Predicting DUV open contact risk with scarce sampling using new contour-based metrics

Abstract

Background: Stochastic effects in DUV lithography are manifested by variabilities in critical dimension (CD), in placement or in shape. A combination of these very local variabilities can lead to yield killer open contacts. Traditionally, opens are massively measured with Voltage Contrast (VC) tools, returning the defects density after etching and metal filling. Aim: A set of contour-based metrics for the quantification of stochastic effects in DUV has already been presented. In this paper, we correlate these metrics and open count to predict failure risk. Approach: With an in-depth analysis of post-lithography CD-SEM images, we investigate if variabilities inside the metrology target are forerunners of open risk inside the product. It is challenging because of the difference between the surface inspected with defectivity tools and the one measured with CD-SEM. Results: We applied the methodology on contacts of a 28 nm node technology, on a Focus Exposure Matrix (FEM) wafer, to obtain post-lithography contour-based metrics mappings. A new metric has been computed: the classification of shapes inside the image. After post-processing, the correlations between contour-based metrics and the log value of open count are presented. A threshold value of size variability emerges above which open risk is too high, enabling process monitoring. Conclusion: As contour-based metrology offers complementary metrics not only related to CD metrology, we can now predict open probability with new indicators coming from traditional CD-SEM images. This early detection of an atypical situation allows the process assessment.