Defect detection strategies and process partitioning for single-expose EUV patterning

Luciana Meli; Karen Petrillo; Anuja De Silva; John Arnold; Nelson Felix; Chris Robinson; Benjamin Briggs; Shravan Matham; Yann Mignot; Jeffrey Shearer; Bassem Hamieh; Koichi Hontake; Lior Huli; Corey Lemley; Dave Hetzer; Eric Liu; Ko Akiteru; Shinichiro Kawakami; Takeshi Shimoaoki; Yusaku Hashimoto; Hiroshi Ichinomiya; Akiko Kai; Koichiro Tanaka; Ankit Jain; Heungsoo Choi; Barry Saville; Chet Lenox

doi:10.1117/1.JMM.18.1.011006

5 September 2018 Defect detection strategies and process partitioning for single-expose EUV patterning

Luciana Meli, Karen Petrillo, Anuja De Silva, John Arnold, Nelson Felix, Chris Robinson, Benjamin Briggs, Shravan Matham, Yann Mignot, Jeffrey Shearer, Bassem Hamieh, Koichi Hontake, Lior Huli, Corey Lemley, Dave Hetzer, Eric Liu, Ko Akiteru, Shinichiro Kawakami, Takeshi Shimoaoki, Yusaku Hashimoto, Hiroshi Ichinomiya, Akiko Kai, Koichiro Tanaka, Ankit Jain, Heungsoo Choi, Barry Saville, Chet Lenox

Author Affiliations +

Journal of Micro/Nanolithography, MEMS, and MOEMS, Vol. 18, Issue 1, 011006 (September 2018). https://doi.org/10.1117/1.JMM.18.1.011006

Abstract

The key challenge for enablement of a second node of single-expose EUV patterning is understanding and mitigating the patterning-related defects that narrow the process window. Typical in-line inspection techniques, such as broadband plasma and e-beam systems, find it difficult to detect the main yield-detracting defects postdevelop, and thus understanding the effects of process improvement strategies has become more challenging. New techniques and methodologies for detection of EUV lithography defects, along with judicious process partitioning, are required to develop process solutions that improve yield. This paper will first discuss alternative techniques and methodologies for detection of lithography-related defects, such as scumming and microbridging. These strategies will then be used to gain a better understanding of the effects of material property changes, process partitioning, and hardware improvements, ultimately correlating them directly with electrical yield detractors.

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Luciana Meli, Karen Petrillo, Anuja De Silva, John Arnold, Nelson Felix, Chris Robinson, Benjamin Briggs, Shravan Matham, Yann Mignot, Jeffrey Shearer, Bassem Hamieh, Koichi Hontake, Lior Huli, Corey Lemley, Dave Hetzer, Eric Liu, Ko Akiteru, Shinichiro Kawakami, Takeshi Shimoaoki, Yusaku Hashimoto, Hiroshi Ichinomiya, Akiko Kai, Koichiro Tanaka, Ankit Jain, Heungsoo Choi, Barry Saville, and Chet Lenox "Defect detection strategies and process partitioning for single-expose EUV patterning," Journal of Micro/Nanolithography, MEMS, and MOEMS 18(1), 011006 (5 September 2018). https://doi.org/10.1117/1.JMM.18.1.011006

Received: 18 May 2018; Accepted: 1 August 2018; Published: 5 September 2018

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