Single wafer process to generate reliable swing

Abstract

Swing curve generation is an important and common exercise in the design, characterization, and optimization of photolithography processes. The development of a robust anti-reflective strategy for a given process often necessitates multiple experimental iterations of the swing curve generation. The traditional methodology for generating a photoresist thickness swing curve plot is time and silicon intensive; usually involving processing and metrology on a dozen or more wafers. In addition, the resulting curve often can convolve systematic and random wafer-wafer effects due to other track/resist/scanner related variables. In some cases, such as very low reflectivity underlying substrate the signal to noise ratio is poor enough to effectively mask the sinusoidal swing behavior from visibility. In this paper, we present a new methodology to generate a swing curve by using a single wafer. The critical point of this method is to generate a temperature gradient on the wafer during the initial step of photoresist dispense and coating. Since the resist viscosity is inversely proportional to the temperature, a significant resist thickness variation can be produced across the wafer, which can easily encompass one swing period of thickness or more. The resulting resist thickness signature across the wafer is seen to be very repeatable, such that a companion wafer can be measured at multiple positions corresponding to CD metrology lcoations on the patterned wafer. The possibility of deconvolving systematic across wafer CD variability due to other process variables is discussed by characterizing a control wafer with conventional uniform resist thickness. Our experiments for I-line and DUV resists indicated that this method not only provides reliable swing curves but also saves photoresist, silicon, and time both for engineering and machine. Moreover, this methodology represents an improved signal to noise ratio such that makes it particularly useful for ARC thickness/composition optimization. Several examples utilizing this method will be presented.