Acceptor defects in polycrystalline Ge layers evaluated using linear regression analysis

Area of Science:

• Materials Science
• Solid State Physics
• Semiconductor Device Physics

Background:

• Polycrystalline germanium (Ge) thin films are crucial for electronic and optical devices.
• Controlling the Fermi level in these films is challenging due to abundant defect-induced acceptors.
• This limits their widespread application in advanced devices.

Purpose of the Study:

• To experimentally determine the origin of acceptor defects in polycrystalline Ge thin films.
• To correlate crystallinity and electrical properties with defect types.
• To develop a method for understanding and controlling these defects.

Main Methods:

• Modulating crystallinity and electrical properties of polycrystalline Ge layers.
• Applying a linear regression analysis based on temperature-dependent hole concentration.
• Analyzing the impact of grain size and post-annealing on hole concentration.

Main Results:

• Identified two distinct acceptor levels in polycrystalline Ge films.
• Deep acceptor levels (53-103 meV) are linked to dangling bonds at grain boundaries.
• Shallow acceptor levels (< 15 meV) are attributed to vacancies within grains.

Conclusions:

• Dangling bonds and vacancies are the primary sources of acceptor defects in polycrystalline Ge.
• A machine learning-based simulation method was proposed for analyzing physical properties.
• Findings provide insights for controlling acceptor defects to enhance Ge thin film applications.