Curve Fitting and Fourier Self-Deconvolution for the Quantitative Representation of Complex Spectra

  • Peter R. Griffiths
  • John A. Pierce
  • Gao Hongjin
Part of the Modern Analytical Chemistry book series (MOAC)


Most techniques for multicomponent analysis require spectral features due to each component to be distinguished in some manner. Many of these methods are based on minimizing the standard deviation between the measured spectrum and a synthetic spectrum. The latter spectrum may be synthesized from a linear combination of spectra of mixtures of known composition, as it is in whole spectrum curve-fitting techniques(1,2) or the K-matrix method,(3) or it may be completely synthetic, i.e., generated from the combination of N bands of known shape with different center wave numbers, v̄ i 0 , peak absorbances, A i , and widths, γ i .(4,5) (In this chapter γ will be defined as the full width at half-height.) The greater the dissimilarity of the spectra of each component, the more accurately may least-squares techniques be applied. Conversely, when absorption bands are located so close together that all spectral features are completely unresolved, least-squares methods tend to break down.


Derivative Spectrum Synthetic Spectrum Component Band Deconvolved Spectrum Derivative Spectrometry 
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  1. 1.
    P. C. Painter, S. M. Rimmer, R. W. Snyder and A. Davis, Appl. Spectrosc. 35, 102 (1981).CrossRefGoogle Scholar
  2. 2.
    M. K. Antoon, J. H. Koenig and J. L. Koenig, Appl. Spectrosc. 31, 518 (1977).CrossRefGoogle Scholar
  3. 3.
    D. M. Haaland and R. G. Easterling, Appl. Spectrosc. 36, 665 (1982).CrossRefGoogle Scholar
  4. 4.
    P. C. Painter, R. W. Snyder, M. Starsinic, M. M. Coleman, D. W. Kuehn and A. Davis, Appl. Spectrosc. 35, 475 (1981).CrossRefGoogle Scholar
  5. 5.
    J. T. Seuftle, D. Kuehn, A. Davis, B. Brozoski, C. Rhoads and P. C. Painter, Fuel 63, 245 (1984).CrossRefGoogle Scholar
  6. 6.
    S. H. Wang and P. R. Griffiths, Fuel 64, 229 (1985).CrossRefGoogle Scholar
  7. 7.
    C. A. Rhoads, J. T. Seuftle, M. M. Coleman, A. Davis and P. C. Painter, Fuel 62, 1387 (1983).CrossRefGoogle Scholar
  8. 8.
    M. Starsinic, Y. Otake, P. L. Walker Jr. and P. C. Painter, Fuel 62, 1387 (1983).CrossRefGoogle Scholar
  9. 9.
    W. I. Maddams, Appl. Spectrosc. 34, 245 (1980).CrossRefGoogle Scholar
  10. 10.
    J. K. Kauppinen, D. J. Moffatt, H. H. Mantsch and D. G. Cameron, Appl. Spectrosc. 35, 271 (1981).CrossRefGoogle Scholar
  11. 11.
    J. K. Kauppinen, D. J. Moffatt, D. G. Cameron and H. H. Mantsch, Appl. Opt. 20, 1866 (1981).CrossRefGoogle Scholar
  12. 12.
    R. D. B. Fraser and E. Suzuki, Anal. Chem. 38, 1770 (1966).CrossRefGoogle Scholar
  13. 13.
    R. D. B. Fraser and E. Suzuki, Anal. Chem. 41, 37 (1969).CrossRefGoogle Scholar
  14. 14.
    R. J. Noll and A. Pines, AppL Spectrosc. 34, 351 (1980).CrossRefGoogle Scholar
  15. 15.
    J. F. Kielkopf, J. Opt. Soc. Am. 63, 987 (1973).CrossRefGoogle Scholar
  16. 16.
    A. Klim, J. Quant. Spectrosc. Radiat. Trans. 26, 537 (1981).CrossRefGoogle Scholar
  17. 17.
    D. G. Cameron, J. K. Kauppinen, D. J. Moffatt and H. H. Mantsch, Appl. Spectrosc. 36, 245 (1982).CrossRefGoogle Scholar
  18. 18.
    J. A. Pierce, K. Van Every, P. R. Griffiths and G. Hongjin, Anal. Chem., submitted (1987).Google Scholar
  19. 19.
    P. C. Painter, M. Starsinic, E. Squires and A. A. Davis, Fuel 62, 742 (1983).CrossRefGoogle Scholar

Copyright information

© Plenum Press, New York 1987

Authors and Affiliations

  • Peter R. Griffiths
    • 1
  • John A. Pierce
    • 1
  • Gao Hongjin
    • 2
  1. 1.Department of ChemistryUniversity of CaliforniaRiversideUSA
  2. 2.Department of Chemistry and Chemical EngineeringTsinghua UniversityBeijingPeoples’ Republic of China

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