Empirical tight-binding is a valuable and reliable tool for the calculation of electronic and optical properties in semiconductor heterostructures and alloys. It has been applied in many contexts, ranging from inorganic semiconductors like arsenides, antimonides, nitrides and their alloys to 2D materials and hybrid perovskites. Here we present recent activities in development and application of empirical tight-binding, in particular regarding disordered alloys. We show some limitations of the most used schemes, and how they can be overcome by more recent parameterizations, and we introduce an alternative machine-learning based parameterization scheme.

Empirical Tight-Binding Parameterizations for Accurate Heterostructure and Alloy Calculations

Pecchia A.
Penultimo
Writing – Review & Editing
;
2024

Abstract

Empirical tight-binding is a valuable and reliable tool for the calculation of electronic and optical properties in semiconductor heterostructures and alloys. It has been applied in many contexts, ranging from inorganic semiconductors like arsenides, antimonides, nitrides and their alloys to 2D materials and hybrid perovskites. Here we present recent activities in development and application of empirical tight-binding, in particular regarding disordered alloys. We show some limitations of the most used schemes, and how they can be overcome by more recent parameterizations, and we introduce an alternative machine-learning based parameterization scheme.
2024
Istituto per lo Studio dei Materiali Nanostrutturati - ISMN
9798350390537
alloys
empirical tight-binding
machin-learning
parameterization
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/521148
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