Practical and bias-free LWR measurement by CDSEM
Practical and bias-free LWR measurement by CDSEM
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通过 CDSEM 进行实用且无偏差的 LWR 测量
DOI：
10.1117/12.772394
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发表时间：
2008
期刊：
影响因子：
--
通讯作者：
Y. Mii
中科院分区：
文献类型：
--
作者：
S.;Y. Chiu;H. Tao;Y. Mii
LWR/LER的重要性已被广泛视为获得良好器件性能的重要工艺参数，特别是进入45 nm时代。随着半导体制造规模的不断缩小，度量的准确估计甚至更加重要。在CDSEM的常规LWR/LER测量中，测量噪声是不可避免的，并且会导致与真实粗糙度的偏差。一种早期的偏差减小粗糙度测量方法是由J. Villarrubia和B提出的。Bunday [Proc. SPIE 5752，480（2005）]，其中收集具有不同帧数的多个图像并求平均值，以在边缘位置对准之后降低噪声水平（这仅在低噪声水平下是可能的）。A的另一个建议。Yamaguchi等[Proc. SPIE 6152，61522 D（2006）]是利用固定的半实验公式对作为求和的扫描线的数量的函数的测量曲线进行曲线拟合。这两种方法都需要复杂的图像/数据收集和计算方法来获得真实的粗糙度。我们提出了一个实用的和无偏粗糙度测量方法在这里，这是两种方法的改进版本，并评估噪声与多个测量在同一行有足够的扫描线求和数，使行边缘对齐是可行的，无论噪声水平。我们已经证实，噪声接近高斯分布和真实的粗糙度是估计不同的扫描线求和数。所获得的真实粗糙度也通过TEM照片进行了验证。该方法的优点是离线计算简单，可用于联合收割机的CDSEM工业应用。
The importance of LWR/LER has been wildly treated as an important process parameter to obtain good device performance especially entering 45nm era. The accurate estimation of the metrics is even more important as semiconductor fabrication keeps downsizing. In regular LWR/LER measurement by CDSEM, measurement noise is inevitable and causes bias from true roughness. One early bias-reduction roughness measurement method is by J. Villarrubia and B. Bunday [Proc. SPIE 5752, 480 (2005)] in which multiple images with different frame number are collected and averaged to reduce the noise level after edge position aligned (that is only possible in low noise level). Another proposal by A. Yamaguchi, etc. [Proc. SPIE 6152, 61522D (2006)] is curve fitting with a fixed semi-experimental formula to a measurement curve as a function of the number of scan line of summing. Both methods require complicated image/data collection and calculation method to obtain true roughness. We propose a practical and bias-free roughness measurement method here that is improved version of the two methods, and evaluate noise with multiple measurements at the same line which has adequate scan line summing number so that line edge alignment is doable no matter the noise level. We have verified that the noise is close to Gaussian distribution and the true roughness is estimable for different scan line summing number. The obtained true roughness is also verified by TEM picture. The advantage of this method is practical to commercial CDSEM application in combine with simple offline calculation.