Feasibility of monitoring a multiple e-beam tool using scatterometry and machine learning: stitching error detection

Guido Rademaker; Yoann Blancquaert; Thibault Labbaye; Lucie Mourier; Nivea Figueiro; Francisco Sanchez; Roy Koret; Jonathan Pradelles; Stéfan Landis; Stéphane Rey; Ronny Haupt; Barak Bringoltz; Michael Shifrin; Daniel Kandel; Avron Ger; Matthew Sendelbach; Shay Wolfling; Laurent Pain

doi:10.1117/12.2326595

19 September 2018 Feasibility of monitoring a multiple e-beam tool using scatterometry and machine learning: stitching error detection

Guido Rademaker, Yoann Blancquaert, Thibault Labbaye, Lucie Mourier, Nivea Figueiro, Francisco Sanchez, Roy Koret, Jonathan Pradelles, Stéfan Landis, Stéphane Rey, Ronny Haupt, Barak Bringoltz, Michael Shifrin, Daniel Kandel, Avron Ger, Matthew Sendelbach, Shay Wolfling, Laurent Pain

Author Affiliations +

Proceedings Volume 10775, 34th European Mask and Lithography Conference; 1077508 (2018) https://doi.org/10.1117/12.2326595
Event: 34th European Mask and Lithography Conference, 2018, Grenoble, France

Abstract

Multiple electron beam direct write lithography is an emerging technology promising to address new markets, such as truly unique chips for security applications. The tool under consideration, the Mapper FLX-1200, exposes long 2.2 μm-wide zones called stripes by groups of 49 beams. The critical dimensions inside and the registration errors between the stripes, called stitching, are controlled by internal tool metrology. Additionally, there is great need for on-wafer metrology of critical dimension and stitching to monitor Mapper tool performance and validate the internal metrology. Optical Critical Dimension (OCD) metrology is a workhorse technique for various semiconductor manufacturing tools, such as deposition, etching, chemical-mechanical polishing and lithography machines. Previous works have shown the feasibility to measure the critical dimension of non-uniform targets by introducing an effective CD and shown that the non-uniformity can be quantified by a machine learning approach. This paper seeks to extend the previous work and presents a preliminary feasibility study to monitor stitching errors by measuring on a scatterometry tool with multiple optical channels. A wafer with OCD targets that mimic the various lithographic errors typical to the Mapper technology was created by variable shaped beam (VSB) e-beam lithography. The lithography process has been carefully tuned to minimize optically active systematic errors such as critical dimension gradients. The OCD targets contain horizontal and vertical gratings with a pitch of 100 nm and a nominal CD of 50 nm, and contain various stitching error types such as displacement in X, Y and diagonal gratings. Sensitivity to all stitching types has been shown. The DX targets showed non-linearity with respect to error size and typically were a factor of 3 less sensitive than the promising performance of DY targets. A similar performance difference has seen in nominally identical diagonal gratings exposed with vertical and horizontal lines, suggesting that OCD metrology for DX cannot be fully characterized due to lithography errors in gratings with vertical lines.

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Guido Rademaker, Yoann Blancquaert, Thibault Labbaye, Lucie Mourier, Nivea Figueiro, Francisco Sanchez, Roy Koret, Jonathan Pradelles, Stéfan Landis, Stéphane Rey, Ronny Haupt, Barak Bringoltz, Michael Shifrin, Daniel Kandel, Avron Ger, Matthew Sendelbach, Shay Wolfling, and Laurent Pain "Feasibility of monitoring a multiple e-beam tool using scatterometry and machine learning: stitching error detection", Proc. SPIE 10775, 34th European Mask and Lithography Conference, 1077508 (19 September 2018); https://doi.org/10.1117/12.2326595

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