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28 June 2013 In-situ repair qualification by applying Computational Metrology and Inspection (CMI) technologies
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Proceedings Volume 8701, Photomask and Next-Generation Lithography Mask Technology XX; 870108 (2013) https://doi.org/10.1117/12.2030688
Event: Photomask and NGL Mask Technology XX, 2013, Yokohama, Japan
Abstract
Computational techniques have been widely adapted in furthering resolution of optical lithography. Now such techniques are expanded into inspection and metrology with many new applications in mask houses and wafer Fabs enabling process advancement, improving process cycle time, and eliminating operator errors. One area of those applications is mask repair. Many times defects repaired do not pass the AIMS check therefore, the mask has to be reloaded back to repair tool to perform another round of repair and verification. Adding more loops of repair and AIMS check significant increases the mask cycle time and effectively reduces the potential throughput of the AIMS and repair tools. Ideally, the mask should not be removed from repair tool until all defects are repaired successfully. Simulation based In-situ Repair Qualifier (IRQ) was developed to meet this goal. IRQ takes SEM image of a repaired site and then simulates the aerial image using the exact scanner optical and illumination conditions (including free form sources). If the CD on the aerial image does not meet spec, the defect has to be repaired again until it does. By doing so, the chance of having repaired defects not meeting the AIMS spec is dramatically reduced or eliminated. In this paper, we will discuss the technical challenges in detail and present results demonstrating the accuracy and benefits of IRQ. Results on both programmed defects and real defects from product masks will be presented. The repair cycle time improvements and effective tool capacity gains before and after using IRQ are presented.
© (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
C. Y. Chen, Ivan Wei, Laurent Tuo, C. S. Yoo, Dongxue Chen, Danping Peng, Masaki Satake, Bo Su, and Linyong Pang "In-situ repair qualification by applying Computational Metrology and Inspection (CMI) technologies", Proc. SPIE 8701, Photomask and Next-Generation Lithography Mask Technology XX, 870108 (28 June 2013); https://doi.org/10.1117/12.2030688
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