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A realistic 40 nm InAs high electron mobility transistor is studied using a two-dimensional, full-band, and atomistic Schrödinger-Poisson solver based on the sp 3 d 5 s * tightbinding model. Bandstructure non-parabolicity effects, strain, alloy disorder in the InGaAs and InAlAs barriers, as well as band-to-band tunneling in the transistor OFF-state are automatically included through the full-band atomistic model. The source and drain contact extensions are taken into account a posteriori by adding two series resistances to the device channel. The simulated current characteristics are compared to measured data and show a good quantitative agreement.

We quantify the effect of various sources of uncertainties in the prediction of thermo-physical properties of polymers using molecular dynamics simulations. We quantify how the choice of polymer builder, force field, molecular weight and data analysis affect predicted values of the glass transition temperature (Tg), room temperature density and coefficient of thermal expansion of poly(methyl-methacrylate) (PMMA) and polystyrene (PS). Interestingly, we find that the data analysis introduces significant uncertainties in Tg (approximately 5%) while the other properties are insensitive to it. The force field is the only variable that significantly affects the predictions of density. Polymer-consistent force field (PCFF) resulted in a higher density for PMMA than Dreiding and the opposite trend was observed in PS; in all cases the difference in density was less than 2%. Strongly correlated with density, we find that PCFF leads to a higher Tg than Dreiding for PMMA and both force fields predict similar Tg values for PS. The trends in Tg can be explained by differences in segmental mobility of the melts predicted by the two force fields. We find that the choice of amorphous polymer builder results in uncertainties in predictions comparable to those associated with the force field due to subtle, but persistent, differences in molecular structure. The results presented here provide insight into the physics behind molecular simulations of polymers and quantitative levels of uncertainties associated with individual sources that can help practitioners of molecular simulations interested in using their results in engineering applications.

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