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Conductance Parametric Analysis of Graphene Nanoribbons with Magnetic Contacts
IEEE Transactions on Nanotechnology ( IF 2.4 ) Pub Date : 2020-01-01 , DOI: 10.1109/tnano.2020.3033835
Savvas Moysidis , Konstantinos Rallis , Ioannis G. Karafyllidis

Graphene nanoribbons with non-magnetic contacts have been extensively studied and are widely used in graphene based devices. In these devices, the nanoribbon conductance is modulated and controlled by applying potentials through top and back gates. Graphene nanoribbons with magnetic contacts have been studied and used as spin valves, mostly at liquid-helium temperatures. The operation of graphene nanoribbons with magnetic contacts at room temperature, where nanoelectronic devices and circuits are expected to operate, has received little attention. Here we study and simulate the operation of graphene nanoribbons with magnetic contacts using tight-binding Hamiltonians and the non-equilibrium Green's functions(NEGF) method, which we extend to incorporate the effect of magnetic contacts. Our results are in very good agreement with experimental measurements of the conductance of graphene nanoribbons with NiFe ferromagnetic contacts. We also perform extensive parametric analysis of the dependence of the nanoribbon conductance on the relative orientations of the contact magnetic polarizations, combined with potentials applied through top and back gates. Our results revealed a very rich parametric space that can be exploited to develop multifunctional platforms which, among others, can be used for digital, analog and neuromorphic computations.

中文翻译:

具有磁性接触的石墨烯纳米带的电导参数分析

具有非磁性触点的石墨烯纳米带已被广泛研究并广泛用于基于石墨烯的器件。在这些器件中,通过顶栅和背栅施加电位来调制和控制纳米带电导。具有磁性接触的石墨烯纳米带已被研究并用作自旋阀,主要用于液氦温度。石墨烯纳米带在室温下具有磁性接触的操作,其中纳米电子器件和电路有望运行,但很少受到关注。在这里,我们使用紧束缚哈密顿量和非平衡格林函数 (NEGF) 方法研究和模拟具有磁性接触的石墨烯纳米带的操作,我们将其扩展到结合磁性接触的影响。我们的结果与石墨烯纳米带与 NiFe 铁磁接触的电导的实验测量非常一致。我们还对纳米带电导对接触磁极化的相对方向的依赖性进行了广泛的参数分析,并结合通过顶栅和背栅施加的电位。我们的结果揭示了一个非常丰富的参数空间,可用于开发多功能平台,其中,可用于数字、模拟和神经形态计算。结合通过顶栅和背栅施加的电位。我们的结果揭示了一个非常丰富的参数空间,可用于开发多功能平台,其中,可用于数字、模拟和神经形态计算。结合通过顶栅和背栅施加的电位。我们的结果揭示了一个非常丰富的参数空间,可用于开发多功能平台,其中,可用于数字、模拟和神经形态计算。
更新日期:2020-01-01
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