Abstract
Accurate characterization of image rippling is critical in early detection of back-end-of-line (BEOL) patterning weakpoints, as most defects are strongly associated with excessive rippling that does not get effectively compensated by optical proximity correction (OPC). We correlate image contour with design shapes to account for design geometry-dependent rippling signature, and explore the best practice of OPC fragmentation for BEOL geometries. Specifically, we predict the optimum contour as allowed by the lithographic process and illumination conditions and locate ripple peaks, valleys, and inflection points. This allows us to identify potential process weakpoints and segment the mask accordingly to achieve the best correction results.
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