29 December 2017 Stochastic effects in EUV lithography: random, local CD variability, and printing failures
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Stochastic effects in lithography are usually quantified through local CD variability metrics, such as line-width roughness or local CD uniformity (LCDU), and these quantities have been measured and studied intensively, both in EUV and optical lithography. Next to the CD-variability, stochastic effects can also give rise to local, random printing failures, such as missing contacts or microbridges in spaces. When these occur, there often is no (reliable) CD to be measured locally, and then such failures cannot be quantified with the usual CD-measuring techniques. We have developed algorithms to detect such stochastic printing failures in regular line/space (L/S) or contact- or dot-arrays from SEM images, leading to a stochastic failure metric that we call NOK (not OK), which we consider a complementary metric to the CD-variability metrics. This paper will show how both types of metrics can be used to experimentally quantify dependencies of stochastic effects to, e.g., CD, pitch, resist, exposure dose, etc. As it is also important to be able to predict upfront (in the OPC verification stage of a production-mask tape-out) whether certain structures in the layout are likely to have a high sensitivity to stochastic effects, we look into the feasibility of constructing simple predictors, for both stochastic CD-variability and printing failure, that can be calibrated for the process and exposure conditions used and integrated into the standard OPC verification flow. Finally, we briefly discuss the options to reduce stochastic variability and failure, considering the entire patterning ecosystem.
© 2017 Society of Photo-Optical Instrumentation Engineers (SPIE)
Peter De Bisschop, Peter De Bisschop, "Stochastic effects in EUV lithography: random, local CD variability, and printing failures," Journal of Micro/Nanolithography, MEMS, and MOEMS 16(4), 041013 (29 December 2017). https://doi.org/10.1117/1.JMM.16.4.041013 . Submission: Received: 31 May 2017; Accepted: 22 November 2017
Received: 31 May 2017; Accepted: 22 November 2017; Published: 29 December 2017

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