Paper
17 December 2003 Enhanced dispositioning of reticle defects for advanced masks using virtual stepper with automated defect severity scoring
Linyong Pang, Alex Lu, Jacky Chen, Eric Guo, Lynn Cai, Jiunn-Hung Chen
Author Affiliations +
Abstract
As the semiconductor industry continues to scale down critical dimensions (CD), proximity effects get more and more severe. As such, aggressive Optical Proximity Correction (OPC) features like hammerheads, serifs and assist bars inevitably appear on fabricated masks. The great challenge, however -- to reliably assure the quality of these advanced masks -- is to be able to directly judge a controversial defect under such complex features. It is necessary to find a more effective way to accurately disposition the defects found on these masks. Simulation-based defect disposition strategies have now become much more important for judging defect printability. In this paper, we will study and characterize the printability prediction of various defects on high-end masks by Virtual Stepper® System with its improved Automated Defect Severity Scoring (ADSSTM) function. Both line-space masks with aggressive OPC features like assist bars and attenuated PSM with contact features with small sizes were used to verify the simulation engine and ADSS algorithm in this study. The Virtual Stepper simulation and defect impact analysis results (the automatically calculated Defect Severity Score) will be compared to the SEM images and measurements of wafer prints using 248nm lithography. In addition, production reticles are also used to compare the accuracy and efficiency of ADSS with human review. A new defect disposition flow is also tentatively proposed here to demonstrate that the Virtual Stepper System with its ADSS feature can provide its user with an automated, fast and accurate way of analyzing the impact of a defect. The Virtual Stepper System with ADSS function has been shown to be a suitable tool for photomask defect criticality assessment in mask shops and wafer fabs.
© (2003) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Linyong Pang, Alex Lu, Jacky Chen, Eric Guo, Lynn Cai, and Jiunn-Hung Chen "Enhanced dispositioning of reticle defects for advanced masks using virtual stepper with automated defect severity scoring", Proc. SPIE 5256, 23rd Annual BACUS Symposium on Photomask Technology, (17 December 2003); https://doi.org/10.1117/12.518211
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CITATIONS
Cited by 7 scholarly publications.
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KEYWORDS
Photomasks

Semiconducting wafers

Inspection

Reticles

Optical proximity correction

Virtual reality

Artificial intelligence

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