Zhang Nien Fan, Silver Richard M, Zhou Hui, Barnes Bryan M
Statistical Engineering Division, National Institute of Standards and Technology, 100 Bureau Drive MS 8980, Gaithersburg, Maryland 20899, USA.
Appl Opt. 2012 Sep 1;51(25):6196-206. doi: 10.1364/AO.51.006196.
Recently, there has been significant research investigating new optical technologies for dimensional metrology of features 22 nm in critical dimension and smaller. When modeling optical measurements, a library of curves is assembled through the simulation of a multidimensional parameter space. A nonlinear regression routine described in this paper is then used to identify an optimum set of parameters that yields the closest experiment-to-theory agreement. However, parametric correlation, measurement noise, and model inaccuracy all lead to measurement uncertainty in the fitting process for optical critical dimension measurements. To improve the optical measurements, other techniques such as atomic force microscopy and scanning electronic microscopy can also be used to provide supplemental a priori information. In this paper, a Bayesian statistical approach is proposed to allow the combination of different measurement techniques that are based on different physical measurements. The effect of this hybrid metrology approach will be shown to reduce the uncertainties of the parameter estimators.
最近，有大量研究在探索用于关键尺寸为22纳米及更小特征的尺寸计量的新光学技术。在对光学测量进行建模时，通过对多维参数空间的模拟来组装一组曲线。然后使用本文中描述的确非线性回归程序来确定能产生最接近实验与理论一致性的最佳参数集。然而，参数相关性、测量噪声和模型不准确性都会在光学关键尺寸测量的拟合过程中导致测量不确定性。为了改进光学测量，还可以使用其他技术，如原子力显微镜和扫描电子显微镜来提供补充的先验信息。本文提出了一种贝叶斯统计方法，以允许基于不同物理测量的不同测量技术进行组合。这种混合计量方法的效果将被证明可以减少参数估计器的不确定性。
