基于平稳小波变换的纳米尺度线边缘粗糙度分析方法(英文)  

Analysis Method for Nanometer-Scale Line Edge Roughness Based on Stationary Wavelet Transform

作　　者：赵学增[1] 李宁[1] 褚巍[1] 周法权[1] 周瑞[2] 

机构地区：[1]哈尔滨工业大学机电工程学院,哈尔滨150001 [2]哈尔滨工业大学能源科学与工程学院,哈尔滨150001

出　　处：《纳米技术与精密工程》2009年第2期147-154,共8页Nanotechnology and Precision Engineering

摘　　要：为了解决微电子制造技术中纳米尺度半导体刻线边缘粗糙度(line edge roughness,LER)的测量问题,笔者提出了基于平稳小波变换的线边缘粗糙度分析方法.首先,使用原子力显微镜测量硅刻线形貌,通过图像处理与阈值方法提取出线边缘粗糙度特征.然后采用基于平稳小波变换的多尺度分析确定线边缘粗糙度特征的能量分布,给出了线边缘粗糙度的多尺度表征参数,包括特征长度和粗糙度指数.仿真出具有不同粗糙程度的线轮廓,计算出其粗糙度指数分别为0.72和6.05,表明该方法可以有效地反映出线边缘的不规则程度,并提供直观的LER空间频率信息.对一组硅刻线的测量数据进行处理,得到其特征长度和粗糙度指数分别为44.56nm和12.17.最后,采用该方法对使用3种不同探针和3组不同扫描间隔的测量数据分别进行分析,结果表明该方法可以有效地量化表征线边缘粗糙度.To resolve the problem of measuring semiconductor line edge roughness （LER） in the microelectronic manufacturing technology, the analysis method for LER based on stationary wavelet transform was presented. First, the topography of Si line structure was measured using atomic force microscope （AFM）, and the feature of LER was obtained by image processing and threshold method. Then the energy distribution of LER in each scale was determined by the multi-scale analysis based on stationary wavelet transform and the parameters of multi-scale characterization were given including the characteristic length I and the roughness exponent R. The simulation data of the line profile with different degree irregularities were generated, and the calculated roughness exponent R is 0.72 and 6.05, respectively. The results show that the roughness exponent R can reflect the irregularities of LER effectively and provide the straightforward spatial information of LER. Applying this multi-scale analysis to the measurement data of Si line, the characteristic length 1 and the roughness exponent R is 44.56 nm and 12.17, respectively. Finally, the experimental data analyses of three kinds of probes and three scanning intervals show that this analysis method can offer an effective quantitative characterization and analysis of LER.

关 键 词：纳米测量 线边缘粗糙度 原子力显微镜 平稳小波变换 多尺度分析 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]