Photonic synaptic transistors are promising neuromorphic computing systems that are expected to circumvent the intrinsic limitations of von Neumann-based computation.The design and construction of photonic synaptic tr...Photonic synaptic transistors are promising neuromorphic computing systems that are expected to circumvent the intrinsic limitations of von Neumann-based computation.The design and construction of photonic synaptic transistors with a facile fabrication process and highefficiency information processing ability are highly desired,while it remains a tremendous challenge.Herein,a new approach based on spin coating of a blend of CsPbBr_(3) perovskite quantum dot(QD)and PDVT-10 conjugated polymer is reported for the fabrication of photonic synaptic transistors.The combination of flat surface,outstanding optical absorption,and remarkable charge transporting performance contributes to high-efficiency photon-to-electron conversion for such perovskite-based synapses.High-performance photonic synaptic transistors are thus fabricated with essential synaptic functionalities,including excitatory postsynaptic current(EPSC),paired-pulse facilitation(PPF),and long-term memory.By utilizing the photonic potentiation and electrical depression features,perovskite-based photonic synaptic transistors are also explored for neuromorphic computing simulations,showing high pattern recognition accuracy of up to 89.98%,which is one of the best values reported so far for synaptic transistors used in pattern recognition.This work provides an effective and convenient pathway for fabricating perovskite-based neuromorphic systems with high pattern recognition accuracy.展开更多
基金supported by the Ministry of Science and Technology of the People’s Republic of China(2018YFA0703200)the National Natural Science Foundation of China(91833306,51633006,51703160,51733004,51725304,and 52003189)Fujian Science&Technology Innovation Laboratory for Optoelectronic Information of China(2021ZZ130 and 2021ZZ129)。
文摘Photonic synaptic transistors are promising neuromorphic computing systems that are expected to circumvent the intrinsic limitations of von Neumann-based computation.The design and construction of photonic synaptic transistors with a facile fabrication process and highefficiency information processing ability are highly desired,while it remains a tremendous challenge.Herein,a new approach based on spin coating of a blend of CsPbBr_(3) perovskite quantum dot(QD)and PDVT-10 conjugated polymer is reported for the fabrication of photonic synaptic transistors.The combination of flat surface,outstanding optical absorption,and remarkable charge transporting performance contributes to high-efficiency photon-to-electron conversion for such perovskite-based synapses.High-performance photonic synaptic transistors are thus fabricated with essential synaptic functionalities,including excitatory postsynaptic current(EPSC),paired-pulse facilitation(PPF),and long-term memory.By utilizing the photonic potentiation and electrical depression features,perovskite-based photonic synaptic transistors are also explored for neuromorphic computing simulations,showing high pattern recognition accuracy of up to 89.98%,which is one of the best values reported so far for synaptic transistors used in pattern recognition.This work provides an effective and convenient pathway for fabricating perovskite-based neuromorphic systems with high pattern recognition accuracy.
