Interpreting IR Difference Spectra

Abstract

From the evaluation of sample difference spectra based on Gaussian model peaks with known peak characteristics, it is shown that interpretation of some parameters from difference spectra, resulting from the rationing or subtraction of a poor background spectra, may be inaccurate or misleading. Difference spectra of this type are commonly observed using techniques such as subtractively normalized interfacial Fourier transform infrared spectroscopy, SNIFTIRS, electrochemically modulated infrared reflectance spectroscopy, EMIRS, or similar infrared spectroelectrochemical techniques, as well as some microsample analyses, studies of biochemical processes, and infrared astronomical observations, to name just a few samples. A mathematical evaluation of the problem is offered to demonstrate what information may realistically be gained from the characteristics of difference spectra. It is shown that in the worst case, where frequency, intensity, and peak width are all changing due to some perturbation of the sample (e.g., from temperature, or surface potential changes between background and sample spectra, etc.), even a qualitative interpretation may not be possible. In many practical cases, however, we show that at least a qualitative interpretation of the data can be obtained from difference spectra. Spectroelectrochemical applications for the calculations shown here are presented as examples, although these results impact a wider range of applications.

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Document Details

Document Type
Technical Report
Publication Date
Sep 26, 1991
Accession Number
ADA241292

Entities

People

  • Diane B. Parry
  • Mahesh G. Samant
  • Owen R. Melroy

Organizations

  • International Business Machines Corporation (Armonk, NY)

Tags

DTIC Thesaurus Topics

  • Absorption
  • Absorption Spectra
  • Adsorbates
  • Chemical Reactions
  • Chemistry
  • Classification
  • Crossings
  • Electrodes
  • Frequency
  • Frequency Shift
  • Infrared Spectroscopy
  • Intensity
  • Military Research
  • Physical Properties
  • Security
  • Spectra
  • Spectroscopy

Readers

  • Computer Vision.
  • Electrochemical Engineering/ Fuel Cell Technologies
  • Theoretical Analysis.