Neuromorphic computation using nanoscale adaptive oxide devices or memristors is a very promising alternative to the conventional digital computing framework. Oxides of transition metals, such as hafnium (HfOx), have been proven to be excellent candidate materials for these devices, because they show non-volatile memory and analog switching characteristics. This work presents a comprehensive study of the transport phenomena in HfOx based memristors and involves the development of a fully coupled electrothermal and mass transport model that is validated with electrical and thermal metrology experiments. The fundamental transport mechanisms in HfOx devices were analyzed together with the local and temporal variation of voltage, current, and temperature. The effect of thermal conductivity of substrate materials on the filament temperature, voltage ramp rate, and set/reset characteristics was investigated. These analyses provide insight into the switching mechanisms of these oxides and allow for the prediction of the effect of device architecture on switching behavior.
