Selective Digital Etching of Silicon-Germanium Using Nitric and Hydrofluoric Acids

Area of Science:

• Materials Science
• Chemical Engineering
• Semiconductor Processing

Background:

• Precise control over etching depth is crucial for advanced semiconductor device fabrication.
• Existing wet etching methods often lack the necessary resolution and repeatability for nanoscale structures.

Purpose of the Study:

• To investigate the digital etching characteristics of p+-silicon (p+-Si) and silicon germanium (Si0.7Ge0.3).
• To develop and validate an oxidation model for wet etching processes using nitric acid.
• To achieve excellent control of etching depth in semiconductor materials.

Main Methods:

• Investigated digital etching using a combination of nitric acid (HNO3) oxidation and buffered oxide etching (BOE) for oxide removal.
• Developed a mathematical model to describe the wet oxidation process with nitric acid.
• Calibrated the oxidation model with experimental data to determine key etching parameters.

Main Results:

• Oxidation was found to saturate over time due to low activation energy and diffusion limitations.
• The saturated relative etched depth per cycle for Si0.7Ge0.3/p+-Si stacks was 0.5 nm (four monolayers) with ~4% variation.
• A corrected selectivity formula was proposed, yielding calculated selectivity values of 3.7-7.7, consistent with the oxidation model.

Conclusions:

• The developed oxidation model accurately predicts saturation time, oxide thickness, and selectivity.
• The proposed digital etching method provides excellent control and repeatability for semiconductor etching.
• The model offers valuable guidance for optimizing wet digital etching experiments and analyzing process variations.