识别和验证硅衬底中不可见缺陷的系统方法

Hongwei Huang, Winnie Wei, J. J. Xin, Candy Liu, Luke Wu, Clieve Dai, Pinglung Liao, Wei Xu
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引用次数: 0

摘要

对于失效分析,大多数缺陷是可见的成像工具,如OM, SEM, FIB, TEM等。然而,仍然有许多不可见的缺陷不能被这些工具捕获。由于这种不可见缺陷失效分析的复杂性非常高,故障分析工程师常常困惑于从何入手。本文给出了两个这样的例子,并给出了解决方案。这些案例的系统方法包括电气数据挖掘,头脑风暴或鱼骨图法列出所有故障可能性,然后使用适当的表征工具或方法来识别和验证假设。最后采用DOE (design of experiments)验证了根本原因。结果发现,磷污染导致嵌入式Flash产品的MOS阈值电压偏移问题,而Power MOS产品源的衬底氧浓度较高导致击穿电压低问题。
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Systematic methods to identify and verify non-visible defects in silicon substrate
For failure analysis, most of defects are visible to imaging tools, such as OM, SEM, FIB, TEM etc. However, there are still lots of non-visible defects which cannot be caught by these tools. As complexity for such non-visible defect failure analysis is much high, FA engineers were often puzzled where to begin from. Two such cases were presented in this paper with solutions. The systematic methods for these cases include electrical data mining, brainstorming or fish-bone diagram method to list all failure possibilities, and then proper characterization tools or methods were used to identify and verify the hypotheses. Finally DOE (design of experiments) was used to verify the root cause. As a result, phosphorus contamination was found for embedded Flash products' MOS threshold voltage shift issue, and higher substrate oxygen concentration for Power MOS products source to drain low breakdown voltage issue.
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