首页> 外文会议>IEEE International Symposium on Physical and Failure Analysis of Integrated Circuits >Defect Density Reduction of Thin SiO2 MOSFET through Oxidation Pre-cleaning improvement – a Fast Wafer Level Reliability Monitoring
【24h】

Defect Density Reduction of Thin SiO2 MOSFET through Oxidation Pre-cleaning improvement – a Fast Wafer Level Reliability Monitoring

机译:通过氧化预清洁改进来降低薄SiO2 MOSFET的缺陷密度-快速晶圆级可靠性监控

获取原文

摘要

We conducted experiment to reduce the level defect density in 7.5nm thin SiO2 CMOS by improving the pre-cleaning of silicon surface before gate oxidation. Fast wafer level reliability monitoring is implemented using ramped voltage stress (RVS) where from the breakdown Weibull chart, the inclination point of intrinsic and extrinsic will give the measurement of defect density (unit is number of defect per cm2). We measured high defect density of >20 times the defect density target. Through systematic problem solving methodology, root cause was found to be due to ineffective cleaning method. With the additional SPM cleaning in the gate oxidation pre-clean step, defect density reduced by almost 95%. SPM chemistry reduces the surface roughness and also improves contaminations removal on the wafer surface prior to gate oxidation. Rougher interface of Si-SiO2 leads to early failure and lower TDDB. Inline silicon surface roughness check is not practical due to very small nature of embedded-type contaminants a rough silicon surface creates. In order to increase detection probability of micro-sized particles, a good reliability monitoring strategy using special test structures is implemented.
机译:我们进行了实验,通过改善栅极氧化之前对硅表面的预清洁来降低7.5nm薄SiO2 CMOS中的能级缺陷密度。使用倾斜电压应力(RVS)来实现快速晶圆级可靠性监控,其中从击穿威布尔图中,本征和非本征的倾斜点将提供缺陷密度的度量(单位是每cm2的缺陷数)。我们测得的高缺陷密度大于目标缺陷密度的20倍。通过系统的问题解决方法,发现根本原因是无效的清洁方法。在栅极氧化预清洁步骤中进行额外的SPM清洁后,缺陷密度降低了近95%。 SPM化学物质可降低表面粗糙度,并改善栅极氧化之前晶片表面上的污染物去除。 Si-SiO2的界面较粗糙会导致早期失效和TDDB降低。在线硅表面粗糙度检查不可行,原因是粗糙的硅表面产生的嵌入型污染物的性质很小。为了增加检测微小颗粒的可能性,采用了特殊的测试结构,实现了良好的可靠性监测策略。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号