2023-09-192023-09-192020-05Saraza Canflanca, P., Díaz Fortuny, J., Castro López, R., Roca, E., Martín Martínez, J., Rodríguez, R.,...,Fernández Fernández, F.V. (2020). A robust and automated methodology for the analysis of Time-Dependent Variability at transistor level. Integration, 72, 13-20. https://doi.org/10.1016/j.vlsi.2020.02.002.0167-92601872-7522https://hdl.handle.net/11441/148995In the past few years, Time-Dependent Variability has become a subject of growing concern in CMOS technologies. In particular, phenomena such as Bias Temperature Instability, Hot-Carrier Injection and Random Telegraph Noise can largely affect circuit reliability. It becomes therefore imperative to develop reliability-aware design tools to mitigate their impact on circuits. To this end, these phenomena must be first accurately characterized and modeled. And, since all these phenomena reveal a stochastic nature for deeply-scaled integration technologies, they must be characterized massively on devices to extract the probability distribution functions associated to their characteristic parameters. In this work, a complete methodology to characterize these phenomena experimentally, and then extract the necessary parameters to construct a Time-Dependent Variability model, is presented. This model can be used by a reliability simulator. © 2020 Elsevier B.V.application/pdf10engAttribution-NonCommercial-NoDerivatives 4.0 Internacionalhttp://creativecommons.org/licenses/by-nc-nd/4.0/Bias temperature instabilityBTICharacterizationCMOSHCIHot-carrier injectionRandom telegraph noiseReliabilityRTNSimulationTDVTime-dependent variabilityinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/openAccess10.1016/j.vlsi.2020.02.002