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Inverse Lithography Technique for advanced CMOS nodes

机译:用于高级CMOS节点的反光刻技术

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Resolution Enhancement Techniques have continuously improved over the last decade, driven by the ever growing constraints of lithography process. Despite the large number of RET applied, some hotspot configurations remain challenging for advanced nodes due to aggressive design rules. Inverse Lithography Technique (ILT) is evaluated here as a substitute to the dense OPC baseline. Indeed ILT has been known for several years for its near-to-ideal mask quality, while also being potentially more time consuming in terms of OPC run and mask processing. We chose to evaluate Mentor Graphics' ILT engine "pxOPCTM" on both lines and via hotspot configurations. These hotspots were extracted from real 28nm test cases where the dense OPC solution is not satisfactory. For both layer types, the reference OPC consists of a dense OPC engine coupled to rule-based and/or model-based assist generation method. The same CM1 model is used for the reference and the ILT OPC. ILT quality improvement is presented through Optical Rule Check (ORC) results with various adequate detectors. Several mask manufacturing rule constraints (MRC) are considered for the ILT solution and their impact on process ability is checked after mask processing. A hybrid OPC approach allowing localized ILT usage is presented in order to optimize both quality and runtime. A real mask is prepared and fabricated with this method. Finally, results analyzed on silicon are presented to compare localized ILT to reference dense OPC.
机译:在过去的十年中,随着光刻工艺的日益严格的限制,分辨率增强技术得到了持续改进。尽管应用了大量的RET,但由于激进的设计规则,某些热点配置对于高级节点仍然具有挑战性。本文对反光刻技术(ILT)进行了评估,以替代密集的OPC基线。实际上,ILT以其接近理想的掩模质量而闻名,而在OPC运行和掩模处理方面也可能花费更多时间。我们选择通过在线和热点配置来评估Mentor Graphics的ILT引擎“ pxOPCTM”。这些热点是从实际的28nm测试案例中提取的,而密集的OPC解决方案并不令人满意。对于这两种类型,参考OPC均由密集的OPC引擎组成,该引擎与基于规则和/或基于模型的辅助生成方法耦合。参考和ILT OPC使用相同的CM1模型。通过使用各种适当的检测器的光学规则检查(ORC)结果,可以显示ILT质量的提高。 ILT解决方案考虑了几个掩模制造规则约束(MRC),并在掩模处理后检查了它们对工艺能力的影响。为了优化质量和运行时间,提出了一种允许本地化ILT使用的混合OPC方法。用这种方法制备并制造出真实的掩模。最后,提出了在硅片上分析的结果,以比较局部ILT与参考密集OPC。

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