Computational approaches to point defect simulations for semiconductor solid solution alloys.

Area of Science:

• Materials Science
• Computational Materials Science
• Solid-State Physics

Background:

• Studying alloy properties using first-principles methods is computationally intensive, especially for materials with random cation site occupation like AlGaN and BaSrTiO3 (BST).
• Point defects significantly influence the properties of technologically important alloys such as AlGaN and BST.
• Explicit simulation of these alloys is often too demanding due to the random distribution of elements on crystallographic sites.

Purpose of the Study:

• To develop a computationally efficient method for approximating defect properties and concentrations in intermediate alloy compositions.
• To investigate the behavior of Si and Ge dopants in n-type Al-rich AlGaN, including self-compensating defects.
• To examine the high-temperature defect chemistry of Mg and Fe in BST.

Main Methods:

• Utilizing interpolation between end-member compounds as a first approximation for defect properties.
• Analyzing self-compensating defects, multi-donor vacancy complexes, and DX configurations for Si and Ge dopants in AlGaN.
• Investigating the variation of defect chemistry for Mg and Fe in BST.

Main Results:

• Demonstrated the efficacy of interpolation for approximating defect properties in AlGaN and BST alloys.
• Identified key defect mechanisms influencing dopant behavior in AlGaN.
• Characterized the high-temperature defect chemistry variations in BST.

Conclusions:

• The interpolation approach provides a viable and computationally tractable first approximation for defect properties in random solid-solution alloys.
• This method is broadly applicable to semiconductors and dielectrics where alloy properties are governed by point defects.
• The findings facilitate a better understanding of dopant incorporation and defect mitigation strategies in advanced materials.