Assessing the Accuracy of Quantitative XRD with Fe-Ore Certified Reference Materials

X-ray diffraction or XRD is a rapid analytical technique that is mainly used for determining ore’s mineralogy. TOPAS quantitative phase analysis (QPA) together with a fast detector incorporated in the XRD system enables rapid, standard-less analysis even with a desktop system.

Amount and type of the iron bearing species for grade control and general quality of the run-off mine material are the standard results obtained in iron ore analysis. Knowledge about the gangue minerals and their composition governs the required steps of beneficiation prior to additional processing of the ore.

The iron’s oxidation state can be easily determined from the quantitative XRD result, thus establishing the CO2 footprint of iron plants. For well crystalline samples, the standard precision can be better at 1 wt-%. This is validated by comparing the QPA result against conventional chemical analysis.

Why X-ray Diffraction in Mining

QPA is often applied for studying geologic materials in both service and research laboratories and also in quality control of mining operations. A better understanding of the properties of ore and gangue is of economic importance for the process mineralogy.

Ores are minerals from which metals are obtained, while gangue is a deleterious mineral that has to be isolated from the ore. Physical properties that establish the material’s processability such as density, hardness, magnetism, or solubility are directly associated with the minerals’ crystal structure and not to their chemical composition.

As a result, these properties directly affect processing conditions such as the method of metals extraction (smelting, flotation, or leaching), the method of separation (dissolution, magnetic, or gravity), operation costs through consumption of acids and other chemicals, the option of the right mill and its energy consumption, and transport of material amid different facilities in a processing plant and the mine.

QPA that uses X-ray diffraction and the Rietveld method data is a direct technique used for acquiring the absolute or relative phase abundances of crystalline and non-crystalline (amorphous or nano- crystalline) components in a mixture.

However, despite this, the precision of this method has been one of the most frequently asked questions which have been answered in this article for Dillinger Hütte’s certified reference materials for ore of well crystallized structure.

TOPAS Quantitative Phase Analysis

QPA using the Rietveld method was carried out by means of the TOPAS software. This analysis is built on the quantification of the entire powder pattern from the crystal structure data.

Hence, it does not depend on calibration curves, and ageing of tube does not need to be taken into account. QPA in the TOPAS software is based on the method which was initially described by Hill and Howard in the year 1987. This technique is based on the assumption that:

  • All phases are crystalline
  • All phases in the specimen are detected
  • The crystal structures of all phases are known

The weight-% wu of a phase u in a mixture of n phases is:

where Z is the number of formula units in the unit cell, S is the scale factor of the Rietveld calculation, M is the mass of a single formula unit, and V is the unit cell volume. As a phase specific scaling parameter, the factor (ZMV) is exclusively defined by the well-known crystal structure of the mineral.

How to Assess Accuracy

The evaluation of the precision of QPA is not a straightforward task. The actual outcome of the analysis is a priori unknown. In fact, even predicted concentrations of artificial mixtures are inclined to experimental uncertainties, for instance errors of weighing.

On the whole, the precision of a sample QPA analysis cannot be evaluated sans any additional data on phase content or composition. However, it is possible to assess the precision of the QPA result by comparing to standard chemical analysis.

Chemical analysis of a multi-phase mixture through XRD follows from the known stoichiometry and phase abundances of the crystalline phases. For this technique, the composition of the crystalline phases needs to be defined well.

However, a major complication, especially for minerals is that compositions that are often idealized are only known and the actual composition of the species contained in the specimen is unknown. In addition, it should be noted that conventional elemental analysis does not help in differentiating between amorphous content and crystalline phase abundances.

The composition of amorphous phases could be either partly known or completely unknown. Amorphous components may be present in even well crystalline material owing to the grains’ non-diffracting surface layers.

Results and Discussion

In Figures 1 and 2, iron ores are shown as standard examples of moderately complex materials. The samples include the reference materials SX11-12 and SX11-14 that are commercially available and certified by Dillinger Hütte.

First, XRD data were determined with Co radiation along with the LYNXEYE detector integrated on a D2 PHASER desktop diffractometer. The conditions of the scan were a step width of 0.02° at 0.2s measuring time per step, and the overall scan time was approximately 12 min.

TOPAS QPA of Dillinger Hütte iron ore certified reference material SX11-12

Figure 1. TOPAS QPA of Dillinger Hütte iron ore certified reference material SX11-12

TOPAS QPA of Dillinger Hütte iron ore certified reference material SX11-14.

Figure 2. TOPAS QPA of Dillinger Hütte iron ore certified reference material SX11-14.

The type of minerals identified for both samples are summarized in Table 1. Tables 2 and 3 show the phase abundances from Rietveld QPA. While the SX11-12 sample is mainly a hematitic high-grade iron ore having very little amounts of gangue, the SX11-14 sample is a magnetite-rich ore having more complicated gangue mineralogy.

In accordance with the minerals’ nominal chemical formulae, the phase abundances were divided into separate oxide-based chemical compositions of the non-iron bearing components and the total metallic iron content.

For all minerals, such fractional concentrations are summarized and compared to the known chemical analysis of the certified reference materials. The predisposition between the bulk chemical analysis and the XRD results is considerably small and well below ±1 wt-% for the two samples.

Besides total metallic iron, the quantity of iron bound as bivalent oxide FeO is also illustrated. This holds a major significance for iron producers as FeO belongs to the major pollutants of CO2, which happens to be a major greenhouse gas.

Table 1. Minerals species identified in iron ore certified reference materials SX11 -12 and 14.

Minerals Formula SX11-12 SX11-14
Hematite Fe2O3 x x
Goethite FeOOH x x
Magnetite Fe3O2 x x
Quartz SiO2 x x
Gibbsite AI(OH)3 x x
Talc Mg3Si4O10(OH)2 - x
Orthoclase KAlSi3O8 - x
Albite NaAlSi3O8 - x
Calcite CaCO3 - x

Table 2. Chemical analysis of the Dillinger Hütte iron ore certified reference material SX11-12, derived from QPA results taking into account the nominal stoichiometry (table 1) of the phases

Minerals Wt-% Fe FeO SiO2 Al2O3
Hematite 88.30 61.76 - - -
Goethite 9.57 6.02 - - -
Magnetite 0.95 0.68 0.29 - -
Quartz 0.09 - - 0.09 -
Gibbsite 1.10 - - - 0.72
XRD   68.46 0.29 0.09 0.72
Chem.   67.83 0.41 0.60 0.70
Bias   0.63 -0.12 -0.51 0.02

Table 3. Chemical analysis of the Dillinger Hütte iron ore certified reference material SX11-14, derived from QPA results taking into account the nominal stoichiometry (table 1) of the phases

Minerals Wt-% Fe FeO SiO2 Al2O3 MgO CaO K2O Na2O C
Hematite 0.37 0.26 - - - - - - - -
Goethite 3.86 2.43 - - - - - - - -
Magnetite 85.97 62.21 26.68 - - - - - - -
Quartz 5.73 - - 5.73 - - - - - -
Gibbsite 0.71 - - - 0.46 - - - - -
Talc 1.79 - - 1.13 - 0.57 - - - -
Orthoclase 0.30 - - 0.19 0.05 - - 0.05 - -
Albite 0.89 - - 0.60 0.18 - - - 0.10 -
Calcite 0.40 - - - - - 0.22 - - 0.19
XRD   64.89 26.68 7.66 0.70 0.57 0.22 0.05 0.10 0.19
Chem.   65.55 27.20 7.47 0.27 0.56 0.42 0.06 0.08 0.12
Bias   -0.66 -0.52 0.19 0.43 0.01 -0.20 -0.01 0.02 0.07

Conclusion

The amount of CO2 produced during iron production relies on the iron’s valence state in the ore, which in turn is defined by the concentrations of the minerals and the type of mineral bearing the metal.

Titration would be a standard method for determining the FeO content, but this method takes significant amount of time and is also an operator prone process. here, both samples demonstrated excellent agreement of the FeO content with the predicted values, thus confirming that XRD is a practical method for determining the valence state of iron ore within a short period to time.

This information has been sourced, reviewed and adapted from materials provided by Bruker AXS Inc.

For more information on this source, please visit Bruker AXS Inc.

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