中国激光, 2020, 47 (8): 0805003, 网络出版: 2020-08-17 复制并引用该论文  本文已被引 9 次  被引通知

图 & 表

图 1. 自由光瞳照明模块示意图

Fig. 1. Diagram of freeform pupil illumination module

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图 2. 自由光瞳照明模块子光束成像示意图

Fig. 2. Sub-beam imaging diagram of freeform pupil illumination module

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图 3. 基于遗传算法的MMA角位置分布算法流程图

Fig. 3. Flow chart of angular position distribution algorithm of MMA based on genetic algorithm

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图 4. 基于遗传算法的MMA角位置分布算法的光瞳强度分布结果。(a1)(b1)(c1)目标光瞳强度分布;(a2)(b2)(c2)算法优化得到的光瞳强度分布

Fig. 4. Pupil intensity distributions generated by MMA angular position distribution algorithm based on genetic algorithm. (a1)(b1)(c1) Target pupil intensity distributions; (a2)(b2)(c2) pupil intensity distributions after algorithm optimization

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图 5. 基于遗传算法的MMA角位置分布算法迭代过程中光瞳强度分布变化图。(a)自由照明模式1;(b)自由照明模式2;(c)自由照明模式3

Fig. 5. Changes of pupil intensity distribution during iteration of MMA angular position distribution algorithm based on genetic algorithm. (a) Free lighting mode 1; (b) free lighting mode 2; (c) free lighting mode 3

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图 6. 基于遗传算法的MMA角位置分布算法得到的角位置分布图。(a)自由照明模式1;(b)自由照明模式2;(c)自由照明模式3

Fig. 6. Angular position distributions gained from MMA angular position distribution algorithm based on genetic algorithm. (a) Free lighting mode 1; (b) free lighting mode 2; (c) free lighting mode 3

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图 7. 基于遗传算法和基于模拟退火算法的MMA角位置分布算法优化过程和结果对比图。(a)基于遗传算法得到的E_RMS值随迭代时间的变化图;(b)基于模拟退火算法得到的E_RMS值随迭代时间的变化图;(c)基于遗传算法和模拟退火算法得到的E_RMS值对比

Fig. 7. Comparison of optimization processes and results of MMA angular position distribution algorithms based on genetic algorithm and simulated annealing algorithm. (a) E_RMS obtained based on genetic algorithm varying with iteration time; (b) E_RMS obtained based on simulated annealing algorithm varying with iteration time; (c) comparison of E_RMSresults between genetic algorithm and simulated annealing algorithm based methods

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图 8. 光刻胶曝光图形x方向和y方向不对称性示意图

Fig. 8. Schematic diagram of asymmetry in x and y directions for photoresist exposure pattern

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图 9. 仿真用到的部分典型光刻曝光图形和关键尺寸差异分布。(a)仿真用到的部分典型光刻曝光图形;(b)算法光瞳和目标光瞳的关键尺寸差异分布

Fig. 9. Partial typical photoresist exposure patterns used in simulation and CD difference distributions. (a) Partial typical photoresist exposure patterns used in simulation; (b) CD difference distributions between algorithm and target pupils

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表 1光刻性能仿真参数

Table1. Simulation parameters of photolithography performance

Item Feature Numerical aperture (NA) 1.35 Pupil of illumination system Free lighting modes 1, 2, and 3 Mask Phase shifting mask, dark field Refractive index of image medium (immersion) 1.44 Refractive index for photoresist film (matched substrate) Photoresist: 1.70; substrate: 1.70 Extinction coefficient for photoresist film (matched substrate) Photoresist: 0.02; substrate: 0.02 Thickness for photoresist film (matched substrate) Photoresist: 100; substrate: ∞

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表 2光刻胶曝光图形不对称性分布光刻性能仿真结果

Table2. Simulation results of photolithography performance for A_Asym distribution of photoresist exposure pattern

Pupil type RMS_x /nm RMS_y /nm Free lightingmode 1 0.03 0.04 Targetpupil Free lightingmode 2 0.03 0.03 Free lightingmode 3 0.03 0.04 Free lightingmode 1 0.03 0.03 Algorithmpupil Free lightingmode 2 0.03 0.03 Free lightingmode 3 0.03 0.03

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曾宗顺, 张方, 牛志元, 马晓喆, 朱思羽, 黄惠杰. 基于遗传算法的微反射镜阵列角位置分布算法[J]. 中国激光, 2020, 47(8): 0805003. Zeng Zongshun, Zhang Fang, Niu Zhiyuan, Ma Xiaozhe, Zhu Siyu, Huang Huijie. Angular Position Distribution Algorithm of Micro Mirror Array Based on Genetic Algorithm[J]. Chinese Journal of Lasers, 2020, 47(8): 0805003.