As a critical command center in organisms,the brain can execute multiple intelligent interactions through neural networks,including memory,learning and cognition.Recently,memristive-based neuromorphic devices have bee...As a critical command center in organisms,the brain can execute multiple intelligent interactions through neural networks,including memory,learning and cognition.Recently,memristive-based neuromorphic devices have been widely developed as promising technologies to build artificial synapses and neurons for neural networks.However,multiple information interactions in artificial intelligence devices potentially pose threats to information security.Herein,a transient form of heterogeneous memristor with a stacked structure of Ag/MgO/SiN_(x)/W is proposed,in which both the reconfigurable resistive switching behavior and volatile threshold switching characteristics could be realized by adjusting the thickness of the SiN_(x)layer.The underlying resistive switching mechanism of the device was elucidated in terms of filamentary and interfacial effects.Representative neural functions,including short-term plasticity(STP),the transformation from STP to long-term plasticity,and integrate-and-fire neuron functions,have been successfully emulated in memristive devices.Moreover,the dissolution kinetics associated with underlying transient behaviors were explored,and the water-assisted transfer printing technique was exploited to build transient neuromorphic device arrays on the water-dissolvable poly(vinyl alcohol)substrate,which were able to formless disappear in deionized water after 10-s dissolution at room temperature.This transient form of memristive-based neuromorphic device provides an important step toward information security reinforcement for artificial neural network applications.展开更多
基金supported by the National Natural Science Foundation of China(62304172,62188102,and 62274130)the Natural Science Basic Research Program of Shaanxi(2022JQ-582 and 2022JQ-684)+2 种基金Guangdong Basic and Applied Basic Research Foundation(2021A1515110020)the Fundamental Research Funds for the Central Universities(ZYTS24119)the Scientific Research Program Foundation of Shaanxi Provincial Education Department(22JK0564)。
文摘As a critical command center in organisms,the brain can execute multiple intelligent interactions through neural networks,including memory,learning and cognition.Recently,memristive-based neuromorphic devices have been widely developed as promising technologies to build artificial synapses and neurons for neural networks.However,multiple information interactions in artificial intelligence devices potentially pose threats to information security.Herein,a transient form of heterogeneous memristor with a stacked structure of Ag/MgO/SiN_(x)/W is proposed,in which both the reconfigurable resistive switching behavior and volatile threshold switching characteristics could be realized by adjusting the thickness of the SiN_(x)layer.The underlying resistive switching mechanism of the device was elucidated in terms of filamentary and interfacial effects.Representative neural functions,including short-term plasticity(STP),the transformation from STP to long-term plasticity,and integrate-and-fire neuron functions,have been successfully emulated in memristive devices.Moreover,the dissolution kinetics associated with underlying transient behaviors were explored,and the water-assisted transfer printing technique was exploited to build transient neuromorphic device arrays on the water-dissolvable poly(vinyl alcohol)substrate,which were able to formless disappear in deionized water after 10-s dissolution at room temperature.This transient form of memristive-based neuromorphic device provides an important step toward information security reinforcement for artificial neural network applications.
