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.
In advanced DRAM semiconductor manufacturing, there is a need to reduce the overlay fingerprints. Reducing on device fingerprints with very high spatial frequency remains one of the bottlenecks to achieve sub-2nm on device overlay. After-etch device overlay measurements using the YieldStar in-device metrology (IDM) allow for previously unassessed and uncontrolled fingerprints to be corrected employing higher-order overlay corrections. This is because this technology allows dramatically increased overlay metrology sampling at affordable throughputs. This paper reports considerations for enabling dense after-etch overlay based corrections in a high volume manufacturing environment. Results will be shown on a front end critical layer of SK hynix that has been sampled with IDM with high density wafer sampling, over dozens of lots spanning several weeks.
To support the manufacturing of DRAM semiconductors for next and future nodes, there is a constant need to reduce the overlay fingerprints. In this paper we evaluate algorithms which are capable of decoupling wafer deformation from mark deformation and extrapolation effects. The algorithms enable lithography tools to use only the wafer deformation component in the alignment feedforward correction. Therefore improving the (wafer to wafer) overlay. First results will be shared showing improvement of wafer to wafer variation in high-volume manufacturing environment.