Recently, graphene has gained a lot of attention in the electronic industry due to its unique properties and has paved the way for realizing novel devices in the field of electronics. For the development of new device applications, it is necessary to grow large wafer-sized monolayer graphene samples. Among the methods to synthesize large graphene films, chemical vapor deposition (CVD) is one of the promising and common techniques. However, during the growth and transfer of the CVD graphene monolayer, defects such as wrinkles, cracks, and holes appear on the graphene surface. These defects can influence the electrical properties and it is of interest to know the quality of graphene samples non-destructively. Electrical impedance tomography (EIT) can be applied as an alternate method to determine conductivity distribution non-destructively. The EIT inverse problem of reconstructing conductivity is highly non-linear and is heavily dependent on measurement accuracy and modeling errors related to an accurate knowledge of electrode location, contact resistances, the exact outer boundary of the graphene wafer, etc. In practical situations, it is difficult to eliminate these modeling errors as complete knowledge of the electrode contact impedance and outer domain boundary is not fully available, and this leads to an undesirable solution. In this paper, a difference imaging approach is proposed to estimate the conductivity change of graphene with respect to the reference distribution from the data sets collected before and after the change. The estimated conductivity change can be used to locate the defects on the graphene surface caused due to the CVD transfer process or environment interaction. Numerical and experimental results with graphene sample of size 2.5 × 2.5 cm are performed to determine the change in conductivity distribution and the results show that the proposed difference imaging approach handles the modeling errors and estimates the conductivity distribution with good accuracy.

中文翻译：

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使用电阻层析成像成像单层石墨烯的电导率变化

近年来，石墨烯因其独特的性能而在电子工业中引起了广泛关注，并为在电子领域中实现新型器件铺平了道路。为了开发新的设备应用，必须生长大型晶片尺寸的单层石墨烯样品。在合成大石墨烯薄膜的方法中，化学气相沉积（CVD）是一种有前途的常用技术。然而，在CVD石墨烯单层的生长和转移期间，诸如皱纹，裂缝和孔的缺陷出现在石墨烯表面上。这些缺陷会影响电性能，因此人们需要无损地了解石墨烯样品的质量。电阻抗断层扫描（EIT）可以用作替代方法来非破坏性地确定电导率分布。重建电导率的EIT反问题是高度非线性的，并且在很大程度上取决于测量精度和与电极位置，接触电阻，石墨烯晶片的确切外边界等的准确知识有关的建模误差。在实际情况中，它很难完全消除电极接触阻抗和外域边界的知识，从而消除这些建模误差，这将导致不良解决方案。在本文中，提出了一种差异成像方法，根据变化前后收集的数据集，估算石墨烯相对于参考分布的电导率变化。估计的电导率变化可用于定位由于CVD转移过程或环境相互作用而导致的石墨烯表面缺陷。用尺寸为2.5×2.5 cm的石墨烯样品进行了数值和实验结果，确定了电导率分布的变化，结果表明，所提出的差分成像方法能够处理建模误差，并能以较高的精度估算电导率分布。