In this work, the SET and RESET processes of bipolar resistive switching memories with silicon nanocrystals (Si-NCs) embedded in an oxide matrix is simulated by a stochastic model. This model is based on the estimation of two-dimensional oxygen vacancy configurations and their relationship with the resistive state. The simulation data are compared with the experimental current-voltage data of Si-NCs/Si${\mathrm{O}}_2$ multilayer-based memristor devices. Devices with 1 and 3 Si-NCs/Si${\mathrm{O}}_2$ bilayers were analyzed. The Si-NCs are assumed as agglomerates of fixed oxygen vacancies, which promote the formation of conductive filaments (CFs) through the multilayer according to the simulations. In fact, an intermediate resistive state was observed in the forming process (experimental and simulated) of the 3-BL device, which is explained by the preferential generation of oxygen vacancies in the sites that form the complete CFs, through Si-NCs.

In this work, the simulation of deoxidation–oxidation of oxygen vacancies (V_Os) in an oxide matrix with embedded conductive nanocrystals (c-NCs) is carried out for the development of bipolar resistive switching memories (BRSMs). We have employed the three-dimensional kinetic Monte Carlo (3D-kMC) method to simulate the RS behavior of BRSMs. The c-NC is modeled as fixed oxygen vacancy (f-V_O) clusters, defined as sites with zero recombination probability. The three-dimensional oxygen vacancy configuration (3D-V_OC) obtained for each voltage step of the simulation is used to calculate the resistive state and the electrical current. It was found that the c-NC reduces the voltage required to switch the memory state from a high to a low resistive state due to the increase in a nonhomogeneous electrical field between electrodes.