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Modeling of Linewidth Measurement in SEMs Using Advanced Monte Carlo Software

机译:使用先进的蒙特卡洛软件对SEM中的线宽测量建模

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Accurate measurement of linewidth is a critical problem in sub-100 nm semiconductor manufacturing, where required accuracy is in the range of 1 nm and below. CD-SEMs are usually used for such measurements. A cross-correlation of CD-SEMs, while demonstrating a good relative trend, is often subject to a significant absolute linewidth error, as well as the parameters of the SEM settings being used. There is no proven algorithm for edge detection in CD-SEMs. Tool manufacturers set up the edge detection voluntarily, as a rule, which is why the absolute errors in measurement occur. In this paper, we demonstrate that edge detection depends greatly on parameters of SEM settings, like beam diameter, and pattern properties, like the wall angle of a pattern. When both the signal and pattern are known, an offset for a specific SEM algorithm can be found. An algorithm for automatic edge detection in CD-SEMs can be tuned for beam parameters and the type of pattern. A SEM signal was simulated using the advanced Monte Carlo software CHARIOT, which is commercially available. Input data for the modeling was 3D microstructures and e-beam parameters. A simulated signal was then compared to a known pattern. Such a comparison allowed us to define the edge position and calibrate a SEM so that any system- and pattern-dependent errors could be removed.
机译:线宽的准确测量是低于100 nm的半导体制造中的关键问题,要求的精度在1 nm以下。 CD-SEM通常用于此类测量。 CD-SEM的互相关性虽然显示出良好的相对趋势,但通常会受到明显的绝对线宽误差以及所用SEM设置参数的影响。 CD-SEM中没有经过验证的边缘检测算法。刀具制造商通常会自动设置边缘检测,这就是为什么会发生测量中绝对误差的原因。在本文中,我们证明了边缘检测在很大程度上取决于SEM设置的参数,例如光束直径和图案属性,例如图案的壁角。当信号和模式都已知时,可以找到特定SEM算法的偏移量。可以针对CD-SEM中的自动边缘检测算法调整光束参数和图案类型。使用先进的蒙特卡洛软件CHARIOT(可商购)模拟SEM信号。建模的输入数据是3D微结构和电子束参数。然后将模拟信号与已知模式进行比较。这样的比较使我们能够定义边缘位置并校准SEM,从而可以消除任何与系统和图案有关的误差。

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