Impact of interface roughness correlation on resonant tunnelling diode variation

Area of Science:

• Semiconductor device physics
• Computational materials science
• Nanoelectronics

Background:

• Interface Roughness (IR) significantly impacts the performance of nanoelectronic devices.
• Existing models for IR in Resonant Tunnelling Diodes (RTDs) may not fully capture the complexities of surface morphology.
• Accurate simulation of IR is essential for predicting and optimizing RTD behavior.

Purpose of the Study:

• To introduce and evaluate an improved Interface Roughness (IR) model within the Nano-Electronic Simulation Software (NESS).
• To investigate the impact of anisotropic IR, considering two perpendicular correlation lengths, on RTD device variation.
• To quantify the differences in device variation between the previous and improved IR models.

Main Methods:

• Utilized the Nano-Electronic Simulation Software (NESS) with both previous and improved IR models.
• Simulated Resonant Tunnelling Diodes (RTDs) with varying correlation lengths (2.5 nm to 10 nm) for IR.
• Quantified device variation using the standard deviation of resonant peak current and bias voltage from current-voltage characteristics.

Main Results:

• The improved IR model significantly increased device variation, with standard deviations rising from 6.2 mV and 9 nA to 24.2 mV and 34.7 nA for a 5 nm correlation length.
• Device variation approximately doubled as correlation length increased from 2.5 nm to 10 nm for both models.
• Anisotropic correlation length studies showed further variations in standard deviations, highlighting the model's sensitivity.

Conclusions:

• The improved IR model, incorporating two correlation lengths, provides a more realistic representation of RTD behavior.
• Accurate simulation of IR with anisotropic properties is critical for future research and development of RTDs.
• NESS's enhanced IR model is vital for precise nanoelectronic device simulations.