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4 May 2020 Measuring local CD uniformity in EUV vias with scatterometry and machine learning
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Abstract
A methodology of obtaining the local critical dimension uniformity of contact hole arrays by using optical scatterometry in conjunction with machine learning algorithms is presented and discussed. Staggered contact hole arrays at 44 nm pitch were created by EUV lithography using three different positive-tone chemically amplified resists. To introduce local critical dimension uniformity variations different exposure conditions for dose and focus were used. Optical scatterometry spectra were acquired post development as well as post etch into a SiN layer. Reference data for the machine learning algorithm were collected by critical dimension scanning electron microscopy (CDSEM). The machine learning algorithm was then trained using the optical spectra and the corresponding calculated LCDU values from CDSEM image analyses. It was found that LCDU and CD can be accurately measured with the proposed methodology both post lithography and post etch. Additionally, since the collection of optical spectra post development is non-destructive, same area measurements are possible to single out etch improvements. This optical metrology technique can be readily implemented inline and significantly improves the throughput compared to currently used electron beam measurements.
Conference Presentation
© (2020) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Dexin Kong, Daniel Schmidt, Jennifer Church, Chi-Chun Liu, Mary Breton, Cody Murray, Eric Miller, Luciana Meli, John Sporre, Nelson Felix, Ishtiaq Ahsan, Aron J. Cepler, Marjorie Cheng, Roy Koret, and Igor Turovets "Measuring local CD uniformity in EUV vias with scatterometry and machine learning", Proc. SPIE 11325, Metrology, Inspection, and Process Control for Microlithography XXXIV, 113251I (4 May 2020); https://doi.org/10.1117/12.2551498
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