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High on/off ratio SiO<sub>2</sub>-based memristors for neuromorphic computing: understanding the switching mechanisms through theoretical and electrochemical aspects

Fei Qin, Yuxuan Zhang, Ziqi Guo, Tae Joon Park, Hongsik Park, Chung Soo Kim, Jeong-Min Park, Xingyu Fu, Kwangsoo No, Han Wook Song, Xiulin Ruan, Sunghwan Lee

2024Materials Advances24 citationsDOIOpen Access PDF

Abstract

Finite element analysis provides visual insights into conductive path evolution in a SiO 2 -based memristor. Electrochemical impedance spectroscopy experimentally validated the theoretical findings by interpreting with an equivalent circuit.

Topics & Concepts

Neuromorphic engineeringMemristorDielectric spectroscopyPath (computing)ElectrochemistryElectrical impedanceMaterials scienceElectrical conductorOptoelectronicsElectronic engineeringComputer scienceNanotechnologyPhysicsElectrical engineeringArtificial intelligenceArtificial neural networkEngineeringElectrodeComposite materialQuantum mechanicsProgramming languageAdvanced Memory and Neural ComputingNeuroscience and Neural EngineeringPhotoreceptor and optogenetics research
High on/off ratio SiO<sub>2</sub>-based memristors for neuromorphic computing: understanding the switching mechanisms through theoretical and electrochemical aspects | Litcius