Principal Component Analysis (PCA) of Surface Contamination by TOF-SIMS

被引：2

作者：

Sek, Kei Lin ^{[1
]}

Lee, Pei Lin ^{[1
]}

Pang, Khin Yin ^{[1
]}

Hua, Younan ^{[1
]}

Zhu, Lei ^{[1
]}

Li, Xiaomin ^{[1
]}

机构：

[1] WinTech Nanotechnol Serv Pte Ltd, Surface & Chem Anal Div, 10 Sci Pk Rd 03-26,Sci Pk 2, Singapore 117684, Singapore

来源：

2021 IEEE INTERNATIONAL SYMPOSIUM ON THE PHYSICAL AND FAILURE ANALYSIS OF INTEGRATED CIRCUITS (IPFA) | 2021年

关键词：

TOF-SIMS; Imaging PCA; contamination;

D O I：

10.1109/IPFA53173.2021.9617378

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Static time of flight secondary ions mass spectrometry (TOF-SIMS) is a qualitative analysis technique with a high detection limit capable of achieving parts per million (ppm) levels [1] and sub monolayer surface detection. Due to its high sensitivity, the data obtained may contains more than hundreds of peaks including information about sample composition, chemical compound, fragments ions, sample purity, and etc. [2]. Therefore, TOF-SIMS data interpretation is complicated and time consuming especially for unknown contamination. These challenges could be overcome by Principal Component Analysis (PCA). PCA is one of a multivariate method used to identify mass peak spectral in various principal component loadings when processing large data sets such as TOF-SIMS data. This paper presents a study of surface contamination analysis using image based PCA to find out the parent ion of the contaminant.

引用

页数：4

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