Comprehensive data analysis of femtosecond transient absorption spectra: A review

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• 作者：C. Ruckebusch^a  ; [Author Vitae] ; M. Sliwa^a ; ^{michel.sliwa@univ-lille1.fr}  ; [Author Vitae] ; P. Pernot^b  ; [Author Vitae] ; A. de Juan^c  ; [Author Vitae] ; R. Tauler^d  ; [Author Vitae]
• 关键词：BDA ; Bayesian Data Analysis ; BIC ; Bayesian Information Criterion ; CA ; Coherent Artifact ; DAS ; Decay Associated Spectra ; DA(D)S ; Decay Associated (Difference) Spectra ; 螖A ; Difference Absorbance ; EFA ; Evolving Factor Analysis ; femto-TA ; Femtosecond Transie
• 刊名：Journal of Photochemistry and Photobiology ; C ; Photochemistry Reviews
• 出版年：2012
• 期刊代码：68_13895567
• 类别：ch
• 出版时间：March, 2012
• 卷：13
• 期：1
• 页码：1-27
• 文件大小：4789 K

摘要

Nowadays, time-resolved spectroscopy data can be routinely and accurately collected in UV-vis femtosecond transient absorption spectroscopy. However, the data analysis strategy and the postulation of a physically valid model for this kind of measurements may be tackled with many different approaches ranging from pure soft-modeling (model-free) to hard-modeling, where the elaboration of a parametric spectro-temporal model may be required. This paper reviews methods that are used in practice for the analysis of femtosecond transient absorption spectroscopy data. Model-based methods, common in photochemistry, are revisited, and soft-modeling methods, which originate from the chemometrics field and that recently disseminated in the photo(bio)chemistry literature, are presented. These soft-modeling methods are designed to suit the intrinsic nature of the multivariate (or multi-way) measurement. Soft-modeling tools do not require a priori physical or mechanistic models to provide a decomposition of the data on the time and wavelength dimensions, the only requirement being that these two (or more) dimensions are separable. Additionally, Bayesian data analysis, which provides a probabilistic framework for data analysis, is considered in detail, since it allows uncertainty quantification and validation of the model selection step.