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基于粒子群优化算法的光刻机光源掩模投影物镜联合优化方法

Source Mask Projector Optimization Method of Lithography Tools Based on Particle Swarm Optimization Algorithm

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摘要

全芯片多参数联合优化是光刻分辨率增强技术的重要发展方向。提出了一种基于粒子群优化(PSO)算法的光源掩模投影物镜联合优化(SMPO)方法。将由像素表征的光源、由离散余弦变换基表征的掩模及由泽尼克系数表征的投影物镜编码为粒子, 以图形误差作为评价函数, 通过不断迭代更新粒子, 实现光源掩模投影物镜联合优化。在标称条件和工艺条件下, 采用含有交叉门的复杂掩模图形对所提方法的仿真验证表明, 图形误差分别降低了94.2%和93.8%, 有效提高了光刻成像质量。与基于遗传算法的SMPO方法相比, 该方法具有更快的收敛速度。此外, 该方法具有优化自由度高和优化后掩模可制造性强的优点。

Abstract

Full-chip multi-parameter optimization is an important development direction of resolution enhancement techniques in optical lithography. A source mask projector optimization (SMPO) method based on particle swarm optimization (PSO) algorithm is proposed. The pixels are used to represent source. The discrete cosine transform basis functions are used to represent the mask. The coefficients of Zernike polynomials are used to represent the projector. The source, the mask and the projector are encoded into particles. The pattern error is adopted as the evaluation function and the particles are updated iteratively to realize the SMPO. This method is simulated and verified by using the complex mask pattern with cross gate design in nominal condition and process condition. Results show that the pattern errors are reduced by 94.2% and 93.8%, respectively, and the quality of lithography imaging is effectively improved. Compared with SMPO method based on genetic algorithm, the proposed method has a faster convergence rate. Besides, the proposed method has the advantages of high degree of optimized freedom and enhanced manufacturability of the optimized mask pattern.

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中图分类号:O436.1

DOI:10.3788/aos201737.1022001

所属栏目:光学设计与制造

基金项目:上海市自然科学基金(17ZR1434100)

收稿日期:2017-04-10

修改稿日期:2017-05-22

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王 磊:中国科学院上海光学精密机械研究所信息光学与光电技术实验室, 上海 201800中国科学院大学, 北京 100049
李思坤:中国科学院上海光学精密机械研究所信息光学与光电技术实验室, 上海 201800中国科学院大学, 北京 100049
王向朝:中国科学院上海光学精密机械研究所信息光学与光电技术实验室, 上海 201800中国科学院大学, 北京 100049
杨朝兴:中国科学院上海光学精密机械研究所信息光学与光电技术实验室, 上海 201800

联系人作者:王磊(wangleizjucn@gmail.com)

备注:王 磊(1990-), 男, 博士研究生, 主要从事高端光刻机分辨率增强技术方面的研究。

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引用该论文

Wang Lei,Li Sikun,Wang Xiangzhao,Yang Chaoxing. Source Mask Projector Optimization Method of Lithography Tools Based on Particle Swarm Optimization Algorithm[J]. Acta Optica Sinica, 2017, 37(10): 1022001

王 磊,李思坤,王向朝,杨朝兴. 基于粒子群优化算法的光刻机光源掩模投影物镜联合优化方法[J]. 光学学报, 2017, 37(10): 1022001

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