Abstract— The paper presents the results of laboratory
experiments on steel desulphurization and deoxidation with slag
from the system CaO-SiO2-TiO2. To determine the influence, on the
desulphurisation and deoxidation process, of the titanium oxide
added in calcium aluminate slag, we experimented, in the
laboratory phase, the steel treatment with a mechanical mixture
consisting of lime, aluminous slag and slag obtained from the
titanium making process through the aluminothermic technology.
The data obtained in the experiments were processed in Excel and
MATLAB programs, resulting simple or multiple correlation
equations, which allowed the elucidation of some physical-
chemical phenomena specific to the desulphurisation processes.
Keywords— desulphurisation and deoxidation process, fluorine,
synthetic slag, steel, refining.
I. INTRODUCTION
The steel refining with liquid slag or various powder
mixtures of synthetic slag is based on the intensification of the
unwanted impurities (sulphur, non-metallic suspensions &
oxygen) passage from the liquid steel in the slag, mainly by
diffusion, or partly through the entrainment of some
suspensions by settling the synthetic slag particles found in the
treated steel bath. The synthetic slag can be also obtained by
adding mechanical mixture directly in the casting ladle; in this
case, for compensating the cooling of the steel in the casting
ladle due to the addition of materials (melting and
superheating), the steel temperature should be at least 20-40oC
higher than the normal one. In the practice of deoxidation with
synthetic slag, we usually use slag that correspond to the
binary systems CaO-Al2O3, CaO-TiO2 and CaO-CaF2, or to the
ternary systems CaO-SiO2-Al2O3 and CaO-CaF2-Al2O3.
According to the literature, the best results were obtained with
synthetic slag that corresponds to the binary system CaO-
Al2O3, containing 50-52% CaO and 38-42% Al2O3.
The viscosity of the synthetic slag has significant influence on
the development of physical and chemical processes during the
treatment of the liquid steel, interfering with significant weight
on the emulsifying capacity of slag. The increase of the slag
viscosity from 0.15 to 0.45 Ns/m2 (from 1.5 to 4.5 Poise)
determines the decrease with approx. 30% of the steel-slag
interaction surface. Such increasing of the calcium aluminate
slag viscosity can be seen when its temperature is decreasing
(for example, from 1600oC to 1470oC). Therefore, it is very
important to ensure, during processing the steel with liquid
slag, the optimum thermal regime specific to the chosen slag
type and to realise its convenient fluidity (viscosity).
At the temperatures of treating the steel with synthetic slag
in the ladle, the minimum viscosity corresponds to the slag
with 56% CaO. But, taking into account the fact that frequent
deviations (1-2%) may occur from this optimum composition
under industrial conditions, we should also consider the danger
of reaching unwanted values (higher than 57% CaO).
Therefore, in the industrial practice it is recommendable a
content of 52-54% CaO in slag, for which the normal
composition deviations can’t provoke sudden viscosity
increases.
The viscosity of the synthetic slag is also influenced by
other components; it increases significantly with the increasing
of the SiO2 content, while MgO contents up to 8% are
favourable. At temperatures higher than 1500oC, the viscosity
is slightly decreasing when adding TiO2 in the calcium
aluminate slag.
Usually, the chemical composition of the synthetic slag that
corresponds to the CaO – Al2O3 system, frequently used in
practice, varies between the following limits: CaO = 48 – 55%;
Al2O3 = 40 -45%; SiO2 = maximum 3.0%; MgO = maximum
3% and FeO = maximum 1%, the balance being other oxides.
Because the diffusion speed in slag increases with increasing
temperature (T) and decreasing viscosity (η), we can highlight
the special importance of the synthetic slag viscosity (i.e. its
fluidity φ=1/η) in the process of treating the steel with
synthetic slag.
Similarly, the bigger is the contact surface between the
synthetic slag and the metallic bath, the faster is the passage of
the significant elements to the slag, the contact surface being,
along with the viscosity, another determinant element in
treating the steel with synthetic slag.
II. PROBLEM FORMULATION
To determine the influence, on the desulphurisation and
deoxidation process, of the addition of titanium oxide in the
calcium aluminate slag, we performed laboratory experiments,
i.e. we treated the slag with liquid synthetic slag obtained by
melting the mixture consisting of limestone, aluminate slag and
slag obtained from the titanium making process through the
aluminothermic technology.
The steel melting was carried out in an induction furnace of
10 kg capacity and the slag melting was carried out in a
crucible furnace (furnace Tammann), both existent in the
″METALLIC MELTS″ laboratory of the Engineering Faculty
of Hunedoara.
Research on steel refining
Adriana PuŃan, HepuŃ Teodor, Vîlceanu Lucia, Vasile PuŃan
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The charge to be melted consisted of steel samples (samples
of steel for tubes, taken from the casting ladle before the LF
treatment, i.e. before introducing the steel in the LF).
To form the liquid synthetic slag, we melted in the crucible
furnace a mechanical mixture consisting of limestone, calcium
aluminate slag (from melting the aluminium scrap) and slag
obtained from the titanium making process through the
aluminothermic technology. The steel quantity obtained was
10 kg/heat, and was poured into two pots of 5 kg capacity
each. The extra liquid slag was poured into the ladle at a rate
of 3%, respectively 150g/laddle (about 300g/stance) before
casting the steel, which ensured a good mix between the two
melts. A number of 20 batches was elaborated, and each was
poured in two pots. By removing the two samples, two bars
were made from each pot.
To determine the sulphur distribution coefficient, we took
steel and slag samples before and after the treatment, in order
to find the sulphur content and chemical composition of the
slag. We also measured the steel and slag temperature before
and after the treatment. The chemical composition of slag
varied among these limits: CaO = 48-58% Al2O3 ≤ 39%,
SiO2 ≤ 20% TiO2 = 2-23% MgO ≤ 1 5%, FeO = 0.25% - 3%
MnO = 0.25 - 2%.
III. PROBLEM SOLUTION
By processing the data obtained in the laboratory phase, we
obtained equations of correlation between the chemical
composition of the synthetic slag and the sulphur distribution
coefficient (L.S), that the degree of removal of oxygen (ηO)
The data were processed in Excel and MATLAB programs,
the results being presented hereunder, in graphical and
analytical forms.
y = -0,0035x4 + 0,2044x3 - 4,2184x2 + 25,188x + 180,7
R2 = 0,9909
y = -0,0001x4 + 0,0406x3 - 1,3722x2 + 6,1429x + 179,81
R2 = 0,9915
y = -0,0023x4 + 0,1425x3 - 3,0382x2 + 16,332x + 179,73
R2 = 0,9178
0
50
100
150
200
250
0 5 10 15 20 25
TiO2 content in slag, %
Sulfur distribution coefficient
Fig. 1 The variation of the sulphur distribution coefficient versus
the TiO2 content in slag
In Fig. 1, we can see that a TiO2 content increase up to 5-
6% leads to the increasing of the L.S., fact explicable, from a
technological point of view, through to the positive influence
of the titanium oxide on the slag fluidity, especially at
temperatures above 1500oC. Therefore, we recommend
contents of 3-6% TiO2 in the refining slag.
In Fig. 2, we see that the increase of the MgO content up to
approx. 8% leads to the increasing of the L.S., fact explicable,
from a technological point of view, by the favourable influence
of this oxide on the viscosity (the viscosity is decreasing).
Therefore, from a technological point of view, we recommend
the maximum MgO content to be 6%.
y = 0,0052x4 - 0,1157x3 + 0,0254x2 + 9,3916x + 178,95
R2 = 0,9788
y = -0,0064x3 + 0,3079x2 - 1,742x + 178,02
R2 = 0,9694
y = -0,0001x4 + 0,05x
3 - 1,2917x
2 + 10,034x + 178,18
R2 = 0,2877
150
160
170
180
190
200
210
220
230
0 2 4 6 8 10 12 14 16
MgO cotent in slag, %
Sulfur distribution coefficient
Fig. 2 The variation of the sulphur distribution coefficient versus the
MgO content in slag
In Fig. 3, we see that the increasing of the SiO2 content
leads to the decreasing of the L.S., which can be explained,
from a technological point of view, on the one hand by the slag
viscosity increasing with the SiO2 content increasing and, on
the other hand, by the decreasing of the free CaO content, the
main oxide in slag that directly participates to the
desulphurisation process. From the graphical representation,
we can see that, when the SiO2 content is increasing, the
variation range of the L.S. becomes narrower and narrower,
especially for values higher than 5%. Technologically, we
recommend the maximum SiO2 content to be 3%.
y = 0,026x3 - 0,2672x2 - 17,68x + 265,03
R2 = 0,9407
y = 0,7411x2 - 27,527x + 262,96
R2 = 0,9078
y = -8,1153x + 134,3
R2 = 0,83770
50
100
150
200
250
300
0 5 10 15 20 25
SiO2 content in slag, %
Sulfur distribution coefficient
Fig. 3 The variation of the sulphur distribution coefficient versus the
SiO2 content in slag
The graphical representation presented in Fig. 4 shows that
the higher values for the L.S. (230-250) were obtained for a
CaO content of 52 -54%. According to the data presented in
the literature [5] the minimum viscosity of the slag that
corresponds to the CaO – Al2O3 system is obtained for
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contents of approx. 56% CaO, which confirms the results
obtained for the slag used in our experiments. The CaO
contents higher than 55%, determine the decreasing of the L.S.
values, because the slag viscosity is increasing. Having in view
that, in industrial conditions, there are frequent deviations
from the above mentioned range of chemical composition, we
recommend contents of 52-56% CaO.
y = -2,6096x2 + 277,61x - 7148,5
R2 = 0,9443
y = -2,13x2 + 227,14x - 5815,8
R2 = 0,748y = -2,1326x2 + 226,56x - 5766,8
R2 = 0,8463
150
170
190
210
230
250
270
45 47 49 51 53 55 57 59
CaO content in slag, %
Sulfur distributuon coefficient
Fig. 4 The variation of the sulphur distribution coefficient versus the
CaO content in slag
Analysing the graphical representation presented in Fig. 5,
we can see a variation in the L.S. depending on the Al2O3
content, similar to the variation depending on the CaO content
in slag. The maximum L.S. value was obtained at 34–37%
Al2O3. The increasing of the aluminium oxide content up to
values that vary between the above mentioned limits is due to
the decreasing of the slag viscosity and, in consequence, the
intensification of the sulphur diffusion in the slag bath. The
increasing of the Al2O3 content beyond the above mentioned
limits determines the decreasing of the L.S. values, as a
consequence of the slag viscosity increasing. We recommend
contents of 33-37% Al2O3 in slag.
y = -2,2412x2 + 158,23x - 2560,5
R2 = 0,5032y = -2,4841x2 + 175,96x - 2860,5
R2 = 0,811
y = -1,8553x2 + 130,52x - 2085,4
R2 = 0,6889
150
170
190
210
230
250
270
30 32 34 36 38 40
Al2O3 content in slag, %
Sulfur distribution coefficient
Fig. 5 The variation of the sulphur distribution coefficient versus the
Al2O3 content in slag
From the graphical correlations presented in Fig. 6 and 7,
we can see that the increasing of the FeO and MnO contents in
slag leads to the decreasing of the L.S., which is consistent
with the fact that the steel desulphurisation is encouraged by
strong basic slag (which presents high [O2-] values) and low
[O] contents. Technologically, for the slag types we have
studied, we recommend the maximum FeO content to be 1.5%
and the maximum MnO content to be 1.0%.
y = -7,0205x2 - 30,509x + 241,33
R2 = 0,9929
y = -15,771x2 - 4,4562x + 259,21
R2 = 0,9908
y = -9,7868x2 - 21,746x + 252,65
R2 = 0,9194
50
100
150
200
250
300
0 0,5 1 1,5 2 2,5 3 3,5
FeO content in slag, %
Sulfur distribution coefficient
Fig. 6 The variation of the sulphur distribution coefficient versus the
FeO content in slag
y = 6,5073x2 - 97,815x + 253,01
R2 = 0,9833
y = -18,177x2 - 47,331x + 270,4
R2 = 0,9728
y = -12,619x2 - 60,484x + 261,09
R2 = 0,9131
50
100
150
200
250
300
0 0,5 1 1,5 2 2,5
MnO content in slag, %
Sulfur distribution coefficient
Fig. 7 The variation of the sulphur distribution coefficient versus the
MnO content in slag
y = 0,5262x2 - 3,3374x + 51,558
R2 = 0,9237
y = 0,5401x2 - 3,5537x + 52,325
R2 = 0,9947
y = 0,5679x2 - 3,3494x + 50,935
R2 = 0,9872
45
46
47
48
49
50
51
52
0 0,5 1 1,5 2 2,5 3 3,5
FeO,%
Removal efficiency,%
med
max
min
Fig. 8 Oxygen removal efficiency depending on FeO
From Fig. 8 and 9 there is a decrease in oxygen removal effi
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ciency with increasing FeO and MnO that caused the
decrease of slag reducing character due to the increase in
oxygen content.
y = -1,827x4 + 4,5545x3 + 0,9097x2 - 9,3938x + 54,237
R2 = 0,8745
y = -3,4345x3 + 12,884x2 - 16,59x + 56,343
R2 = 0,91
y = -3,7705x3 + 14,065x2 - 17,674x + 55,365
R2 = 0,9539
45
46
47
48
49
50
51
52
53
54
0 0,3 0,6 0,9 1,2 1,5 1,8 2,1
MnO
Removal efficiency of oxygen,%
med
max
min
Fig. 9 Oxygen removal efficiency depending on MnO
On Fig. 10 and 11 is observed that reaches a maximum
removal efficiency of oxygen that has a CaO content 52-56%
and 34-38% clay content which has good fluidity, basic feature
of slags .
y = -0,1651x2 + 17,542x - 414,84
R2 = 0,9605
y = -0,1444x2 + 15,338x - 357,81
R2 = 0,9407
y = -0,0055x3 + 0,7315x
2 - 30,72x + 448,32
R2 = 0,867
43
44
45
46
47
48
49
50
51
52
45 50 55 60
CaO,%
Removal efficiencyof oxygen,%
med
max
min
Fig. 10 Oxygen removal efficiency depending on CaO
y = 0,0007x4 - 0,1193x3 + 6,8153x2 - 165,37x + 1493,1
R2 = 0,9752
y = -0,1979x2 + 14,016x - 195,89
R2 = 0,9527
y = -0,2269x2 + 16,182x - 237,64
R2 = 0,9281
43
44
45
46
47
48
49
50
51
52
53
28 30 32 34 36 38 40
Al2O3
Removal efficiency, %
med
max
min
Fig. 11 Oxygen removal efficiency depending on Al2O3
In the TiO2 content (Fig. 12) is getting good results of the
oxygen removal efficiency if the slag is 2-9% TiO2 content,
known as the ability to break the oxide anions complex
network, so flow positive influence, (as Al2O3).
y = -0,001x4 + 0,0472x3 - 0,7436x2 + 4,4419x + 41,984
R2 = 0,6195
y = -0,0006x4 + 0,0287x3 - 0,484x2 + 3,1259x + 42,959
R2 = 0,9304
y = -0,0009x4 + 0,0403x3 - 0,6235x2 + 3,555x + 44,973
R2 = 0,9598
45
46
47
48
49
50
51
52
53
0 3 6 9 12 15 18 21
TiO2
ηη ηηO2
med
max
min
Fig. 12 Oxygen removal efficiency depending on TiO2
For each correlation, we determined the equation of the
regression curve, along with the equations afferent to the
curves that bound the variation range (both upper and lower
limits). By processing the data in the MATLAB program, we
obtained multiple correlation equations and, by graphically
represented them, we obtained the correlation surfaces. To
establish the optimum chemical composition range, we
analysed the regression surfaces for finding the value of the
L.S., desirable above the average value obtained from the data
afferent to the analysed heats.
a)
b)
Fig. 13 The variation of the sulphur distribution coefficient (L.S)
versus the TiO2 and Al2O3 content in slag: a) surface; b) contour lines
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INTERNATIONAL JOURNAL of ENERGY and ENVIRONMENT
a)
b)
Fig. 14 The variation of the sulphur distribution coefficient (L.S)
versus the TiO2 and CaO content in slag: a) surface; b) contour lines
a)
b)
Fig. 15 The variation of the sulphur distribution coefficient (L.S)
versus the CaO and Al2O3 content in slag: a) surface; b) contour lines
7535.373049.12
7139.07016.43080.02473.0
4988.028670.021468.020.3260xv
−−
−+++−
−−++=
z
yyzxz
xyzy
6854.3432 =med
OAl
4657.5178813.20
5878.163080.08670.01478.0 22
+−
−−++=
y
xxyyxz
a)
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INTERNATIONAL JOURNAL of ENERGY and ENVIRONMENT
b)
Fig. 16 The variation of removal efficiency of oxygen versus the CaO
and FeO content in slag: a) surface; b) contour lines
a)
b)
Fig. 17 The variation of removal efficiency of oxygen versus the FeO
and Al2O3 content in slag: a) surface; b) contour lines
8625.53=medCaO
6598.82833.4
1060.222473.08670.03260.0 22
++
+−−+=
y
xxyyxz
a)
b)
Fig. 18 The variation of removal efficiency of oxygen versus the CaO
and Al2O3 content in slag: a) surface; b) contour lines
4758.1=medFeO
6439.54168.1
3367.44988.01478.03260.0 22
−+
++−+=
y
xxyyxz
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903.11
1903.115529.156874.30550.00825.0
5732.01097.00617.00.3247xv 222
−
−−++−+
+−++=
zyxyzxz
xyzy
232 TiOzCaOyOAlx ===
9613.498625.536854.34 === medmedmed zyx
a)
b)
Fig. 19 The variation of removal efficiency of oxygen versus the TiO2
and CaO content in slag: a) surface; b) contour lines
a)
b)
Fig. 20 The variation of removal efficiency of oxygen versus the TiO2
and Al2O3 content in slag: a) surface; b) contour lines
a)
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INTERNATIONAL JOURNAL of ENERGY and ENVIRONMENT
b)
Fig. 21 The variation of removal efficiency of oxygen versus the CaO
and Al2O3 content in slag: a) surface; b) contour lines
IV. CONCLUSION
Based on the experiments, on the results obtained from data
processing and on the technical analysis of these data, we
concluded the followings:
� From a technological point of view, the slag
types used in our experiments met our needs, mainly
due to their adequate fluidity;
� The chemical composition of the slag has a
significant influence on the L.S., either indirectly,
due to the viscosity, or directly, due to the affinity of
the oxide cautions to the sulphur anions and oxygen;
� We consider that it is possible to obtain very
good results in the desulphurisation and deoxidation
process by using synthetic slag having the following
chemical composition: CaO = 50 - 56%; Al2O3 = 34
- 38%; SiO2 ≤ 5%; TiO2 = 2 – 7%; MgO = 5 -10
%; FeO = 0,25% - 3%; MnO = 0,25 – 2%;
� Knowledge of graphics in MATLAB
PROGRAM allows limits of variation for the
chemical composition of slag in order to obtain the
value set for sulfur distribution ratio, that the degree
of removal of oxygen.
Based on the results obtained during the laboratory phase,
we believe that good results can be achieved under industrial
conditions, too. So, we propose to perform such experiments
in a future stage.
REFERENCES
[1] HepuŃ, T., Ardelean, E., Socalici, A., Maksay, St. Găvănescu, A., Steel
desulphurization with synthetic slag, Revista de Metalurgia 43(3),
Madrid, 2007, pp. 181-187.
[2] HepuŃ, T., Ardelean, E., Kiss, I., Some influence of the viscosity of
synthetic slags used in continuous steel casting, Revista de Metalurgia
41(3), Madrid, 2005, pp. 220-226.
[3] Tripşa, I. Pumnea, C., Steel deoxidation, Ed. Tehnică, Bucureşti, 1981,
pag. 332.
[4] Vacu, S., ş.a., Elaboration of alloy steel vol. I, Ed. Tehnică, Bucureşti,
1980, pag. 250.
[5] Vacu, S., ş.a., Elaboration of alloy steel vol. II, Ed. Tehnică, Bucureşti,
1980, pag. 89.
[6] Socalici A., Heput T., Ardelean E., Ardelean M., Valorization of
Powdery Ferrous Wastes in the Context of Sustainable Development, 6th
WSEAS International Conference on ENERGY,ENVIRONMENT,
ECOSYSTEMS and SUSTAINABLE DEVELOPMENT (EEESD '10) -
Politehnica University of Timisoara, Romania October 21-23, 2010,
pp153-157.
[7] Socalici A., Heput T., Ardelean E., Ardelean M., Researches Regarding
the Obtaining of Active Slag by Using Reactive Admixtures Produced
from Ferrous and Basic Scrap, 6th WSEAS International Conference on
ENERGY,ENVIRONMENT, ECOSYSTEMS and SUSTAINABLE
DEVELOPMENT (EEESD '10) - Politehnica University of Timisoara,
Romania October 21-23, 2010, pp 158 –163.
[8] Socalici A., Heput T., Ardelean E., Ardelean M., Researches Regarding
the Recovery of Small and Powder Ferrous Wastes within Iron and Steel
Industry, 6th IASME / WSEAS International Conference on ENERGY
&ENVIRONMENT (EE '11) , Cambridge, UK , February 23-25, 2011
pp 282-287.
[9] Ferat Shala, Milaim Sadiku, Blerim Rexha, Bedri Dragusha, Sala
Berisha Shala ,Industrial Landfill Source of Air Pollution in Mitrovica ,
Proceedings of the 5th WSEAS International Conference on WASTE
MANAGEMENT, WATER POLLUTION, AIR POLLUTION,
INDOOR CLIMATE (WWAI '11) , Iasi, Romania July 1-3, 2011 pp.37-
42
[10] Comparative Analysis between Technological Systems for Disposal of
Slag and Ash by Complex Energy Balance at Turceni Power Plant-
Luminita Georgeta Popescu, Adrian Gorun, Mihai Cruceru -
International Conference on ENERGY, ENVIRONMENT,DEVICES,
SYSTEMS, COMMUNICATIONS, COMPUTERS (EEDSCC
'11)Venice, Italy , March 8-10, 2011, pagina 128-133
[11] Determination of optimal dosage activator, essential factor in the
pozzolanic binder formulation - ANDREI BOGDAN , UNGUREANU
VALENTIN-VASILE - 11th WSEAS International Conference on
Sustainability in Science Engineering, Romania, Timisoara, 2009 ,
pagina 346-351(http://www.wseas.us/e-
library/conferences/2009/timisoara/SSE2/SSE2-14.pdf)
[12] Evaluating and planning waste landfill top covers with the help of
vegetation and population ecology - Brigitte Klug, Johannes Tintner,
Marion Huber-Humer,Katharina Meiss, - 1st WSEAS International
Conference on ENVIRONMENTAL and GEOLOGICAL SCIENCE and
ENGINEERING (EG'08) Malta, September 11-13, 2008, pagina 76-84
[13] The improving of the energetic regime of the small Electric Arc
Furnaces, working with foaming slag - ION MELINTE, MIHAELA
BALANESCU, GEORGE DARIE - Proceedings of the WSEAS Int.
Conference on Energy Planning, Energy Saving, Environmental
Education, Arcachon, France, October 14-16, 2007, pagina 61-66
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