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Quantitative Determination of Moisture in Lubricants by Fourier Transform Infrared Spectroscopy
Volume 58, Number 2 (Feb. 2004) Page 193-198
van de Voort, F.R.; Sedman, J.; Yaylayan, V.; Saint Laurent, C.; Mucciardi, C.
This paper describes the development of a practical Fourier transform infrared (FT-IR) method for the determination of moisture in lubricants through the combined use of signal transduction and differential spectroscopy to circumvent matrix effects. The acid-catalyzed stoichiometric reaction of 2,2-dimethoxypropane (DMP) with moisture to produce acetone was used to provide IR signals proportional to the amount of moisture present in oils. Calibration standards were prepared by spiking polyalphaolefin (PAO) gravimetrically with water using dioxane as a carrier. For FT-IR analysis, standards and samples were diluted with acidified isooctane and then split, with one aliquot treated with DMP and the other with a blank reagent. The spectra of the two aliquots were collected, and a differential spectrum was obtained so as to ratio out the invariant spectral contributions from the sample. Quantitation for moisture was based on measurement of the peak height of the ν(C = O) absorption of acetone at 1717 cm-1, yielding a standard error of calibration of ~40 ppm H2O. The method was validated by standard addition of water in dioxane to PAO containing added base as well as to new and used oils. In all cases the method responded quantitatively to standard addition, the average standard error of prediction being ~80 ppm, with the results showing only a minor dependence on the oil formulation. From an analytical perspective, the FT-IR method is both more reproducible and more accurate than Karl Fischer methods and has advantages in terms of environmental considerations, sample size, and speed of analysis as well as the variety of oil types that can be handled. Signal transduction/differential spectroscopy may have broader utility as an alternative means for the determination of low levels of moisture in complex matrices.