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• W2912892722 abstract "Volatile resistive switching memory (RRAM) is raising strong interest as potential selector device in crosspoint memory and short-term synapse in neuromorphic computing. To enable the design and simulation of memory and computing circuits with volatile RRAM, compact models are essential. To fill this gap, we present here a novel physics-based analytical model for volatile RRAM based on a detailed study of the switching process by molecular dynamics (MD) and finite-difference method (FDM). The analytical model captures all essential phenomena of volatile RRAM, e.g., threshold/holding voltages, on-off ratio, and size-dependent retention. The model is validated by extensive comparison with data from Ag/SiO <sub xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>x</sub> RRAM. To support the circuit-level capability of the model, we show simulations of crosspoint arrays and neuromorphic time-correlated learning." @default.
• W2912892722 created "2019-02-21" @default.
• W2912892722 creator A5001731684 @default.
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• W2912892722 date "2018-12-01" @default.
• W2912892722 modified "2023-09-25" @default.
• W2912892722 title "Physics-based modeling of volatile resistive switching memory (RRAM) for crosspoint selector and neuromorphic computing" @default.
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• W2912892722 doi "https://doi.org/10.1109/iedm.2018.8614556" @default.
• W2912892722 hasPublicationYear "2018" @default.
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