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

NL Aung, WJ Chung, L Subramany… - … Process Control for …, 2016 - spiedigitallibrary.org
NL Aung, WJ Chung, L Subramany, S Hussain, P Samudrala, H Gao, X Hao, YJ Chen…
Metrology, Inspection, and Process Control for Microlithography XXX, 2016spiedigitallibrary.org
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 …
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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