利用FEOL中的焦点点监测数据来解决高影响MOL缺陷:DI:缺陷检查和减少

F. Khatkhatay, Chih-chieh Huang, Ludmila Popova, Jongyoon Yoon, Thomas Zalocha, Phillip Tatti, Krishan Gopal, Hongliang Shen, Ho Young Song, Amit Gupta
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引用次数: 1

摘要

随着14nm及以上技术中特征尺寸的缩小,像中线(MOL)这样的聚焦窗口有限浸入式光刻步骤最容易受到晶圆形貌局部小变化引起的热点的影响。MOL中的热点几乎总是致命的,由于单个热点缺陷的存在,整个骰子失败的概率接近100%。焦点由光刻扫描仪中的调平系统识别,并作为故障检测和分类(FDC)信号报告,驱动晶圆配置和工具动作。对焦点点信号的全面报告开辟了利用大量焦点点数据代替缺陷数据的可能性,在缺陷数据中,空间上独特的热点信号可能会在随机基线缺陷中丢失。我们分析了在较低冲击前端线(FEOL)步骤收集的焦点点数据,以降低高冲击MOL步骤的热点,这两者都受到来自共同识别工具重复通过的传入缺陷的影响。这项工作是通过创新地利用大量焦点现场监测数据来智能解决跨模块污染问题的一个例子。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Leveraging focus spot monitoring Data in FEOL to resolve a high impact MOL defect: DI: Defect inspection and reduction
As feature sizes shrink in 14nm technology and beyond, focus window limited immersion lithography steps like those in the middle of line (MOL) are most susceptible to hotspots caused by small localized variations in wafer topography. Hotspots in MOL are almost always killer, with a near 100% probability of the entire die failing due to the presence of a single hotspot defect. Focus spots are identified by the leveling system in the lithography scanner and the reported as a fault detection and classification (FDC) signal, driving wafer disposition and tool actions. Comprehensive reporting of focus spot signals opens up the possibility of utilizing high volume focus spot data in lieu of defect data where spatially unique hotpsot signals may be lost in the random baseline defectivity. We have analyzed focus spot data collected at a lower impact front end of line (FEOL) step to drive down hotspots at a high impact MOL step, both of which are affected by incoming defectivity due to repeat passes on a common identified tool. This work is an example of the smart resolution of a cross-module contamination issue by innovatively leveraging high volume focus spot monitoring data.
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