Rashidian Vaziri Mohammad Reza
Photonics and Quantum Technology Research School, Nuclear Science and Technology Research Institute, Tehran, Iran.
Microsc Res Tech. 2020 Sep;83(9):1132-1140. doi: 10.1002/jemt.23505. Epub 2020 Jul 8.
In the way of making graphene an industry-friendly material, it must be mass-produced with high-quality and reduced cost over large areas. Assisted by machine-learning techniques, rapid, nondestructive and accurate determination of large graphene sheets on SiO /Si substrates has been made possible in recent years by the optical microscopy method. Optimization of the substrate to achieve the maximum contrast can further extend the application of the optical microscopy method for quality control of the mass-produced graphene. Graphene/n /n three-layer structures, where n and n are refractive indices, are routinely used for identifying the number of graphene layers by optical reflection microscopy. In this paper, two analytical equations are derived that can be easily used for high-contrast optical imaging of graphene sheets without any need to resort to the cumbersome numerical methods. One of the equations is derived for choosing the best material with refractive index n that when coated on a substrate with refractive index n , maximizes the optical contrast. The other equation is derived for finding the best thickness of the SiO layer in graphene/SiO /Si structures, which are in common use for fabrication of graphene-based devices. The results are implemented in a MATLAB GUI, see Supporting Information, to assist the users in using the equations.
要使石墨烯成为一种适合工业应用的材料，必须在大面积上高质量、低成本地进行大规模生产。近年来，借助机器学习技术，通过光学显微镜方法能够快速、无损且准确地测定SiO₂/Si衬底上的大片石墨烯。优化衬底以实现最大对比度可进一步拓展光学显微镜方法在大规模生产石墨烯质量控制方面的应用。石墨烯/n₁/n₂三层结构（其中n₁和n₂为折射率）常用于通过光学反射显微镜识别石墨烯层数。本文推导了两个解析方程，无需借助繁琐的数值方法即可轻松用于石墨烯片的高对比度光学成像。其中一个方程用于选择具有折射率n₁的最佳材料，当该材料涂覆在折射率为n₂的衬底上时，可使光学对比度最大化。另一个方程用于确定石墨烯/SiO₂/Si结构中SiO₂层的最佳厚度，这种结构常用于制造基于石墨烯的器件。结果在MATLAB GUI中实现（见支持信息），以帮助用户使用这些方程。
