THE POSSIBILITY OF USING HANDHELD XRF IN CEMENT
APPLICATIONS
Dr. Michelle Cameron, Bruker Elemental, Kennewick, WA
Denver X-ray Conference 2011
ABSTRACT
Handheld XRF may become a useful and cost-saving tool in the cement industry,
especially for measuring raw materials and making quick decisions in the field.
Calibration methods are explained and results are presented for a Bruker S1 TURBOSD
LE used to measure limestone and related materials used in the cement industry.
Results are discussed for measurements of powders, pressed pellets, and unprepared
rock samples. Variations in calibration assumptions are also discussed, which allow
better tailoring of a calibration to measurement of different matrices.
INTRODUCTION
Laboratory and benchtop x-ray diffraction (XRD) and x-ray fluorescence (XRF) are used
regularly as part of the quality control process in cement plants. These have all but
replaced traditional wet chemistry methods in this process. X-ray-based methods are
considered as rapid analysis tools to ensure quality final product, and are qualified by
demonstrating compliance to the requirements in ASTM C-114. They are also used in
other parts of the cement-making process to monitor raw materials and clinker.
Use of laboratory XRD and XRF requires
significant sample preparation. This is
important for XRF because low energy x-rays
from elements like Mg, Al, and Si are very weak
and don't travel far in air or in a solid matrix.
Table 1 shows the path lengths of selected
elements through air and through a silica
matrix. Even Ca, which is a "heavier" element in
the cement process, only has a path length of
27μm. Since only the first 30μm of the sample is
being measured, ensuring homogeneity of the
sample is essential for accurate measurement.
Element
Air (cm)
Silica (microns)
Be
0.049
0.1
C
0.428
0.5
O
0.147
2.1
Na
0.595
3.1
Mg
0.986
5.1
Si
2.46
12.4
Ca
22
27.3
Ti
40.1
47.3
Fe
115.6
128
Table 1. Path lengths of Selected Elements in
Air and SiO2
Traditional sample preparation methods are fused beads and pressed pellets. Fused
beads ensure the best homogeneity because the sample is crushed and the powder
mixed with a flux, which is then heated to around 1000ºC and cooled to form a bead.
Pressed pellets are made by using high pressure to flatten the powder into a little cake,
either with or without a binder to hold it together. Pressed pellets require less work to
prepare, but may have more issues with homogeneity than the fused beads.
Sample preparation and lab analysis take time and the high level of accuracy required
by ASTM C-114 may not be necessary in all parts of the cement-making process. The
requirements in ASTM C-114 only govern the final product. Less accurate results can
still be useful in homogenizing feed material or in other raw material decisions. What if
less accurate but good enough results could be obtained with little or no sample
preparation? This paper presents a study done with handheld XRF using powders,
pressed pellets, and unprepared rocks to demonstrate the ability of handheld XRF to be
used as a cost-saving device in the cement-making industry.
EXPERIMENTAL
Calibrations were developed for the Bruker S1 TURBOSD LE using pressed pellets and
powders and were tested on a variety of relevant samples. The calibration made from
powders was done by measuring known customer standards and certified geological
standards. Powders were used as-is, with no additional grinding. They were placed in a
sample cup covered with 4μm Ultralene foil and measured for 180 seconds. These data
were used to create a fundamental parameters-based, semi-empirical calibration that
reports MgO, Al2O3, SiO2, SO3, K2O, CaCO3, TiO2, MnO, and Fe2O3. This is the standard
composition of limestone, the highest quality raw material for the cement-making
process.
The assumptions about the stoichiometry of each element are key parameters in
obtaining accurate results. Based on the results obtained, two more versions of the
calibration were created, using different stoichiometric assumptions. The first assumes
Ca and Mg exist as carbonates and the rest of the elements are their standard oxides.
This mimics the composition of dolomite. The second assumes Ca is also a standard
oxide (CaO) along with the rest. This is the composition of ignited limestone/dolomite,
including clinker and everything after the kiln.
The calibration made from pressed pellets was designed for measuring unprepared
rock surfaces. Pressed pellets more closely resemble rocks because there are not
additional errors arising from packing density variations in the powder. The pellets
were measured for 180 seconds each, and a semi-empirical calibration similar to that
with the powders was created. Three versions of this calibration were made, each using
a different set of assumptions, to demonstrate the effect that stoichiometric assumptions
have on the final performance of the calibration.
The first version assumes Ca as a carbonate (CaCO3) and the other elements as their
standard oxides. It also normalizes the results to 100% by summing the measured
values and multiplying them by a factor to cause the sum to be 100%. This is the same
set of assumptions used in the powder calibration. The second version also assumes the
same stoichiometry but does not normalize the results. The third version assumes all
elements to be in their standard oxide form (Ca = CaO) and does not normalize, but
uses a CO2 matrix balance, which assumes all remaining percent composition (all
unmeasurable material) is carbon dioxide. The matrix balance sometimes causes
instabilities in the calculations, but still can often be helpful.
Normalization is a very useful tool,
but should be used carefully. It can
correct for problems like large grain
size variation or the sample not
sitting flat on the nose of the
instrument. Figure 1 shows the
effect of normalization on the Ca
content reported for measurements
of the same sample with grain sizes
varying from fine powder to larger
rocks about the size of almonds. The
normalized data only show about a
two percent variation of the CaCO3
Figure 1. Normalization
values, while the non-normalized
data show around a 30% variation in the reported CaO. Note that the normalized
calibration reports CaCO3 instead of CaO. This is because when using normalization, all
the elements present must be accounted for, including the x-ray-invisible elements like
C, O and H. If they cannot be measured, they must be included through stoichiometry.
The absorption characteristics of the invisible elements are also used in the calculation
of concentration from intensity for the measured elements.
All test samples were measured for 180 seconds. Powder samples were in a sample cup
with 4μm Ultralene foil. Each powder sample was shaken to homogenize, then tapped
on a surface to ensure equivalent packing density in all samples.
RESULTS
Powder Calibration
The original calibration made from powder standards was tested on certified geologic
powder standards. Table 2 contains the data for these tests. There is very good
agreement between known and measured values on the limestone samples. As the
stoichiometry diverges from the assumptions, the agreement in the data goes down.
The dolomite and gypsum show deviations in the CaCO3 values because of their
GeoMajors Geological
Standards
Limestone_04
MgO
Al2O3
SiO2
SO3
K2O
CaCO3
TiO2
Mn2O3
Fe2O3
known
measured
0.15
1.65
0.12
0.61
0.70
0
0.02
0.088
0.02
0.045
98.8
97.5
0.009
0.006
0.010
0.017
0.045
0.069
known
measured
1.94
0.804
0.405
0.429
3.04
4.17
0.118
0.064
0.030
0.043
87.7
90.6
0.049
0.023
0.178
0.155
2.715
2.270
known
measured
21.4
20.1
0.054
0
0.376
0
0.010
0.032
0.020
0.114
54.3
79.6
0
0.004
0.004
0.010
0.030
0.075
known
measured
1.74
3.23
0.34
0
1.68
2.24
51.9
43.6
0.095
0.080
70.1
50.7
0.019
0.008
0
0.025
0.153
0.125
known
measured
0.21
6.03
1.1
0.804
2.92
3.68
42.8
33.1
0
0.005
31.5(CaO)
0
40.4
0.023
0
0.020
0.4
0.308
known
measured
0.3
0
31.6
25.8
51.1
70.0
0.250
0.009
2.23
1.91
0.304
0
1.08
1.02
0
0.01
1.04
1.24
known
0.42
4.85
21.8
2.25
0.110
70(CaO)
0
0
0.3
measured
1.27
2.38
22.8
1.62
0.078
71.6
0.008
0.030
0.178
Limestone_14
Dolomite_05
Gypsum_19
SuperPhosphate_20
Clay
Cement_01
Table 2. Powder Calibration, Geological Standards
differing chemistries. Although the clay has good agreement in Ca, it diverges in SiO2
and Al2O3. This has not been fully investigated, but it is suspected that the divergence is
caused by normalizing the calibration without including the proper loss on ignition
(LOI). In clays, CaO is more likely to be present instead of CaCO3. Using an assumption
of CaCO3 is not an accurate representation of the LOI for a clay-type material. This
would cause deviations in the major elements, with the SiO2 divergence being the
largest because it is the most prevalent element.
The superphosphate was chosen as a test sample to demonstrate the effect of choosing
totally wrong stoichiometry. Because the stoichiometry assumed in the calibration is
nothing like that of the superphosphate, and the P2O5 is not taken into account, rather
wild results can be seen. This demonstrates the importance of at least having some idea
of the mineralogy of a sample in order to get accurate results. If just a rough idea of the
composition is needed, a generalized mining or soil cal can be used to get estimates of
the elements present, even for unusual stoichiometries.
An interesting sample was the cement sample, which is a final-product cement. Because
this has been ignited in the kiln, the CO2 burned off, leaving CaO instead of CaCO3. The
reported value for the calcium was correct, but the units are very misleading. A better
assumption for the final cement product, as well as clinker and anything that has been
previously ignited, is CaO.
GeoMajors Geological Standards MgCO3 Al2O3
Dolomite_05
known
44.8
0.054
Dolomite Assumptions measured 40.5
0
GeoMajors Geological Standards
MgO
Al2O3
Cement
known
0.42
4.85
Cement Assumptions measured 0.565
3.6
SiO2
SO3
K2O
CaCO3
TiO2
Mn2O3 Fe2O3
0.376
0
SiO2
0.010
0.037
SO3
0.020
0.083
K2O
54.3
59.3
CaO
0
0.004 0.030
0.003 0.009 0.049
TiO2 Mn2O3 Fe2O3
21.8
22.1
2.25
1.850
0.110
0.12
70
71.4
0
0.01
0
0.04
0.3
0.37
Table 3. Dolomite and Cement Assumptions
In order to test the hypothesis that stoichiometric assumptions were responsible for the
deviations, a set of assumptions was applied to the calibration for dolomite. Another set
of assumptions for gypsum were applied and the samples recalculated with these
changes. Table 3 shows the results for dolomite (Mg-Ca-carbonate) and ignited cement
(Ca oxide, no CO2). It is obvious that the assumptions were the cause of the deviations,
and with the proper assumptions, good values can be obtained for these matrices. One
thing to keep in mind when using the cement (CaO) assumptions is that if it is used to
look at final product, additional elements could be present from blending with other
materials. These would not be taken into account in this calibration, which is designed
primarily for raw materials.
Some customer samples were also tested. These samples are representative of the types
of raw materials used in their process. Table 4 shows results for these. The same trends
were seen as in the geologic standards. The limestones have very good agreement, with
the clays diverging a little. However, all the materials tested showed good enough
agreement to provide useful results. Decisions about raw materials can be made based
on this quality of results, thus saving time and money on sample preparation and lab
analysis.
Customer Samples
limestone
C15A04e2bb
precrusher stockpile
C15B02f285
MgO
feed limestone
C15B02d59b
weekly clay
C15B02a6cf
K2O
CaCO3
TiO2
Fe2O3
0.63
0.3
1.28
0.02
0.08
96.8
0.02
0.28
1.4
0.73
0
0.080
0.056
97.4
0.0063
0.316
known
0.12
18.2
67.8
0.06
0.15
0.125
1.1
7.36
0
17.2
72.6
0.002
0.22
0.147
1.1
8.6
known
1.09
1.61
12.5
0.04
0.34
81.8
0.09
1.09
measured
0.48
1.18
13.1
0.083
0.29
83.5
0.033
1.26
known
0.67
0.76
4.72
0.42
0.18
91.1
0.05
0.99
0
0.51
5.69
0.52
0.18
91.8
0.027
1.19
known
0.28
1.22
5.27
41.0
0.22
53.2
0.04
0.59
measured
4.15
1.16
6.58
37.6
0.26
49.5
0.042
0.69
known
0.2
28.0
57.2
0.23
0.39
0.77
1.36
2.91
0
28.6
65.2
0.029
0.44
0.94
1.57
3.25
0.29
23.7
66.8
0.04
1.03
0.09
1.08
0.7
0
27.6
69.2
0.0022
1.09
0
1.22
0.90
measured
clay-birdwood
C15A04e2bc
SO3
measured
measured
cement fringes
C15B02d348
SiO2
known
measured
stockpile
C15B02f1c0
Al2O3
known
measured
Table 4. Powder Calibration, Cement Process Samples
Pressed Pellet Calibration
Pressed pellets were chosen for the calibration to be used for unprepared rocks in order
to more closely simulate the rocks than a powder calibration. This is because the pellets
don't have added uncertainties due to variations in the packing density of the powder.
As seen in the powders, choosing the stoichiometry closest to that of the samples to be
measured is very important because the absorption characteristics of the "invisible"
elements are used in the calculation. For high quality raw materials used in cement
manufacturing, the CaCO3 assumption is usually valid. If other compositions are
known to be prevalent, the assumptions of a calculation can be easily changed to
accommodate the new stoichiometry.
Table 5 shows data taken on unprepared rocks, as well as on pressed pellets made from
those rock samples. For each sample number, a bag of rock chips was provided. From
this bag, three representative samples were chosen for measurement. When there was a
visible color difference between the rocks in a bag, samples were chosen to represent
the whole range of colors.
Known
CaCO3 Norm (CaCO3)
Sample #
1
pellet
raw ave
raw range
2
pellet
raw ave
raw range
3
pellet
raw ave
raw range
4
pellet
raw ave
raw range
5
pellet
raw ave
raw range
6
pellet
raw ave
raw range
7
pellet
raw ave
raw range
8
pellet
raw ave
raw range
9
pellet
raw ave
raw range
96.3
89.48
74.2
88.14
81.43
79.8
97.25
85.43
75.78
98
96.7
95.8 - 97.9
91.6
89.5
77.4 - 96.2
80.7
79.7
78.7 - 81.3
88.1
89.9
88.1 - 92.9
85.6
86.8
76.5 - 92.1
84.3
79.6
78.2 - 84.4
97.3
96.2
94.3 - 99.1
85.6
69.5
32.2 - 89.8
80.7
81
80.1 - 81.9
No Norm
(CaCO3)
98.4
95
91.7 - 98.1
92.1
87.8
71 - 97.8
78.1
75.3
72.4 - 80.4
90.3
96.1
93.6 - 98.7
85.1
85.4
68.5 - 94.2
83.5
81.5
80.4 - 82.7
99.3
100
100 - 100
87.4
75.7
32.9 - 99.4
79.3
77.6
76.4 - 79.4
Known CO2 Matrix
CaO
(CaO)
53.93
50.11
41.56
49.36
45.6
44.69
54.46
47.84
42.44
55.8
51.3
43.6 - 57.9
52.4
47.6
32.5 - 59.9
40.5
37.5
31.4 - 46.8
54.3
67.4
59.3 - 79.5
46.9
47.2
30.2 - 56.4
45.7
47
43.4 - 49.1
59.1
71.2
58.6 - 77.8
51.9
58.2
19.3 - 92.8
42.7
39.3
38.3 - 41.2
Table 5. Rock and Pellet Data
The data shows that although there can be a large range in measured values for the
rocks, the average value is generally close to the known value. This demonstrates the
importance of taking multiple measurements on inhomogeneous samples. The
normalized calibration showed the least variation in the rock samples, but not by a huge
amount. The non-normalized CaCO3 had slightly higher variation, but approximately
the same average deviation from the known. The CaO with CO2 matrix had the most
variation in the rock samples and deviated significantly on more samples than the
others.
One interesting anomaly is Sample #8. This sample was visibly heterogeneous within
each rock chip, with spots of white (presumably SiO2) on a grey background. This
sample showed a huge deviation between measurements, and the average was not that
close to the known value. This is a case when taking more than three measurements is
important. If five or ten measurements were taken, it is likely that the average value
would approach the known value. When there is visible heterogeneity, it is very
important to take multiple measurements.
CONCLUSION
These data suggest that the use of handheld XRF in measuring raw materials in the
cement-making process may result in significant time and money savings. The data on
powders and even on unprepared rock samples show that good enough results can be
obtained to make decisions in the field. While handheld XRF will not replace the
benchtop or laboratory instruments in the cement industry, it can provide a cost-saving
enhancement to the users that will enable them to make faster decisions about raw
material management.