Stochastic based compact model to predict highly variable electrical characteristics of organic CBRAM devices
Résumé
A compact model is proposed using a stochastic approach to capture the resistive switching behavior of conductive-bridge random access memory (CBRAM) device featuring a solid polymer electrolyte consisting of Polyethylene Oxide (PEO). This model considers the statistical distribution of five electrical parameters used to describe the resistive switching observed in experimental data. A switching probability is defined to control the change of resistive state. This approach gives the model the stochastic behavior of current–voltage characteristics observed in this kind of devices. A good agreement between the simulation and the experimental curves is observed despite the unusual variability cycle-to-cycle for this type of ReRAM.
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