Hybrid Modeling and Sensitivity Analysis on Reduced Graphene Oxide Field-Effect Transistor
Hybrid Modeling and Sensitivity Analysis on Reduced Graphene Oxide Field-Effect Transistor
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DOI：
10.1109/tnano.2021.3076135
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发表时间：
2021
影响因子：
2.4
通讯作者：
Chao Wang;H. Pu;Xiaoyu Sui;Shiyu Zhou;Junhong Chen
中科院分区：
文献类型：
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作者：
Chao Wang;H. Pu;Xiaoyu Sui;Shiyu Zhou;Junhong Chen
还原氧化石墨烯（RGO）场效应晶体管（FET）已被开发并应用于各个领域。然而，由于RGO中带隙和态密度的随机性，对RGO FET的有效建模和灵敏度分析仍然是一个非常具有挑战性的问题。在本文中，我们提出了解决RGO FET建模问题，通过整合数据驱动的思维和石墨烯FET模型开发一个混合模型。该模型利用石墨烯和RGO之间的相似性来推广现有的石墨烯FET模型，并采用RGO FET漏极电流数据来表征模型的特异性。该模型的基本思想是将石墨烯DOS修改为近似RGO DOS，从而可以通过近似的RGO DOS来获得电荷密度、迁移率和其他参数。我们验证了模型的准确性与RGO FET为基础的传感器，检测在水环境中的化学浓度。RGO FET的灵敏度分析也被证明，为RGO FET的应用和制造提供指导。
The reduced graphene oxide (RGO) field-effect transistor (FET) has been developed and applied in various areas. However, the effective modeling and sensitivity analysis on RGO FET is still a very challenging problem due to the randomness of bandgap and density of states (DOS) in RGO. In this paper, we propose to solve the RGO FET modeling problem by integrating the data-driven thinking and the graphene FET model to develop a hybrid model. The proposed model takes advantages of the similarities between graphene and RGO to generalize the existing graphene FET model, and employs RGO FET drain-current data to characterize the specificity of the model. The basic idea in the proposed model is to modify the graphene DOS to approximate the RGO DOS so that the charge density, mobility and other parameters can be achieved through the approximated RGO DOS. We validate the model accuracy with the RGO FET based sensors that detect chemical concentrations in the aqueous environment. The RGO FET sensitivity analysis is also demonstrated to provide guidance for RGO FET application and manufacturing.