Mr. Brian Watson Profile

Brian Watson

at Micron Technology, Inc.

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Author

Publications (3)

Proceedings Article | 22 February 2021 Poster + Presentation + Paper

Robustness improvement in imaging-based overlay metrology for high topography layers by Talbot targets

Brian Watson, Shlomit Katz, Richard Housley, Kar Wui Thong, Nikhil Aditya Kumar Roy, Yoav Grauer, Diana Shapirov, Raviv Yohanan, Greg Gray, Yonglei Li, Daniel Chalom

Proceedings Volume 11611, 1161133 (2021) https://doi.org/10.1117/12.2583831

KEYWORDS: Metrology, Optical parametric oscillators, Overlay metrology, Imaging metrology, 3D metrology, 3D acquisition

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Proceedings Article | 22 February 2021 Presentation + Paper

Novel diffraction-based overlay metrology utilizing phase-based overlay for improved robustness

Masazumi Matsunobu, Toshiharu Nishiyama, Michio Inoue, Richard Housley, Cornel Bozdog, Justin Lim, Brian Watson, Jason Reece, Steve McCandless, Olger Zwier, Maurits van der Schaar, Murat Bozkurt, Masudur al Arif, Elliott McNamara, Pieter Kapel, Alan Khan, Simon Strom, Paul Turner, Ping Olson, Ewoud van West

Proceedings Volume 11611, 1161126 (2021) https://doi.org/10.1117/12.2584759

KEYWORDS: Overlay metrology, Diffraction, Diffraction gratings, Semiconducting wafers

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Proceedings Article | 20 March 2020 Presentation + Paper

Contact etch process control application for advanced NAND memory structures

R. Kris, G. Klebanov, I. Friedler, E. Frishman, S. Duvdevani Bar, J. Geva, V. Mirovoy, N. Teomim, D. Rathore, D. Rogers, J. Chess, B. Watson

Proceedings Volume 11325, 113251F (2020) https://doi.org/10.1117/12.2559399

KEYWORDS: Etching, Scanning electron microscopy, Process control, Critical dimension metrology, Metrology, Image processing, Signal processing, Shape analysis, Image classification, Image analysis, Machine learning

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CD measurements of advanced 3D-NAND Staircase process require development of new approaches in CD metrology [1]. The current CD SEM Contact Analysis used for 3D-NAND assumes that process control could be provided through a set of geometric parameters defining the contact shape (i.e. parameters of contact shape elliptic fit such as equivalent contact top diameter (Top CD), equivalent contact bottom diameter (Bottom CD), ellipticity, minor, major axis). The limitation of this approach for process control of complex structures was considered, and a new approach based on Grey Level Analysis of contact features in SEM images was proposed. However, this analysis is not enough for controlling the complicated 3D-NAND Staircase formation process steps, as contact holes with same geometric parameters but different depths cannot be separated by traditional CD SEM metrology measurement procedure (Figures 1 and 2). Thus, traditional CD SEM approach needs revisiting in order to work in situations where process control requires analysis of sophisticated Grey Level uniformity distribution. We propose a novel approach combining traditional metrology with machine learning methods. The essence of this new approach is to combine Grey Level attributes and traditional CD measured geometric parameters of the feature, obtained by traditional CD metrology flow, in a classification scheme (Figures 2 and 3). The proposed approach was qualified at Micron site demonstrating ~98% purity classification results.
The proposed approach is generic and can be extended to a large variety of process control applications. Enhancing regular metrology flow with the capability to classify Etch process quality eliminates the need for the expensive and destructive cross-sectional SEM analysis. Furthermore, this method has a clear advantage during the early R&D phase of process development as it increases the usefulness of the in-line metrology tool while the process is still immature and unstable.

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