The flexible electronics has been deemed to be a promising approach to the wearable electronic systems.However,the mismatching between the existing flexible deices and the conventional computing paradigm results an im...The flexible electronics has been deemed to be a promising approach to the wearable electronic systems.However,the mismatching between the existing flexible deices and the conventional computing paradigm results an impasse in this field.In this work,a new way to access to this goal is proposed by combining flexible devices and the neuromorphic architecture together.To achieve that,a high-performance flexible artificial synapse is created based on a carefully designed and optimized memristive transistor.The device exhibits high-performance which has near-linear non-volatile resistance change under 10,000 identical pulse signals within the 515%dynamic range,and has the energy consumption as low as 45 fJ per pulse.It also displays multiple synaptic plasticity features,which demonstrates its potential for real-time online learning.Besides,the adaptability by virtue of its threeterminal structure specifically contributes its improved uniformity,repeatability,and reduced power consumption.This work offers a very viable solution for the future wearable computing.展开更多
基金This work was supported China Scholarship Council(CSC)This work was supported by Shanghai Science and Technology Innovation action plan(17JC1401300 and 15JC1400100).
文摘The flexible electronics has been deemed to be a promising approach to the wearable electronic systems.However,the mismatching between the existing flexible deices and the conventional computing paradigm results an impasse in this field.In this work,a new way to access to this goal is proposed by combining flexible devices and the neuromorphic architecture together.To achieve that,a high-performance flexible artificial synapse is created based on a carefully designed and optimized memristive transistor.The device exhibits high-performance which has near-linear non-volatile resistance change under 10,000 identical pulse signals within the 515%dynamic range,and has the energy consumption as low as 45 fJ per pulse.It also displays multiple synaptic plasticity features,which demonstrates its potential for real-time online learning.Besides,the adaptability by virtue of its threeterminal structure specifically contributes its improved uniformity,repeatability,and reduced power consumption.This work offers a very viable solution for the future wearable computing.
