Paper
28 September 2017 SEM AutoAnalysis: enhancing photomask and NIL defect disposition and review
Kristian Schulz, Kokila Egodage, Gilles Tabbone, Christian Ehrlich, Anthony Garetto
Author Affiliations +
Proceedings Volume 10446, 33rd European Mask and Lithography Conference; 104460I (2017) https://doi.org/10.1117/12.2280828
Event: 33rd European Mask and Lithography Conference, 2017, Dresden, Germany
Abstract
For defect disposition and repair verification regarding printability, AIMS™ is the state of the art measurement tool in industry. With its unique capability of capturing aerial images of photomasks it is the one method that comes closest to emulating the printing behaviour of a scanner. However for nanoimprint lithography (NIL) templates aerial images cannot be applied to evaluate the success of a repair process. Hence, for NIL defect dispositioning scanning, electron microscopy (SEM) imaging is the method of choice. In addition, it has been a standard imaging method for further root cause analysis of defects and defect review on optical photomasks which enables 2D or even 3D mask profiling at high resolutions. In recent years a trend observed in mask shops has been the automation of processes that traditionally were driven by operators. This of course has brought many advantages one of which is freeing cost intensive labour from conducting repetitive and tedious work. Furthermore, it reduces variability in processes due to different operator skill and experience levels which at the end contributes to eliminating the human factor. Taking these factors into consideration, one of the software based solutions available under the FAVOR® brand to support customer needs is the aerial image evaluation software, AIMS™ AutoAnalysis (AAA). It provides fully automated analysis of AIMS™ images and runs in parallel to measurements. This is enabled by its direct connection and communication with the AIMS™tools. As one of many positive outcomes, generating automated result reports is facilitated, standardizing the mask manufacturing workflow. Today, AAA has been successfully introduced into production at multiple customers and is supporting the workflow as described above. These trends indeed have triggered the demand for similar automation with respect to SEM measurements leading to the development of SEM AutoAnalysis (SAA). It aims towards a fully automated SEM image evaluation process utilizing a completely different algorithm due to the different nature of SEM images and aerial images. Both AAA and SAA are the building blocks towards an image evaluation suite in the mask shop industry.
© (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Kristian Schulz, Kokila Egodage, Gilles Tabbone, Christian Ehrlich, and Anthony Garetto "SEM AutoAnalysis: enhancing photomask and NIL defect disposition and review", Proc. SPIE 10446, 33rd European Mask and Lithography Conference, 104460I (28 September 2017); https://doi.org/10.1117/12.2280828
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KEYWORDS
Scanning electron microscopy

Photomasks

Image analysis

Nanoimprint lithography

Image processing

Image resolution

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