Powder Technology 235 (2013) 341–348
Contents lists available at SciVerse ScienceDirect
Powder Technology
journal homepage: www.elsevier.com/locate/powtec
Mixing variables for prebaked anodes used in aluminum production
Kamran Azari a, b, Houshang Alamdari a, b,⁎, Gholamreza Aryanpour b, Donald Picard b,
Mario Fafard b, Angelique Adams c
a
b
c
Department of Mining, Metallurgical and Materials Engineering, 1065 Ave. de la Médecine, Laval University, Quebec, QC, Canada G1V 0A6
NSERC/Alcoa Industrial Research Chair MACE3 and Aluminium Research Centre — REGAL, Laval University, Quebec, QC, Canada G1V 0A6
Alcoa Primary Metals, 900 South Gay Street, Knoxville Tennessee, 37902, United States
a r t i c l e
i n f o
Article history:
Received 29 June 2012
Received in revised form 8 October 2012
Accepted 19 October 2012
Available online 27 October 2012
Keywords:
Anode
Mixing
Porosity
Density
Tomography
Permeability
a b s t r a c t
The quality of anode electrode used in aluminum electrolysis industry and its dependence on the production
parameters are studied in this work. Using a calcined petroleum coke and a coal tar pitch, anode pastes were
made at laboratory scale at four mixing temperatures and four mixing times. The pastes were compacted in a
cylindrical mold at a maximum pressure of 60 MPa. The green samples were then baked at 1130 °C for 12 h.
Measurement of density variations as well as porosity and pore size distribution was carried out on the green
and baked samples as a function of mixing temperature and time. For the setup used, an optimum mixing
time and temperature were suggested, resulting in a better mixing effectiveness, maximum density, and minimum air permeability and specific surface area.
© 2012 Elsevier B.V. All rights reserved.
1. Introduction
Prebaked carbon anodes are used in electrolysis cells to produce aluminum. Calcined petroleum coke and coal tar pitch are mixed to make
anode paste. In a homogeneous paste, coke aggregates are uniformly distributed in the binder matrix that is a mixture of pitch and fine coke
particles. Pitch and binder matrix have also the possibility to penetrate
into the coke pores during mixing. Better mixing can result in a more homogeneous paste and a better penetration of pitch. This can lead to a
compacted paste with lower amount of trapped air between and within
the particles. The anode properties are thus improved by reducing electrical resistivity, air permeability and carbon consumption that can lead to
longer service life and improved energy efficiency in the electrolysis
cell. A good mixing process has also the potential to reduce the pitch consumption leading to lower level of volatiles and thus reducing the internal
pressure and cracking rate during the anode baking cycle [1]. Efficient
mixing can be performed using sufficient mixing power and time and
proper mixing temperature.
Although effects of raw materials and anode making parameters on
the baked anode quality have been extensively investigated, little has
been published on the influence of mixing variables. Belitskus [2] studied
the effects of preheating temperatures, mixing time and mold temperature on the green and baked apparent density as well as electrical resistivity of bench scale anodes. He reported an optimum mixing time for a
given raw material and mixer, beyond which mixing could be detrimental to anode properties. The effects of pitch content and mixing time,
temperature and intensity on the volume of intra-particle pores (0.02–
100 μm) were explained by Stokka [3]. He found that with increasing
mixing temperature and pitch content, a shorter mixing time was required to obtain a given volume of paste porosity. Clery [4] used paste
density as an indication for optimizing the mixing process to obtain anodes with consistent green apparent density. He described that using
an intensive mixer after the kneader can improve the mixing effectiveness. However, he did not describe how mixing variables influence
paste and green anode properties. Azari et al. [5] studied the influence
of mixing time and temperature on the pore volume and pore size in
the paste before compaction. They reported the optimum mixing variables to obtain the minimum paste porosity.
The importance of anodes in the aluminum industry and the state of
limited research performed on the mixing process, indicate the necessity
of studying the effect of mixing variables which is expressed by
Table 1
Chemical composition of coke used for anode fabrication.
⁎ Corresponding author at: NSERC/Alcoa Industrial Research Chair MACE3 and Aluminium Research Centre — REGAL, Laval University, Quebec, QC, Canada G1V 0A6.
E-mail address: [email protected] (H. Alamdari).
0032-5910/$ – see front matter © 2012 Elsevier B.V. All rights reserved.
http://dx.doi.org/10.1016/j.powtec.2012.10.043
Na [ppm]
Si [ppm]
%S
Ca [ppm]
V [ppm]
Fe [ppm]
Ni [ppm]
100 ± 7
120 ± 17
2.13 ± 0.06
130 ± 7
360 ± 18
460 ± 23
250 ± 13
342
K. Azari et al. / Powder Technology 235 (2013) 341–348
Table 2
Properties of coal tar pitch used as binder in anode samples.
Mettler softening point
(°C)
Quinoline insoluble
(%)
109
15.5
Table 4
Mixing time and temperature for anode pastes.
Viscosity
Sample
158 °C 168 °C 178 °C 188 °C
4.08
3.15
1.12
Time (min)
Temperature (°C)
0.66
homogeneity and properties of green and baked anode. This study aimed
to investigate the influence of mixing time and temperature on the green
and baked anode features using several characterization techniques.
X-ray computed tomography, mercury porosimetry, air permeability
and BET surface area were carried out to determine the mixing effectiveness. This work can be used to optimize the commercial anode fabrication
parameters.
2. Materials and methods
2.1. Sample preparation
Commercially available calcined petroleum coke with a real density of 2.057 g/cm 3 and coal tar pitch were used as raw materials for
manufacturing the bench scale anodes. Chemical composition of the
coke and pitch properties are indicated in Tables 1 and 2, respectively.
The coke was classified into desired size fractions and a fine fraction
was made using a ball mill. Table 3 shows the size distribution of
coke particles used for making the anode paste. The pitch/coke ratio
was 16.2/100 for all samples. Pitch and different size fractions of
coke were individually weighed and added into the mixer to avoid
variations in the composition of samples.
Coke fractions and pitch were preheated in an oven for 120 and
30 min [5], respectively, at the mixing temperatures shown in
Table 4. The mixing parameters were selected based on a previous
work on anode paste [5]. The preheated materials were mixed in a
Hobart N50 mixer using seven combinations of mixing time and
temperature, indicated in Table 4. The mixer was installed in the
preheating oven to ensure a uniform temperature. The pastes were
compacted at 150 °C in a rigid cylindrical mold with a hardness of
55 Rockwell C and an internal diameter of 68 mm. Compaction was
performed at a constant displacement rate of 10 mm/min to a
maximum pressure of 60 MPa. The details for compaction conditions
applied to the pastes have been explained elsewhere [6]. Three samples for each set of mixing parameters were made.
1
2
3
4
5
6
7
6
178
10
178
15
178
20
178
10
158
10
168
10
188
0.15× 0.15× 0.6 mm3 (pixel length× pixel width× slice thickness)
using a Siemens Somatom Sensation 64, shown in Fig. 1. The CT numbers gave a 3D density map of the sample. MATLAB software was used
to construct the images from CT numbers and to analyze the data. Average and standard deviation of CT numbers were calculated. Maximum
height of CT number profile was defined as the difference between
the maximum and minimum CT numbers along the diameter of a
slice. The maximum height of CT number fluctuations was determined
along the diameter of 10 slices from each green sample and the average
was calculated. The 10 slices had similar positions in each whole green
anode.
Two sections with a thickness of 20 mm were cut from the bench
scale green compacts, as shown in Fig. 2. The volume of sections 1
and 2 was measured using water displacement method with a precision of 0.1 ml. and green apparent density (GAD) was determined
(± 0.002 g/cm 3). The samples had been covered with a known
volume of paraffin to avoid water penetration in the open pores.
The green samples were then cut and a helium pycnometer
(Micromeritics, AccuPyc II 1340) was used to measure the volume
of few chunks with a weight of 50–62 g. Gas pycnometer results for
this material are not sensitive to the sample size when it lies in cm
range. This volume consists of the volume of the material and the
volume of closed pores. The percentage of open porosity in the
total volume of green samples was determined using the green
apparent density of section 1 and the density determined by Hepycnometer (Eq. (1)).
% Open porosity ¼
Density by pycnometer−Apparent Density
100
Density by pycnometer
ð1Þ
A mercury porosimeter (Micromeritics, AutoPore IV) was used to
measure the pore volume and pore size distribution of the green samples to study the influence of mixing time and temperature on the penetration of binder matrix into the coke pores and cracks. Green parts
with the weight of 6.5–8.5 g were used for pore structure analysis.
2.2. Characterization of green samples
2.3. Characterization of baked samples
Apparent density of the green compacts was calculated using geometrical volume and mass. X-ray computerized tomography (CT) was
also used to determine the homogeneity of the distribution of
porosity, pitch and coke particles in the green sample as an indication
of mixing effectiveness. X-ray computed tomography is a nondestructive method to obtain 3D attenuation of X-ray in material. The
attenuation depends on atomic number and bulk density of the material. When attenuation is calibrated, the intensity of X-ray, expressed by
CT numbers in Hounsfield unit (HU), can be associated with density
[7] as Adams [8] and Picard [9] did for apparent density of carbon
anodes. One sample for each set of mixing variables was selected and
the entire green sample was scanned with a voxel resolution of
Section 2 of the samples was baked at a maximum temperature of
1130 °C for 12 h. Water displacement method was used to determine
the baked apparent density (BAD). The baked samples were core drilled
to disks with a diameter of 50 mm and thickness of 20 mm. Air permeability was determined following ISO Standard 15906 using R&D
Carbon equipment. The disks were then cut and the volume of few
chunks with a weight of 40–47 g was measured by the helium pycnometer. The percentage of open porosity in baked samples was determined
using the baked apparent density of section 2 and pycnometry results
(Eq. (1)). Specific surface area of the baked chunks with a weight of
2.3–2.8 g was measured using BET method (Micromeritics, TriStar II).
Table 3
Size distribution of coke particles in the paste samples.
Size range (US mesh)
Wt.%
−4 + 8
22.0
−8 + 16
10.0
−16 + 30
11.5
−30 + 50
12.7
−50 + 100
9.5
−100 + 200
17.2
−200 + 400
8.7
−400
8.4
K. Azari et al. / Powder Technology 235 (2013) 341–348
Fig. 1. CT scanner used for green samples (Siemens Somatom Sensation 64).
3. Results
3.1. Green anodes
Green apparent density variations were investigated to reveal the
influence of mixing variables. Fig. 3 shows the average of green apparent density for the entire samples as well as for sections 1 and 2, as a
function of mixing time (Fig. 3.a) and temperature (Fig. 3.b). It can be
observed that there is a meaningful variation in GAD depending on
both variables. At a mixing temperature of 178 °C, when mixing time
was extended from 6 to 10 min, the obtained density increased; while
mixing for longer than 10 min led to a slightly lower green apparent
density, as shown in Fig. 3.a. For a mixing time of 10 min in Fig. 3.b,
when mixing temperature increased from 158 °C to 178 °C, the average
GAD of the entire samples increased from 1.47 g/cm3 to 1.51 g/cm3.
Further increase of mixing temperature to 188 °C reduced the green
density to 1.49 g/cm3. As expected, Fig. 3 confirms that a density gradient exists and GAD reduces from top to the bottom of the samples, produced with a one-side compaction method.
Volume percentage of open pores in section 1 was calculated using
Eq. (1) and is shown in Fig. 4. As expected, the results follow a trend
in agreement with GAD variation, i.e. the minimum volume of open
pores was obtained when the anode paste was mixed for 10 min at
178 °C.
Density gradients highlighted previously were investigated using
X-ray computed tomography by means of density profiles in the
green samples. Fig. 5 demonstrates an example of CT profile of slices
(0.6 mm thickness) located at the middle of the height of three samples made with different mixing times and temperatures. It also indicates the fluctuations in the profile along the diameter of the slices.
Average CT number was used as an indication of average apparent
density. Fig. 6.a shows an example of gradient in apparent density
determined by average CT number, along the height of a green sample. Fig. 6.b demonstrates both vertical and radial gradient in density.
Density decreased from the central axis to the border of the sample
which is due to the wall effect in the mold. It is more obvious towards
the bottom of the sample.
Standard deviation of CT number was used to express the degree
of homogeneity in the distribution of porosity, pitch and coke particles throughout the paste. The CT number of a voxel represents the
GAD
CT scan
1
GAD
2
GAD
3
D=68 mm
343
presence and the amount of pitch, coke and air (pore) in the voxel.
Pitch is a carbonaceous material and its CT number is close to that
of coke. In addition, binder matrix that fills the voids between the
large particles contains pitch and fine coke particles. Thus, the
major difference between the CT numbers is due to the presence or
dispersion of the pores in the voxels, rather than the non-uniform
distribution of pitch or coke particles. In other words, CT with the
voxel resolution of 0.15 × 0.15 × 0.6 mm 3 can reveal large inhomogeneity in the distribution of pitch and coke, such as accumulation of
pitch and agglomeration of the fine particles, where a voxel consists
of only pitch or coke. The maximum height of CT number profile
can be another indicator for density fluctuations along a linear path.
Fig. 7.a shows standard deviation of CT number as a function of
mixing time for both entire green samples and the section 1 of each
sample. CT number decreases when mixing time increases from
6 min to 10 min but it does not show a meaningful variation when
the time is extended beyond 10 min. It may be an indication that
mixing for 10 min at 178 °C resulted in the homogeneous distribution of porosity, pitch and coke aggregates. Fig. 7.b shows that for
both entire green samples and the section 1 of each sample, the average CT number increases by increasing mixing time up to 10 min.
Again, this average does not change significantly by further increase
of mixing time. This is in agreement with GAD results presented in
Fig. 3.a since the average CT number is directly related to the GAD.
Anodes with mixing time of 10 min showed the minimum height in
the CT number profile that means the minimum density fluctuations.
Standard deviation of CT numbers as a function of mixing temperature is presented in Fig. 8.a. It is noted that the standard deviation
decreases significantly by increasing the mixing temperature from
158 °C to 178 °C and it increases by further increase in mixing temperature. The average CT number vs. mixing temperature for both entire
samples and section 1 of each sample (Fig. 8.b) confirms the GAD results
presented in Fig. 3.b assuming once again that GAD is directly related to
the average CT number. The minimum height of the CT number profile
was also observed for the samples mixed at 178 °C for 10 min.
Section 1 of the green samples demonstrated larger average of CT
number compared to the entire samples. It confirms the density gradient in the entire anode and higher density in top layers of the sample, as indicated in Figs. 3 and 6.
Pore size distribution of green samples was determined by mercury porosimetry. The samples consist of large pores in the range of
300–500 μm, medium pores between 5 μm and 30 μm, and small
pores smaller than 5 μm. Fig. 9 shows that with extending mixing
time from 6 to 20 min at 178 °C the size of the largest medium pore
decreased from 24 μm to 12 μm. The maximum size of medium
pores also reduced from 26 μm towards 11 μm with increasing
mixing temperature from 158 °C to 188 °C.
3.2. Baked anodes
Apparent density of the baked sections (section 2) was studied as a
function of mixing parameters. As indicated in Fig. 10.a, when mixing
time was increased from 6 to 10 min at a mixing temperature of
178 °C, the average BAD was improved from 1.47 g/cm3 to 1.52 g/cm3.
Extended mixing time to 15 and 20 min decreased the density to
1.485 g/cm3 and 1.489 g/cm3, respectively. For a mixing time of
10 min, when mixing temperature increased from 158 °C to 178 °C,
Baking
1130oC, 12 hr
Hg-porosimeter
He-pycnometer
BAD
Core sample
D=50 mm
Air permeability
He-pycnometer
BET surface area
Fig. 2. Schematic representation for characterization of green and baked samples.
344
K. Azari et al. / Powder Technology 235 (2013) 341–348
b
1.56
Mixing temperature: 178 C
1.54
1.52
1.5
1.48
Entire sample
Section 1
Section 2
1.46
1.44
0
5
10
15
20
25
Green apparent density (g/cm3)
Green apparent density (g/cm3)
a
1.56
Mixing time: 10 minutes
1.54
1.52
1.5
1.48
Entire sample
Section 1
Section 2
1.46
1.44
150
160
Mixing time (min)
170
180
190
200
Mixing temperature (C)
Fig. 3. Dependence of green apparent density on (a) mixing time at a constant mixing temperature of 178 °C; (b) mixing temperature for a constant mixing time of 10 min.
C
1.55
19
1.5
18
17
1.45
16
15
1.4
%Open porosity
Green apparent density
14
13
1.35
0
5
10
15
20
25
Mixing time (min)
Mixing time: 10 minutes
21
1.55
20
19
1.5
18
17
1.45
16
15
1.4
14
%Open porosity
Green apparent density
13
12
150
160
170
180
190
1.35
200
Green apparent density (g/cm3)
Mixing temperature:
20
Open porosity in green samples (%)
b
178o
Green apparent density (g/cm3)
Open porosity in green samples (%)
a
Mixing temperature (oC)
Fig. 4. Dependence of open porosity of section 1 on (a) mixing time at a constant mixing temperature of 178 °C; (b) mixing temperature for a constant mixing time of 10 min.
Fig. 5. Constructed images form CT numbers and the profile of CT number along the diameter (black line) of green samples made with different mixing times and temperatures.
the average BAD increased from 1.44 g/cm3 to 1.52 g/cm3, as shown in
Fig. 10.b. This is in agreement with the GAD results in Fig. 3.b where
mixing temperature of 178 °C resulted in the highest green density.
Mixing at 188 °C slightly reduced the baked density to 1.485 g/cm3.
The percentage of open porosity in the total volume of baked sections was calculated using the baked apparent density and the density determined by He-pycnometer. The results are compared with
baked apparent density in Fig. 10 and are in a good accordance, as
K. Azari et al. / Powder Technology 235 (2013) 341–348
a
b
345
140
390
Top
Botto
120
370
Height (voxel)
Average CT number (HU)
410
350
330
310
290
270
500
100
400
80
300
60
200
40
100
20
250
0
20
40
60
80
100
0
Height (mm)
0
50
100
150
0
200
Radius (voxel)
b
Average of CT numbers (HU)
a
Standard deviation of CT
numbers (HU)
170
160
150
140
130
Entire sample
Section1
120
0
5
10
15
20
1000
380
370
900
360
800
350
700
340
600
330
500
320
400
310
Entire sample
Maximum height of profile
300
0
25
Section 1
300
5
10
Mixing time (min)
15
20
25
Maximum height of profile (HU)
Fig. 6. Variations in the average CT number of a green sample mixed for 10 min at 178 °C (a) on the surface of the slices along the height; (b) on the circles with different radius on
the slices along the height (Radius 0 shows the center of the slice).
Mixing time (min)
Fig. 7. Results of CT numbers in the entire and the section 1 of anode samples mixed at 178 °C for different mixing times; (a) standard deviation of CT numbers; (b) average and
fluctuations of CT numbers.
200
190
180
170
160
150
140
130
120
150
Entire sample
160
170
Section 1
180
190
200
Mixing temperature (oC)
380
1000
360
900
340
800
320
300
700
280
600
260
500
240
400
220
200
150
Entire sample
160
Section1
Maximum height of profile
170
180
190
300
200
Maximum height of profile (HU)
b
Average of CT numbers (HU)
Standard deviation of CT numbers
(HU)
a
Mixing temperature (oC)
Fig. 8. Results of CT numbers in the entire and the section 1 of anode samples mixed for 10 min at different mixing temperatures; (a) standard deviation of CT numbers; (b) average
and fluctuations of CT numbers.
expected. Mixing time of 10 min and mixing temperature of 178 °C
resulted in the minimum percentage of open porosity. Air permeability of the baked sections, indicated in Fig. 11, validates the results of
apparent density and open pore content of the anodes.
In order to validate the effect of mixing variables on the mixing effectiveness the specific surface area (BET surface area) of small chunks of
the baked sections was measured. Mixing at 178 °C for 10 min resulted
in the lowest BET surface area (0.176 m2/g), as observed in Fig. 12.a. Specific surface area then increased to 0.237 m2/g with longer mixing times
as apparent density reduced. Fig. 12.b shows that BET surface area
reduced from 0.226 m2/g to 0.166 m2/g with increasing mixing temperature from 158 °C to 168 °C. Higher mixing temperatures up to 188 °C
resulted in a slight raise in the BET surface area. The trend of BET surface
area as a function of mixing temperature is not in accordance with that of
baked apparent density. In addition, one may expect that the BET value
increases by decreasing the density while, such a trend is not clearly observed. This inconsistency is partially due to the considerably large error
bars on some points, especially at low BET values. It could also be due to
the effect of pore size distribution. Large pores have a great contribution
to density and a small contribution to specific surface area. The small
pores, on the other hand, have the opposite effect greatly contributing
to BET value. For instance, one may note that in Fig. 9.b, the amount of
very large pores decreases as the mixing temperature increases and,
beyond 178 °C it begins to increase. At 178 °C, the sample exhibits a
346
K. Azari et al. / Powder Technology 235 (2013) 341–348
b
Log differential intrusion (ml/g)
0.5
Mixing temperature: 178oC
0.45
0.4
0.35
0.3
0.25
0.2
6 minutes
10 Minutes
15 minutes
20 minutes
0.15
0.1
0.05
0
100
10
1
Log differential intrusion (ml/g)
a
0.5
Mixing time: 10 minutes
0.45
0.4
0.35
0.3
0.25
0.2
158 C
168 C
178 C
188 C
0.15
0.1
0.05
0
100
0.1
Pore size radius (µm)
10
1
0.1
Pore size radius (µm)
Fig. 9. Effect of mixing time and mixing temperature on the pore size distribution of the green samples.
1.55
27
1.5
26
1.45
25
24
1.4
%Open porosity
23
Baked apparent density
22
1.35
0
5
10
15
20
25
Mixing time: 10 minutes
28
1.55
27
1.5
26
1.45
25
24
1.4
23
%Open porosity
Baked apparent density
22
150
160
170
180
190
1.35
200
Baked apparent density (g/cm3)
Mixing temperature: 178 C
28
Open porosity in baked samples (%)
b
o
Baked apparent density (g/cm3)
Open porosity in baked samples (%)
a
Mixing temperature (oC)
Mixing time (min)
4
1.45
3
2
1.4
1
Baked apparent density
Permeability
1.35
0
0
5
10
15
20
25
Mixing time (min)
Mixing time: 10 minutes
1.55
6
5
1.5
4
1.45
3
2
1.4
1
Baked apparent density
1.35
150
Permeability
160
170
180
190
Permeability (npm)
5
1.5
3
6
Baked apparent density (g/cm )
Mixing temperature: 178oC
1.55
Permeability (npm)
Baked apparent density (g/cm3)
Fig. 10. Dependence of baked apparent density and open porosity of baked samples on (a) mixing time at a constant mixing temperature of 178 °C; (b) mixing temperature for a
constant mixing time of 10 min.
0
200
Mixing temperature (oC)
Fig. 11. Effect of mixing time and mixing temperature on the air permeability of the baked sections.
maximum density thus the minimum BET value is expected. This is not
observed since the small pores compensate the effect of total pore volume fraction.
4. Discussions
4.1. Mixing time
Extending mixing time from 6 to 10 min resulted in an increase in
the green apparent density (Fig. 3.a) and decrease in the volume of
open pores of green anodes (Fig. 4.a), when mixing was performed at
178 °C. The trend of the average CT number in Fig. 7.a also confirms
the GAD determined by water displacement. Mixing for longer times
of 15 and 20 min led to a minor decrease in both GAD and average CT
number. It suggests that mixing time is a variable with considerable
influence on the anode quality. For the mixing process and mixer used
in this study, 10 min was the optimum mixing time which may have
resulted in a better distribution of coke particles and pores in the
paste and more uniform distribution of pitch over the aggregates. The
continuous pitch film that forms over the particles may have two consequences; a better particle rearrangement and densification during
compaction, and improved compression strength after baking due to a
better pitch-coke bridging between the coke particles [10]. The hypothesis of more uniform distribution is supported when the variations in
the CT number are considered (Fig. 7.b). Anodes with mixing time of
10 min demonstrated the minimum standard deviation for CT number
and minimum height of CT number profile which is an indication for
more homogeneous paste. It may have also resulted in more penetration of binder matrix into the coke pores which contributed to enhancing the GAD. Fig. 9.a reveals that with longer mixing time smaller pores
in green samples were filled by binder matrix and the maximum size of
medium pores (30–5 μm) reduced from 24 μm to 12 μm.
Baked samples with 10 min of mixing also showed the maximum apparent density and therefore the minimum percentage of open pores and
air permeability. A decrease in BET surface area for baked samples was
also observed when mixing time was increased from 6 to 10 min. It
1.55
0.3
1.5
0.25
1.45
0.2
1.4
0.15
BET surface area
Baked apparent density
1.35
0.1
0
5
10
15
20
25
BET surface area (m2/g)
BET surface area (m2/g)
b
Mixing temperature: 178oC
0.35
Baked apparent density (g/cm3)
a
0.35
347
1.55
Mixing time: 10 minutes
0.3
1.5
0.25
1.45
0.2
1.4
0.15
BET surface area
Baked apparent density
0.1
1.35
150
160
170
180
190
Baked apparent density (g/cm3)
K. Azari et al. / Powder Technology 235 (2013) 341–348
200
Mixing temperature (oC)
Mixing time (min)
Fig. 12. Influence of mixing time and mixing temperature on the BET surface area of the baked sections.
can be another indication for penetration of binder matrix into the coke
pores with a more effective mixing. Similar effects of mixing time have
previously been observed on green paste properties [5].
Mixing for longer than 10 min resulted in a decrease in BAD and an
increase in open porosity, air permeability and BET surface area. Belitskus
[2] had reported the degradation of anode properties with mixing over
an optimum time. Particle breaking may occur due to over mixing and,
therefore, new surfaces will appear which may have lower chance to
be wetted by pitch. In addition, the coke granulometry is changed.
These uncovered surfaces as well as non-optimum granulometry deteriorate the paste compaction and lead to lower density and higher porosity
and permeability. When particles are broken, closed pores in coke particles have the chance to become open to the new surfaces. These empty
pores contribute to the increase in open porosity and specific surface
area, as demonstrated in Figs. 10 and 12, respectively. Fig. 9.a also indicates that the volume of large pores has increased with mixing over
10 min. Longer mixing times may also result in the coke attrition and incorporation of new coke fines into the pitch [2]. This increases the viscosity and results in lower penetration ability of pitch. High viscosity of pitch
may also decrease the amount of binder-coke bridges that form between
coke particles resulting in paste degradation and lower density.
4.2. Mixing temperature
Increasing mixing temperature from 158 °C to 178 °C resulted in
an increase in the green apparent density, average CT number and
baked apparent density of the anodes, indicated in Figs. 3, 8.a, and
10, respectively. Mixing at 188 °C for 10 min led to a decrease in
GAD, average CT number and BAD. According to pitch softening
point of 109 °C, the pitch is not fluid enough at 158 °C. The viscous
pitch results in agglomeration of the fine particles without penetration into the open pores. High standard deviation of CT numbers,
shown in Fig. 8.b, confirms the non-uniform distribution in anodes
mixed at 158 °C. Such a low mixing effectiveness and heterogeneity
in the paste led to the highest porosity, permeability and BET surface
area, as shown in Figs. 4.b, 11 and 12, respectively. Increasing the
mixing temperature to 178 °C reduced the viscosity of pitch, as indicated in Table 2, which may have improved its distribution and flowability
and increased its penetration and pore filling effect. The results of a previous work [5] made on the same samples of the current work are
shown in Fig. 13 and indicate that after mixing at 178 °C more coke
pores are filled by pitch comparing to the mixing temperature of
158 °C. Fig. 9.b exhibits that higher mixing temperature led to pitch
penetration into smaller pores and the maximum size of medium
pores reduced to 11 μm. This resulted in the maximum density and consequently the minimum level of porosity and permeability.
Further increase of mixing temperature to 188 °C resulted in a decrease in apparent density and deteriorated anode porosity and permeability. It can be due to the fact that viscosity of pitch decreases at higher
temperatures and improves the pitch penetration into the coke pores.
Thus, the amount of remained pitch may not be enough to fill the
voids between the particles [2,3]. It is shown in Fig. 9.b where with increasing the mixing temperature over 178 °C, the volume of large
pores increased. This increase in the volume of voids between the particles can be responsible for the increase observed in BET surface area
when the temperature was increased from 168 °C to 188 °C (Fig. 12).
It has also been reported that optimum mixing time decreases for
higher mixing temperatures [3]. A mixing time of 10 min at 188 °C
may thus be longer than the optimum time at this temperature.
5. Conclusion
Consistent high quality anodes are a basic requirement of anode industry. Mixing the anode constituents is an important step in the anode
Fig. 13. Microstructure of green samples mixed for 10 min at (a) 158 °C and (b) 178 °C [5]. The samples are impregnated with resin and polished. White arrows indicate open pores
filled by resin while black ones demonstrate the pores filled by pitch (light gray: coke, medium gray: resin, dark gray/black: pitch).
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K. Azari et al. / Powder Technology 235 (2013) 341–348
production so that the mixing variables can influence the mixing effectiveness and consequently the anode quality. The results of the current
study showed that there is an optimum mixing time and temperature to
improve the distribution of coke, pitch and porosity and penetration of
binder matrix, leading to enhanced anode density. Mixing parameters,
including time and temperature, influenced homogeneity, pore volume
and pore size, and therefore the density and permeability of the anodes.
It can be suggested that for the materials and experimental setup used
in this study, mixing at 178 °C for 10 min revealed the best mixing effectiveness and resulted in the lowest volume of pores, specific surface
area and permeability.
Acknowledgment
Authors would like to acknowledge the financial support of NSERC
and Alcoa. A part of the research presented in this paper was financed
by the Fonds de Recherche du Québéc-Nature et Technologies (FRQ-NT)
by the intermediary of the Aluminium Research Centre — REGAL. The
assistance of INRS in Quebec City for conducting the tomography tests
is gratefully acknowledged. The authors would also like to extend
their appreciation to Dr. Donald Ziegler from Alcoa Canada Primary
Metals for the scientific discussions as well as Pierre Mineau at
Alcoa, Deschambault plant, and Martin Plante at Laval University for
their technical support.
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Kamran Azari received his MSc degree in Materials Science and Engineering in 2001 from Isfahan University of
Technology, Iran. He worked at Naghsh Jahan Steel Research Institute, Iran on the optimization of steelmaking
processes to improve steel cleanliness. In 2008, he pursued
his academic formation. He is currently a PhD student at
the Department of Mining, Metallurgical and Materials Engineering, Université Laval, Canada. His research project is
on the carbonaceous raw materials and formation of
prebaked anodes used in Aluminium production, in collaboration with Aluminium Research Centre-REGAL and
Alcoa Canada.
H. Alamdari received his MSc degree in 1996 and PhD degree in 2000 from Université Laval, Canada. He pursued his
research activities at Hydro-Québec research institute,
Canada on synthesis of nanocrystalline materials for hydrogen storage. He held the process director position at
Nanox Inc, Canada and was involved in development and
scale up of a production process for nanostructured
perovskite-type materials for automotive catalysts. In
2006, he joined Laval University as professor at Department of Mining, Metallurgy and materials Engineering,
Université Laval, Canada. He is currently the director of Regal–Laval research center where his research activities are
focused on aluminum production process.
Gholamreza Aryanpour, earned his PhD from Universite
Grenoble I, France in 1999. He has been an assistant professor in Isfahan University of Technology from 1999 to
2009. Since 2009 he has been working in the Universite
du Quebec a Chicoutimi and then in Universite Laval as a
professional researcher. His research interests are in the
fields of metallurgy and mechanics of materials.
Donald Picard graduated from Université Laval in Mechanical Engineering and completed his PhD in 2007 in
the field of carbon materials characterisation. He has developed an expertise in the field of thermomechanical
characterisation of carbon materials and in modeling of
viscoelastic constitutive laws. He is actually a professional
researcher at Université Laval and he is mainly involved in
one Industrial Research Chair and one Collaborative Research and Development projects financed by the Natural
Sciences and Engineering Research Council of Canada
(NSERC) and Alcoa Canada.
Mario Fafard is a Professor at Université Laval since 1987.
He is the holder of the NSERC/Alcoa Industrial Research
Chair, at the Civil and Water Engineering Department. His
main research interests are in the areas of advanced numerical modeling of aluminum cell, and thermomechanical testing on refractory materials at high temperature. He is also
the founding director of the Aluminium Research Centre —
REGAL in the Province of Quebec, Canada.
Dr. Angelique Adams is the Global Technology Development Director in Alcoa's Global Primary Products Business
Unit. She has accountability for the strategic development
of the R&D program for smelting conventional technology
and for driving implementation of new smelting technologies across Alcoa's global system. Angelique has 14 years of
smelting experience in operations, technical support, and
R&D. Angelique has a B.S. in Chemical Engineering and an
M.S. and Ph.D. in Fuel Science from the Pennsylvania State
University.