On-cell thickness monitoring of chalcogenide alloy layer using spectral interferometry, Raman spectroscopy, and hybrid machine learning

Hyunwoo Ryoo; Seul Ji Song; Min Ji Jeon; Juhyun Moon; JiHye Lee; ByungHyun Hwang; Jeongho Ahn; Yoon-jong Song; Hidong Kwak; Lior Neeman; Noga Meir; Jaehong Jang; Ik Hwan Kim; Hyunkyu Kim

doi:10.1117/12.3012496

9 April 2024 On-cell thickness monitoring of chalcogenide alloy layer using spectral interferometry, Raman spectroscopy, and hybrid machine learning

Hyunwoo Ryoo, Seul Ji Song, Min Ji Jeon, Juhyun Moon, JiHye Lee, ByungHyun Hwang, Jeongho Ahn, Yoon-jong Song, Hidong Kwak, Lior Neeman, Noga Meir, Jaehong Jang, Ik Hwan Kim, Hyunkyu Kim

Author Affiliations +

Proceedings Volume 12955, Metrology, Inspection, and Process Control XXXVIII; 129550G (2024) https://doi.org/10.1117/12.3012496
Event: SPIE Advanced Lithography + Patterning, 2024, San Jose, California, United States

Abstract

The thickness of the chalcogenide ovonic threshold switching (OTS) layer is one of the most critical parameters for the switch-only memory (SOM) process control. Traditionally, the OTS thickness and composition were measured by XRF using the amounts of Ge, As, and Se. Still, XRF has a few limitations in delivering the required performance, especially for products with multilayer memory architecture. For these products, x-ray fluorescence (XRF) signals overlap and cannot be used to measure the thickness of each layer. In the current paper, we have studied three new alternative approaches for measurements of the OTS thickness on-cell: Spectral Interferometry, Raman spectroscopy, and Hybrid Machine Learning technique. The first method, Spectral interferometry with the Vertical Traveling Scatterometry approach (VTS), allowed OCD modeling of the top of the structure by blocking the complex underlayers and measuring only the top OTS thickness on all targets, including within the chip. The second method, Raman spectroscopy, demonstrated oncell dimensional capabilities with an excellent correlation of the Ge-Se, As-Se, and Ge-Ge bonds of Raman active chalcogenide to TEM OTS thickness values. Finally, the third method used Raman parameters calibrated with TEM as a reference thickness for the ML solution using the VTS spectra on-cell. This ML method is fast, model-free, and requires minimal TEM samples for setup. All three methods have demonstrated capability for on-cell measurements and HVM process control.

Conference Presentation

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Hyunwoo Ryoo, Seul Ji Song, Min Ji Jeon, Juhyun Moon, JiHye Lee, ByungHyun Hwang, Jeongho Ahn, Yoon-jong Song, Hidong Kwak, Lior Neeman, Noga Meir, Jaehong Jang, Ik Hwan Kim, and Hyunkyu Kim "On-cell thickness monitoring of chalcogenide alloy layer using spectral interferometry, Raman spectroscopy, and hybrid machine learning", Proc. SPIE 12955, Metrology, Inspection, and Process Control XXXVIII, 129550G (9 April 2024); https://doi.org/10.1117/12.3012496

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