All electronic devices, in this case, SiC MOS transistors, are exposed to aging mechanisms and variability issues, that can affect the performance and stable operation of circuits. To describe the behavior of the devices for circuit simulations, physical models which capture the degradation of the devices are required. Typically compact models based on closed-form mathematical expressions are often used for circuit analysis, however, such models are typically not very accurate. In this work, we make use of physical reliability models and apply them for aging simulations of pseudo-CMOS logic inverter circuits. The model employed is available via our reliability simulator Comphy and is calibrated to evaluate the impact of bias temperature instability (BTI) degradation phenomena on the inverter circuit’s performance made from commercial SiC power MOSFETs. Using Spice simulations, we extract the propagation delay time of inverter circuits, taking into account the threshold voltage drift of the transistors with stress time under DC and AC operating conditions. To achieve the highest level of accuracy for our evaluation we also consider the recovery of the devices during low bias phases of AC signals, which is often neglected in existing approaches. Based on the propagation delay time distribution, the importance of a suitable physical defect model to precisely analyze the circuit operation is discussed in this work too.
Statistical Strategies to Capture Correlation between Overshooting Effect and Propagation Delay Time in nano-CMOS Inverters
