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基于膜忆容系统的忆阻计算

Memcomputing with membrane memcapacitive systems.

作者信息

Pershin Y V, Traversa F L, di Ventra M

机构信息

Department of Physics and Astronomy, University of South Carolina, Columbia, SC 29208, USA.

出版信息

Nanotechnology. 2015 Jun 5;26(22):225201. doi: 10.1088/0957-4484/26/22/225201. Epub 2015 May 12.

Abstract

We show theoretically that networks of membrane memcapacitive systems-capacitors with memory made out of membrane materials-can be used to perform a complete set of logic gates in a massively parallel way by simply changing the external input amplitudes, but not the topology of the network. This polymorphism is an important characteristic of memcomputing (computing with memories) that closely reproduces one of the main features of the brain. A practical realization of these membrane memcapacitive systems, using, e.g., graphene or other 2D materials, would be a step forward towards a solid-state realization of memcomputing with passive devices.

摘要

我们从理论上证明,由膜材料制成的具有记忆功能的膜电容系统网络(即带记忆的电容器),只需改变外部输入幅度,而无需改变网络拓扑结构,就能以大规模并行方式执行一整套逻辑门。这种多态性是忆阻计算(基于记忆的计算)的一个重要特征,它紧密再现了大脑的一个主要特征。使用例如石墨烯或其他二维材料来实际实现这些膜电容系统,将是朝着用无源器件实现忆阻计算的固态实现迈出的一步。

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