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Powder-Pattern: A System of Programs for Processing and Interpreting Powder Diffraction Data*

Published online by Cambridge University Press:  06 March 2019

Nikos P. Pyrros
Affiliation:
JCPDS--International Centre for Diffraction Data, National Bureau of Standards, Washington, DC 2023A
Camden R. Hubbard
Affiliation:
Center for Materials Science, National Bureau of Standards, Washington, DC 20234
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Extract

The production of standard x-ray diffraction patterns at NBS imposes special requirements in the data processing of powder patterns. The patterns should be complete and have an overall accuracy of better than 0.01 degree two theta. To ensure completeness all the observable peaks should be indexed. To make certain that the sample is a pure phase, weak peaks have to be identified as well.

The indexing of all the peaks implies that the cell constants must be known and there should be a good agreement between all the calculated and observed peak positions. In practice this is achieved by a least-squares refinement of the unit cell parameters. This serves as a test of the assumed unit cell and also as an interpretation of the observed peaks. Finally, an attempt is made to identify the space group. This step also requires the identification of weak peaks. The agreement of a known space group with the observed reflections further confirms the purity of the sample.

Type
II. Search/Match Procedures, Powder Diffraction File
Copyright
Copyright © International Centre for Diffraction Data 1982

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Footnotes

*

Contribution from the National Bureau of Standards. Not subject to copyright.

References

Evans, H. T., Appleman, D. E., and Handwerker, D. S. (1963). Report #PB216188, U.S. Dept, of Commerce, National Technical Information Center, 5285 Port Royal Rd., Springfield, VA 22151.Google Scholar
Goehner, R.P. (1979). Specplot-An Interactive Data Reduction and Display Program for Spectral Data, Adv-in X-Ray Analysis, 23, 305–2.Google Scholar
Ladell, J., Zagofsky, A. and Pearlman, S. (1975). CuKα Elimination Algorithm, Appl. Cryst. 8, 499–2.Google Scholar
Mallory, C.L. and Snyder, R.L. (1979). The Alfred University X-Ray Powder Diffraction System, Technical Paper No. 144, New York State College of Ceramics, Alfred University, Alfred, N.Y. 14802.Google Scholar
Morris, M.C., McMurdie, H.F., Evans, E.H., Paretzkin, B., Parker, H. S., Panagiotopoulos, N.C. and Hubbard, C.R. (1981). Standard X-Ray Diffraction Powder Patterns, NBS Monograp. 25, Sect. 18. National Bureau of Standards, Washington. D.C. 20234Google Scholar
Pyrros, N.P. and Hubbard, C.R. (1983). Rational Functions as Profile Models in Powder Diffraction. Submitted for publication.Google Scholar
Savitzky, A. and Golay, M.J. (1964). Smoothing and Differentiation of Data by simplified Least Squares Procedures, Anal. Chem. 36, 1627–29.Google Scholar
Sonneveld, E.J. and Visser, J.W. (1975). Automatic Collection of Powder Data from Photographs, Appl. Cryst. 8, 17.Google Scholar
Snyder, R.L., Hubbard, C.R., and Panagiotopoulos, N.C. (1982). A Second Generation Automated Powder Diffraction Control System, Adv. in X-Ray Analysis 25, 245–2.Google Scholar
Visser, J. W. (1969). A Fully Automatic Program for Finding the Unit Cell from Powder Data, Appl. Cryst. 2, 8995.Google Scholar