title: High-throughput large-area automated identification and quality control of graphene and few-layer graphene films.
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 nonuniformity 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 mechanically exfoliated, chemically derived, deposited or epitaxial graphene on an industrial scale.
authors.affiliation: Nano-Device Laboratory, Department of Electrical Engineering and Materials Science and Engineering Program, University of California-Riverside, Riverside, California 92521, USA.
authors.forename: Craig M
authors.initials: CM
authors.lastname: Nolen
authors.forename: Giovanni
authors.initials: G
authors.lastname: Denina
authors.forename: Desalegne
authors.initials: D
authors.lastname: Teweldebrhan
authors.forename: Bir
authors.initials: B
authors.lastname: Bhanu
authors.forename: Alexander A
authors.initials: AA
authors.lastname: Balandin