Synaptic modulation of conductivity and magnetism in a CoPt-based electrochemical transistor

Among various neuromorphic devices for artificial intelligence, the electrochemical transistor, in which the channel conductance can be modulated by the insertion of ions according to the history of gate voltage across the electrolyte, emerges as an efficient one. Despite the striking progress in ex...

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Bibliographic Details
Main Authors: Li, Shengyao, Miao, Bojun, Wang, Xueyan, Teo, Siew Lang, Zhu, Qiang, Piramanayagam, S. N., Wang, Renshaw Xiao
Other Authors: School of Physical and Mathematical Sciences
Format: Article
Language:English
Published: 2023
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Online Access:https://hdl.handle.net/10356/167401
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Institution: Nanyang Technological University
Language: English
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Summary:Among various neuromorphic devices for artificial intelligence, the electrochemical transistor, in which the channel conductance can be modulated by the insertion of ions according to the history of gate voltage across the electrolyte, emerges as an efficient one. Despite the striking progress in exploring novel channel materials, few studies report the ferromagnetic metal-based synaptic transistors, limiting their application in synaptic spintronics. Here, we present synaptic modulation of both conductivity as well as magnetism based on the three-terminal electrochemical transistor with a channel of ferromagnetic CoPt alloy. The CoPt metal channel exhibits perpendicular magnetization and anomalous Hall effect. Then, we demonstrated its essential synaptic functionalities, including depression and potentiation of synaptic weight as well as paired-pulse facilitation. Additionally, we are also able to switch the short-term to long-term plasticity transition using different gate parameters, such as amplitude, duration, and frequency. Last, the device presents multilevel reversible and nonvolatile states of conductivity and magnetic coercivity (HC), both of which exhibit satisfying retention behaviours. The results provide a platform to construct future spin-based synaptic devices.