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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. [ABSTRACT FROM AUTHOR]

A back-gated multilayer nanoribbon molybdenum disulfide (MoS2) transistor grown by chemical vapor transport and doped using polyethylene oxide cesium perchlorate is fabricated and characterized. Ions in the polymer dielectric are directed by side gates to the source and drain access regions where they form electric double layers (EDLs) that control the carrier densities. This allows the junctions of the same transistor channel to be reconfigured as an n-MOSFET, p-MOSFET, and as a tunnel field-effect transistors. The EDLs are formed at room temperature and then locked into place by cooling the polymer below the glass transition temperature (~240 K). Transport measurements are presented and explained using simulated band diagrams. Both n and p-conduction in MoS2 is demonstrated using solid polymer ion doping, enabling characterization of a semiconductor in which the doping of the same channel has been reconfigured to form three different transistor configurations. [ABSTRACT FROM AUTHOR]