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Analysis and modulation of aberration in an extreme ultraviolet lithography projector via rigorous simulation and a back propagation neural network

机译:经由严格仿真和后传播神经网络分析和调制极端紫外光刻投影仪中的像差

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摘要

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 ofEUVLin the optical design stage. (C) 2020 Optical Society of America.
机译:镜头像差是影响光刻的关键因素,一个劣化图像保真度和对比度。由于完美的镜头不存在,像差控制对于实际光学系统很重要,特别是对于极端紫外线(EUVL)。通过选择过程变化带(PVB)和图案移位(PS)作为光刻性能指示器,本文提出了像差控制的逆分析模型。首先,差异对36个Zernike术语对光刻性能的影响是向前分析的。使用最终筛选设计(DSD)和借助统计分析方法的统计分析方法和F检验的分析方法,识别通向PVB和PS突出的Zernike术语。在简要介绍后展示神经网络(BPNN)之后,然后建立基于DSD和BPNN的像差控制模型。最后,分析了几个例子以证明像差控制模型的有效性和鲁棒性。预测结果表明,由像差模型给出的Zernike系数的最佳分布可以产生对成像质量的最小影响,并且这种影响非常接近零像差。结果表明,基于BPNN的像差模型具有用于控制光学设计阶段的uvlin的像差的有效指导方法。 (c)2020美国光学学会。

著录项

  • 来源
    《Applied optics》 |2020年第23期|共9页
  • 作者单位

    Chinese Acad Sci Inst Microelect Integrated Circuit Adv Proc Ctr Beijing 100029 Peoples R China;

    Chinese Acad Sci Inst Microelect Integrated Circuit Adv Proc Ctr Beijing 100029 Peoples R China;

    Shandong Univ Sch Microelect Jinan 250100 Shandong Peoples R China;

    Chinese Acad Sci Inst Microelect Integrated Circuit Adv Proc Ctr Beijing 100029 Peoples R China;

    Chinese Acad Sci Inst Microelect Integrated Circuit Adv Proc Ctr Beijing 100029 Peoples R China;

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  • 正文语种 eng
  • 中图分类 应用;
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