Physics Guided Exponential Model Design of High Ge Content SiGe Selective Epitaxy for Gate All Around Source/Drain Applications

TL;DR

This paper introduces a physics-guided exponential model for optimizing high Ge content SiGe epitaxy in nanoscale trenches, enabling precise control of Ge incorporation for advanced GAA transistors.

Contribution

A novel physics-based exponential model linking epitaxial growth parameters to Ge incorporation kinetics in nanoscale trenches.

Findings

Achieved maximum Ge content of 57.93% in 60 nm trenches.

Demonstrated 100% selectivity against SiN and SiO.

Validated the model with TEM and EDS analyses showing graded Ge profiles.

Abstract

High germanium content silicon germanium (SiGe) epitaxy is critical for strain engineering in advanced gate all around (GAA) transistors. This paper demonstrates a physics guided exponential function model that quantitatively links selective epitaxial growth (SEG) parameters to Ge incorporation kinetics in nanoscale trenches. By coupling surface diffusion limited transport, gradient strain, and competitive adsorption dynamics, the model predicts optimal conditions for bottom-up filling with maximal Ge content. For trenches with widths of approximately 60 nm, the optimized process achieved a maximum Ge content of 57.93% and demonstrated 100% selectivity against silicon nitride (SiN) and silicon dioxide (SiO). Cross sectional TEM and EDS analyses reveal a graded Ge profile that minimizes interfacial defects and strain energy. Our results show that the established process physics correlation will significantly facilitate the development of GAA devices with 5nm CMOS technology nodes and beyond.