一种对缺陷进行软材料光谱分析的方法

G. Kumar, Lakshmi N. Pedapudi, A. Chaudhari, Shashank S. Agashe, Taehyoung Lee, C. Park
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引用次数: 0

摘要

用物质光谱法(MS)鉴定微颗粒的元素组成。能量色散x射线光谱学(EDX或EDS)就是这样一种方法。对晶圆检测中发现的缺陷进行EDX分析有助于进行根本原因分析(RCA)。然而,由于EDX的处理时间长,它只适用于少数选定的缺陷。晶圆片通常包含约100个缺陷。EDX的缺陷覆盖率约为1%[1],因此在正确诊断和RCA方面存在相当大的差距。为了克服这个问题,我们演示了一种软方法来执行缺陷的质谱。与EDX对相同缺陷的预测结果相比,该方法能准确预测缺陷和背景的元素组成(~80%F1)。该方法快速,可以将MS的缺陷覆盖率提高到100%,这可以显著提高RCA,从而有助于良率提高(YE)。计算准确的YE是复杂的,因为它涉及许多隐藏的和不可追踪的因素。我们对更有形的因素进行了理论上的高水平建模,即Fab每月的盈利能力与YE成正比,理论上使用我们的软质谱方法显示14.6%的改进。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Method to Perform Soft Material Spectroscopy of a Defect
Material spectroscopy (MS) is used to identify elemental composition of micro particles. Energy dispersive X-Ray spectroscopy (EDX or EDS) is one such method. EDX analysis of defects found during wafer inspection aids in performing their root cause analysis (RCA). However, due to large processing time of EDX, it is applied very judiciously on a few chosen defects only. A wafer can typically contain ~100s of defects. The defect coverage of EDX is ~1% [1] thereby resulting in considerable gap in proper diagnosis and RCA. To overcome this issue, we demonstrate a soft method to perform MS of defects. The method predicts accurate elemental compositions of defect and background (~80%F1) when compared with EDX predictions on the same defect. The method is fast and could increase defect coverage for MS to ~100%• This can significantly improve RCA and thus help in Yield Enhancement (YE). Computing exact YE is complex as it involves many hidden and un-trackable factors. We perform theoretical high level modelling of more tangible factors i.e. profitability per month of Fab which is directly proportional to YE and theoretically show 14.6% improvement using our soft MS method.
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