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A hybrid ambipolar synaptic transistor emulating multiplexed neurotransmission for motivation control and experience-dependent learning 被引量:1
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作者 Zhipeng Xu Yao Ni +5 位作者 Hong Han Huanhuan Wei Lu Liu Shuo Zhang Hao Huang Wentao Xu 《Chinese Chemical Letters》 SCIE CAS CSCD 2023年第2期557-562,共6页
Artificial synapses with full synapse-like functionalities are of crucial importance for the implementation of neuromorphic computing and bioinspired intelligent systems. In particular, the development of artificial s... Artificial synapses with full synapse-like functionalities are of crucial importance for the implementation of neuromorphic computing and bioinspired intelligent systems. In particular, the development of artificial synapses with the capability to emulate multiplexed neural transmission is highly desirable, but remains challenging. In this work, we proposed a hybrid ambipolar synaptic transistor that combines two-dimensional(2D) molybdenum disulfide(Mo S_(2)) sheet and crystalline one-dimensional(1D) poly(3-hexylthiophene-2,5-diyl) polymer nanowires(P3HT NWs) as dual excitatory channels. Essential synaptic functions, including excitatory postsynaptic current, paired-pulse facilitation, synaptic potentiation and depression, and dynamic filtering were emulated using the synaptic transistor. Benefitting from the dual excitatory channels of the synaptic transistor, the device achieved a fast switch between short-term and long-term memory by altering the charge carriers in the dual channels, i.e., electrons and holes. This emulated the multiplexed neural transmission of different excitatory neurotransmitters, e.g., dopamine and noradrenaline. The plasticity-switchable artificial synapse(PSAS) simulates the task-learning process of individuals under different motivations and the impact of success or failure on task learning and memory, which promises the potential to enable complex functionalities in future neuromorphic intelligent electronics. 展开更多
关键词 Hybrid ambipolar Artificial synapse Dual excitatory channels fast-switching plasticity Task-learning process
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