Image resolution enhancement for advanced semiconductor nodes

L. Rencker; O. Tajalizadehkhoob; K. Elsayed; A. Khachaturiants; H. Pahlavani; Y. Guo; J. van de Laar; E. Simons; N. Saikumar; H. Sadeghian

doi:10.1117/12.3011239

9 April 2024 Image resolution enhancement for advanced semiconductor nodes

L. Rencker, O. Tajalizadehkhoob, K. Elsayed, A. Khachaturiants, H. Pahlavani, Y. Guo, J. van de Laar, E. Simons, N. Saikumar, H. Sadeghian

Author Affiliations +

Proceedings Volume 12955, Metrology, Inspection, and Process Control XXXVIII; 129553J (2024) https://doi.org/10.1117/12.3011239
Event: SPIE Advanced Lithography + Patterning, 2024, San Jose, California, United States

Conference Poster

Abstract

Advanced semiconductor nodes are pushing the limits of feature sizes and require metrology with sub-nm resolution without compromising on the throughput as needed for in-line process control. Recently, high-throughput scanning probe microscopy (SPM) based metrology and inspection tools capable of meeting these needs have been introduced to the market and qualified for use in HVM. While innovative measurement methods and tool architecture have allowed for a leap of improvement in throughput, the next step in further reducing imaging time can be obtained through the application of machine learning for enhancing the resolution of measured images for extraction of relevant parameters. In this work, we provide the general framework under which a neural network-based resolution enhancer is designed and used for SPM images. We showcase the effectiveness of this framework using measurements performed on Line/Space structures with a pitch of 200 nm. For the reusability of a pre-developed pre-trained model, we additionally leverage transfer learning and show that a new model for slightly differing structures can be re-trained and calibrated with a smaller data set of measurements performed on Line/Space structures with a pitch of 100 nm.

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

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L. Rencker, O. Tajalizadehkhoob, K. Elsayed, A. Khachaturiants, H. Pahlavani, Y. Guo, J. van de Laar, E. Simons, N. Saikumar, and H. Sadeghian "Image resolution enhancement for advanced semiconductor nodes", Proc. SPIE 12955, Metrology, Inspection, and Process Control XXXVIII, 129553J (9 April 2024); https://doi.org/10.1117/12.3011239

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