The application of multi-scale simulation in advanced electronic packaging.

Area of Science:

• Electronic engineering
• Materials science
• Computational physics

Background:

• Electronic packaging protects devices from environmental factors.
• Packaging design involves complex multi-physics phenomena like thermal transport and mechanical stress.
• Assessing electronic device performance and reliability necessitates understanding multiphysics coupling.

Purpose of the Study:

• To provide a comprehensive overview of multiphysics coupling in electronic packaging.
• To summarize recent advancements in multi-scale simulation techniques for electronic packaging.
• To illustrate the application of these methods in studying electronic packaging aspects.

Main Methods:

• Review of multi-scale simulation techniques: finite element methods (FEM), molecular dynamics (MD), density functional theory (DFT).
• Focus on machine learning (ML) methods for bridging different simulation scales.
• Application examples in material properties, interfacial failure, thermal management, electromigration, and stress analysis.

Main Results:

• Multi-scale simulations are essential for analyzing complex electronic packaging phenomena.
• Machine learning shows promise in integrating macroscopic and microscopic simulation scales.
• These techniques enable detailed study of critical electronic packaging issues.

Conclusions:

• Multi-scale simulation techniques offer significant potential for advancing electronic packaging design and reliability.
• Challenges and future research directions in applying these methods are identified.
• Further investigation into ML-driven multi-scale simulations is recommended for electronic packaging.