Superlattice Growth via MBE and Green's Function Techniques.

Area of Science:

• Materials Science
• Condensed Matter Physics
• Computational Modeling

Background:

• Epitaxial growth of quantum dots (QDs) is crucial for advanced semiconductor devices.
• Understanding strain distribution is key to controlling QD morphology and performance.
• Existing models often simplify the complex elastic interactions within heterostructures.

Purpose of the Study:

• To develop a computational model for simulating the growth of epitaxially grown quantum dot arrays.
• To predict optimal locations for new quantum dot formation based on surface strain.
• To investigate the influence of elastic anisotropy on QD growth patterns.

Main Methods:

• Modeled substrate and spacer layers as anisotropic elastic half-spaces.
• Represented quantum dots as buried point inclusions.
• Calculated surface strain using a weighted average of in-plane strains, informed by DFT results.
• Iteratively placed new QDs at predicted surface strain minima.

Main Results:

• The model successfully simulates QD array growth by identifying minimum strain locations for new QD nucleation.
• The model's predictions show better agreement with experimental data for SiGe QDs compared to (In,Ga)As QDs.
• The assumption of neglecting diffusional anisotropy simplifies the model while maintaining relevance for certain QD systems.

Conclusions:

• The developed elastic model provides a valuable tool for understanding and predicting quantum dot growth dynamics.
• Strain-mediated self-assembly is a viable mechanism for controlled QD array fabrication.
• The model's accuracy is dependent on the material system, performing better for SiGe due to specific growth characteristics.