Scatterometry-based defect detection for DSA in-line process control

Robin Chao; Chi-Chun Liu; Cornel Bozdog; Aron Cepler; Matthew Sendelbach; Oded Cohen; Shay Wolfling; Todd Bailey; Nelson Felix

doi:10.1117/12.2087093

19 March 2015 Scatterometry-based defect detection for DSA in-line process control

Robin Chao, Chi-Chun Liu, Cornel Bozdog, Aron Cepler, Matthew Sendelbach, Oded Cohen, Shay Wolfling, Todd Bailey, Nelson Felix

Author Affiliations +

Proceedings Volume 9424, Metrology, Inspection, and Process Control for Microlithography XXIX; 942419 (2015) https://doi.org/10.1117/12.2087093
Event: SPIE Advanced Lithography, 2015, San Jose, California, United States

Abstract

Successful implementation of directed self-assembly in high volume manufacturing is contingent upon the ability to control the new DSA-specific local defects such as “dislocations” or “line-shifts” or “fingerprint-like” defects. Conventional defect inspection tools are either limited in resolution (brightfield optical methods) or in the area / number of defects to investigate / review (SEM). Here we explore in depth a scatterometry-based technique that can bridge the gap between area throughput and detection resolution. First we establish the detection methodology for scatterometry-based defect detection, then we compare to established methodology. Careful experiments using scatterometry imaging confirm the ultimate resolution for defect detection of scatterometry-based techniques as low as <1% defect per area sampled – similar to CD-SEM based detection, while retaining a 2 orders of magnitude higher area sampling rate.

Citation Download Citation

Robin Chao, Chi-Chun Liu, Cornel Bozdog, Aron Cepler, Matthew Sendelbach, Oded Cohen, Shay Wolfling, Todd Bailey, and Nelson Felix "Scatterometry-based defect detection for DSA in-line process control", Proc. SPIE 9424, Metrology, Inspection, and Process Control for Microlithography XXIX, 942419 (19 March 2015); https://doi.org/10.1117/12.2087093

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