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The Use of Fourier Self-Deconvolution to Resolve Overlapping X-Ray Powder Diffraction Peaks

Published online by Cambridge University Press:  10 January 2013

Ernest E. Armstrong  and
David G. Cameron
Ernest E. Armstrong
Affiliation:
BP America Research and Development, 4440 Warrensville Center Road, Cleveland, Ohio 44128, U.S.A.
David G. Cameron
Affiliation:
BP America Research and Development, 4440 Warrensville Center Road, Cleveland, Ohio 44128, U.S.A.
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Abstract

Fourier self-deconvolution has been successfully applied as a means of obtaining semi-quantitative information by resolving the overlapping peaks in X-ray powder diffractograms collected from mixtures of kaolinite and ripidolite. A series of diffractograms were collected from known mixtures of the two minerals. The diffractograms were then processed using Fourier self-deconvolution over a selected range between 23 and 27° 2θ (encompassing the overlapping peaks of kaolinite (002) and ripidolite (004) at 24.85 and 25.13° 2θ, respectively). Once deconvoluted, areas under individual peaks of kaolinite and ripidolite were calculated using curve fitting. The calculated percentage of kaolinite in the mixtures was then plotted versus the true weight percent of kaolinite. The same procedure was conducted on the original diffractograms using only curve fitting without first deconvoluting. A comparison of results shows that, provided the number of peaks are known, both methods give nearly equal results. However, Fourier self-deconvolution, by increasing the resolution, greatly improves the ability to detect overlapping peaks.

Type
Research Article
Information
Powder Diffraction , Volume 4 , Issue 3 , September 1989 , pp. 144 - 151
Copyright
Copyright © Cambridge University Press 1989

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References

Brigham, E.O. (1974). The Fast Fourier Transform. Englewood, NJ: Prentice-Hall.Google Scholar
Cameron, D.G. & Moffatt, D.J. (1984). Deconvolution, derivation, and smoothing of spectra using Fourier transforms. J. Testing and Evaluation, 12, 78–85.Google Scholar
Huang, T.C. & Parrish, W. (1977). Qualitative analysis of complicated mixture by profile fitting X-ray diffractometer patterns. In Adv. X-Ray Anal. 19, 275.Google Scholar
Jackson, M.L. (1967). Soil Chemical Analysis. Published by the author. Dept. of Soil Science, Univ. of Wisconsin, Madison.Google Scholar
Kauppinen, J.K., Moffatt, D.J., Mantsch, H.H. & Cameron, D.G. (1981). Fourier transforms in the computation of self-deconvoluted and first-order derivative spectra of overlapped band contours. Anal. Chem. 53, 1454–1457Google Scholar
Kauppinen, J.K., Moffatt, D.J., Cameron, D.G. & Mantsch, H.H. (1981). Noise in Fourier self-deconvolution. Appl. Opt. 20, 1866–1879.Google Scholar
Kauppinen, J.K., Moffatt, D.J., Mantsch, H.H. & Cameron, D.G. (1981). Fourier self-deconvolution: a method for resolving intrinsically overlapped bands. Appl. Spectrosc. 35, 271–276.Google Scholar
NRCC Bulletins 13-18. Chemistry Division, NRCC, Sussex Drive, Ottawa, Ont. K1A 0R6, Canada.Google Scholar
Slaughter, M. (1979). Deconvolution of overlapping X-ray powder diffraction spectra for quantitative analysis. NIOSH Report 210-79-0078. Public Health Service, U.S. Dept. of Health, Education and Welfare.Google Scholar
Stokes, A.R. (1948). Proc. Phys. Soc. London 61, 382.Google Scholar