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Proceedings Paper

SLICE image analysis for diblock copolymer characterization and process optimization
Author(s): Yang Hong; Li-Wen Chang; Albert Lin; H.-S. Philip Wong
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Paper 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.

Paper Details

Date Published: 2 April 2010
PDF: 6 pages
Proc. SPIE 7637, Alternative Lithographic Technologies II, 76371J (2 April 2010); doi: 10.1117/12.848378
Show Author Affiliations
Yang Hong, Stanford Univ. (United States)
Li-Wen Chang, Stanford Univ. (United States)
Albert Lin, Stanford Univ. (United States)
H.-S. Philip Wong, Stanford Univ. (United States)

Published in SPIE Proceedings Vol. 7637:
Alternative Lithographic Technologies II
Daniel J. C. Herr, Editor(s)

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