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High-throughput large-area automated identification and quality control of graphene and few-layer graphene films

机译:石墨烯和几层石墨烯薄膜的高通量大面积自动识别和质量控制

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摘要

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.
机译:石墨烯的实际应用需要可靠的高通量石墨烯识别和质量控制方法,该方法可用于大规模基板和晶片。我们已经提出并通过实验测试了一种用于确定石墨烯样品中原子平面数量的快速且全自动的方法。该程序允许原位识别具有相同数量原子面的区域边界。它基于原始图像处理算法,该算法利用微拉曼校准,光背景减法,照明不均匀性校正以及每个像素的彩色和灰度图像处理。所开发程序的结果是伪彩色图,该伪色图标记了可以用光学显微镜捕获的任何尺寸的基底上的单层和少层石墨烯区域。我们的方法适用于各种基材,并且可以工业规模应用于机械剥离,化学衍生,沉积或外延的石墨烯。

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