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Short-Term Memory Dynamics of TiN/Ti/TiO2/SiOx/Si Resistive Random Access Memory.


ABSTRACT: In this study, we investigated the synaptic functions of TiN/Ti/TiO2/SiOx/Si resistive random access memory for a neuromorphic computing system that can act as a substitute for the von-Neumann computing architecture. To process the data efficiently, it is necessary to coordinate the information that needs to be processed with short-term memory. In neural networks, short-term memory can play the role of retaining the response on temporary spikes for information filtering. In this study, the proposed complementary metal-oxide-semiconductor (CMOS)-compatible synaptic device mimics the potentiation and depression with varying pulse conditions similar to biological synapses in the nervous system. Short-term memory dynamics are demonstrated through pulse modulation at a set pulse voltage of -3.5 V and pulse width of 10 ms and paired-pulsed facilitation. Moreover, spike-timing-dependent plasticity with the change in synaptic weight is performed by the time difference between the pre- and postsynaptic neurons. The SiOx layer as a tunnel barrier on a Si substrate provides highly nonlinear current-voltage (I-V) characteristics in a low-resistance state, which is suitable for high-density synapse arrays. The results herein presented confirm the viability of implementing a CMOS-compatible neuromorphic chip.

SUBMITTER: Cho H 

PROVIDER: S-EPMC7559005 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature

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Short-Term Memory Dynamics of TiN/Ti/TiO<sub>2</sub>/SiO<i><sub>x</sub></i>/Si Resistive Random Access Memory.

Cho Hyojong H   Kim Sungjun S  

Nanomaterials (Basel, Switzerland) 20200912 9


In this study, we investigated the synaptic functions of TiN/Ti/TiO<sub>2</sub>/SiO<i><sub>x</sub></i>/Si resistive random access memory for a neuromorphic computing system that can act as a substitute for the von-Neumann computing architecture. To process the data efficiently, it is necessary to coordinate the information that needs to be processed with short-term memory. In neural networks, short-term memory can play the role of retaining the response on temporary spikes for information filter  ...[more]

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