-Layer Graphene: Prospects of Industry-Scale Applications

TL;DR

This paper presents a rapid, automated optical method for identifying and mapping the number of atomic layers in graphene across large areas, suitable for industrial-scale quality control.

Contribution

The authors developed and validated a novel image processing technique that enables in situ, high-throughput identification of graphene layer number on various substrates.

Findings

Effective for large-area substrates

Works with different graphene production methods

Provides clear pseudo-color maps of graphene layers

Abstract

Practical applications of graphene require a reliable high-throughput method of graphene identification and quality control, which can be used for large-scale substrates and wafers. We have proposed and experimentally tested a fast and fully automated approach for determining the number of atomic planes in graphene samples. The procedure allows for in situ identification of the borders of the regions with the same number of atomic planes. It is based on an original image processing algorithm, which utilizes micro-Raman calibration, light background subtraction, lighting non-uniformity correction, and the color and grayscale image processing for each pixel. The outcome of the developed procedure is a pseudo-color map, which marks the single-layer and few-layer graphene regions on the substrate of any size that can be captured by an optical microscope. Our approach works for various substrates, and can be applied to the mechanically exfoliated, chemically derived, deposited or epitaxial graphene on an industrial scale.