JART ECM v1 vardoi:10.26165/JUELICH-DATA/WHSSZAJülich DATA2025-08-151Ahmad, Rana Walied; Menzel, Stephan, 2025, "JART ECM v1 var", https://doi.org/10.26165/JUELICH-DATA/WHSSZA, Jülich DATA, V1JART ECM v1 vardoi:10.26165/JUELICH-DATA/WHSSZAAhmad, Rana WaliedMenzel, StephanJülich DATAMenzel, StephanAhmad, Rana Walied2025-07-27Computer and Information ScienceEngineeringPhysicsOthermemristive devices, variability-aware modeling, ReRAM, ECM, CBRAM, SPICE level, compact modelA purely physics-based variability-aware compact model of electrochemical metallization memory (ECM) cells is presented. Since this extension consists of several different features allowing for a realistic variability-aware fit, it depicts a unique model comprising physics-based, stochastically and experimentally originating variabilities and reproduces them well. It is based on the deterministic ECM model JART ECM v1. The variability-aware model introduces device-to-device variability by choosing the model parameters from a physically reasonable value range. The cycle-to-cycle variability can be introduced by updating these parameters according to a random walk algorithm after a certain time step. Moreover, a stochastic feature is added to the gap evolution within the model’s main dynamics-determining differential equation. The model is validated by experimental data of Cu/SiO2/W ECM cells. This model can be used in higher-level circuit simulators like Spectre to design variability-aware application circuits. [1] shows (a) experimentally measured and (b) simulatively verified device-to-device variability for SET kinetics analysis. [2] shows experimentally measured I–V sweeps in red, simulated I–V sweeps in blue: (a) experimentally recorded I–V sweep, (b) simulated I-V sweep characteristics with all simulation modifications, (c) - (f) simulated I–V sweep characteristics showing individual types of simulation modifications.CC0 Waiver10.1088/2634-4386/ad57e7R. W. Ahmad et al. “Variability-Aware Modeling of Electrochemical Metallization Memory Cells”. In: Neuromorphic Computing and Engineering 4.3 (2024)Figure4-1.svg[1] (a) Experimentally measured and (b) simulatively verified device-to-device variability for SET kinetics analysis. Simulation also includes the SET kinetics curve obtained by mean parameter values (in black). It shows the first steeper slope from 0.3–3.5 V related to the electron transfer regime and the second flatter slope from 3.5–4.8 V related to the mixed control regime.image/svg+xmlFigure5-1.svg[2] Experimentally measured I–V sweeps in red, simulated I–V sweeps in blue: (a) experimentally recorded I–V sweep, (b) simulated I–V sweep characteristics with all four modifications, (c) only staircase I–V sweep and parameter variation after each SET and RESET, (d) only staircase I–V sweep, current averaging for each staircase step and parameter variation after each staircase step, (e) only parameter variation after each staircase step, but continuous sweep and continuous current and (f) only stochasticity in the gap evolution within the ODE.image/svg+xmlveriloga.vaJART ECM v1 varapplication/octet-stream