A Simulation Study on Minimizing Threshold Voltage Variability by Optimizing Oxygen Vacancy Concentration under Metal Gate Granularity

In this work, we discuss the mitigation of threshold voltage ( ${V}_{{TH}}$ ) variability in nanoscale FinFET by exploiting the interaction of oxygen vacancies (OV) against metal gate granularity (MGG). Deposition of a metal gate on high- $\kappa$ dielectric HfO2 is known to generate OV in the dielectric which induces variability in surface potential. A higher workfunction of metal grain increases the probability of OV formation. Interestingly, while a higher workfunction metal grain decreases the surface potential of the channel underneath, the positive charge of OV increases the potential. Therefore, the concentration of OV can be controlled to negate the surface potential variability induced by MGG. We discuss the law of mass action-based concentration models of OV under MGG to analyze this. We also present TCAD simulations supporting the above hypothesis. In our simulations, for 10-nm channel FinFET, MGG-induced $\sigma$ ( ${V}_{{TH}}$ ) can be reduced to 20 mV from 35 mV for four-sided planar grains with 8 nm average edge length under the optimal OV concentration.