Infrared Absorption Spectroscopy

Barber, Tye E.; Ayala, N.L.; Storey, John; Powell, G.L.; Brosey, W.D.; Smyrl, N.R.

doi:10.1002/0471473332.ch5

Cited by 2 publications

(2 citation statements)

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“…Both MIMS and FTIR methods are widely used for various industrial and environmental applications. 2,[4][5][6][7][8][9][10][11] Different approaches have been taken in order to differentiate between various samples or structurally similar compounds from IR data. For example, Elliott et al 12 used various chemometric approaches, such as principal component analysis (PCA), discriminant function analysis (DFA), and multiple linear regression (MLR) for differentiation of soil classes by their FTIR spectra.…”

Section: Introductionmentioning

confidence: 99%

“…But, quantitation of structurally similar compounds such as alkanes is difficult or even impossible from a multicomponent spectrum as it gets more difficult to find specific IR absorption bands for each individual compound. Both MIMS and FTIR methods are widely used for various industrial and environmental applications. ,− Different approaches have been taken in order to differentiate between various samples or structurally similar compounds from IR data. For example, Elliott et al used various chemometric approaches, such as principal component analysis (PCA), discriminant function analysis (DFA), and multiple linear regression (MLR) for differentiation of soil classes by their FTIR spectra.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Evaluation of Mathematical Algorithm for Solving of Fourier Transform Infrared Spectroscopic and Mass Spectra

Ketola¹,

Tarkiainen²,

Kiuru³

et al. 2008

Ind. Eng. Chem. Res.

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The aim of this study was to evaluate the benefits of the simultaneous use of two different analytical methods, namely Fourier transform infrared spectroscopy (FTIR) and mass spectrometry (MS), for online analysis of environmental and process samples. A mathematical method (NALMS) that identifies and quantifies all single components from a single multicomponent spectrum was previously developed for MS, and in this study, the same method, named as SPECTACS, was adopted for solving also an FTIR spectrum and a combined FTIR-MS spectrum. The performance of SPECTACS was evaluated by analyzing various gaseous samples, as case studies, containing volatile organic compounds, and the performance was compared with other methods, which are used to identify and quantitate organic compounds from multicomponent spectra. The results obtained show that SPECTACS with optimized noise reduction and solving a combined FTIR-MS spectrum can increase the reliability of identifying components in a single spectrum and also the accuracy in quantitative measurements when compared to the analysis with one analytical technique alone. The reasons for this improvement is evaluated and discussed in detail.

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