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Tracing the Si Dangling Bond Nanopathway Evolution ina-SiN(x):H Resistive Switching Memory by the Transient Current

With the big data and artificial intelligence era coming, SiN(x)-based resistive random-access memories (RRAM) with controllable conductive nanopathways have a significant application in neuromorphic computing, which is similar to the tunable weight of biological synapses. However, an effective way...

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Detalles Bibliográficos
Autores principales: Chen, Tong, Leng, Kangmin, Ma, Zhongyuan, Jiang, Xiaofan, Chen, Kunji, Li, Wei, Xu, Jun, Xu, Ling
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9823840/
https://www.ncbi.nlm.nih.gov/pubmed/36615995
http://dx.doi.org/10.3390/nano13010085
Descripción
Sumario:With the big data and artificial intelligence era coming, SiN(x)-based resistive random-access memories (RRAM) with controllable conductive nanopathways have a significant application in neuromorphic computing, which is similar to the tunable weight of biological synapses. However, an effective way to detect the components of conductive tunable nanopathways in a-SiN(x):H RRAM has been a challenge with the thickness down-scaling to nanoscale during resistive switching. For the first time, we report the evolution of a Si dangling bond nanopathway in a-SiN(x):H resistive switching memory can be traced by the transient current at different resistance states. The number of Si dangling bonds in the conducting nanopathway for all resistive switching states can be estimated through the transient current based on the tunneling front model. Our discovery of transient current induced by the Si dangling bonds in the a-SiN(x):H resistive switching device provides a new way to gain insight into the resistive switching mechanism of the a-SiN(x):H RRAM in nanoscale.