Abstract

Ferroelectric (FE) materials are being studied for a variety of applications in memory, logic, and neuromorphic computing, for which predictive models of FE polarization are essential. In this paper, we present a Monte Carlo simulation framework capable of predicting the dynamic, history-dependent response of an FE under arbitrary input waveforms. The simulation is developed by generalizing the physics-based nucleation-limited switching model for polarization reversal in a polycrystalline FE. Measured polarization reversal data from fabricated FE Hf0.5Zr0.5O2 capacitors are used to extract the statistical distribution of FE grains. After parameter extraction, the model is able to predict the dynamics of the FE capacitor without further calibration. Finally, the model is applied to characterize the dynamic response of FE-dielectric bilayer structures and quantify the reduction in memory window due to device variability.