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Single-angle-of-incidence ellipsometry

机译:单入射角椭圆仪

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We introduce single angle-of-incidence (SAI) ellipsometry [U.S. patent application 20070024850 (14 July 2006)] as a technique to completely identify, i.e., totally characterize, film-substrate systems. We show that only one measurement of the ellipsometric function rho at one angle of incidence and one wavelength is totally sufficient to determine the optical constant of the film N_(1), its thickness d, and the substrate's optical constant N_(2). Obviously, it is also sufficient for characterizing only the film, determining N_(1) and d, and for characterizing only the substrate, determining N_(2) and d, as well as for characterizing only bare substrates. An inverse genetic algorithm (IGA) for complete identification is presented that is based on a physical condition of the transparent-film-absorbing-substrate system. This IGA is used to identify the film-substrate system in four separate cases. We show that removing the film thickness from the fitness function of the genetic algorithm and using the defined optimum population size to characterize the film reduces the computational effort from 20,000 to 69 fitness-function calculations; the number of calculations to characterize an absorbing layer is reduced from 80,000 to 180. This is a very significant reduction and is very welcome in real-time applications. An error analysis is presented that shows that the IGA is resilient to, not affected by, random experimental errors and that it gives very good results in the presence of both random and systematic errors of the ellipsometer system. Experimental results are given that also prove the robustness, stability, and high accuracy of the method. We present data only for the SiO_(2)-Si film-substrate system, but the IGA works for any film-substrate system, physical or not.
机译:我们介绍了单入射角(SAI)椭圆仪[U.S.专利申请20070024850(2006年7月14日)]作为一种技术来完全识别(即完全表征)薄膜-基材系统。我们表明,仅在一个入射角和一个波长下对椭偏函数rho进行一次测量就完全可以确定薄膜N_(1)的光学常数,其厚度d和基底的光学常数N_(2)。显然,对于仅表征膜,确定N_(1)和d,仅表征衬底,确定N_(2)和d,以及仅表征裸露的衬底,也就足够了。提出了一种基于完全透明薄膜吸收基质系统的物理条件进行完全识别的逆遗传算法(IGA)。该IGA用于在四种不同情况下识别薄膜-基材系统。我们表明,从遗传算法的适应度函数中除去薄膜厚度,并使用定义的最佳种群规模来表征薄膜,可以将计算量从20,000减少到69。表征吸收层的计算次数从80,000减少到180。这是一个非常重要的减少,在实时应用中非常受欢迎。进行了误差分析,该分析表明IGA可以抵抗随机实验误差,并且不受其影响,并且在椭偏仪系统存在随机误差和系统误差的情况下,都能给出很好的结果。给出的实验结果也证明了该方法的鲁棒性,稳定性和高精度。我们仅提供SiO_(2)-Si薄膜-基材系统的数据,但IGA可用于任何物理或非物理的薄膜-基材系统。

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