Overlay optimization for 1x node technology and beyond via rule based sparse sampling

Nyan Lynn Aung; Woong Jae Chung; Lokesh Subramany; Shehzeen Hussain; Pavan Samudrala; Haiyong Gao; Xueli Hao; Yen-Jen Chen; Juan-Manuel Gomez

doi:10.1117/12.2218161

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8 March 2016 Overlay optimization for 1x node technology and beyond via rule based sparse sampling

Nyan Lynn Aung, Woong Jae Chung, Lokesh Subramany, Shehzeen Hussain, Pavan Samudrala, Haiyong Gao, Xueli Hao, Yen-Jen Chen, Juan-Manuel Gomez

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Proceedings Volume 9778, Metrology, Inspection, and Process Control for Microlithography XXX; 97782G (2016) https://doi.org/10.1117/12.2218161
Event: SPIE Advanced Lithography, 2016, San Jose, California, United States

Abstract

We demonstrate a cost-effective automated rule based sparse sampling method that can detect the spatial variation of overlay errors as well as the overlay signature of the fields. Our technique satisfies the following three rules: (i) homogeneous distribution of ~200 samples across the wafer, (ii) equal number of samples in scan up and scan down condition and (iii) equal number of sampling on each overlay marks per field. When rule based samplings are implemented on the two products, the differences between the full wafer map sampling and the rule based sampling are within 3.5 nm overlay spec with residuals M+3σ of 2.4 nm (x) and 2.43 nm (y) for Product A and 2.98 nm (x) and 3.32 nm (y) for Product B.

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Nyan Lynn Aung, Woong Jae Chung, Lokesh Subramany, Shehzeen Hussain, Pavan Samudrala, Haiyong Gao, Xueli Hao, Yen-Jen Chen, and Juan-Manuel Gomez "Overlay optimization for 1x node technology and beyond via rule based sparse sampling", Proc. SPIE 9778, Metrology, Inspection, and Process Control for Microlithography XXX, 97782G (8 March 2016); https://doi.org/10.1117/12.2218161

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