In all investigations that we performed over the past years; it has been clearly demonstrated that the off-line mask-to-mask overlay as determined on the Zeiss PROVE tool correlates very well with the on-wafer measurements. It all started off with a correlation study utilizing wafer alignment marks. Wafer alignment marks are metrology structures that can be read out inside ASML scanners by the wafer alignment sensor. In that work, the impact of the reticle alignment marks required to align the mask inside the scanner was incorporated as well. An excellent correlation (R2 < 0.96) was shown with an accuracy of 0.58-nm. This result was achieved after carefully setting up an experiment in photoresist and by ruling out any other additional overlay contributors other than mask and the scanner baseline overlay performance. After this initial success, we continued the investigation by considering µ-DBO (Diffraction Based Overlay) metrology targets that can be read out on an ASML Yieldstar (YS:375) overlay metrology tool. In this work, the complexity of the experiment was increased. Instead of using only photo resist, an industry relevant process Litho-Etch process flow was selected. The mask was written on a state-of-the-art writing tool (EBM-9000). Again, excellent correlation coefficients (R2 < 0.92) were obtained. This time within the sub-nanometer range at wafer level. During the execution of that work, an error source that contributes to the small mismatch (< 0.14-nm) between mask and on-wafer measurements was addressed: the sampling scheme difference of the signal generating areas. While the PROVE tool has been designed to measure local (feature) placement errors, this is not the case for an overlay metrology tool or the scanner wafer alignment sensor. For the latter two metrology systems, a position is obtained from a much larger region of interest (ROI) for which local placement errors are averaged out. The observed mismatch can easily be mitigated by increasing the number of PROVE measurements with a small ROI to match it with the ROI of the overlay metrology tool or the wafer alignment sensor. While studying the increasing number of local registration measurements by the PROVE tool, an interesting observation was made. The way the mask had been written on the mask e-beam writer seemed to be reflected in the residual local registration measurements! Stripes were observed that appear to be running across the full width of the mask. Since the typical dimensions of the stripes at wafer level are small compared to the areas that are used for overlay measurements and/or wafer alignment measurements, they are hard to detect on wafer by using optical techniques. In this follow-up work, we explore the correlation between mask registration measurements and the on-wafer measurement for individual device features. This means that we make another step-in complexity, the length scales of interest are now significantly below the typical dimensions of an overlay metrology target. To continue the correlation study, a large field of view SEM is required to measure the relative positions of the device features. We show that the way the mask has been written can indeed be found back on wafer! Although the local placement errors for a single logic device feature is in the order of ~0.5-nm at wafer level, we show that the correlation between mask measurements and wafer measurement still holds. This enables an interesting new application space that is addressed in the current paper.
In this paper, budget characterization and wafer mapping of the Edge Placement Error (EPE) is studied to manage and improve pattern defects with a use case selected from SK Hynix’s most advanced DRAM 1x nm product. To quantify EPE, CD and overlay were measured at the multiple process steps and then combined for the EPE reconstruction. Massive metrology was used to capture extreme statistics and fingerprint across the wafer. An EPE budget breakdown was performed to identify main contributors and their variations. The end result shows EPEmax is mostly driven by local CD and overlay components while EPE variation is dominated by overlay and global CD components. Beyond EPE budget, a novel EPE wafer mapping methodology is introduced to visualize the temporal and spatial EPE performance which captures variation not seen from CD and overlay. This enables root-cause analysis of the pattern defects, and provides a foundation towards a better process monitoring solution. For EPE improvement, serial CD and overlay optimization simulation was performed to verify opportunities for reduction of the EPE and variation using the available ASML applications. The potential improvement for this use-case was confirmed to be 4.5% compared to baseline performance.
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