Process window qualification using focus-exposure wafers is an essential step in lithography and a key use case for CD-SEM metrology. An automated analysis using the correlation between CD and focus/dose is easily possible but rarely done due to missing safety checks. Pattern fidelity that is analyzed by eye and problematic focus/dose conditions that may cause pattern degradation are excluded by hand. Specifically, when EUV lithography is utilized for exposing the most critical layers, roughness estimation becomes much more important, as it will restrict the process window further. We develop and describe unbiased and stable roughness estimates for contact hole patterns and integrate them into the process window analysis pipeline and inline monitoring routine. The analysis goes beyond simple roughness values and can detect a variety of possible CD-SEM measurement problems and shape deviations as well. Furthermore, we introduce a novel image-based machine-learning approach to detect outliers and quantify defective or abnormal patterns. Notably, the underlying model does not require knowledge of the types of CD features or design information for which outliers should be detected. We demonstrate that the approach can reliably detect local defects and a variety of other pattern anomalies. Using the generated visualizations, images with anomalous features can be flagged automatically and the locations of the defects or deviations are pinpointed. The approach yields not only the final missing piece in automated process window qualification, but also new opportunities to monitor pattern fidelity in lithographical semi-conductor processes.
An absolute alignment measurement of an underlayer and overlayer of overlay mark enables an innovative overlay control by which each layer’s grid errors can be independently corrected, versus of a conventional relative overlay measurement and control. We demonstrate an absolute alignment measurement of stacked overlay marks such as Diffraction-Based Overlay (DBO) by adopting a unique method incorporated in a standalone, image-based alignment metrology system. An alignment accuracy of each layer is evaluated using product wafers by comparing alignment measurement result to the reference data. In conclusion, we were able to achieve R2>0.97 coefficient.
As a result of the continuously shrinking features of the integrated circuit, the overlay budget requirements have become very demanding. Historically, overlay has been performed using metrology targets for process control, and most overlay enhancements were achieved by hardware improvements. However, this is no longer sufficient, and we need to consider additional solutions for overlay improvements in process variation using computational methods. In this paper, we present the limitations of third-order intrafield distortion corrections based on standard overlay metrology and propose an improved method which includes a prediction of the device overlay and corrects the lens aberration fingerprint based on this prediction. For a DRAM use case, we present a computational approach that calculates the overlay of the device pattern using lens aberrations as an additional input, next to the target-based overlay measurement result. Supporting experimental data are presented that demonstrate a significant reduction of the intrafield overlay fingerprint.
As overlay margin is getting tighter, traditional overlay correction method is not enough to secure more overlay margin without extended correction potential on lithography tool. Timely, the lithography tool has a capability of wafer to wafer correction. From these well-timed industry’s preparations, the uncorrected overlay error from current sampling in a lot could be corrected for yield enhancement.
In this paper, overlay budget break was performed prior to experiments with the purpose of estimating amount of overlay improvement. And wafer to wafer correction was simulated to the specified layer of a 2x node DRAM device. As a result, not only maximum 94.4% of residual variation improvement is estimated, but also recognized that more samplings to cover all wafer’s behavior is inevitable. Integrated metrology with optimized sampling scheme was also introduced as a supportive method for more samplings.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.