Photonic synapses combining photosensitivity and synaptic function can efficiently perceive and memorize visual information,making them crucial for the development of artificial vision systems.However,the development ...Photonic synapses combining photosensitivity and synaptic function can efficiently perceive and memorize visual information,making them crucial for the development of artificial vision systems.However,the development of high-performance photonic synapses with low power consumption and rapid optical erasing ability remains challenging.Here,we propose a photon-modulated charging/discharging mechanism for self-powered photonic synapses.The current hysteresis enables the devices based on CsPbBr3/solvent/carbon nitride multilayer architecture to emulate synaptic behaviors,such as excitatory postsynaptic currents,paired-pulse facilitation,and long/short-term memory.Intriguingly,the unique radiation direction-dependent photocurrent endows the photonic synapses with the capability of optical writing and rapid optical erasing.Moreover,the photonic synapses exhibit exceptional performance in contrast enhancement and noise reduction owing to the notable synaptic plasticity.In simulations based on artificial neural network(ANN)algorithms,the pre-processing by our photonic synapses improves the recognition rate of handwritten digit from 11.4%(200 training epochs)to 85%(~60 training epochs).Furthermore,due to the excellent feature extraction and memory capability,an array based on the photonic synapses can imitate facial recognition of human retina without the assistance of ANN.展开更多
Current synaptic characteristics focus on replicating basic biological operations,but developing devices that combine photoelectric responsiveness and multifunctional simulation remains challenging.An optoelectronic t...Current synaptic characteristics focus on replicating basic biological operations,but developing devices that combine photoelectric responsiveness and multifunctional simulation remains challenging.An optoelectronic transistor is presented,utilizing a PMHT∕Al_(2)O_(3)heterostructure for photoreception,memory storage,and computation.This artificial synaptic transistor processes optical and electrical signals efficiently,mimicking biological synapses.The work presents four logic functions:“AND”,“OR”,“NOR”,and“NAND”.It demonstrates electrical synaptic plasticity,optical synaptic plasticity,sunburned skin simulation,a photoelectric cooperative stimulation model for improving learning efficiency,and memory functions.The development of heterostructure synaptic transistors and their photoelectric response enhances their application in neuromorphic computation.展开更多
基金supported by the Natural Science Foundation of Shandong Province(ZR2021YQ32)the China Postdoctoral Science Foundation(2023M740472)+2 种基金the National Natural Science Foundation of China(62175162,62205214,and 61901222)the Taishan Scholars Program of Shandong Province(tsqn201909117)the Special Fund for Science and Technology Innovation Teams of Shanxi Province and Foundation of Shenzhen Science and Technology(20200814100534001).
文摘Photonic synapses combining photosensitivity and synaptic function can efficiently perceive and memorize visual information,making them crucial for the development of artificial vision systems.However,the development of high-performance photonic synapses with low power consumption and rapid optical erasing ability remains challenging.Here,we propose a photon-modulated charging/discharging mechanism for self-powered photonic synapses.The current hysteresis enables the devices based on CsPbBr3/solvent/carbon nitride multilayer architecture to emulate synaptic behaviors,such as excitatory postsynaptic currents,paired-pulse facilitation,and long/short-term memory.Intriguingly,the unique radiation direction-dependent photocurrent endows the photonic synapses with the capability of optical writing and rapid optical erasing.Moreover,the photonic synapses exhibit exceptional performance in contrast enhancement and noise reduction owing to the notable synaptic plasticity.In simulations based on artificial neural network(ANN)algorithms,the pre-processing by our photonic synapses improves the recognition rate of handwritten digit from 11.4%(200 training epochs)to 85%(~60 training epochs).Furthermore,due to the excellent feature extraction and memory capability,an array based on the photonic synapses can imitate facial recognition of human retina without the assistance of ANN.
基金National Natural Science Foundation of China(6257030508)Natural Science Foundation of Heilongjiang Province,China(LH2023F045)Basic Scientific Research Funds of Heilongjiang Universities Special Fund Project of Heilongjiang University(2023-KYYWF-1434)。
文摘Current synaptic characteristics focus on replicating basic biological operations,but developing devices that combine photoelectric responsiveness and multifunctional simulation remains challenging.An optoelectronic transistor is presented,utilizing a PMHT∕Al_(2)O_(3)heterostructure for photoreception,memory storage,and computation.This artificial synaptic transistor processes optical and electrical signals efficiently,mimicking biological synapses.The work presents four logic functions:“AND”,“OR”,“NOR”,and“NAND”.It demonstrates electrical synaptic plasticity,optical synaptic plasticity,sunburned skin simulation,a photoelectric cooperative stimulation model for improving learning efficiency,and memory functions.The development of heterostructure synaptic transistors and their photoelectric response enhances their application in neuromorphic computation.
