Mr. JungTae Lee Profile

JungTae Lee

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Publications (4)

Proceedings Article | 10 April 2024 Presentation + Paper

Improving EUV sub-40nm via single patterning using wavefront and pupil co-optimization

Soojung Kim, No Young Chung, Kwangseok Maeng, Hyunjae Cho, Jerry Lim, Hyungrok Jang, Jae Hyoung Kim, Insung Kim, Eelco van Setten, Hidde Keizers, Ajinkya Patil, Steven Beekmans, Jungtae Lee, Ki-Seok Kim, James Lee, Sung-Woon Park, Jialei Tang, Stephen Hsu, Youping Zhang, Paul Derks

Proceedings Volume 12953, 1295306 (2024) https://doi.org/10.1117/12.3009878

KEYWORDS: Wavefronts, Extreme ultraviolet, Extreme ultraviolet lithography, Light sources and illumination, Stochastic processes, Diffraction, Optical lithography, Source mask optimization, Projection systems

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Proceedings Article | 26 March 2019 Paper

Improved accuracy and robustness for advanced DRAM with tunable multi-wavelength imaging and scatterometry overlay metrology

Honggoo Lee, Sangjun Han, Minhyung Hong, Jieun Lee, Dongyoung Lee, Ahlin Choi, Chanha Park, Dohwa Lee, Seongjae Lee, Jungtae Lee, Jeongpyo Lee, DongSub Choi, Sanghuck Jeon, Zephyr Liu, Hao Mei, Tal Marciano, Eitan Hajaj, Lilach Saltoun, Dana Klein, Eran Amit, Anna Golotsvan, Wayne Zhou, Eitan Herzel, Roie Volkovich, John Robinson

Proceedings Volume 10959, 109591E (2019) https://doi.org/10.1117/12.2515015

KEYWORDS: Overlay metrology, Semiconducting wafers, Metrology, Scatterometry, Wafer-level optics, Manufacturing, Quality measurement, Imaging systems, Scanning electron microscopy, Diffractive optical elements

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Overlay process control is a critical aspect of integrated circuit manufacturing. Advanced DRAM manufacturing overlay error budget approaches the sub-2nm threshold, including all sources of overlay error: litho processing, non-litho processing, metrology error, etc. Overlay measurement quality, both for accuracy and robustness, depends on the metrology system and its recipe setup. The optimal configuration depends on the layer and materials involved. Increased flexibility of metrology setup is of paramount importance, paired with improved methods of recipe optimization.

Both optical image-based overlay (IBO) and scatterometry diffraction overlay (SCOL®) are necessary tools for overlay control. For some devices and layers IBO provides the best accuracy and robustness, while on others SCOL provides optimum metrology. Historically, wavelength selection was limited to discrete wavelengths and at only a single wavelength. At advanced nodes IBO and SCOL require wavelength tunability and multiple wavelengths to optimize accuracy and robustness, as well as options for polarization and numerical aperture (NA). In previous studies^1,2,3 we investigated wavelength tunability analysis with landscape analysis, using analytic techniques to determine the optimal setup. In this report we show advancements in the landscape analysis technique for IBO through both focus and wavelength, and comparisons to SCOL. A key advantage of imaging is the ability to optimize wavelength on a per-layer basis. This can be a benefit for EUV layers in combination with those of 193i, for example, as well as other applications such as thick 3D NAND layers. The goal is to make accurate and robust overlay metrology that is immune from process stack variations, and to provide metrics that indicate the quality of metrology performance. Through both simulation and on-wafer advanced DRAM measurements, we show quantitative benefits of accuracy and robustness to process stack variability for IBO and SCOL applications.

Methodologies described in this work can be achieved using Archer™ overlay metrology systems, ATL™ overlay metrology systems, and 5D Analyzer® advanced data analysis and patterning control solution.

Proceedings Article | 27 April 2018 Paper

Spectral tunability for accuracy, robustness, and resilience

Einat Peled, Eran Amit, Yuval Lamhot, Alexander Svizher, Dana Klein, Anat Marchelli, Roie Volkovich, Tal Yaziv, Aaron Cheng, Honggoo Lee, Sangjun Han, Minhyung Hong, Seungyoung Kim, Jieun Lee, Dongyoung Lee, Eungryong Oh, Ahlin Choi, DongSub Choi, DoHwa Lee, Sanghuck Jeon, Jungtae Lee, Seongjae Lee, Zephyr Liu, Jeongpyo Lee, John Robinson

Proceedings Volume 10585, 105850S (2018) https://doi.org/10.1117/12.2300507

KEYWORDS: Metrology, Semiconducting wafers, Laser scattering, Laser metrology, Overlay metrology, Quality measurement, Scatterometry, Apodization, Polarization, Image quality

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In overlay (OVL) metrology the quality of measurements and the resulting reported values depend heavily on the measurement setup used. For example, in scatterometry OVL (SCOL) metrology a specific target may be measured with multiple illumination setups, including several apodization options, two possible laser polarizations, and multiple possible laser wavelengths. Not all possible setups are suitable for the metrology method as different setups can yield significantly different performance in terms of the accuracy and robustness of the reported OVL values. Finding an optimal measurement setup requires great flexibility in measurement, to allow for high-resolution landscape mapping (mapping the dependence of OVL, other metrics, and details of pupil images on measurement setup). This can then be followed by a method for analyzing the landscape and selecting an accurate and robust measurement setup. The selection of an optimal measurement setup is complicated by the sensitivity of metrology to variations in the fabrication process (process variations) such as variations in layer thickness or in the properties of target symmetry. The metrology landscape changes with process variations and maintaining optimal performance might require continuous adjustments of the measurement setup. Here we present a method for the selection and adjustment of an optimal measurement setup. First, the landscape is measured and analyzed to calculate theory-based accurate OVL values as well as quality metrics which depend on details of the pupil image. These OVL values and metrics are then used as an internal ruler (“self-reference”), effectively eliminating the need for an external reference such as CD-SEM. Finally, an optimal measurement setup is selected by choosing a setup which yields the same OVL values as the self-reference and is also robust to small changes in the landscape. We present measurements which show how a SCOL landscape changes within wafer, wafer to wafer, and lot to lot with intentionally designed process variations between. In this case the process variations cause large shifts in the SCOL landscape and it is not possible to find a common optimal measurement setup for all wafers. To deal with such process variations we adjust the measurement setup as needed. Initially an optimal setup is chosen based on the first wafer. For subsequent wafers the process stability is continuously monitored. Once large process variations are detected the landscape information is used for selecting a new measurement setup, thereby maintaining optimal accuracy and robustness. Methods described in this work are enabled by the ATL (Accurate Tunable Laser) scatterometry-based overlay metrology system.

Proceedings Article | 28 March 2017 Paper

Impact of stochastic process variations on overlay mark fidelity "towards the 5nm node"

Michael Adel, Roel Gronheid, Chris Mack, Philippe Leray, Evgeni Gurevich, Bart Baudemprez, Dieter Vandenheuvel, Antonio Mani, Sharon Aharon, Dana Klein, Jungtae Lee, Mark Smith

Proceedings Volume 10145, 1014509 (2017) https://doi.org/10.1117/12.2258353

KEYWORDS: Overlay metrology, Line edge roughness, Lithography, Stochastic processes, Process control, Manufacturing, Semiconducting wafers, Extreme ultraviolet, Statistical analysis, Line width roughness, Extreme ultraviolet lithography, Image segmentation, Scanning electron microscopy

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