Intra-wafer CDU characterization to determine process and focus contributions based on scatterometry metrology

Current advanced lithography processes are based on a Critical Dimension (CD) budget of 10nm or less with errors caused by exposure tool, wafer substrate, wafer process, and reticle. As such, allowable CD variation across wafer becomes an important parameter to understand, control and minimize. Three sources of errors have an effect on intra-wafer CD Uniformity (CDU), run-to-run (R2R), wafer-to-wafer (W2W) and intra-wafer. While R2R and W2W components are characterized and compensation control techniques were developed to minimize their contribution (1) the intra-wafer component is more or less ignored with the consequence that its sources of errors have not been characterized and no compensation technique is available. In this paper, we propose an approach to analyze intra- wafer CD sources of variations identifying the non-random CDU behavior and connect this with disturbances caused by processing errors described by their wafer spatial coordinates. We defined a process error as disturbance and its effect as a feature response. We study the impact of modeling spatial distribution of a feature response as calculated by diffractive optical CD metrology (scatterometry) and relate it to a programmed process disturbance. Process disturbances are classified in terms of time characteristics that define their spatial distribution. We demonstrated feature response to a disturbance behavior in terms of statistical values as well as spatial profile. We identified that CD response is not sufficient to determine the sources of process disturbance and consequently added other feature responses to enhance detection of CDU sources of error. These came from scatterometry principle that starts with a litho pattern described by a shape with characteristic parameters: bottom CD, resist thickness, sidewall angle and bottom antireflective layer thickness. Our results show that process errors with continuous intra-wafer variation, such as PEB and BARC thickness have larger effects on CDU then errors with discrete behavior such as dose and defocus. Correlation between multiple feature responses to process disturbance is characterized by spatial covariance between CD to resist thickness and CD to SWA and this proves to enhance capability to infer sources of process disturbance from metrology data.