基于广度优先搜索的全芯片光源掩模优化关键图形筛选方法  

Critical Pattern Selection Method Based on Breadth-First Search for Full-Chip Source-Mask Optimization

作　　者：杨欣华 江一鹏 李思坤[1,2] 廖陆峰 张双 张利斌 张生睿[4] 施伟杰 韦亚一 王向朝 Yang Xinhua;Jiang Yipeng;Li Sikun;Liao Lufeng;Zhang Shuang;Zhang Libin;Zhang Shengrui;Shi Weijie;Wei Yayi;Wang Xiangzhao(Department of Advanced Optical and Microelectronic Equipment,Shanghai Institute of Optics and Fine Mechanics,Chinese Academy of Sciences,Shanghai 201800,China;Center of Materials Science and Optoelectronics Engineering,University of Chinese Academy of Sciences,Beijing 100049,China;EDA Center,Institute of Microelectronics of Chinese Academy of Sciences,Beijing 100029,China;Dongfang Jingyuan Electron Co.,Ltd.,Beijing 100176,China;School of Integrated Circuits,University of Chinese Academy of Sciences,Beijing 100049,China;College of Optical Science and Engineering,Zhejiang University,Hangzhou 310058,Zhejiang,China)

机构地区：[1]中国科学院上海光学精密机械研究所高端光电装备部,上海201800 [2]中国科学院大学材料与光电研究中心,北京100049 [3]中国科学院微电子研究所EDA中心,北京100029 [4]东方晶源微电子科技(北京)有限公司,北京100176 [5]中国科学院大学集成电路学院,北京100049 [6]浙江大学光电科学与工程学院,浙江杭州310058

出　　处：《光学学报》2024年第9期131-141,共11页Acta Optica Sinica

基　　金：国家自然科学基金(62374167,U22A2070);国家02科技重大专项(2017ZX02101004-002,2017ZX02101004)。

摘　　要：提出一种基于广度优先搜索的全芯片光源掩模优化关键图形筛选方法。通过广度优先搜索算法得到所有图形数最少的关键图形组。以45 nm标准单元库测试图形集为例,采用商用计算光刻软件Tachyon Tflex对本文方法的筛选结果进行仿真验证。结果表明,本文方法获得的关键图形组的工艺窗口优于Tachyon Tflex中的同类技术。相比于基于深度优先搜索的全芯片SMO关键图形筛选方法,本文方法只筛选出所有图形数量最少的关键图形组,图形筛选效率更高。Objective The full-chip source-mask optimization(SMO)technique,developed by the collaborative optimization of light sources and masks,plays a crucial role in achieving process nodes of 28 nm and smaller.During full-chip SMO,it is essential to employ graphic selection techniques to identify critical patterns from the mask layout.Based on these critical patterns,an illumination mode suitable for the full-chip mask patterns can be determined.Among the various methods for graphic selection,the spectrum-based approach stands out due to its advantages of not requiring a priori knowledge and offering high reliability.However,existing spectrum-based methods fall short in efficiently selecting the smallest set of critical patterns within the shortest time,leaving room for further improvement in efficiency.Methods In this paper,we propose a critical pattern selection method based on the breadth-first search algorithm.Based on existing spectrum graphic selection methods,our approach leverages the breadth-first search mechanism to ensure that the nearest leaf nodes to the root node are discovered during the search process.By finding the shortest paths and combining them,we efficiently select all minimal critical pattern groups without traversing the entire critical pattern tree.This approach significantly improves the efficiency of critical pattern selection.Results and Discussions In this paper,ASML s Tachyon Tflex software is used for simulation verification.The simulation employs a set of 60 randomly selected patterns from the 45 nm standard cell library.Under the condition of distinguishing pattern periodicity,our proposed method identifies two minimal critical pattern groups(Fig.7),whereas Tachyon Tflex software produces only one group(Fig.8).When various critical metrics are compared under a 10%CD deviation and 5%EL,group A in our method exhibits MEEF and ILS indicators similar to Tachyon Tflex,but with a significantly better depth of focus(DOF)(Table 2).Furthermore,without considering pattern periodicity,our method id

关 键 词：集成光学 图形筛选 计算光刻 全芯片光源掩模联合优化 广度优先搜索 

分 类 号：TN305.7[电子电信—物理电子学]