论文标题

对神经形态系统的石墨烯/离子液体循环设备的表征

Characterization of Graphene/Ionic Liquid Memristive Devices for Neuromorphic Systems

论文作者

Köymen, Itır, Liu, Shuyu, Ergöktaş, Said, Kocabas, Coskun

论文摘要

柔性和生物相容性的回忆设备对生物电机系统特别有吸引力,因为有兴趣改善计算能力以及与包括药物输送,神经界面和生物传感器在内的生物系统接触电子系统的动机。由更非正统的有机材料制成的结构由于其特征而可以解决不同的问题:柔韧性,合并性,生物相容性以及简单且低成本的制造。已经观察到,门控石墨烯/离子液体(IL)设备会导致在石墨烯/IL界面处形成了双层(厚度为几纳米厚度为几纳米的离子的薄层),这也是由于局部电位差,这也控制了局部电导率。该结构基于沿通道的动态P-N结的形成提供了一种回忆机制。由这种回忆行为的激励,将石墨烯/IL设备组装在一起,目的是展示回忆行为和关联学习。这项工作研究了柔性石墨烯/ IL设备在聚合物底物上的回忆特性。研究了这些新型设备和切换机制的I-V特性。设备的两个不同的拓扑结构(单输入,单输出和双输入,单输出)是制造并测试的。据观察,正极和负极性的电压脉冲序列的应用会增加设备电导,并在重复激发后允许更大的电流通过。该特征被利用为条件设备并效仿关联学习。

Flexible and biocompatible memristive devices are particularly attractive for bioelectronic systems due to the interest in improving computing capabilities and the motivation to interface electronics with biological systems including drug delivery, neural interfaces and biosensors. Structures made of more unorthodox, organic material can address different issues due to their characteristics: flexibility, conformability, biocompatibility and simple and low-cost fabrication. It has been observed that gating graphene/ionic liquid (IL) devices leads to the formation of an electrical double layer (a thin layer of ions with a thickness of a few nanometers) at the graphene/IL interface due to the local potential difference which also controls the local conductivity. This structure provides a memristive mechanism based on a dynamic p-n junction formation along the channel. Motivated by this memristive behavior, graphene/IL devices were assembled with the aim of demonstrating memristive behavior and associative learning. This work investigates memristive properties of flexible graphene/ IL devices on polymer substrates. The I-V characteristics of these novel devices and switching mechanism are investigated. Two distinct topologies (single input, single output and double input, single output) of devices are manufactured and tested to mimic conditioning. It is observed that the application of voltage pulse trains of both positive and negative polarities increases the device conductance and allows larger currents to pass after repetitive excitation. This characteristic was exploited to condition devices and emulate associative learning.

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