Hostname: page-component-848d4c4894-pftt2 Total loading time: 0 Render date: 2024-06-03T09:26:30.326Z Has data issue: false hasContentIssue false
  • English
  • Français

Some Successful Approaches to Quantitative Mineral Analysis as Revealed by the 3rd Reynolds Cup Contest

Published online by Cambridge University Press:  01 January 2024

Oladipo Omotoso ,
Douglas K. McCarty ,
Stephen Hillier  and
Reinhard Kleeberg
Oladipo Omotoso*
Affiliation:
CANMET Energy Technology Centre, Natural Resources Canada, Devon, AB, Canada T9G 1A8
Douglas K. McCarty
Affiliation:
Chevron ETC, Houston, TX 77042-5397, USA
Stephen Hillier
Affiliation:
Macaulay Institute, Cragiebuckler, Aberdeen AB15 8QH, UK
Reinhard Kleeberg
Affiliation:
TU Bergakademie Freiberg, Institute of Mineralogy, Freiberg D-09596, Germany
*
*E-mail address of corresponding author: oomotoso@NRCan.gc.ca
Get access Rights & Permissions [Opens in a new window]

Abstract

Details of the quantitative techniques successfully applied to artificial rock mixtures distributed for the third Clay Minerals Society Reynolds Cup (RC) contest are presented. Participants each received three samples, two containing 17 minerals each and a third containing ten minerals. The true composition of the samples was unknown to all participants during the contest period. The results submitted were ranked by summing the deviations from the actual compositions (bias). The top three finishers used mainly X-ray diffraction (XRD) for identification and quantification. The winner obtained an average bias of 11.3% per sample by using an internal standard and modified single-line reference intensity ratio (RIR) method based on pure mineral standards. Full-pattern fitting by genetic algorithm was used to measure the integrated intensity of the diagnostic single-line reflections chosen for quantification. Elemental-composition optimization was used separately to constrain phase concentrations that were uncertain because the reference mineral standards were lacking or not ideal. Cation exchange capacity, oriented-sample XRD analysis, and thermogravimetric analysis were also used as supplementary techniques. The second-place finisher obtained an average bias of 13.9%, also by using an RIR method, but without an added internal standard and with intensity measured by whole-pattern fitting. The third-place finisher, who obtained an average bias of 15.3%, used the Rietveld method for quantification and identification of minor phases (using difference plots). This participant also used scanning electron microscopy (with X-ray microanalysis) to identify minor components and verify the composition of structures used in Rietveld analysis. As in the previous contests, successful quantification appears to be more dependent on analyst experience than on the analytical technique or software used.

Keywords

Clay MineralsPure Reference MineralsQuantitative AnalysisReference Intensity RatioReynolds CupRietveldThe Clay Minerals SocietyWhole-pattern Fitting
Type
Research Article
Information
Clays and Clay Minerals , Volume 54 , Issue 6 , December 2006 , pp. 748 - 760
Copyright
Copyright © 2006, The Clay Minerals Society

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

Bergmann, J. and Kleeberg, R., (1998) Rietveld analysis of disordered layer silicates Materials Science Forum 278–281 1 300–305 10.4028/www.scientific.net/MSF.278-281.300.CrossRefGoogle Scholar
Bish, D.L. and Post, J.E., (1993) Quantitative mineralogical analysis using the Rietveld full-pattern fitting method American Mineralogist 78 932–940.Google Scholar
Chipera, S.J. and Bish, D.L., (2002) FULLPAT: A full-pattern quantitative analysis program for X-ray powder diffraction using measured and calculated patterns Journal of Applied Crystallography 35 744–749 10.1107/S0021889802017405.CrossRefGoogle Scholar
Chung, F.H., (1974) Quantitative interpretation of X-ray diffraction patterns of mixtures. I. Matrix-flushing method for quantitative multicomponent analysis Journal of Applied Crystallography 7 519–525 10.1107/S0021889874010375.CrossRefGoogle Scholar
Chung, F.H., (1974) Quantitative interpretation of X-ray diffraction patterns of mixtures. II. Adiabatic principles of X-ray diffraction analysis of mixtures Journal of Applied Crystallography 7 526–531 10.1107/S0021889874010387.CrossRefGoogle Scholar
Eberl, D.D. (2003) User’s guide to Rockjock — a program for determining quantitative mineralogy from powder X-ray diffraction data. US Geological Survey Open-File Report 03–78.Google Scholar
Eberl, D.D. Środoń, J. Lee, M. Nadeau, P.H. and Northrop, H.R., (1987) Sericite from Silverton caldera, Colorado: correlation among structure, composition, origin, and particle thickness American Mineralogist 72 914–934.Google Scholar
Hillier, S., (1999) Use of an air-brush to spray dry samples for X-ray powder diffraction Clay Minerals 34 127–135 10.1180/000985599545984.CrossRefGoogle Scholar
Hillier, S., (2002) Spray drying for X-ray powder diffraction specimen preparation IUCR CPD Newsletter 27 7–9.Google Scholar
Hiller, S. (2003) Quantitative analysis of clay and other minerals in sandstones by X-ray powder diffraction (XRPD). Pp. 213–251 in: Clay Minerals Cements in Sandstones (Worden, R.H. and Morad, S., editors). Special Publication 34, International Association of Sedimentologists.Google Scholar
Howard, S.A. Preston, K.D., Bish, D.L. and Post, J.E., (1989) Profile fitting of powder diffraction patterns Modern Powder Diffraction Washington, D.C Mineralogical Society of America 217–275 10.1515/9781501509018-011.CrossRefGoogle Scholar
Jenkins, R. and Snyder, R.L., (1996) Introduction to X-ray Powder Diffractometry New York John Wiley and Sons 10.1002/9781118520994.CrossRefGoogle Scholar
Kleeberg, R., (2005) Results of the second Reynolds Cup contest in quantitative mineral analysis IUCr CPD Newsletter 30 22–26.Google Scholar
Le Bail, A., (1995) Modelling the silica glass structure by the Rietveld method Journal of Non-Crystalline Solids 183 39–42 10.1016/0022-3093(94)00664-4.CrossRefGoogle Scholar
McCarty, D.K., (2002) Quantitative mineral analysis of clay bearing mixtures: The Reynolds Cup contest IUCr CPD Newsletter 27 12–16.Google Scholar
Mystkowski, K., Środoń, J. and McCarty, D.K. (2002) Application of evolutionary programming to automatic XRD quantitative analysis of clay-bearing rocks. The Clay Minerals Society 39th Annual Meeting, Boulder, Colorado, Abstracts with Programs.Google Scholar
Schulze, D.G., (1986) Correction of mismatches in 28 scales during differential X-ray diffraction Clays and Clay Minerals 34 681–685 10.1346/CCMN.1986.0340610.CrossRefGoogle Scholar
Środoń, J., Mystkowski, K., McCarty, D.K. and Drits, V.A. (2006) BESTMIN: A computer program for refining the quantities and the chemical composition of clays and other mineral components of fine-grained rocks. International Conference ‘Clays and Clay Minerals’ Pushchino, Russia 26–30 June, 2006, Abstracts with Programs.Google Scholar
Ufer, K. Roth, G. Kleeberg, R. Stanjek, H. Dohrmann, R. and Bergmann, J., (2004) Description of X-ray powder pattern of turbostratically disordered layer structures with a Rietveld compatible approach Zeistchrift für Kristallographie 219 519–527.Google Scholar