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Source Mask Optimization Based on Dynamic Fitness Function
Yang CX(杨朝兴); Li SK(李思坤); Wang XC(王向朝); yangcoloy@siom.ac.cn; wxz26267@siom.ac.cn
2016
Source Publication光学学报
Volume36Issue:1Pages:111006
AbstractA dynamic source mask optimization (SMO) method is developed. The dynamic SMO method uses a dynamic fitness function in genetic algorithm to simulate the process variations in real lithography process. So the imaging quality of the optimized source and mask is not sensitive to the process errors. The dynamic SMO method can get similar result as the conventional weighted SMO method without the necessity of weighting coefficient optimization. Simulation results show that the dynamic method can get a usable defocus of 200 nm when the dose error is 15%. This is comparable with the optimized result of the weighted method. The dynamic SMO method can be also used to make the optimized source and mask less sensitive to other process errors, such as coma errors.
SubtypeArticle
Other Abstract提出了一种基于动态适应度函数的光刻机光源掩模优化方法(SMO)。动态适应度函数方法在遗传算法优化过程中采用动态适应度函数模拟真实光刻工艺条件误差对光刻结果的影响,得到对光刻工艺条件误差不敏感的优化光源和优化掩模。该方法无需优化权重系数,即可获得与权重优化后的加权适应度函数方法相近的工艺宽容度。典型逻辑图形的仿真实验表明,曝光剂量误差为15%时,动态适应度函数方法得到的优化光源和优化掩模的可用焦深达到200 nm,与加权适应度函数方法的优化效果相当。动态适应度函数方法也可用于降低SMO的优化光源和掩模对其他
Department信息光电
DOI10.3788/AOS201636.0112002
Funding Organization国家自然科学基金 ; 国家自然科学基金 ; 国家自然科学基金 ; 国家自然科学基金
Indexed ByCSCD
Funding Organization国家自然科学基金 ; 国家自然科学基金 ; 国家自然科学基金 ; 国家自然科学基金
WOS IDCSCD:5710778
CSCD IDCSCD:5710778
Citation statistics
Cited Times:3[CSCD]   [CSCD Record]
Document Type期刊论文
Identifierhttp://ir.siom.ac.cn/handle/181231/28527
Collection信息光学与光电技术实验室
Corresponding Authoryangcoloy@siom.ac.cn; wxz26267@siom.ac.cn
Affiliation中国科学院上海光学精密机械研究所
Recommended Citation
GB/T 7714
Yang CX,Li SK,Wang XC,et al. Source Mask Optimization Based on Dynamic Fitness Function[J]. 光学学报,2016,36(1):111006.
APA 杨朝兴,李思坤,王向朝,yangcoloy@siom.ac.cn,&wxz26267@siom.ac.cn.(2016).Source Mask Optimization Based on Dynamic Fitness Function.光学学报,36(1),111006.
MLA 杨朝兴,et al."Source Mask Optimization Based on Dynamic Fitness Function".光学学报 36.1(2016):111006.
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