After nearly half a century of research into the bias temperature instability, two classes of models have emerged as the strongest contenders. One class of models, the reaction-diffusion models, is built around the idea that hydrogen is released from the interface and that it is the diffusion of some form of hydrogen that controls both degradation and recovery. Although various variants of the reaction-diffusion idea have been published over the years, the most commonly used recent models are based on nondispersive reaction rates and nondispersive diffusion. The other class of models is based on the idea that degradation is controlled by first-order reactions with widely distributed (dispersive) reaction rates. We demonstrate that these two classes give fundamentally different predictions for the stochastic degradation and recovery of nanoscale devices, therefore providing the ultimate modeling benchmark. Using detailed experimental timedependent defect spectroscopy data obtained on such nanoscale devices, we investigate the compatibility of these models with experiment. Our results show that the diffusion of hydrogen (or any other species) is unlikely to be the limiting aspect that determines degradation. On the other hand, the data are fully consistent with reaction-limited models. We finally argue that only the correct understanding of the physical mechanisms leading to the significant device-to-device variation observed in the degradation in nanoscale devices will enable accurate reliability projections and device optimization.

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