1. Contour based metrology: getting more from a SEM image
- Author
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Charlotte Beylier, Christian Gardin, B. Le Gratiet, Alexandre Chagoya-Garzon, R. Bouyssou, J. Ducote, Matthieu Milléquant, Christophe Dezauzier, Alain Ostrovsky, Patrick Schiavone, Paolo Petroni, STMicroelectronics [Crolles] (ST-CROLLES), Laboratoire des technologies de la microélectronique (LTM ), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), and Aselta Nanographics
- Subjects
Image quality ,business.industry ,Computer science ,02 engineering and technology ,021001 nanoscience & nanotechnology ,01 natural sciences ,Toolbox ,Image (mathematics) ,Metrology ,law.invention ,010309 optics ,Wafer fabrication ,law ,0103 physical sciences ,Key (cryptography) ,Process control ,Computer vision ,Artificial intelligence ,Radar ,[SPI.NANO]Engineering Sciences [physics]/Micro and nanotechnologies/Microelectronics ,0210 nano-technology ,business ,ComputingMilieux_MISCELLANEOUS - Abstract
In semiconductor fabs, electron microscopes are key equipment for metrology, failure analysis, physical characterization and defect review classification. In a wafer fab like ST Crolles 300mm, CDSEMs are generating more than 20 Million of images per year. The image is by itself a raw material on which the metrology is performed. It is needed to get access to CD which is very often a single value extracted. If the CD is in specification, it is very unlikely that someone will look at the picture. If someone would do so in a systematic way, it would see that there is much more information available in the image than a single CD value. Unfortunately, most of this information passes under the radar of SPC charts and is somehow wasted. This paper presents results obtained by CDSEM image contour analysis from various kind of technologies and applications in manufacturing in our fab. These results show that images contain significant amounts of information that can be extracted and analyzed using an efficient contour extraction and analysis toolbox. Process variability of complex shapes can be shown, robust layer to layer metrics can be computed, pattern shifting, shape changes, image quality and many others too. This opens new possibilities for process control and process variability monitoring and mitigation.
- Published
- 2019
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