Information from complexity: Challenges of TOF-SIMS data interpretation
Information from complexity: Challenges of TOF-SIMS data interpretation
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DOI：
10.1016/j.apsusc.2006.02.149
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发表时间：
2006-07-30
影响因子：
6.7
通讯作者：
Castner, David G.
中科院分区：
文献类型：
--
作者：
Graham, Daniel J.;Wagner, Matthew S.;Castner, David G.
飞行时间二次离子质谱（TOF-SIMS）数据很复杂，即使对于最简单的系统也是如此。然而，正是在这种复杂性中，关于样品组成、分子取向、表面有序、化学键合、样品纯度等的信息，被控制住了挑战在于如何轻松地从光谱和图像中提取这些信息。多变量分析（MVA）在驯服TOF-SIMS数据所带来的复杂性挑战方面表现出了希望，同时使用了整个频谱中的所有信息。最近的成功MVA方法，如主成分分析（PCA）和偏最小二乘法（PLS）在有机和生物材料的光谱和成像分析，导致了极大的增加，在MVA处理的TOF-SIMS数据的兴趣。然而，仍然需要更好地理解使用什么数据来回答给定的问题，如何在应用MVA之前最佳地处理数据，以及如何正确地解释MVA结果。TOF-SIMS数据解释的挑战只会变得更加复杂，特别是对于生物样品，进一步增加了对控制良好的MVA方法的需求。(c)2006 Elsevier B. V.保留所有权利。
Time-of-flight secondary ion mass spectrometry (TOF-SIMS) data are complex, even for the simplest systems. Yet it is within this complexity that information about sample composition, molecular orientation, surface order, chemical bonding, sample purity, etc., is contained. The challenge is how to easily extract this information from the spectra and images. Multivariate analysis (MVA) has shown promise in taming the complexity challenges presented by TOF-SIMS data while using all the information in the entire spectrum. The recent success of MVA methods such as principal component analysis (PCA) and partial least squares (PLS) in the spectroscopic and imaging analysis of organic and biological materials has led to a great increase in the interest of MVA processing of TOF-SIMS data. However, there is still a need to better understand what data to use to answer a given question, how to optimally process the data before applying MVA, and how to correctly interpret the MVA results. The challenges of TOF-SIMS data interpretation will only get more complex, especially for biological samples, further increasing the need for well-controlled MVA methodologies. (c) 2006 Elsevier B.V. All rights reserved.