Automated data mining of secondary ion mass spectrometry spectra

被引：8

作者：

Tuccitto, Nunzio ^{[1
,2
]}

机构：

[1] Univ Catania, Dept Chem Sci, Catania, Italy

[2] CSGI, Catania, Italy

来源：

JOURNAL OF CHEMOMETRICS | 2018年 / 32卷 / 03期

关键词：

PCA; Polymeric Surfaces; Surface Analysis; ToF-SIMS; Wavelet; MULTIVARIATE STATISTICAL-ANALYSIS; TOF-SIMS DATA; SURFACES; IMAGES; GOLD;

D O I：

10.1002/cem.2968

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Time of flight secondary ion mass spectrometry (ToF-SIMS) allows the reliable analytical determination of organic and polymeric materials. Since a typical raw data may contain thousands of peaks, the amount of information to deal with is accordingly large, so that data reduction techniques become indispensable for extracting the most significant information from the given dataset. Here, the use of the wavelet-principal component analysis-based signal processing of giant raw data acquired during ToF-SIMS experiments is presented. The proposed procedure provides a straightforwardly manageable dataset without any binning procedure neither detailed integration. By studying the principal component analysis results, detailed and reliable information about the chemical composition of polymeric samples have been gathered.

引用

页数：7

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