Search

Bipolar redox-based resistive random-access memory cells are intensively studied for new storage class memory and beyond von Neumann computing applications. However, the considerable variability of the resistance values in ON and OFF state as well as of the SET voltage remains challenging. In this paper, we discuss the physical origin of the significant reduction in the switching variability of HfO2-based devices achieved by the insertion of a thin TiOx layer between the HfO2 layer and the oxygen exchange metal layer. Typically, HfO2 single layer cells exhibit an abrupt SET process, which is difficult to control. In contrast, self-compliance effects in the HfO2/TiOx bilayer devices lead to an increased stability of SET voltages and OFF-state resistances. The SET process is gradual and the RESET becomes abrupt for higher switching currents. Comparison of the experimental data with simulation results achieved from a physics-based compact model for the full description of the switching behavior of the single layer and bilayer devices clearly reveal three major effects. The TiOx layer affects the temperature distribution during switching (by modifying the heat dissipation), forms an additional series resistance and changes the current conduction mechanism in the OFF state of the bilayer device compared to the single layer device. [ABSTRACT FROM AUTHOR]

In this paper, we investigate in depth Forming, SET, and Retention of conductive-bridge random-access memory (CBRAM). A kinetic Monte Carlo model of the CBRAM has been developed considering ionic hopping and chemical reaction dynamics. Based on inputs from ab initio calculations and the physical properties of the materials, the model offers the simulation of both the Forming/SET and the Data Retention operations. It aims to create a bond between the physics at atomic level and the device behavior. From the model and experimental results obtained on decananometric devices, we propose an understanding of the physical mechanisms involved in the CBRAM operations. Using the consistent Forming/SET and Data Retention model, we obtained good agreement with the experimental data. Finally, the impact of each layer of the CBRAM on the Forming/SET behavior is decorrelated, allowing an optimization of the performance. [ABSTRACT FROM AUTHOR]

In this paper, we show performance and reliability improvement of Ag-GeS2-based conductive bridge RAM (CBRAM) devices by addition of a 2-nm-thick HfO2 layer between the electrolyte and the W bottom electrode. Our optimized dual-layer electrolyte stack (2-nm HfO2\--30\-nm~GeS2) leads to a resistance ratio (ROFF/RON) higher than 10^6 and projected 10 years read disturb immunity at 0.04 V. The improved memory resistance ratio is explained by means of physical modeling. Using compact modeling and circuit level simulations, we show that our optimized CBRAM device, integrated in a 1T-2R architecture, fits well with the aggressive requirements of field programmable gate array-type reconfigurable applications. Nonvolatility, back-end-of-line compatibility, and 1.3-nA leakage current during continuous reverse read operation at 1 V are strong benefits demonstrated on our device for such applications. [ABSTRACT FROM AUTHOR]

Understanding the physical mechanisms for resistance change in metal oxides is a key challenge to assess the scalability of resistive-switching random access memory (RRAM) devices. From this standpoint, the time dependence of filament formation and dissolution in metal oxides can provide a useful insight into the fundamental mechanism of resistive switching. In this paper, we show an experimental study of the time-dependent filament growth and of the voltage dependence of set/reset times in \HfOx-based RRAM devices. The voltage across the device is shown to be regulated at any given time irrespective of the compliance current and the applied voltage, evidencing that voltage is the controlling parameter for the filament formation and dissolution during switching. These results are explained in terms of a thermally-activated ion migration model for filamentary switching. The model allows for an analytical calculation of the scaling dependence of set/reset times and energies in RRAM. [ABSTRACT FROM AUTHOR]