Manipulating the expression of synaptic plasticity of neuromorphic devices provides fascinating opportunities to develop hardware platforms for artifi-cial intelligence.However,great efforts have been devoted to explo...Manipulating the expression of synaptic plasticity of neuromorphic devices provides fascinating opportunities to develop hardware platforms for artifi-cial intelligence.However,great efforts have been devoted to exploring biomimetic mechanisms of plasticity simulation in the last few years.Recent progress in various plasticity modulation techniques has pushed the research of synaptic electronics from static plasticity simulation to dynamic plasticity modulation,improving the accuracy of neuromorphic computing and providing strategies for implementing neuromorphic sensing functions.Herein,several fascinating strategies for synap-tic plasticity modulation through chemical techniques,device structure design,and physical signal sensing are reviewed.For chemical techniques,the underly-ing mechanisms for the modification of functional materials were clarified and its effect on the expression of synaptic plasticity was also highlighted.Based on device structure design,the reconfigurable operation of neuromorphic devices was well demonstrated to achieve programmable neuromorphic functions.Besides,integrating the sensory units with neuromorphic processing circuits paved a new way to achieve human-like intelligent perception under the modulation of physical signals such as light,strain,and temperature.Finally,considering that the relevant technology is still in the basic exploration stage,some prospects or development suggestions are put forward to promote the development of neuromorphic devices.展开更多
Spike-based neural networks,which use spikes or action potentialsto represent information,have gained a lot of attention because of their high energyefficiency and low power consumption.To fully leverage its advantage...Spike-based neural networks,which use spikes or action potentialsto represent information,have gained a lot of attention because of their high energyefficiency and low power consumption.To fully leverage its advantages,convertingthe external analog signals to spikes is an essential prerequisite.Conventionalapproaches including analog-to-digital converters or ring oscillators,and sensorssuffer from high power and area costs.Recent efforts are devoted to constructingartificial sensory neurons based on emerging devices inspired by the biologicalsensory system.They can simultaneously perform sensing and spike conversion,overcoming the deficiencies of traditional sensory systems.This review summarizesand benchmarks the recent progress of artificial sensory neurons.It starts with thepresentation of various mechanisms of biological signal transduction,followed bythe systematic introduction of the emerging devices employed for artificial sensoryneurons.Furthermore,the implementations with different perceptual capabilitiesare briefly outlined and the key metrics and potential applications are also provided.Finally,we highlight the challenges and perspectives for the future development of artificial sensory neurons.展开更多
Expanding wearable technologies to artificial tactile perception will be of significance for intelligent human-machine interface,as neuromorphic sensing devices are promising candidates due to their low energy consump...Expanding wearable technologies to artificial tactile perception will be of significance for intelligent human-machine interface,as neuromorphic sensing devices are promising candidates due to their low energy consumption and highly effective operating properties.Skin-compatible and conformable features are required for the purpose of realizing wearable artificial tactile perception.Here,we report an intrinsically stretchable,skin-integrated neuromorphic system with triboelectric nanogenerators as tactile sensing and organic electrochemical transistors as information processing.The integrated system provides desired sensing,synaptic,and mechanical characteristics,such as sensitive response(~0.04 kPa^(-1))to low-pressure,short-and long-term synaptic plasticity,great switching endurance(>10000 pulses),symmetric weight update,together with high stretchability of 100%strain.With neural encoding,demonstrations are capable of recognizing,extracting,and encoding features of tactile information.This work provides a feasible approach to wearable,skin-conformable neuromorphic sensing system with great application prospects in intelligent robotics and replacement prosthetics.展开更多
基金financial support from the National Natural Science Foundation of China(Nos.62104017 and 52072204)Beijing Institute of Technology Research Fund Program for Young Scholars.
文摘Manipulating the expression of synaptic plasticity of neuromorphic devices provides fascinating opportunities to develop hardware platforms for artifi-cial intelligence.However,great efforts have been devoted to exploring biomimetic mechanisms of plasticity simulation in the last few years.Recent progress in various plasticity modulation techniques has pushed the research of synaptic electronics from static plasticity simulation to dynamic plasticity modulation,improving the accuracy of neuromorphic computing and providing strategies for implementing neuromorphic sensing functions.Herein,several fascinating strategies for synap-tic plasticity modulation through chemical techniques,device structure design,and physical signal sensing are reviewed.For chemical techniques,the underly-ing mechanisms for the modification of functional materials were clarified and its effect on the expression of synaptic plasticity was also highlighted.Based on device structure design,the reconfigurable operation of neuromorphic devices was well demonstrated to achieve programmable neuromorphic functions.Besides,integrating the sensory units with neuromorphic processing circuits paved a new way to achieve human-like intelligent perception under the modulation of physical signals such as light,strain,and temperature.Finally,considering that the relevant technology is still in the basic exploration stage,some prospects or development suggestions are put forward to promote the development of neuromorphic devices.
基金supported by the Key-Area Research and Development Program of Guangdong Province(Grants No.2021B0909060002)National Natural Science Foundation of China(Grants No.62204219,62204140)Major Program of Natural Science Foundation of Zhejiang Province(Grants No.LDT23F0401).
文摘Spike-based neural networks,which use spikes or action potentialsto represent information,have gained a lot of attention because of their high energyefficiency and low power consumption.To fully leverage its advantages,convertingthe external analog signals to spikes is an essential prerequisite.Conventionalapproaches including analog-to-digital converters or ring oscillators,and sensorssuffer from high power and area costs.Recent efforts are devoted to constructingartificial sensory neurons based on emerging devices inspired by the biologicalsensory system.They can simultaneously perform sensing and spike conversion,overcoming the deficiencies of traditional sensory systems.This review summarizesand benchmarks the recent progress of artificial sensory neurons.It starts with thepresentation of various mechanisms of biological signal transduction,followed bythe systematic introduction of the emerging devices employed for artificial sensoryneurons.Furthermore,the implementations with different perceptual capabilitiesare briefly outlined and the key metrics and potential applications are also provided.Finally,we highlight the challenges and perspectives for the future development of artificial sensory neurons.
基金The Foundation of National Natural Science Foundation of China,Grant/Award Number:61421002City University of Hong Kong,Grant/Award Numbers:9678274,9667221,9680322+5 种基金Research Grants Council of Hong Kong Special Administrative Region,Grant/Award Numbers:21210820,11213721,11215722Regional Joint Fund of the National Science Foundation of China,Grant/Award Number:U21A20492The Sichuan Science and Technology Program,Grant/Award Numbers:2022YFH0081,2022YFG0012,2022YFG0013The Sichuan Province Key Laboratory of Display Science and TechnologyInnoHK Project on Project 2.2—AI-based 3D ultrasound imaging algorithm at Hong Kong Centre for Cerebro-Cardiovascular Health Engineering(COCHE)RGC Senior Research Fellow Scheme,Grant/Award Number:SRFS2122-5S04.
文摘Expanding wearable technologies to artificial tactile perception will be of significance for intelligent human-machine interface,as neuromorphic sensing devices are promising candidates due to their low energy consumption and highly effective operating properties.Skin-compatible and conformable features are required for the purpose of realizing wearable artificial tactile perception.Here,we report an intrinsically stretchable,skin-integrated neuromorphic system with triboelectric nanogenerators as tactile sensing and organic electrochemical transistors as information processing.The integrated system provides desired sensing,synaptic,and mechanical characteristics,such as sensitive response(~0.04 kPa^(-1))to low-pressure,short-and long-term synaptic plasticity,great switching endurance(>10000 pulses),symmetric weight update,together with high stretchability of 100%strain.With neural encoding,demonstrations are capable of recognizing,extracting,and encoding features of tactile information.This work provides a feasible approach to wearable,skin-conformable neuromorphic sensing system with great application prospects in intelligent robotics and replacement prosthetics.
