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Machine learning and hybrid metrology using scatterometry and LE-XRF to detect voids in copper lines
During SAQP process development, the challenges in conventional in-line metrology techniques start to surface. For instance, critical-dimension scanning electron microscopy (CDSEM) is commonly the first choice for CD and pitch variation control. However, it is found that the high aspect ratio at mandrel level processes and the trench variations after etch prevent the tool from extracting the true bottom edges of the structure in order to report the position shift. On the other hand, while the complex shape and variations can be captured with scatterometry, or optical CD (OCD), the asymmetric features, such as pitch walk, show low sensitivity with strong correlations in scatterometry. X-ray diffraction (XRD) is known to provide useful direct measurements of the pitch walk in crystalline arrays, yet the data analysis is influenced by the incoming geometry and must be used carefully.
A successful implementation of SAQP process control for yield improvement requires the metrology issues to be addressed. By optimizing the measurement parameters and beam configurations, CDSEM measurements distinguish each of the spaces corresponding to the upstream mandrel processes and report their CDs separately to feed back to the process team for the next development cycle. We also utilize the unique capability in scatterometry to measure the structure details in-line and implement a “predictive” process control, which shows a good correlation between the “predictive” measurement and the cross-sections from our design of experiments (DOE). The ability to measure the pitch walk in scatterometry was also demonstrated. This work also explored the frontier of in-line XRD capability by enabling an automatic RSM fitting on tool to output pitch walk values. With these advances in metrology development, we are able to demonstrate the impacts of in-line monitoring in the SAQP process, to shorten the patterning development learning cycle to improve the yield.
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