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Leveraging focus spot monitoring Data in FEOL to resolve a high impact MOL defect: DI: Defect inspection and reduction

机译:利用FEOL中的焦点监视数据来解决影响较大的MOL缺陷:DI:缺陷检查和减少

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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.
机译:随着14nm技术及更多技术中特征尺寸的缩小,像晶圆中线(MOL)一样,聚焦窗口受限的浸没式光刻步骤最容易受到晶片形貌局部微小变化所引起的热点的影响。 MOL中的热点几乎总是致命的,由于单个热点缺陷的存在,整个管芯发生故障的几率接近100%。焦点由光刻扫描仪中的调平系统识别,并报告为故障检测和分类(FDC)信号,驱动晶圆配置和工具动作。焦点信号的全面报告开辟了利用大量焦点数据代替缺陷数据的可能性,在缺陷数据中,空间独特的热点信号可能会在随机基线缺陷中丢失。我们已经分析了在较低影响力的前端(FEOL)步骤收集的焦点数据,以在具有较高影响力的MOL步骤降低驱动力热点,这两个数据都受到在通用已识别工具上重复加工而导致的缺陷率的影响。这项工作是通过创新性地利用大量焦点监测数据来智能解决跨模块污染问题的一个示例。

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