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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 CD Uniformity (CDU) budget, run-to-run (R2R), wafer-to-wafer (W2W) and intra-wafer. While R2R and W2W components are characterized and compensation conrol techniques were developed to minimize their contribution 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 as statistical values as well as spatial profile. We identified that CD response is not sufficient to determine the sources of process disturbance and accordingly added responses from other features, which add to detection of CDU sources of error. The added respsonses came from scatterometry principle based on model difinition of a litho patter described by its shape with characteristic features: 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 compared to process errors with discrete intra-wafer behavior, such as dose and defocus. Correlation between multiple feature responses to process disturbance was characterized as spatial covariance between
CD to resist thickness and CD to SWA. Spatial feature covariance enhances capability to infer sources of process disturbance from metrology data.
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