Paper
8 October 2014 Study of high sensitivity DUV inspection for sub-20nm devices with complex OPCs
Sang Hoon Han, Hong Yul Jung, Sun Pyo Lee, In-Yong Kang, Gi Sung Yoon, Dong Hoon Chung, Chan-Uk Jeon, Yulia Brand, Yair Eran, Yoad Bar-Shean, Alexander Chereshnya, Chung Ki Lyu
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Abstract
EUV lithography has been delayed due to well-known issues such as source power, debris, pellicle, etc. for high volume manufacturing. For this reason, conventional optical lithography has been developed to cover more generations with various kinds of Resolution Enhancement Techniques (RETs) and new process technology like Multiple Patterning Technology (MPT). Presently, industry lithographers have been adopting two similar techniques of the computational OPC scheme such as Inverse Lithography Technology (ILT) and Source Mask Optimization (SMO) [1]. Sub-20 nm node masks including these technologies are very difficult to fabricate due to many small features which are near the limits of mask patterning process. Therefore, these masks require the unseen level of difficulty for inspection. In other words, from the viewpoint of mask inspection, it is very challenging to maintain maximum sensitivities on main features and minimum detection rates on the Sub-Resolution Assist Features (SRAFs). This paper describes the proper technique as the alternative solution to overcome these critical issues with Aerial Imaging (AI) inspection and High Resolution (HR) imaging inspection.
© (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Sang Hoon Han, Hong Yul Jung, Sun Pyo Lee, In-Yong Kang, Gi Sung Yoon, Dong Hoon Chung, Chan-Uk Jeon, Yulia Brand, Yair Eran, Yoad Bar-Shean, Alexander Chereshnya, and Chung Ki Lyu "Study of high sensitivity DUV inspection for sub-20nm devices with complex OPCs", Proc. SPIE 9235, Photomask Technology 2014, 92351K (8 October 2014); https://doi.org/10.1117/12.2076308
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CITATIONS
Cited by 2 patents.
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KEYWORDS
Inspection

SRAF

Photomasks

Artificial intelligence

Optical proximity correction

Evolutionary algorithms

Image resolution

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