Hostname: page-component-cd9895bd7-fscjk Total loading time: 0 Render date: 2024-12-23T18:42:26.359Z Has data issue: false hasContentIssue false
  • English
  • Français

Multireflection RIR and intensity normalizations for quantitative analyses: Applications to feldspars and zeolites

Published online by Cambridge University Press:  10 January 2013

Steve J. Chipera  and
David L. Bish
Steve J. Chipera
Affiliation:
Earth and Environmental Sciences Division, Los Alamos National Laboratory, Mail Stop D469, Los Alamos, New Mexico 87545, U.S.A.
David L. Bish
Affiliation:
Earth and Environmental Sciences Division, Los Alamos National Laboratory, Mail Stop D469, Los Alamos, New Mexico 87545, U.S.A.
Get access Rights & Permissions [Opens in a new window]

Abstract

Quantitative determination of phase abundances using X-ray powder diffraction is a technique in wide use today. Of the various methods employed, the Chung, or RIR method, is one of the most common because it can provide reliable results for all sample types. However, improvements can be made to the Chung method of analysis for phases which exhibit large chemical or preferred orientation effects. These effects can often be accommodated by using intensity regions that encompass several reflections, by averaging intensities from nonparallel reflections, or by using RIR values that are allowed to vary based on a predetermined functional relationship. To accommodate the effects of preferred orientation and variable composition in feldspars, RIR values versus the intensity ratio between two peaks of feldspar standards mixed with corundum have been determined. Curves of RIR have been formulated for: (1) feldspar RIR13.0−14.0° versus the intensity ratio (13.0–14.0° 2θ intensity region/27.0–28.75° 2θ intensity region); (2) feldspar RIR23.6° peak versus the intensity ratio (23.6° 2θ peak/27.0–28.75° 2θ intensity region); and (3) clinoptilolite RIR020 versus (020 reflection/22.1–23.0° 2θ intensity region). For example, RIR values for the highly variable 13.0–14.0° 2θ region for feldspar can be improved such that the quantitative results produced has a standard deviation of only 15% instead of 53% using a fixed-average value. From these curves, improved RIR values can be obtained for the quantitative analysis of unknowns. Additionally, intensity ratios can be determined between two peaks of a phase so that given the intensity of one peak, the intensity of the other peak can be readily calculated. This allows for subtraction of the intensity of a peak from one phase overlapping a peak from a second phase which is to be used for quantitative analysis but which cannot be decomposed by profile fitting.

Keywords

quantitative XRDRIRfeldsparclinoptilolitezeolite
Type
Research Article
Information
Powder Diffraction , Volume 10 , Issue 1 , March 1995 , pp. 47 - 55
Copyright
Copyright © Cambridge University Press 1995

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

Bish, D. L., and Chipera, S. J. (1988). “Problems and solutions in quantitative analysis of complex mixtures by X-ray powder diffraction,” in Advances in X-ray Analysis (Plenum, New York), Vol. 31, pp. 295–308.CrossRefGoogle Scholar
Bish, D. L., and Howard, S. A. (1988). “Quantitative phase analysis using the Rietveld method,” J. Appl. Cryst. 21, 86–91.CrossRefGoogle Scholar
Bish, D. L., and Reynolds, R. C. Jr., (1989). “Sample preparation for X-ray diffraction,” in Modern Powder Diffraction (Mineralogical Society of America, Washington, DC); Rev. in Mineralogy 20, 73–99.CrossRefGoogle Scholar
Chipera, S. J., and Bish, D. L. (1986). “Clinoptilolite-smectite assemblages,” Proceedings of the 23rd annual meeting of the Clay Minerals Society, Jackson Mississippi, 12–15 Oct., 17.Google Scholar
Chung, F. H. (1974a). “Quantitative interpretation of X-ray diffraction patterns of mixtures: I. Matrix-flushing method for quantitative multicomponent analysis,” J. Appl. Cryst. 7, 519–525.CrossRefGoogle Scholar
Chung, F. H. (1974b). “Quantitative interpretation of X-ray diffraction patterns of mixtures: II. Adiabatic principle of X-ray diffraction analysis of mixtures,” J. Appl. Cryst. 7, 526–531.CrossRefGoogle Scholar
Davis, B. L., and Smith, D. K. (1988). “Tables of experimental reference intensity ratios,” Powder Diffr. 3, 205–208.CrossRefGoogle Scholar
Davis, B. L., Smith, D. K., and Holomany, M. A. (1989). “Tables of experimental reference intensity ratios. Table No. 2, December 1989,” Powder Diffr. 4, 201–205.CrossRefGoogle Scholar
Hill, R. J., and Howard, C. J. (1987). “Quantitative phase analysis from neutron powder diffraction data using the Rietveld method,” J. Appl. Cryst. 20, 467–474.CrossRefGoogle Scholar
Hubbard, C. R., Evans, E. H., and Smith, D. K. (1976). “The reference intensity ratio I/I C for computer simulated powder patterns,” J. Appl. Cryst. 9, 169–174.CrossRefGoogle Scholar
Klug, H. P., and Alexander, L. E. (1974). X-ray Diffraction Procedures for Polycrystalline and Amorphous Materials (Wiley, New York).Google Scholar
Smith, D. K., Johnson, G. G., Scheible, A., Wims, A. M., Johnson, J. L., and Ullmann, G. (1987). “Quantitative X-ray powder diffraction method using the full diffraction pattern,” Powder Diffr. 2, 73–77.CrossRefGoogle Scholar