Literature DB >> 19281652

Near-infrared spectroscopy as a useful tool for analysis in solution in common organic solvents.

Reikichi Iwamoto1.   

Abstract

In the present paper we report that near-infrared spectroscopy is a useful tool for analyzing solutes in solution in common organic solvents. This is because the near-infrared absorptions of the solvent are not so strong as to disturb the separation of the characteristic near-infrared bands, by subtraction, of the solute. To demonstrate this capability, we first showed that the near-infrared absorptions of heptane and toluene, each of which represents aliphatic or aromatic solvents, do not significantly affect the noise level of the difference spectrum, in which the near-infrared spectrum of a solute is to be separated by subtraction. Second, we showed that the characteristic near-infrared absorptions of 1-heptene as a solute were well separated from the spectrum of the solution in heptane and toluene. Four of the five indicator bands of 1-heptene were recognizable and sufficiently detected at the almost limiting concentration of 0.1% (v/v) in both solvents. The minimum magnitude of the detectable signal is discussed in terms of the signal-to-noise ratios of the indicator bands. As an application, we investigated the interaction properties of a C identical with CH group of 1-heptyne from the CH stretching fundamental, combination, and overtone bands in the pure liquid and in solution in three solvents at various concentrations.

Entities:  

Year:  2009        PMID: 19281652     DOI: 10.1366/000370209787598942

Source DB:  PubMed          Journal:  Appl Spectrosc        ISSN: 0003-7028            Impact factor:   2.388


  2 in total

Review 1.  Breakthrough Potential in Near-Infrared Spectroscopy: Spectra Simulation. A Review of Recent Developments.

Authors:  Krzysztof B Beć; Christian W Huck
Journal:  Front Chem       Date:  2019-02-22       Impact factor: 5.221

2.  Theoretical Simulation of Near-Infrared Spectrum of Piperine: Insight into Band Origins and the Features of Regression Models.

Authors:  Justyna Grabska; Krzysztof B Beć; Sophia Mayr; Christian W Huck
Journal:  Appl Spectrosc       Date:  2021-07-08       Impact factor: 3.588

  2 in total

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