Contributions of point defects, chemical disorder, and thermal vibrations to electronic properties of Cd(1-x)Zn(x)Te alloys

We present a first principles study based on density functional theory of thermodynamic and electronic properties of the most important intrinsic defects in the semiconductor alloy Cd(1-x)Zn(x)Te with x<0.13. The alloy is represented by a set of supercells with disorder on the Cd/Zn sublattice. Defect formation energies as well as electronic and optical transition levels are analyzed as a function of composition. We show that defect formation energies increase with Zn content with the exception of the neutral Te vacancy. This behavior is qualitatively similar to but quantitatively rather different from the effect of volumetric strain on defect properties in pure CdTe. Finally, the relative carrier scattering strengths of point defects, alloy disorder, and phonons are obtained. It is demonstrated that for realistic defect concentrations carrier mobilities are limited by phonon scattering for temperature above approximately 150 K

Contributions of point defects, chemical disorder, and thermal vibrations to electronic properties of Cd1-xZnxTe alloys

We present a first-principles study based on density functional theory of thermodynamic and electronic properties of the most important intrinsic defects in the semiconductor alloy Cd1-xZnxTe with x < 0.13. The alloy is represented by a set of supercells with disorder on the Cd/Zn sublattice. Defect formation energies as well as electronic and optical transition levels are analyzed as a function of composition. We show that defect formation energies increase with Zn content with the exception of the neutral Te vacancy. This behavior is qualitatively similar to but quantitatively rather different from the effect of volumetric strain on defect properties in pure CdTe. Finally, the relative carrier scattering strengths of point defects, alloy disorder, and phonons are obtained. It is demonstrated that for realistic defect concentrations, carrier mobilities are limited by phonon scattering for temperatures above approximately 150 K

LTAU-FF: Loss Trajectory Analysis for Uncertainty in Atomistic Force Fields

Model ensembles are effective tools for estimating prediction uncertainty in deep learning atomistic force fields. However, their widespread adoption is hindered by high computational costs and overconfident error estimates. In this work, we address these challenges by leveraging distributions of per-sample errors obtained during training and employing a distance-based similarity search in the model latent space. Our method, which we call LTAU, efficiently estimates the full probability distribution function (PDF) of errors for any test point using the logged training errors, achieving speeds that are 2--3 orders of magnitudes faster than typical ensemble methods and allowing it to be used for tasks where training or evaluating multiple models would be infeasible. We apply LTAU towards estimating parametric uncertainty in atomistic force fields (LTAU-FF), demonstrating that its improved ensemble diversity produces well-calibrated confidence intervals and predicts errors that correlate strongly with the true errors for data near the training domain. Furthermore, we show that the errors predicted by LTAU-FF can be used in practical applications for detecting out-of-domain data, tuning model performance, and predicting failure during simulations. We believe that LTAU will be a valuable tool for uncertainty quantification (UQ) in atomistic force fields and is a promising method that should be further explored in other domains of machine learning