https://physique.cuso.ch/fileadmin/physique/document/2005_vanStokkum_lecturenotes.pdf

Global and target analysis of time-resolved spectra

Window factor analysis (WFA) is a self-modeling method for extracting the concentration profiles of individual components from evolutionary processes such as flow injection, chromatography, titrations and reaction kinetics. The method takes advantage of the fact that each component lies in a specific region along the evolutionary axis, called the window. Theoretical equations are derived. The method is used to extract the concentration profiles and spectra of seven bismuth species from data obtained by Gemperline and Hamilton, who injected bismuth perchlorate into a flowing stream of hydrochloric acid.

Window factor analysis: Theoretical derivation and application to flow injection analysis data

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.

Comprehensive data analysis of femtosecond transient absorption spectra: A review

Apparatus and methods are provided for rapid and sensitive quantitative analysis of a sample’s fluorescence decay properties. A repetitively pulsed excitation light source generates pulsed fluorescence in the sample. A fluorescence wavelength selector receives a portion of the pulsed fluorescence emanating from the sample and outputs fluorescence photons whose wavelengths lie within a specified wavelength range. A photodetector receives the fluorescence photons within the specified wavelength range as an input from the fluorescence wavelength selector and outputs a time-dependent electrical signal. An array of memory element stores a representation of the time-dependent electrical signal as a time-series of analog voltages or charges. Successive elements in the array correspond to a time increment of no greater than 4 ns. An analog-to-digital converter transforms the time-series of analog voltages or charges into a corresponding digitized fluorescence waveform.

Multi-dimensional fluorescence apparatus and method for rapid and highly sensitive quantitative analysis of mixtures

Advanced data analysis methods suitable for the analysis of kinetic spectroscopic data from complex chemical and biological systems are defined and reviewed. The aim of this chapter is on the one hand to introduce beginners dealing with complex data analysis problems into the matter. On the other hand it is intended as a relatively simple description, using only a minimum of mathematics, that should enable non-specialist readers from other fields to better understand the methods currently used to deal with complex kinetic problems. The first part introduces the basic concepts and terms by using a simple kinetic scheme as an example. The fundamentally different concepts of “mathematical data fitting” and “physical model testing” are defined and illustrated with some examples. Their capabilities and limitations are then discussed in detail. Further subsections deal with the mathematical optimization procedures, proper weighting of data points, and the importance of performing an error analysis. As a first-hand illustration to the use of these methods in current research problems somerecent applications in the field of photosynthesis research are given.

F. J. Knorr

Papers

Resolution of multicomponent fluorescence spectra by an emission wavelength-decay time data matrix