Paper misturas autorredutoras

1. Kinetic of Self-Reducing Mixtures of Iron Ore and Biomass of
Elephant Grass*
Rocha, E.P.1,a
; Castro, J.A.1,b
; Vitoretti, F.P.1,c
; Junior, F.V.2,d
1
EEIMVR – Fluminense Federal University, Av. dos Trabalhadores, 420 Volta Redonda
RJ – CEP 27255-125 - Brazil
21
EEL – São Paulo University, Estrada Municipal do Campinho, Lorena
SP – CEP 12602-810 - Brazil
a
elisa_procha@yahoo.com.br, b
joseadilsoncastro@id.uff.br; c
flaviapv@metal.eeimvr.uff.br;
d
vernilli@demar.eel.usp.br
Keywords: self-reducing pellets, biomass, BOF dust, kinect.
Abstract In this work, kinetic runs of self-reducing mixtures composed by pellet feed, BOF dust
and biomass of elephant grass were performed using TGA-DSC method, for the temperatures, 900,
950, 1000, 1050 and 1100o
C, and carbon percentages (15, 20 and 30% of carbon). The converted
fraction versus time was calculated, and the different regions of the reactions progress were selected
to analyze the reactions kinetics that occur in the mixture (devolatilization of biomass, Boudouard
and sequence of reduction reactions). The kinetic behavior for the different steps showed good
agreement with the first-order kinetic law. Using Arrhenius plot, was possible to estimate the
apparent activation energy values obtained for the reaction mechanisms corresponding to
Fe3O4→FeO and FeO→Fe. The kinetic constants for the 1100o
C temperature and mixture
containing 30% of carbon were the higher values: 0.0037 s-1
for the reaction Fe3O4 → FeO and
0.0258 s-1
for the mechanism FeO →Fe.
Introduction
The self-reducing technology has presented advantages such as: reducing the demand for
coking coal in processes of iron ore reduction, since this technology accept different carbonaceous
sources (charcoal and biomass); reduction of temperature and consequently, minimizing energy
costs; and the possibility to use fines of steel mill wastes which are rich in iron source such as, BOF
and EAF dusts [1].
When the iron ore fines are mixed with carbon particles, the contact between these particles
result in the global reaction given by Eq.1:
Fe2O3 + p C → 2 Fe + u CO + v CO2
(1)
The CO2 product originated in Eq. 1 starts the Boudouard reaction (Eq. 2), generating CO
gas, reducing agent that will provide the continuity of the sequence of reduction reactions of iron
oxides present in the pellet, according to Eq.3 to 5.
C(s) + CO2(g)→ 2CO(g)
(2)
a Fe2O3(s) + b CO(g)  c Fe3O4(s) + d CO2(g) (3)
e Fe3O4(s) + f CO(g)  g FeO(s) + h CO2(g) (4)
i FeO(s) + j CO(g)  k Fe(s) + l CO2(g) (5)
Common researches [2-4] used to analyze the carbothermic reduction of iron oxide have
either centered on the first order irreversible mode as demonstrated in Equation 6.
ln(1-α) = -kt
(6)
Materials Science Forum Submitted: 2016-01-18
ISSN: 1662-9752, Vol. 869, pp 1007-1012 Accepted: 2016-03-10
doi:10.4028/www.scientific.net/MSF.869.1007 Online: 2016-08-31
© 2016 Trans Tech Publications, Switzerland
All rights reserved. No part of contents of this paper may be reproduced or transmitted in any form or by any means without the written permission of Trans
Tech Publications, www.ttp.net. (#68814818, Federal Fluminense University, Volta Redonda, Brazil-27/07/16,03:54:08)

2. Where α is the converted fraction, including devolatilization, Boudouard and reduction
reactions; k is the kinetic constant and t is the time reaction.
In the case of self-reducing pellets, the diffusion of the gases occurs inside to outside of the
pellet and the reactions take place within the agglomerates which leads to the control of the
reactions progresses commonly controlled by chemical and heat supply steps, and thus turns the
diffusion control irrelevant for the kinetic behavior. These phenomena ensure that the kinetic
behavior of the self-reducing pellets is essentially controlled by chemical reactions, where the
Boudouard reaction at lower temperatures plays the major role with heat transfer at higher
temperatures being the most important parameter to be controlled [3].
Materials and Methods
In this work kinetic runs in TGA-DSC Q600 were carried out to analyze the kinetic behavior
of self-reducing mixtures. Some important kinetic parameters were obtained such as kinetic
constant temperature dependence and apparent activation energy.
Self-reducing mixtures production
The compositions of the mixtures were based on the carbon percentage according to the
Table 1.
Table 1. Composition of the self-reducing mixtures.
Mixtures % Pellet Feed % BOF dust % Biomass
Mixture 1 36.5 47.7 15.8
Mixture 2 32.1 47.1 20.8
Mixture 3 27.9 41.0 31.1
The percentage values of the mixtures described in the Table 1were based on the carbon
content in the biomass (56.2% of fixed carbon).
In addition, a special attention was paid to the zinc oxide percentage present in the mixtures
due to well-known deleterious effects on the conventional reduction processes. In this work the
maximum zinc oxide was kept lower than 2.9% which limited the amount BOF slag in the mixtures.
Kinetic runs of the self-reducing mixtures
The mass changes during the experiment were recorded using TGA-DSC Q600 equipment
as can be seen in Fig. 1. Some parameters used in the experiments were: heating rate 5ºC/min, until
to achieve the temperatures 900, 950, 1000, 1050 and 1100ºC and keeping at this temperature for 60
minutes (except for 1100ºC, the experiment took around 5 hours in this temperature to ensure that
all carbon present in the sample is reacted). In addition, the atmosphere used was nitrogen with a
flow constant of 100ml/min.
(a) (b)
Fig. 1. (a) Inner furnace of the equipment; (b) TGA-DSC used for kinetic runs.
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3. Kinetic Parameters Estimation
The reacted fraction was calculated applying the Eq. 7.
(7)
Where mo is the initial mass, mt is the mass changing with the time and mf is the final mass
in the higher temperature, in this case, 1100ºC. The diagrams for the three different concentrations
were divided in regions according to the reactions that occur during the time. Applying Equation 6,
it was obtained the kinetic constant for the different regions; and using these results the activation
energy was predicted according to Eq. 8.
(8)
The regions were defined according to the change of the inclination of the curve in the
diagram α x t, showed in the Table 2.
Table 2. Different regions where the reactions occur.
Regions Definition Temperature range
1 Humidity Until 300ºC
2 Devolatilization 300ºC < T < 380ºC
3 Boudouard and Reduction Fe2O3 → Fe3O4 650ºC < T < 750ºC
4 Reduction Fe3O4 → FeO 800ºC < T < 880ºC
5 Reduction FeO → Fe 880ºC < T < until the end
Results and Discussion
Results of TGA-DSC experiments
The results are presented taking the derivative values of the converted fractions and the heat
flows during the runs.
(a) (b)
Materials Science Forum Vol. 869 1009

4. (c) (d)
(e) (f)
Fig. 2. (a), (c) and (e): derivative of α for 15, 20 and 30% of carbon present in the mixtures,
respectively. (b), (d) and (f): heat flow curves for 15, 20 and 30% of carbon present in the mixtures,
respectively.
The Fig. 2 (a to f) are the results of the derivative of α versus time and heat flow versus time
for the three mixtures with different carbon content. The peaks that appear in the diagrams obtained
for (dα/dt) versus time represent the weight change that occurs when different reactions happen,
described in Table 2. For all mixtures (15, 20 and 30% of carbon), it was possible to observe the
highest degree of conversion occurred at 1100 ° C, since the endothermic character of the reactions;
whereas for 1000 and 1050ºC with 30% of carbon, the reduction process was completed around
300min, with a maximum peak around 200 min test, that probably represents the reaction
mechanism FeO → Fe. For the results for the mixture containing 15% of carbon at 1050ºC it is
possible to visualize a peak around to 200 min of run which is smaller than the previous peak, and
this fact does not occur for 20 and 30% of carbon. This guarantees that for 20 and 30% of carbon
the reaction was completed since for the mixture containing 15% of carbon is not allowing the
amount of carbon to complete the reduction. For lower temperatures and for all concentrations the
converted fraction was lower compared to higher temperatures. In addition, the first peak that
appears around the 50 min of run occurs between the temperature values of 350 to 400o
C and this
was corroborated by an experiment performed in previous research [5] that is consistent with the
kinetic analysis of elephant grass biomass using TGA-DSC. Analyzing the heat flow diagrams in
Figures 2 (b), (d) and (f) it is possible to observe the inflections along the curve in the same time
intervals where the peaks of dα/dt. occur These inflections represent the endothermic reactions and
the heat flux is negative due to the output of energy of the furnace to the sample.
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5. Results of kinetic parameters
Applying the kinetic law of order first, described in Equation 6, to the different regions
defined in this study it was possible to find the kinetic constant, k, for the reactions corresponding
to the different regions. Tab. 3 shows the results of the kinetic constants for each region defined, for
the three concentrations, being that for regions 1, 2 and 3, it was displayed the average constant,
since all the peaks for these regions were obtained in the same temperature, due to the heating rate
has been constant.
Table 3. Kinetic constants for regions 1, 2 and 3 for the different concentrations of carbon.
Concentration Regions Kinetic constant(s-1
)
1 0.00082
15% 2 0.00098
3 0.0066
1 0.00088
20% 2 0.00094
3 0.00638
1 0.00086
30% 2 0.00112
3 0.00756
The bigger constant was for the sample containing 30% of carbon for the mechanism Fe2O3
→Fe3O4 (region 3), since a bigger fraction of hematite is reacted.
For 4 and 5 regions the kinetic constant values were increasing according to the increase of
temperature. Applying Equation 8, the activation energy was predicted for these regions. The results
are displayed in the Tab. 4. The bigger kinetic constants obtained for the 4 and 5 regions were
respectively, 0.00237 e 0.0258 s-1
for 1100 o
C temperature to the 30% of carbon samples.
According to the studies performed previously [6], many authors have determined the activation
energy using Arrhenius law and the values reported are between 40KJ/mol and 418KJ/mol.
Table 4. Apparent activation energy for different samples of 4 and 5 regions.
Carbon Regions Apparent Activation Energy (J/mol)
15% 5801.84
20% 4 9601.84
30% 12727.07
15% 84578.32
20% 5 142011.42
30% 178327.00
The lowest apparent activation energy values were for mixtures containing 15% of carbon,
since this composition is not enough to complete the reaction.
Conclusions
• In this work it was verified that the self-reducing mixtures containing biomass elephant
grass, iron ore and dust LD follows the first order kinetic law.
• The difference of kinetic behavior for samples containing, 20 and 30% of carbon was
negligible, and then, it is advantageous use the mixture with less fuel.
• When the activation energy values obtained for the reactions of Fe3O4 → FeO and FeO →
Fe are compared with values of global activation energy for self-reducing agglomerates
reported in the literature, the values obtained in this work were relatively lower, due to the
high reactivity of the biomass requiring a smaller energy demand.
• Applying the biomass as a carbonaceous source for self-reducing pellets requires a further
studies. However, according with these preliminary results, it is clear the kinetic advantages
of the mixtures with biomasses of elephant grass compared with fossil fuels.
Materials Science Forum Vol. 869 1011

6. References
[1] F.F. Grillo, J.A.S. Tenório, J.R Oliveira: Rev. Esc. Minas Vol. 66 (2013), p. 301.
[2] J.C. D’abreu, K.M. Martins, J.H. Noldin Junior, The iron morphology of self-reducing
briquettes. In: Brazil-Japan Symposium on dust processing-energy-environment in
metallurgical industries, 4, 2002, Sao Paulo. Proceedings…São Paulo: EPUSP 89-102.
[3] M.B. Mourão, C. Takano: Mineral Processing and Extractive Metallurgy Review: An
International Journal Vol. 24 (2002), p.183.
[4] A. Bonalde, A. Henriquez, M. Manrique: ISIJ International Vol. 45 (2005), p. 1255.
[5] V. Strezov, T.J. Evans, C. Hayman: Bioresource Technology Vol. 99 (2008), p. 8394.
[6] M.B. Mourão, R.C. Nascimento, C. Takano: Canadian Metallurgical Quarterly Vol. 45 (2006),
p. 161.
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