Background: Natural physical phenomena occurring at length scales of a few nm produces variation in many aspects of the EUV photoresist relief image: edge roughness, width roughness, feature-tofeature variability, etc. 1,2,3,4. But the most damaging of these variations are stochastic or probabilistic printing failures 5, 6. Stochastic or probabilistic failures are highly random with respect to count and location and occur on wafers at spectra of unknown frequencies. Examples of these are space bridging, line breaking, missing and merging holes. Each has potential to damage or destroy the device, reducing yield 6, 10. Each has potential to damage or destroy the device, reducing yield 6, 10. The phenomena likely originates during exposure where quantized light and matter interact1 . EUV lithography is especially problematic since the uncertainty of energy absorbed by a volume of resist is much greater at 13.5 nm vs. 248 nm and 193 nm. Methods: In this paper, we use highly accelerated rigorous 3D probabilistic computational lithography and inspection to scan an entire EUV advanced node layout, predicting the location, type and probability of stochastic printing failures.
Mask defectivity continues to be a critical challenge to full industrialization of extreme ultraviolet (EUV) lithography. The most concerning defects are those that originate from the blank substrate or multilayer deposition process and are not easily repaired or compensated for. These can best be avoided by hiding them underneath the unexposed absorber regions of the reticle layout. In this paper, we present a comprehensive blank defect avoidance solution that substantially mitigates the risk of printing blank defects. In the first step of this solution, we apply an automatic defect classification to all available blank inspections, categorizing defects into various critical and noncritical bins. In the second step, we register these defects to very high accuracy using a mask registration tool. In the final step, we use a fast polygon-based nonlinear optimization algorithm that outputs the best possible placement of all critical defects so that they are located under the absorber patterns. It does so by optimizing the global mask pattern shift and rotation and accounts for uncertainty in defect positioning and E-beam writing. After the optimal reticle shift and rotation are computed, they are verified by simulating possible wafer print impact. An overall impact score is computed for that specific combination of blank and pattern file and done so for all available blanks in the unused blank database. The E-beam writer operator can then select the blank with the lowest impact score or least risk of printing. Integrated within the KLA RDC and KlearView™ systems, this comprehensive extreme ultraviolet (EUV) blank defect avoidance solution has been validated in pilot production. By maximizing entitlement of EUV blanks across various grade levels, this solution has helped reduce costs and improve yields.
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