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The first intrinsic process monitoring system for 90nm device with Focus and Dose Line Navigator (FDLN)

机译:首款具有聚焦和剂量线导航器(FDLN)的90nm器件固有过程监控系统

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Focus and exposure dose control in lithography is a key challenge for CD (critical dimension) control at 90 nm technology node and beyond. Specially, more high accurate focus control will be necessary for low power MOS devices. Focus and dose line navigator (FDLN) is one of the candidates as in-line controller. The FDLN methodology involves two steps: first, create a focus-dose matrix (FEM) for building the library as supervised data using test wafer. The library means relational equation between the topography of photoresist patterns (line width: CD, height: HT, a side wall angle: SWA) and FEM exposure conditions, second, measure standard production wafer and feed the raw data into the library (which extrapolate focus and dose), which is then provided to the user. Using FDLN, current volume production's focus and dose deviation from the best condition can be obtained. In this time, we have evaluated FDLN using an optical CD measurement tool and process wafer. STI, Cu-CMP, metal wafers are used in this time as actual process. We acquired several FEM set of image feature from wafers, which were exposed by ArF scanner. According to our experiment, the estimation precision for focus and dose are below 24nm and below 1.7% respectively. And CD difference in a chip can reduce to one third as compared with the conventional QC method. These results suggest that FDLN can be the solution as in-line focus controller for volume production, enabling the progression toward Advanced Process Control (APC)
机译:光刻中的聚焦和曝光剂量控制是在90 nm技术节点及更高水平进行CD(临界尺寸)控制的关键挑战。特别地,对于低功率MOS器件,将需要更高精度的聚焦控制。聚焦和剂量线导航仪(FDLN)是作为在线控制器的候选产品之一。 FDLN方法涉及两个步骤:首先,创建聚焦剂量矩阵(FEM),以使用测试晶圆将库构建为受监管的数据。该库意味着光刻胶图形的形貌(线宽:CD,高度:HT,侧壁角:SWA)和FEM曝光条件之间的关系方程,其次,测量标准生产晶圆并将原始数据馈入库中(外推)焦点和剂量),然后提供给用户。使用FDLN,可以获得当前量产的焦点和最佳条件下的剂量偏差。这次,我们使用光学CD测量工具和处理晶圆对FDLN进行了评估。这次将STI,Cu-CMP,金属晶片用作实际工艺。我们从晶圆上获得了一些FEM图像特征集,这些图像特征由ArF扫描仪曝光。根据我们的实验,焦点和剂量的估计精度分别低于24nm和1.7%。并且,与传统的QC方法相比,芯片中的CD差异可以减少到三分之一。这些结果表明,FDLN可以作为批量生产的在线焦点控制器的解决方案,从而实现向高级过程控制(APC)的发展

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