Zhao Rongbo, Dong Lisong, Bo Chunyue, Wei Yayi, Su Xiaojing
Appl Opt. 2020 Aug 10;59(23):7074-7082. doi: 10.1364/AO.397250.
Lens aberration is a critical factor affecting lithography, one that deteriorates the image fidelity and contrast. As the perfect lens does not exist, the aberration control is important for real optical systems, especially for extreme ultraviolet lithography (EUVL). By choosing the process variation band (PVB) and pattern shift (PS) as the lithographic performance indicators, the inverse analysis model for aberration control is proposed in this paper. First, the effects of aberration with 36 Zernike terms on lithography performance are forward analyzed. Using the definitive screening design (DSD) and with the help of statistical analysis methods of analysis of variance and F test, the combined Zernike terms leading to prominent PVB and PS are identified. After giving a brief introduction of backpropagation neural network (BPNN), the aberration control model based on DSD and BPNN is then established. Finally, several examples are analyzed to demonstrate the effectiveness and robustness of the aberration control model. Predicted results show that the optimum distribution of Zernike coefficients given by the aberration model can generate minimum impact on imaging quality, and this impact is very close to that of zero aberration. The results demonstrate that the BPNN-based aberration model has the potential to be an efficient guiding method for controlling the aberration of EUVL in the optical design stage.
透镜像差是影响光刻的一个关键因素，它会降低图像保真度和对比度。由于不存在完美透镜，像差控制对于实际光学系统很重要，尤其是对于极紫外光刻（EUVL）。本文通过选择工艺变化带（PVB）和图案偏移（PS）作为光刻性能指标，提出了像差控制的逆分析模型。首先，对具有36个泽尼克项的像差对光刻性能的影响进行正向分析。利用确定性筛选设计（DSD）并借助方差分析和F检验等统计分析方法，识别出导致显著PVB和PS的组合泽尼克项。在简要介绍反向传播神经网络（BPNN）之后，建立了基于DSD和BPNN的像差控制模型。最后，通过几个例子分析来证明像差控制模型的有效性和稳健性。预测结果表明，像差模型给出的泽尼克系数的最优分布对成像质量的影响最小，且这种影响非常接近零像差的影响。结果表明，基于BPNN的像差模型有潜力成为在光学设计阶段控制EUVL像差的一种有效指导方法。
