Natural physical phenomena occurring at length scales of a few nm in EUV lithography give rise to variation in photoresist images: edge, width, and top roughness, feature-to-feature CD or shape variability, edge placement errors, etc. The most damaging are stochastic printing failures caused by undesirable film thickness loss, admitting etch in line regions, or film thickness gain, preventing etch in space regions. In this work, we begin from analysis of well-calibrated rigorous physical stochastic EUV lithography models to study nanoscale exposure effects affecting stochastic failures. We apply acceleration to the stochastic model and perform computational inspection and classification of hot spots on a large layout area. The agreement between predicted probabilities of occurrence and observed defect frequencies are given for both line and space hot spots. We then perform computational inspection upon a virtual process and select hot spot locations and affect repairs. The actual mask is then fabricated, real wafers are exposed, processed, inspected and measured to compare the predicted reductions in defect probabilities with actual measured defect frequencies on wafer.
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.
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