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Proceedings Paper

Surface topography analysis and performance on post-CMP images (Conference Presentation)
Author(s): Jusang Lee; Abner F. Bello; Shinichiro Kakita; Nicholas Pieniazek; Timothy A. Johnson

Paper Abstract

Surface topography on post-CMP processing can be measured with white light interference microscopy to determine the planarity. Results are used to avoid under or over polishing and to decrease dishing. The numerical output of the surface topography is the RMS (root-mean-square) of the height. Beyond RMS, the topography image is visually examined and not further quantified. Subjective comparisons of the height maps are used to determine optimum CMP process conditions. While visual comparison of height maps can determine excursions, it’s only through manual inspection of the images. In this work we describe methods of quantifying post-CMP surface topography characteristics that are used in other technical fields such as geography and facial-recognition. The topography image is divided into small surface patches of 7x7 pixels. Each surface patch is fitted to an analytic surface equation, in this case a third order polynomial, from which the gradient, directional derivatives, and other characteristics are calculated. Based on the characteristics, the surface patch is labeled as peak, ridge, flat, saddle, ravine, pit or hillside. The number of each label and thus the associated histogram is then used as a quantified characteristic of the surface topography, and could be used as a parameter for SPC (statistical process control) charting. In addition, the gradient for each surface patch is calculated, so the average, maximum, and other characteristics of the gradient distribution can be used for SPC. Repeatability measurements indicate high confidence where individual labels can be lower than 2% relative standard deviation. When the histogram is considered, an associated chi-squared value can be defined from which to compare other measurements. The chi-squared value of the histogram is a very sensitive and quantifiable parameter to determine the within wafer and wafer-to-wafer topography non-uniformity. As for the gradient histogram distribution, the chi-squared could again be calculated and used as yet another quantifiable parameter for SPC. In this work we measured the post Cu CMP of a die designed for 14nm technology. A region of interest (ROI) known to be indicative of the CMP processing is chosen for the topography analysis. The ROI, of size 1800 x 2500 pixels where each pixel represents 2um, was repeatably measured. We show the sensitivity based on measurements and the comparison between center and edge die measurements. The topography measurements and surface patch analysis were applied to hundreds of images representing the periodic process qualification runs required to control and verify CMP performance and tool matching. The analysis is shown to be sensitive to process conditions that vary in polishing time, type of slurry, CMP tool manufacturer, and CMP pad lifetime. Keywords: Keywords: CMP, Topography, Image Processing, Metrology, Interference microscopy, surface processing [1] De Lega, Xavier Colonna, and Peter De Groot. "Optical topography measurement of patterned wafers." Characterization and Metrology for ULSI Technology 2005 788 (2005): 432-436. [2] de Groot, Peter. "Coherence scanning interferometry." Optical Measurement of Surface Topography. Springer Berlin Heidelberg, 2011. 187-208. [3] Watson, Layne T., Thomas J. Laffey, and Robert M. Haralick. "Topographic classification of digital image intensity surfaces using generalized splines and the discrete cosine transformation." Computer Vision, Graphics, and Image Processing 29.2 (1985): 143-167. [4] Wang, Jun, et al. "3D facial expression recognition based on primitive surface feature distribution." Computer Vision and Pattern Recognition, 2006 IEEE Computer Society Conference on. Vol. 2. IEEE, 2006.

Paper Details

Date Published: 28 April 2017
PDF: 1 pages
Proc. SPIE 10145, Metrology, Inspection, and Process Control for Microlithography XXXI, 101450W (28 April 2017); doi: 10.1117/12.2258357
Show Author Affiliations
Jusang Lee, GLOBALFOUNDRIES Inc. (United States)
Abner F. Bello, GLOBALFOUNDRIES Inc. (United States)
Shinichiro Kakita, GLOBALFOUNDRIES Inc. (United States)
Nicholas Pieniazek, SUNY Polytechnic Institute Colleges of Nanoscale Science and Engineering (United States)
Timothy A. Johnson, Nanometrics Inc. (United States)

Published in SPIE Proceedings Vol. 10145:
Metrology, Inspection, and Process Control for Microlithography XXXI
Martha I. Sanchez, Editor(s)

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