Temperature dependent analytical modeling and simulations of nanoscale memristor

In this paper, modeling of memristor has been carried out contemplating the temperature effect on its various parameters. A relationship is established between temperature and mobility, based on the temperature dependent conductivity. The derived mobility is extrapolated to determine other parameters of memristor like RON, ROFF including maximum possible memorized charge and inner diffusion coefficient. The results reveal that the derived mobility is less prone to temperature variation as compared to reported mobility, and is more sagacious during memristor operation. In order to validate our results, each parameter is compared with reported data. Apart from this, memristor's I-V characteristics, memristance, and state variable are rendered at different temperatures and impact of temperature is analyzed. It is seen that the current through the memristor increases and switching rate becomes faster at higher temperatures. There is an increment of two orders in current and 33% reduction in switching delay is observed by stepping up the temperature from 200 K to 400 K.