SLICE image analysis for diblock copolymer characterization and process optimization

Yang Hong; Li-Wen Chang; Albert Lin; H.-S. Philip Wong

doi:10.1117/12.848378

2 April 2010 SLICE image analysis for diblock copolymer characterization and process optimization

Yang Hong, Li-Wen Chang, Albert Lin, H.-S. Philip Wong

Proceedings Volume 7637, Alternative Lithographic Technologies II; 76371J (2010) https://doi.org/10.1117/12.848378
Event: SPIE Advanced Lithography, 2010, San Jose, California, United States

Abstract

While directed self-assembly of diblock copolymers is increasingly developed in terms of process flow, metrology and evaluation are the next crucial step in maximizing its effectiveness for integration into device design based on directed self-assembly trends. We present a novel image processing and data analysis program, SLICE (Sub-Lithography Imaging Computation and Evaluator), whose capabilities enable a systematic, automated analysis and characterization of directed self-assembly (SA) of block copolymers for high-density circuit integration. Key features such as defect-free region detection and trench-to-trench comparison of SA quality illustrate the potentially significant impact of SLICE to the process optimization and commercialization of sub-lithographic techniques.

Citation Download Citation

Yang Hong, Li-Wen Chang, Albert Lin, and H.-S. Philip Wong "SLICE image analysis for diblock copolymer characterization and process optimization", Proc. SPIE 7637, Alternative Lithographic Technologies II, 76371J (2 April 2010); https://doi.org/10.1117/12.848378

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