Comprehensive data analysis of femtosecond transient absorption spectra: A review

• Published in: Journal of photochemistry and photobiology. C, Photochemistry reviews Vol. 13; no. 1; pp. 1 - 27
• Main Authors: Ruckebusch, C., Sliwa, M., Pernot, P., de Juan, A., Tauler, R.
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.03.2012; Elsevier
• Subjects: Bayesian data analysis; Chemical Sciences; Chemometrics; Femtosecond time-resolved spectroscopy; Global analysis; Hard-modeling; Model-based; Model-free; Multivariate curve resolution; or physical chemistry; Photochemistry; Soft-modeling; Theoretical and; SVD; EFA; lof; SRA; iid; Global analysis; MCMC; Hard-modeling; MCR-WALS; femto-TA; DA(D)S; LDM; Multivariate curve resolution; MCR-ALS; BIC; CA; Model-based; Photochemistry; ΔA; Femtosecond time-resolved spectroscopy; Bayesian data analysis; pdf; Model-free; GVD; GTA; Soft-modeling; DAS; LDAC; IRF; GLA; MAP; MCR; SA(D)S; BDA; HS-MCR; Chemometrics
• ISSN: 1389-5567; 1873-2739
• DOI: 10.1016/j.jphotochemrev.2011.10.002

► We present novel advanced data analysis for ultrafast spectroscopy. ► We review methods that are used in practice. ► We describe model-based methods and soft-modeling methods. ► We show how multivariate curve resolution can be applied. ► We demonstrate the potential and advantage of Bayesian data analysis. 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.