Optimizing hybrid metrology through a consistent multi-tool parameter set and uncertainty model

Abstract

There has been significant interest in hybrid metrology as a novel method for reducing overall measurement uncertainty and optimizing measurement throughput (speed) through rigorous combinations of two or more different measurement techniques into a single result. This approach is essential for advanced 3-D metrology when performing model-based critical dimension measurements. However, a number of fundamental challenges present themselves with regard to consistent noise and measurement uncertainty models across hardware platforms, and the need for a standardized set of model parameters. This is of paramount concern when the various techniques have substantially different models and underlying physics. In this paper we present realistic examples using scanning electron microscopy, atomic force microscopy, and optical critical dimension (CD) methods applied to sub-20 nm dense feature sets. We will show reduced measurement uncertainties using hybrid metrology on 15 nm CD features and evaluate approaches to adapt quantitative hybrid metrology into a high volume manufacturing environment.