Atomic-Level Monte Carlo Modeling of SiN Deposition by PECVD

Abstract

Plasma-enhanced chemical vapor deposition (PECVD) is a critical technique in integrated circuit manufacturing. As semiconductor devices continue to scale down in advanced technology nodes, the details of PECVD processes are difficult to be captured by traditional Technology Computer Aided Design (TCAD) approaches. In this study, we present a Monte Carlo approach to predict the profile evolution of Si3N4 thin film deposition by PECVD at feature scale. By employing a new transport algorithm for reactive species in vacuum, our method achieves an atomic-level modeling of deposition profile evolution within acceptable computational time. Experimental validation demonstrates that this model achieves a mean prediction errors below 10 % for the deposition of trenches with different aspect ratios.