Mr. Gisung Yoon Profile

Gisung Yoon

Principal Engineer at Micron Technology Inc

SPIE Involvement:

Author

Proceedings Article | 1 December 2022 Presentation + Paper

Extreme ultraviolet lithography reticle local CD uniformity correlation to wafer local CD uniformity

Adam Lyons, Tom Wallow, Dong-Seok Nam, Gisung Yoon, Baorui Yang, Mike Hermes

Proceedings Volume 12293, 122930M (2022) https://doi.org/10.1117/12.2643523

KEYWORDS: Photomasks, Semiconducting wafers, Critical dimension metrology, Scanning electron microscopy, Reticles, Stochastic processes, Metrology, Extreme ultraviolet lithography, Image analysis

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Proceedings Article | 13 June 2022 Presentation

Development of a standalone zoneplate based EUV mask defect review tool

Chami Perera, Gi Sung Yoon, Ryan Carlson, Baorui Yang, Mike Hermes, Dave Houser, Alexander Khodarev, Chuck Murray, Travis Grodt, Arnaud Allézy, Weilun Chao, Farhad Salmassi, Eric Gullikson, Patrick Naulleau

Proceedings Volume PC12051, PC120510E (2022) https://doi.org/10.1117/12.2617277

KEYWORDS: Extreme ultraviolet, Photomasks, Reticles, Microscopes, Imaging systems, Zone plates, Semiconductors, Semiconducting wafers, Patents, Metrology

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Proceedings Article | 23 October 2015 Paper

Improvement in accuracy of defect size measurement by automatic defect classification

Bhamidipati Samir, Mark Pereira, Sankaranarayanan Paninjath, Chan-Uk Jeon, Dong-Hoon Chung, Gi-Sung Yoon, Hong-Yul Jung

Proceedings Volume 9635, 963520 (2015) https://doi.org/10.1117/12.2202511

KEYWORDS: Inspection, Photomasks, Defect inspection, Liquids, Coating, Image processing, Neodymium, Extreme ultraviolet, Semiconducting wafers, Optical properties

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The blank mask defect review process involves detailed analysis of defects observed across a substrate’s multiple preparation stages, such as cleaning and resist-coating. The detailed knowledge of these defects plays an important role in the eventual yield obtained by using the blank. Defect knowledge predominantly comprises of details such as the number of defects observed, and their accurate sizes. Mask usability assessment at the start of the preparation process, is crudely based on number of defects. Similarly, defect size gives an idea of eventual wafer defect printability. Furthermore, monitoring defect characteristics, specifically size and shape, aids in obtaining process related information such as cleaning or coating process efficiencies.

Blank mask defect review process is largely manual in nature. However, the large number of defects, observed for latest technology nodes with reducing half-pitch sizes; and the associated amount of information, together make the process increasingly inefficient in terms of review time, accuracy and consistency. The usage of additional tools such as CDSEM may be required to further aid the review process resulting in increasing costs.

Calibre® MDPAutoClassify™ provides an automated software alternative, in the form of a powerful analysis tool for fast, accurate, consistent and automatic classification of blank defects. Elaborate post-processing algorithms are applied on defect images generated by inspection machines, to extract and report significant defect information such as defect size, affecting defect printability and mask usability. The algorithm’s capabilities are challenged by the variety and complexity of defects encountered, in terms of defect nature, size, shape and composition; and the optical phenomena occurring around the defect [1].

This paper mainly focuses on the results from the evaluation of Calibre® MDPAutoClassify™ product. The main objective of this evaluation is to assess the capability of accurately estimating the size of the defect from the inspection images automatically. The sensitivity to weak defect signals, filtering out noise to identify the defect signals and locating the defect in the images are key success factors. The performance of the tool is assessed on programmable defect masks and production masks from HVM production flow. Implementation of Calibre® MDPAutoClassify™ is projected to improve the accuracy of defect size as compared to what is reported by inspection machine, which is very critical for production, and the classification of defects will aid in arriving at appropriate dispositions like SEM review, repair and scrap.

Proceedings Article | 8 October 2014 Paper

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

Proceedings Volume 9235, 92351K (2014) https://doi.org/10.1117/12.2076308

KEYWORDS: Inspection, SRAF, Photomasks, Artificial intelligence, Optical proximity correction, Evolutionary algorithms, Resolution enhancement technologies, Image resolution, Optical lithography, Source mask optimization

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Proceedings Article | 1 October 2013 Paper

Improving inspectability of sub-2x-nm node masks with complex SRAF

In Yong Kang, Gisung Yoon, Jonghee Lee, Donghoon Paul Chung, Byung-Gook Kim, Chan-Uk Jeon, Gregg Inderhees, Trent Hutchinson, Wonil Cho, Jiuk Hur

Proceedings Volume 8886, 88860O (2013) https://doi.org/10.1117/12.2030976

KEYWORDS: Inspection, Photomasks, SRAF, Printing, Source mask optimization, Calibration, Model-based design, Scanners, Lithography, Image processing

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Proceedings Article | 28 June 2013 Paper

Extending DUV mask inspection tool for inspecting 2xnm HP and beyond

Jihoon Na, Sang Hoon Han, Gisung Yoon, Dong Hoon Chung, Byung-Gook Kim, Chanuk Jeon, Dana Bernstein, Lior Shoval, Ido Dolev, Ofer Shopen, Ju Sang Lee, Chung ki Lyu, Seung Ryong Bae

Proceedings Volume 8701, 870115 (2013) https://doi.org/10.1117/12.2032774

KEYWORDS: Photomasks, Inspection, Printing, Deep ultraviolet, Signal to noise ratio, Defect detection, Semiconducting wafers, Optical inspection, Wafer-level optics, Geometrical optics

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Proceedings Article | 8 November 2012 Paper

EUV mask inspection study for sub-20nm device

Inkyun Shin, Gisung Yoon, Ji Hoon Na, Paul D. Chung, Chan-Uk Jeon

Proceedings Volume 8522, 85220M (2012) https://doi.org/10.1117/12.964964

KEYWORDS: Inspection, Photomasks, Extreme ultraviolet, Extreme ultraviolet lithography, Semiconducting wafers, Polarization, Printing, Modulation, Lithographic illumination, Scanning electron microscopy

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Proceedings Article | 27 March 2008 Paper

Lifetime of EUVL masks as a function of degree of carbon contamination and capping materials

Sungmin Huh, Hoon Kim, Gisung Yoon, Jaehyuck Choi, Han-Shin Lee, Dong Gun Lee, Byungsup Ahn, Hwan-Seok Seo, Dongwan Kim, Seoung Sue Kim, Han Ku Cho, Takeo Watanabe, Hiroo Kinoshita

Proceedings Volume 6921, 692115 (2008) https://doi.org/10.1117/12.772412

KEYWORDS: Photomasks, Carbon, Contamination, Ruthenium, Extreme ultraviolet lithography, Silicon, Critical dimension metrology, Reflectivity, Extreme ultraviolet, Semiconducting wafers

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Proceedings Article | 27 March 2007 Paper

Phase-shifted assist feature OPC for sub-45-nm node optical lithography

Gi-Sung Yoon, Hee-Bom Kim, Jeung-Woo Lee, Seong-Woon Choi, Woo-Sung Han

Proceedings Volume 6520, 65201A (2007) https://doi.org/10.1117/12.712445

KEYWORDS: Photomasks, Optical proximity correction, Diffraction, Semiconducting wafers, Manufacturing, SRAF, Optical lithography, Opacity, Nanoimprint lithography, Critical dimension metrology

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Proceedings Article | 28 June 2005 Paper

The application of phase grating to CLM technology for the sub-65nm node optical lithography

Gi-Sung Yoon, Sung-Hyuck Kim, Ji-Soong Park, Sun-Young Choi, Chan-Uk Jeon, In-Kyun Shin, Sung-Woon Choi, Woo-Sung Han

Proceedings Volume 5853, (2005) https://doi.org/10.1117/12.617201

KEYWORDS: Photomasks, Optical lithography, Camera shutters, Semiconducting wafers, Optical proximity correction, Manufacturing, Chromium, Nanoimprint lithography, Lithography, Wafer-level optics

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Showing 5 of 10 publications

Conference Committee Involvement (1)

Photomask Technology 2025

21 September 2025 | Monterey, California, United States

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