Presentation + Paper
20 March 2020 Run to run and model variability of overlay high order process corrections for mean intrafield signatures
Author Affiliations +
Abstract
As the industry moves from node to node, lithographers have been pushed to use complex models to correct overlay errors and drive down model residuals. High order models are now used in combination with Correction per Exposure capabilities for critical layers on immersion scanners [1]. Mean overlay intrafield signatures are linked to the reticles (current and reference) and illuminations used, therefore the intrafield High Order Process Correction (iHOPC) model should be as stable as possible in terms of correction parameters. However, iHOPC data shows that the overlay parameters can drift over time and a Run to Run can follow these slow drifts. IHOPC R2R integration in production overlay correction flow is discussed in this paper: How corrections are generated from overlay measurement? What metrics are used to secure the model application? What results on production lots can be achieved? Then, a focus is made on the model variability. To operate properly, the R2R needs a high frequency variability as low as possible. Some factors like scanner lens aberration correction, metrology tool matching, measurement layouts, have been found to have an impact on lot-to-lot variability. These effects will be investigated in this paper to provide a conclusion on the usage of an iHOPC R2R for mean overlay intrafield signatures.
Conference Presentation
© (2020) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Benjamin Duclaux, Maxime Gatefait, Olivier Mermet, and Jean-Damien Chapon "Run to run and model variability of overlay high order process corrections for mean intrafield signatures", Proc. SPIE 11325, Metrology, Inspection, and Process Control for Microlithography XXXIV, 113251K (20 March 2020); https://doi.org/10.1117/12.2551062
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KEYWORDS
Semiconducting wafers

Overlay metrology

Reticles

Data modeling

Metrology

Scanners

Sensors

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