Hostname: page-component-78c5997874-8bhkd Total loading time: 0 Render date: 2024-11-11T07:50:22.975Z Has data issue: false hasContentIssue false
  • English
  • Français

Application of diffraction instrumental monitoring to the analysis of diffraction patterns from a Round Robin project on KCl

Published online by Cambridge University Press:  05 March 2012

Giovanni Berti
Giovanni Berti
Affiliation:
Department of Earth Sciences, University of Pisa, Via S. Maria 53, 56126 Pisa, Italy
Get access Rights & Permissions [Opens in a new window]

Abstract

The outcome of the analysis of data from a Round Robin on a KCl sample is reported. The research project has led to a definition of a working protocol for the treatment of X-ray diffraction data from powders (XRPD). The protocol is based on the method of “Diffraction Instrumental Monitoring” (DIM), whose main characteristics are briefly illustrated. When experimental data are referred to the expected standard values of the lattice parameter, the method enables comparison with data obtained from differing instrumentation found in different laboratories. Application of DIM to the KCl Round Robin demonstrates the ability of DIM to effectively evaluate systematic contribution. Accuracy on the cell parameter is obtained as a direct consequence; in this application, where the knowledge of the KCl d-spacing was not a problem, the accuracy of lattice parameter is a feedback for constraining the evaluation of the effective values of the experiment-related parameters.

Type
Technical Articles
Information
Powder Diffraction , Volume 16 , Issue 1 , March 2001 , pp. 6 - 15
Copyright
Copyright © Cambridge University Press 2001

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Appleman, D. E., and Evans, H. T., Jr. (1973). “Indexing and least-squares refinement of powder diffraction data,” U.S. Geol. Comp. Centr., p. 20.Google Scholar
Azaroff, L. V., Kaplow, R., Kato, N., Weiss, R. J., Wilson, A. J. C., and Young, R. A. (1974). X-ray Diffraction (McGraw Hill, New York).Google Scholar
Berti, G., Di Guglielmo, G., and Marzoni Fecia di Cossato, Y. (1990). “Interpretation of powder diffraction pattern by numerical and computer graphics system,” J. Appl. Crystallogr. JACGAR 23, 6–10. acr, JACGAR CrossRefGoogle Scholar
Berti, G., and Palamidese, P. (1990). “Analysis of the CuKβ X-ray diffraction pattern of YAG (Yittrium Alluminium Garnet), by numerical and computerized graphic techniques,” Powder Diffr. PODIE2 5, 186–191. pdj, PODIE2 CrossRefGoogle Scholar
Berti, G. (1991). “DISP: A Fortran Code to determine the peak centroid displacement in X-ray powder diffractometry,” Quaderni di software-Dip. Scienze della Terra-Univ. di Pisa, No. 3, pp. 12–15.Google Scholar
Berti, G. (1992). “Background and Bragg scattering component separation in powders via XRD technique,” Mater. Sci. Forum MSFOEP 133–136, 83–88 (Trans. Technical Pub., Switzerland).Google Scholar
Berti, G., and Enea, A. (1992). “Disvar: Un pacchetto per il calcolo degli effetti sistematici che alterano la posizione del centroide e della varianza dei picchi in diffrattometria di polveri a raggi x. Regole d’istallazione e uso,” Quaderni di Software-Dip. Scienze della Terra-Univ. di Pisa No. 4, pp. 3–10.Google Scholar
Berti, G. (1993). “Variance and optimization in X-ray powder diffraction analysis,” Powder Diffr. PODIE2 8, 87–95. pdj, PODIE2 CrossRefGoogle Scholar
Berti, G., Giubbilini, S., and Tognoni, E. (1995). “DISVAR93: A software package for determining systematic effects in X-ray powder diffractometry,” Powder Diffr. PODIE2 10, 104–111. pdj, PODIE2 CrossRefGoogle Scholar
Berti, G. (1996). “Detection and modelling of micro-crystallinity by means of X-ray powder diffractometry,” in Advances X-ray Analysis, Vol. 38 (Plenum, New York) p.405–412.Google Scholar
Berti, G. (2000). “Microstructure of polycrystalline natural samples for the ak profile analysis of diffraction data,” Mater. Sci. Forum MSFOEP 347–349, 309–314 (Trans. Technical Pub., Switzerland). msf, MSFOEP CrossRefGoogle Scholar
Berti, G., Citi, S., Baldi, G., Cantelli, V., De Paolis, F., Giampaolo, C., Guelfi, F., Justi, S., and Pardini, G. F. (2000). “Results of monitoring the calibration of diffractometers using diffraction instrumental monitoring (DIM) with data of corundum from different instruments,” Abstract collection book EPDIV-VII, Barcellona May 20–23, 2000, p. 94.Google Scholar
Berti, G. (2001). “A method for routine comparison of XRPD measurements,” Powder Diffr. PODIE2 16, 1–5. pdj, PODIE2 CrossRefGoogle Scholar
Delhez, R., and Mittemeijer, E. J. (1975). “An improved α2 elimination,” J. Appl. Crystallogr. JACGAR 8, 609–611. acr, JACGAR CrossRefGoogle Scholar
Handbook of Chemistry and Physics, 78th ed., edited by D. R. Lide (CRC Press, Boca Raton, FL 1997–1998).Google Scholar
International Table for Crystallography, A.J.C. Wilson, Ed. for IUCr, Dordrect/Boston/London (Kluwer Academic, 1992), Vol. C.Google Scholar
ISO5725-1. “Accuracy (trueness and precision of measurements method and results. Part 1: General principles and definitions. Ref. No. ISO5725-1: 1994 (E).Google Scholar
Klug, H-P., and Alexander, L. E. (1974). X-ray Diffraction Procedures from Polycrystalline and Amorphous Materials (Wiley, New York).Google Scholar
Masciocchi, N., and Artioli, G. (1996). “Lattice parameters determination from powder diffraction data: Results from a Round Robin project,” Powder Diffr. PODIE2 11, 253–258. pdj, PODIE2 CrossRefGoogle Scholar
Powder Diffraction File Computer Data BAse of ICDD, Newtown Square, PA (1992).Google Scholar
Scardi, P., Lutterotti, L., and Maistrelli, P. (1994). “Experimental determination of the instrumental broadening in the Bragg–Brentano geometry,” Powder Diffr. PODIE2 9, 180–186. pdj, PODIE2 Google Scholar
Wilson, A. J. C. (1963). The Mathematical Theory of X-ray Powder Diffraction, Philips Technical Library (The Netherlands).Google Scholar