Applied Magnetic Resonance

, 22:335 | Cite as

Correction of biased time domain NMR estimates of the solid content of partially crystallized systems

  • M. Kané
  • M. Djabourov
  • J. -L. Volle
  • D. N. Rutledge


The solid content values obtained from the intensity of the nuclear magnetic resonance free induction decay signal of partially crystallized samples such as fats, supersaturated solutions, solid dispersions of waxes, gels are biased due to the difference between the proton density and mass density of the samples. It is shown here that this can be easily corrected with the specific volumes (determined gravimetrically) and proton densities (determined by time-domain nuclear magnetic resonance) of completely liquefied models of the solid and liquid phases and provided that the total amount of crystallizable material is known. The corrected data are in excellent agreement with the values obtained by differential scanning calorimetry for both model systems and real petroleum samples.


Differential Scanning Calorimetry Solid Content Solid Dispersion Proton Density Free Induction Decay 
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  1. 1.
    Dirand M., Chevallier V., Provost E., Boutroukba M., Petijean D.: Fuel77, 1253–1260 (1998)CrossRefGoogle Scholar
  2. 2.
    Gribnau M.C.M.: Trends Food Sci. Technol.3, 186–190 (1992)CrossRefGoogle Scholar
  3. 3.
    Rutledge, D.N.: Analusis Mag.20, 58–62 (1992)Google Scholar
  4. 4.
    Pedersen W.B., Hansen A.B., Larsen E., Nielsen A.B.: Energy Fuels5, 908–913 (1991)CrossRefGoogle Scholar
  5. 5.
    Ruffier-Meray V., Roussel J.-C., Défontaines A.-D.: Rev. Inst. Fr. Pét.53, 531–535 (1998)Google Scholar
  6. 6.
    Lourens J.A.J., Reynhardt E.C.: J. Phys. D.: Appl. Phys.12, 1963–1972 (1979)CrossRefADSGoogle Scholar
  7. 7.
    Reynhardt E.C.: J. Phys. D.: Appl. Phys.18, 1185–1197 (1985)CrossRefADSGoogle Scholar
  8. 8.
    Araujo M., Hunger M., Martin R.: Fuel68, 1079–1081 (1989)CrossRefGoogle Scholar
  9. 9.
    Létoffé J.M., Claudy P., Garcin M., Volle J.L.: Fuel74, 92–95 (1995).CrossRefGoogle Scholar
  10. 10.
    Létoffé J.M., Claudy P., Kok M.V., Garcin M., Volle J.L.: Fuel74, 810–817 (1995)CrossRefGoogle Scholar
  11. 11.
    Van Putte K., Vermaas L., Van Den Enden J., Den Hollander C.: J. Am. Oil Chem. Soc.52, 179–181 (1975)CrossRefGoogle Scholar
  12. 12.
    Templeman G.J., Sholl J.J., Labuza T.P.: J. Food Sci.42 (2), 432–435 (1977)CrossRefGoogle Scholar
  13. 13.
    Desarzens C., Besson A., Bouldoires J.-P.: Rev. Franç. Corps Gras4, 183–186 (1978)Google Scholar
  14. 14.
    Leung H.K., Anderson G.R., Norr P.J.: J. Food Sci.50, 942–945 (1985)CrossRefGoogle Scholar
  15. 15.
    I.U.P.A.C. Standard Methods for the Analysis of Oils, Fats and Derivatives, 6th edn., 1st Supplement, Part 6. Oxford: Pergamon Press 1982.Google Scholar
  16. 16.
    Rutledge D.N., Diris, J., Bugner E., Belliardo J.-J.: Fresenius J. Anal. Chem.338, 441–448 (1990)CrossRefGoogle Scholar

Copyright information

© Springer 2002

Authors and Affiliations

  • M. Kané
    • 1
  • M. Djabourov
    • 1
  • J. -L. Volle
    • 2
  • D. N. Rutledge
    • 3
  1. 1.Laboratoire de Physique ThermiqueEcole Supérieure de Physique et Chimie IndustriellesParisFrance
  2. 2.Elf Exploration Production Centre Scientifique et Technique Jean FegerPau CedexFrance
  3. 3.Laboratoire de Chimie AnalytiqueInstitut National Agronomique Paris-GrignonParisFrance

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