石墨烯
晶体管
材料科学
光电子学
纳米技术
电气工程
工程类
电压
作者
Anastasia Chouprik,Elizaveta Guberna,Islam Mutaev,Ilya Margolin,Evgeny Guberna,Maxim Rybin
摘要
Artificial synapse is a key element of future brain-inspired neuromorphic computing systems implemented in hardware. This work presents a graphene synaptic transistor based on all-technology-compatible materials that exhibits highly tunable biorealistic behavior. It is shown that the device geometry and interface properties can be designed to maximize the memory window and minimize power consumption. The device exhibits a virtually continuous range of multiple conductance levels, similar to synaptic weighting, which is achieved by gradual injection/emission of electrons into the floating gate and interface traps under the influence of an external electric field. Similar to the biological synapse, the transistor has short-term intrinsic dynamics that affects the long-term state. The temporal injection/emission dynamics of an electronic synapse closely resembles those of its biological counterpart and is exploited to emulate biorealistic behavior using a number of synaptic functions, including paired-pulse facilitation/depression, spike-rate-dependent plasticity, and others. Such a synaptic transistor can serve as a building block in hardware artificial networks for advanced information processing and storage.
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