Literature DB >> 34357495

Do Spectra Live in the Matrix? A Brief Tutorial on Applications of Factor Analysis to Resolving Spectral Datasets of Mixtures.

Andrzej J Kałka1, Andrzej M Turek2.   

Abstract

In spite of a rapid growth of data processing software, that has allowed for a huge advancement in many fields of chemistry, some research issues still remain problematic. A standard example of a troublesome challenge is the analysis of multi-component mixtures. The classical approach to such a problem consists of separating each component from a sample and performing individual measurements. The advent of computers, however, gave rise to a relatively new domain of data processing - chemometry - focused on decomposing signal recorded for the sample rather than the sample itself. Regrettably, still a very few chemometric methods are practically used in everyday laboratory routines. The Authors believe that a brief 'user-friendly' guide-like article on several 'flagship' algorithms of chemometrics may, at least partly, stimulate an increased interest in the use of these techniques among researchers specializing in many fields of chemistry. In the paper, five different techniques of factor analysis are used for the analysis of a three-component system of fluorophores. These algorithms, applied on the excitation-emission spectra, recorded for the 'unknown' mixture, allowed to unambiguously determine its composition without the need for physical separation of the components. An example of using chemometric methods for physical chemistry research is also provided. For each presented technique of the data analysis, a short description of its theoretical background followed by an example of its practical performance is given. In addition, the Reader is supplemented with a basic information on matrix algebra, detailed experimental 'recipes', reference specialist literature and ready-to-use MATLAB codes.
© 2021. The Author(s).

Keywords:  Evolving factor analysis; Excitation-emission maps; Fluorescence quenching; Multivariate curve resolution; Rank annihilation factor analysis; Spectral data matrices of mixtures

Year:  2021        PMID: 34357495     DOI: 10.1007/s10895-021-02753-w

Source DB:  PubMed          Journal:  J Fluoresc        ISSN: 1053-0509            Impact factor:   2.217


  8 in total

1.  Calculation of equilibrium constants from multiwavelength spectroscopic data-I Mathematical considerations.

Authors:  H Gampp; M Maeder; C J Meyer; A D Zuberbühler
Journal:  Talanta       Date:  1985-02       Impact factor: 6.057

2.  Calculation of equilibrium constants from multiwavelength spectroscopic data-III Model-free analysis of spectrophotometric and ESR titrations.

Authors:  H Gampp; M Maeder; C J Meyer; A D Zuberbühler
Journal:  Talanta       Date:  1985-12       Impact factor: 6.057

3.  Rank annihilation factor analysis method for spectrophotometric study of second-order reaction kinetics.

Authors:  Hamid Abdollahi; Azadeh Golshan
Journal:  Anal Chim Acta       Date:  2011-03-17       Impact factor: 6.558

4.  The Parallel Factor Analysis of Beer Fluorescence.

Authors:  Tatjana Dramićanin; Ivana Zeković; Jovana Periša; Miroslav D Dramićanin
Journal:  J Fluoresc       Date:  2019-08-08       Impact factor: 2.217

5.  Processing Excitation-Emission Matrix Fluorescence and Total Synchronous Fluorescence Spectroscopy Data Sets with Constraint Randomised Non-negative Factor Analysis: a Novel Fluorescence Based Analytical Procedure to Analyse the Multifluorophoric Mixtures.

Authors:  Keshav Kumar
Journal:  J Fluoresc       Date:  2018-08-20       Impact factor: 2.217

6.  Non-negative Factor (NNF) Assisted Partial Least Square (PLS) Analysis of Excitation-Emission Matrix Fluorescence Spectroscopic Data Sets: Automating the Identification and Quantification of Multifluorophoric Mixtures.

Authors:  Keshav Kumar
Journal:  J Fluoresc       Date:  2019-09-10       Impact factor: 2.217

7.  Application of Partial Least Square (PLS) Analysis on Fluorescence Data of 8-Anilinonaphthalene-1-Sulfonic Acid, a Polarity Dye, for Monitoring Water Adulteration in Ethanol Fuel.

Authors:  Keshav Kumar; Ashok Kumar Mishra
Journal:  J Fluoresc       Date:  2015-06-24       Impact factor: 2.217

8.  Fast Decomposition of Three-Component Spectra of Fluorescence Quenching by White and Grey Methods of Data Modeling.

Authors:  Andrzej J Kałka; Andrzej M Turek
Journal:  J Fluoresc       Date:  2018-04-03       Impact factor: 2.217

  8 in total

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