Advanced OPC Mask-3D and Resist-3D modeling

Szucs, A.; Planchot, Jonathan; Farys, V.; Yesilada, Emek; Depre, L.; Kapasi, Sanjay; Gourgon, C.; Besacier, M.; Mouraille, Orion; Driessen, Frank

doi:10.1117/12.2047281

Cited by 9 publications

(1 citation statement)

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“…Attempts have been made to calibrate such models, based on measured resist-profile data [using atomic force microscopy (AFM) and=or cross-section scanning electron microscopy (SEM)] or even resist profiles obtained with a rigorous lithography simulator (such as S-Litho or Prolith), or a combination of these three. The results published on such modeling attempts are encouraging, 6) but the R3D model calibration problem does not seem solved yet, and R3D models are not yet commonly used.…”

Section: Resist Modelmentioning

confidence: 99%

Optical proximity correction: A cross road of data flows

Bisschop¹

2016

Jpn. J. Appl. Phys.

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This paper reviews the various data flows that occur in the generation and verification of optical proximity correction (OPC) for an optical lithography photomask. First we review the models that are or can be used in the OPC model-calibration flow, with some emphasis on those models that are not yet standard practice. Through an efficient selection of calibration structures, the data amounts needed for model calibrations can be usually kept reasonably small. This is much less the case in the OPC verification step (computationally first and on-wafer afterwards), where data volumes can be very large. Especially the inspection of printed test wafer, where the printability of large number of structures needs to be assessed throughout the intended process window, currently presents important challenges as “hotspot” detection and printability quantification needs to be combined with a short turn-around time. We will discuss some of the approaches that are being employed to deal with these conflicting requirements.

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Section: Resist Modelmentioning

confidence: 99%