【作者】 李宁；

【导师】 陈志坚； 林晓玲； 章晓文；

【作者基本信息】 华南理工大学 ， 集成电路工程（专业学位）， 2023， 硕士

【摘要】 如今集成电路和我们生活戚戚相关,随处都能看到其身影,在医疗、航天、军事等领域中更是处于核心地位,一旦芯片出现问题,将产生难以预计的后果,因此集成电路的可靠性一直以来都备受关注。随着制造工艺技术的快速发展,器件的特征尺寸越来越小,集成度越来越高,金属布线的层数越来越多,制造工序越来越复杂,特别是互连的材料由铜替代了铝,其工艺也随着改变。由此引发新的可靠性问题,这对集成电路的特性和寿命产生了显著影响,其中电迁移是最严重的可靠性问题之一,而电迁移中比较重要的一个模型参数就是激活能。目前国内外对于Black模型参数优化的研究相对较少,本文主要对65nm铜互连系统可靠性展开相关研究,针对残余应力对模型参数的影响以及模型参数优化问题,通过不同温度点的电迁移加速寿命试验,提出二次多项式拟合的方法对模型参数进行优化,达到准确评价电迁移可靠性的目的。首先,本文从铜互连工艺流程中分析可靠性问题,基于电迁移基本理论对电迁移失效的驱动机制进行分析,研究残余应力对电迁移可靠性的影响,并通过拉曼光谱检测验证了残余应力的存在,证实了残余应力随温度变化的特性。其次,根据实验目的设计了开尔文测试结构,进行了不同温度点的电迁移加速寿命试验,同时给出了电迁移实验结束后采集失效时间数据的两种类型;实验后发现大部分测试样品电阻会发生多次跳变,并通过扫描电子显微镜证明了电阻出现多次跳变的原因。最后,本文对电迁移测试失效结果进行分析研究:(1)不同的失效判据对电迁移中值失效时间有影响,且其失效模式也会发生改变,本文通过采用不同失效判据并结合累计失效概率图的方法证明失效判据为电阻变化10%更符合电迁移失效机制。(2)残余应力随实验温度的下降而增大,使得激活能缓慢降低,本文通过二次多项式拟合的方法对激活能进行优化,激活能从300℃时的0.743eV降低到125℃时的0.553eV,用125℃下的激活能外推的寿命是300℃的18%。更多还原

【Abstract】 Nowadays,integrated circuits are closely related to our lives,and can be seen everywhere.They are at the core of medical,aerospace,military and other fields.Once the chip has problems,it will have unpredictable consequences.Therefore,the reliability of integrated circuits has always been concerned.With the rapid development of manufacturing technology,the feature size of the device is getting smaller and smaller,the integration is getting higher and higher,the number of layers of metal wiring is increasing,and the manufacturing process is becoming more and more complex.In particular,the interconnection material is replaced by copper instead of aluminum,and its process is also changing.This leads to new reliability problems,which have a significant impact on the characteristics and life of integrated circuits.Electromigration is one of the most serious reliability problems,and one of the more important model parameters in electromigration is activation energy.At present,there are relatively few studies on the optimization of Black model parameters at home and abroad.This thesis mainly studies the reliability of 65 nm copper interconnect system.Aiming at the influence of residual stress on model parameters and the optimization of model parameters,through the electromigration accelerated life test at different temperature points,the method of quadratic polynomial fitting is proposed to optimize the model parameters,so as to accurately evaluate the reliability of electromigration.Firstly,this thesis analyzes the reliability problem from the copper interconnection process.Based on the basic theory of electromigration,the driving mechanism of electromigration failure is analyzed,and the influence of residual stress on electromigration reliability is studied.The existence of residual stress is verified by Raman spectroscopy,and the characteristics of residual stress changing with temperature are confirmed.Secondly,the Kelvin test structure is designed according to the experimental purpose,and the electromigration accelerated life test at different temperature points is carried out.At the same time,two types of failure time data collected after the electromigration experiment are given.After the experiment,it was found that most of the test samples had multiple jumps in resistance,and the reason for the multiple jumps in resistance was proved by scanning electron microscopy.Finally,this thesis analyzes the failure results of electromigration test:(1)Different failure criteria have an effect on the median failure time of electromigration,and its failure mode will also change.In this thesis,by using different failure criteria and combining the cumulative failure probability diagram,it is proved that the failure criterion is10% resistance change,which is more in line with the electromigration failure mechanism.(2)The residual stress increases with the decrease of experimental temperature,which makes the activation energy decrease slowly.In this thesis,the activation energy is optimized by quadratic polynomial fitting method.The activation energy is reduced from 0.743 eV at300 °C to 0.553 eV at 125 °C.The life extrapolated by the activation energy at 125 °C is 18 %of that at 300 °C.更多还原