Physics-based modeling of volatile resistive switching memory (RRAM) for crosspoint selector and neuromorphic computing

W Wang and A Bricalli and M Laudato and E Ambrosi and E Covi and D Ielmini, 2018 IEEE INTERNATIONAL ELECTRON DEVICES MEETING (IEDM) (2018).

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/SiOX RRAM. To support the circuit-level capability of the model, we show simulations of crosspoint arrays and neuromorphic time-correlated learning.

Return to Publications page