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无偏差粗糙度测量:去除SEM效应,第2部分

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发表于 2018-11-27 13:36:25 | 显示全部楼层 |阅读模式
Unbiased roughness measurements: Subtracting out SEM effects, part 2
无偏差粗糙度测量:去除SEM效应,第2部分
Journal of Vacuum Science & Technology B 36, 06J503 (2018);

https://doi.org/10.1116/1.5046477
Gian F. Lorusso1, Vito Rutigliani1, Frieda Van Roey1, and Chris A. Mack2,a)
Hide Affiliations
1IMEC, Kapeldreef 75, B-3001 Leuven, Belgium
2Fractilia, LLC, 1605 Watchhill Rd, Austin, Texas 78703
a)Electronic mail: chris.mack@fractilia.com

ABSTRACT
摘要

The measurement of roughness of small lithographic patterns is biased by noise in the scanning electron microscopes (SEMs) used to make the measurements. Unbiasing the roughness measurement requires the measurement and subtraction of the image noise based on its unique frequency behavior. Improvement to prior white noise removal is achieved by applying a pink noise model. This pink noise removal technique was applied to roughness measurements made with different electron doses (frames of integration), different operating voltages, and different generations of SEM tools. Effective noise removal to create accurate unbiased estimates of the roughness was achieved over a wider range of SEM tool parameter settings than has been previously achieved. As a result, unbiased roughness measurements can now be used to characterize and improve stochastic variability in semiconductor lithography and patterning.



        小的光刻图案的粗糙度的测量受到用于进行测量的扫描电子显微镜(SEM)中的噪声的影响而产生偏差。无偏差粗糙度测量需要基于其独特的频率特性来进行测量和消除图像噪声。通过应用粉红噪声模型实现对先前去除白噪声的改进。这种粉红噪声去除技术适用于使用不同电子剂量(集成框架)、不同工作电压和不同年代的SEM工具进行的粗糙度测量。通过比先前使用的更广泛的SEM工具参数设置来实现有效的噪声去除以得到准确的无偏差粗糙度估算。其结果是,无偏差粗糙度测量现在可用于表征和改善半导体光刻和图案化中的随机量估算。

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