a-Si Pinhole Detection and Characterization using Haze Monitoring : CFM: Contamination Free Manufacturing

Asli Sirman, Fuad H. Al-amoody, Chandar Palamadai, B. Saville, Ankit Jain, Kha X. Tran
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引用次数: 1

Abstract

This paper describes a novel methodology for identifying pinholes (defects in thin films) in an amorphous silicon (a-Si) film using a KLA Surfscan® SP5 laser scattering-based unpatterned wafer inspection system. Inherent to the deposition mechanism, pinholes exist at the interface between a-Si/substrate. It is crucial to find the optimized film thickness that is free of pinholes. In this study we developed a unique process monitoring method adapted to quantify pinhole defects using surface haze. Haze is the background scattering signal of the wafer obtained from the inspection system [1] and the defect signal from scanning electron microscope (SEM) images from an eDR® e-beam defect review system. A macro program was developed to automatically process the SEM images and quantify the defect signal. A strong correlation between haze and a-Si pinhole count was observed. The method can be extended to different films including SiN, TiN and similar scenarios, where unconventional defect detection methods are needed.
利用雾霾监测的a-Si针孔检测和表征:CFM:无污染制造
本文描述了一种使用KLA Surfscan®SP5激光散射无图像化晶圆检测系统识别非晶硅(a- si)薄膜中针孔(薄膜缺陷)的新方法。由于沉积机制,针孔存在于a-Si/衬底之间的界面上。找到无针孔的最佳膜厚是至关重要的。在这项研究中,我们开发了一种独特的过程监测方法,适用于利用表面雾度来量化针孔缺陷。雾度是检测系统获得的晶圆片背景散射信号[1]和eDR®电子束缺陷评审系统扫描电镜(SEM)图像的缺陷信号。开发了一个宏程序,对扫描电镜图像进行自动处理,并对缺陷信号进行量化。雾霾与A - si针孔数有很强的相关性。该方法可以扩展到不同的薄膜,包括SiN, TiN和类似的场景,在这些场景中需要非常规的缺陷检测方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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