Electromigration phenomena in metallic lines are studied by using a biased resistor network model. The void formation induced by the electron wind is simulated by a stochastic process of resistor breaking, while the growth of mechanical stress inside the line is described by an antagonist process of recovery of the broken resistors. The model accounts for the existence of temperature gradients due to current crowding and Joule heating. Alloying effects are also accounted for. Monte Carlo simulations allow the study within a unified theoretical framework of a variety of relevant features related to the electromigration. The predictions of the model are in excellent agreement with the experiments and in particular with the degradation towards electrical breakdown of stressed Al-Cu thin metallic lines. Detailed investigations refer to the damage pattern, the distribution of the times to failure (TTFs), the generalized Black's law, the time evolution of the resistance, including the early-stage change due to alloying effects and the electromigration saturation appearing at low current densities or for short line lengths. The dependence of the TTFs on the length and width of the metallic line is also well reproduced. Finally, the model successfully describes the resistance noise properties under steady state conditions.
The role of carbon related traps in GaN-based ungated HEMT structures has been investigated both experimentally and by means of numerical simulations. A clear quantitative correlation between experimental data and numerical simulations has been obtained. The observed current decrease in the tested structure during backgating measurements has been explained simply by means of a thermally activated hole-emission process with E A =0.9eV, corresponding to the distance of the acceptor-like hole-trap level from the GaN valence band. Moreover, it has been demonstrated by means of electrical measurements and numerical simulations that only a low percentage of the nominal Carbon doping levels induces the observed current reduction when negative substrate bias are applied to the tested structure.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.