Paper
1 October 2009 Aerial imaging for source mask optimization: mask and illumination qualification
Amir Sagiv, Jo Finders, Robert Kazinczi, Andre Engelen, Frank Duray, Ingrid Minnaert-Janssen, Shmoolik Mangan, Dror Kasimov, Ilan Englard
Author Affiliations +
Abstract
As the semiconductor industry moved to 4X technology nodes and below, low-k1 ArF lithography approached the theoretical limits of single patterning resolution, a regime typically plagued by marginally small process windows. In order to widen the process window bottleneck, projection lithography must fully and synergistically employ all available degrees of freedom. The holistic lithography source mask optimization (SMO) methodology aims to increase the overall litho performance and achieve a robust process window for the most challenging patterns by balancing between the mask and illumination source design influences. The typical complexity of both mask and illumination source that results from a generic SMO process exceeds the current norm in the lithographic industry. In particular, the SMO literature reports on masks that fully operate as diffractive optical elements, with features that have little resemblance to the final wafer-level pattern. Additionally, SMO illumination sources are characterized by parametric or pixelated shapes and a wide range of transmission values. As a consequence of the new mask and source designs, qualifying the mask for printing and non-printing defects and accurate assessment of critical dimensions becomes one of the main mask inspection challenges. The aerial imaging technologies of Applied Material's Aera2TM mask inspection tool provide enabling solutions by separating out only the defects that matter and accurately measures aerial imaging critical dimensions. This paper presents the latest numerical and experimental SMO mask qualifications research results performed at Applied Materials with a mask containing two-dimensional DRAM production structures.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Amir Sagiv, Jo Finders, Robert Kazinczi, Andre Engelen, Frank Duray, Ingrid Minnaert-Janssen, Shmoolik Mangan, Dror Kasimov, and Ilan Englard "Aerial imaging for source mask optimization: mask and illumination qualification", Proc. SPIE 7488, Photomask Technology 2009, 74880Z (1 October 2009); https://doi.org/10.1117/12.832724
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Cited by 1 scholarly publication.
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KEYWORDS
Source mask optimization

Photomasks

Signal detection

Inspection

Airborne remote sensing

Lithography

Lithographic illumination

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