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Binary Cr Etch Process Control Directed at the 45nm Node

机译:针对45nm节点的二元Cr蚀刻工艺控制

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It is clear that whatever the method, endpoint detection on low load Cr photomasks remains a challenge. However, by combining several endpoint techniques (e.g. OES, laser reflectance, throttle valve position, match positions), many of the weaknesses of the individual systems can be overcome. Using a strong optimization technique such as a genetic algorithm to scale each data channel, the signal to noise ratio of the endpoint signal can be significantly enhanced. Beyond the obvious benefits obtained from enhanced endpoint detection, a multi-channel system offers the opportunity for significant improvements in process control and monitoring. The genetic algorithm technique could be applied to detect specific fault situations as easily as it is applied to endpoint. One need only to select the proper process state function and be able to define the fitness of each coefficient set. Future efforts will focus on the selection of appropriate process state functions as well as the evolution of coefficient sets using several data sets simultaneously.
机译:显然,无论采用哪种方法,在低负载Cr光掩模上进行终点检测仍然是一个挑战。但是,通过组合多种端点技术(例如OES,激光反射率,节气门位置,匹配位置),可以克服各个系统的许多缺点。使用强大的优化技术(例如遗传算法)缩放每个数据通道,可以显着提高端点信号的信噪比。除了增强的端点检测带来的明显好处外,多通道系统还为重大改进过程控制和监视提供了机会。遗传算法技术可以像应用于端点一样容易地用于检测特定的故障情况。只需选择适当的过程状态函数并能够定义每个系数集的适用性即可。未来的工作将集中在选择合适的过程状态功能以及同时使用多个数据集的系数集演变上。

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