Variability Modeling and Process Optimization for the 32 nm BEOL Using In-Line Scatterometry Data

Semiconductor Manufacturing, IEEE Transactions(2014)

引用 1|浏览7
暂无评分
摘要
Process variability is a great concern when it comes to the fabrication of nano-scaled devices precisely. The effect of any imprecision can be directly translated into uncertain behavior of the devices. To address the process related issues, it is now essential to identify physical variability properly for a quality end product. If the effects of the variations are not correctly characterized, there is no other way of guaranteeing that the design will meet the specified budgets. This paper describes the essential variability modeling and analyses for the BEOL critical parameters. We used AQUAIA, to model end-of-the-line electrical resistances and capacitances based on 32 nm technology assumptions. By using scatterometry and reference metrology data, we have compared the correlations among the physical in-line measurements and end of the line electrical measurements which eventually address the potential variability issues between them specifically for the 32 nm technology node. It shows good correlation between scatterometry measurement results and results obtained from the AQUAIA simulation. Fitting parameters are generated with the help of AQUAIA's simulation results and physics model. Finally, we have developed a spreadsheet for the RC graph using those fitting parameters to manipulate and optimize the BEOL specification for 32 nm technology. This spreadsheet can be used as a guideline for the process development and control.
更多
查看译文
关键词
cmos integrated circuits,electric resistance measurement,graph theory,integrated circuit interconnections,integrated circuit modelling,optimisation,aquaia,beol critical parameters,rc graph,capacitances,electrical measurements,end-of-the-line electrical resistances,fitting parameters,nanoscaled devices fabrication,physical in-line measurements,physical variability,process variability,quality end product,reference metrology data,scatterometry measurement results,size 32 nm,spreadsheet,variability modeling,32 nm beol,modeling,monitoring and control,optimization,process,scatterometry,variability,metals,process control
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要