Image Processing To Aid in Graphene Detection
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Image Processing To Aid in Graphene Detection Ryan D. Gorby and Lihong (Heidi) Jiao School of Engineering, Grand Valley State University, Grand Rapids, MI 49504, U.S.A.
ABSTRACT Qualitative techniques for the detection of graphene on a Si/SiO2 substrate, without the use of sophisticated equipment, are presented. Once calibrated, this technique can be used to detect Single Layer Graphene (SLG) and Few Layer Graphene (FLG) with the use of an inexpensive optical microscope (OM), OM camera system, and image processing software. This technique could be transferred to graphene deposited on other substrates or other 2-D materials with minor updates to mathematical theory. INTRODUCTION Over the last decade, graphene has gained tremendous attention in the scientific community for its extraordinary electrical and mechanical properties; launching a graphene frenzy. The material has attracted investors, researchers, and corporations alike in the hopes to discover the next novel products and materials. As with any new innovation, one of the first steps is the ability to procure or produce material samples for lab exploration. Samples of graphene can be obtained by a variety of methods including mechanical exfoliation, chemical exfoliation, reduced graphene oxide, Chemical Vapor Deposition (CVD), or epitaxial growth to name a few [1]. This paper presents a qualitative description for the detection of graphene on a silicon / silicon oxide (Si/SiO2) substrate, without the use of sophisticated equipment. Once calibrated, this technique can detect Single Layer Graphene (SLG) and Few Layer Graphene (FLG) with the use of an inexpensive Optical Microscope (OM), OM Camera System, and Image Processing Software. More sophisticated instruments including Scanning Electron Microscope (SEM), Atomic Force Microscopes (AFM), and Raman Spectroscopy have the ability to detect graphene on a variety of substrates, but all suffer from increased equipment cost and slow detection times. In order to enhance viewing of graphene under an OM, the substrate in which the graphene resides should be optimized. The paper provides optimization suggestions for viewing graphene on Si/SiO2 substrate. It then explores the use of simple image processing software for the verification of graphene, without using sophisticated and expensive equipment. Next, the paper describes laboratory experiment, verifying the predicted theory with real laboratory results. CONTRAST OPTIMIZATION A common inexpensive substrate for viewing graphene is silicon dioxide (SiO2) on silicon (Si) wafer. Graphene visibility on this type of substrate can be explained by interference color of reflected light in comparison to the bare substrate. This “contrast” difference allows graphene to be easily viewed, despite graphene’s single atom thick atomic structure. The two main factors that determine graphene visibility are the incident light wavelength (λ) and thickness of SiO2 layer. When graphene sits on SiO2/Si substrate, light interacts with each interface; air ↔ graphene, graphene ↔ SiO2, and S
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