Mechanism of composite additive in promoting reduction of copper slag to produce direct reduction iron for weathering resistant steel

Powder Technology 329 (2018) 55–64

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Mechanism of composite additive in promoting reduction of copper slag to produce direct reduction iron for weathering resistant steel Zhengqi Guo, Jian Pan ⁎, Deqing Zhu ⁎, Yang Congcong School of Minerals Processing and Bioengineering, Central South University, Changsha 410083, People's Republic of China

a r t i c l e

i n f o

Article history: Received 4 May 2017 Received in revised form 13 November 2017 Accepted 23 January 2018 Available online 31 January 2018 Keywords: Copper slag Particle growth Isothermal kinetic Composite additive

a b s t r a c t The mechanism of composite additive in promoting reduction of copper slag was revealed. In this paper, the kinetic study of direct reduction of copper slag (CS) was studied by isothermal method, and the phase transformation and growth behaviors of metallic iron particles during reduction process were clarified by X-ray diffraction, Scanning Electron Microscopy, and Energy Dispersive X-ray Spectroscopy analyses. The results indicated that the apparent activation energy of reduction reactions of iron oxides within CS sample was decreased from 71.27 KJ/mol to 49.86 KJ/mol with the addition of 15% composite additive, and the mean particle size of metallic iron particles increased from 9.2 μm to 35.2 μm. The composite additive can promote the reduction of iron minerals and induce the adequate growth of metallic iron particles, which is beneficial for iron and copper recovery in magnetite separation process. © 2018 Published by Elsevier B.V.

1. Introduction It is estimated that approximately 2–3 tons of copper slag (CS) is generated from per ton of copper production depending on the properties of copper concentrates and operating conditions in the pyrometallurgical process [1–4]. Currently, about 12 million tons of CS is produced every year, and the amount of accumulated CS has reached over 140 million tons by 2016 in China [5,6], resulting in high costs for land filling and heavy pollution to water, land and air. The treatment and disposal of CS has been a huge challenge for the copper industry, due to large quantities and many hazardous metals contained in it, such as Cu, Pb, Zn [7,8]. The chemical compositions of CS vary with the types of furnace or processes of treatment. Generally, it contains about 35–45 wt% of iron and 0.5–1.5 wt% of copper, which can be recovered, if treated suitably. In recent years, great efforts have been made to recover the valuable metals from that. The methods are roughly classified to physical separation processes and pyro-metallurgical processes, including flotation [9–11], magnetic separation [12], leaching [13–15] and roasting [16–22]. Indeed, it is considerably successful to recovery copper from slow-cooled CS by flotation process. However, the most of iron contained in CS is not be recycled since iron constituents in CS mainly exist as the form of fayalite (Fe2SiO4). It is therefore useless to recovery the iron by magnetic separation process.

⁎ Corresponding authors. E-mail addresses: [email protected] (J. Pan), [email protected] (D. Zhu).

https://doi.org/10.1016/j.powtec.2018.01.063 0032-5910/© 2018 Published by Elsevier B.V.

Some investigation on CS indicated that an appreciable amount of nonferrous metals can be recovered by leaching. Nonetheless, high concentration acid leaching has shown problems of the formation of silica gel, which not only prejudices metal extraction and pulp filtration, but also causes crud formation during solvent extraction. Hence, effectively upgrading these samples by conventional treatment processes can be challenging. To solve this problem, several researchers have focused on the direct reductive roasting of CS, followed by magnetic separation. Kim et al. carried out a research on reduction-magnetic separation process, where reduction at 1250 °C for 1.5 h and then followed by dry magnetic separation to recover iron, but the iron grade of product was only 66.1% and SiO2 content was as high as 12.7% [23]. Busolic et al. extracted the iron by smelting reduction at 1450 °C for 40 min, producing Fe\\Cu alloy containing 98% Fetotal and 0.6% Cu, whereas the iron recovery was not high and further experiments should be run in order to increase iron recovery [24]. In our previous work of coal-based direct reduction-magnetic separation to upgrade the CS, the iron concentrate, assaying 90.68% Fetotal, and 0.66% Cu was obtained and the desired recoveries of iron and copper were 90.49% and 79.53%, respectively [25]. The final product can be used as a burden along with scrap steel for making weathering resistant steel by electric arc furnace. Particularly, the composite additive used in the previous study plays an important role of promoting reduction of CS. The present work, the mechanism of composite additive in improving reduction of CS and its behaviors in reduction process was further verified through putting forth an isothermal kinetic study for the reduction of CS along with calculation of the associated apparent activation energy.

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2. Experimental 2.1. Materials 2.1.1. Copper slag For the present investigation, the copper slag (CS) sample was collected from Tongling Non-ferrous Metals Group Holding Co., Ltd (Tongling city, Anhui province, China). The CS sample was analyzed by using X-ray fluorescence (XRF) and the result is summarized in Table 1. It can be seen from that the main chemical compositions contained in the CS sample are 43.68% FeO and 30.81% SiO2, and the content of Cu reaches 0.33%. The dominate minerals of CS determined by X-ray diffraction (XRD) are fayalite and magnetite, as shown in Fig.1. The size of copper slag is 84.28% and 96.74% passing 0.044 mm and 0.074 mm, respectively. Fig. 2 presents the micrographs of CS, which further shows that fayalite and magnetite are the main minerals in the CS sample, and they closely combine with copper matte and glassy phase. Hence, the fine dissemination of the minerals responds very poorly to conventional flotation and magnetic separation processes due to the insufficient mineral liberation from the gangue mineral through grinding. 2.1.2. Reducing coal The soft coal was used as reductant agent for carbothermal reduction purpose which has been collected from Shanxi province. The main chemical composition of coal ash and the proximate and fusibility analysis of soft coal were determined by the standard proximate analysis method, and the results are shown in Tables 2 and 3, respectively. As can be seen from that, the soft coal bears low ash content of 4.49%, moderate fixed carbon content of 52.12% and appropriate volatiles content of 30.41%. 2.1.3. Flux Limestone containing 60.38% of CaO and 37.47% of loss of ignition (LOI) was used as flux in this work to adjust the binary basicity (mass ratio of CaO/SiO2) of mixture, and its particle size is less than 0.074 mm. 2.1.4. Composite additive The composite additive mainly containing hematite (16.38%), magnetite (41.45%) and some sodium humate (42.17%) was produced by Central South University, which is in a form of powder with over 90% passing 0.074 mm. 2.2. Experimental methods The experimental procedure mainly includes: (1) mixing the CS with a certain amount of composite additive and limestone, (2) pelletizing of mixture, (3) preheating of dried pellets, (4) reduction of preheated pellets. The detail technology flowsheet can be seen in our previous paper [25]. 2.2.1. Reduction kinetic and reduction roasting tests The isothermal reduction kinetic and the reduction roasting tests of CS were carried out in a muffle furnace (model: KSY-12-18), as can be seen in Fig. 3 and the chemical sequential extraction method was adopted to determine the contents of various Fe species to study the reduction kinetics of iron oxides. First, about 60 g the preheated pellets covered with the required amount of coal (C/Fe mass ratio was 2) were loaded into alumina crucible. The purpose of using this excess coal in this alumina crucible Table 1 Chemical compositions of copper slag (wt%). Element TFe

FeO

SiO2

CaO

MgO Al2O3 Cu

Content 39.85 43.68 30.81 2.00 1.28

2.83

Pb

Zn

S

LOI

0.33 0.22 2.81 0.18 0.19

Fig. 1. X-ray diffraction patterns of CS sample.

was to maintain reducing atmosphere in which the pellets were to be reduced. When the temperature of the MoSi2 electric furnace reached the experiment temperature, the samples were put into the hot zone of the furnace rapidly and then were reduced for a specified duration isothermally. Then, the alumina crucible was taken out from the furnace and covered by pulverized coal to cool down in the air to prevent reduced pellets from being re-oxidized. Subsequently, the reduced pellets were crushed to the size of −3 mm and mixed uniformly. And samples were taken by coning and quartering methods for analyses of total iron, metallic iron and ferrous oxide. After that, the reduction degrees (R) of iron were calculated according to Eq. (1): " RI ¼ 1−

0:43  ðTFe−MFeÞ−0:112  FeO 0:43  TFe0 −0:112  FeO0

# TFe0  100 pct  TFe

ð1Þ

where RI is the reduction degree of iron, %; TFe is the total iron content of reduced pellets, %; MFe is the iron metallization ratio of reduced pellets, %; FeO is the ferrous oxide content of reduced pellets, %; FeO0 is the ferrous oxide content of preheated pellets, %; TFe0 is the total iron content of preheated pellets, %. Other samples were charged to phase analysis by XRD and microstructure analysis by SEM-EDS.

2.2.2. Analytic tests The composition of phases in the samples was investigated using X-ray diffractometer (XRD, RIGAKU, D/Max-2500). Microstructures of reduced pellets were performed by Leica DMLP optical microscopy, FEI Quata-200 scanning electron microscope and EDAX32 genesis spectrometer. SEM images were recorded in backscatter electron modes operating in low vacuum mode at 0.5 Torr and 20 keV. The image J software was used to measure the size of iron particles.

3. Results and discussion In this study, the mechanism of composite additive in promoting reduction of CS was revealed from two aspects: comparison of reduction kinetics of preheated pellets with or without composite additive in the coal-based reduction process, iron particle growth behaviors of preheated pellets with various dosages of composite additive.

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Fig. 2. Representative SEM micrographs of CS sample.

3.1. Isothermal kinetic study of reduction Isothermal kinetic studies on the reduction of iron oxide ores have attracted a lot of attention by many researchers. In the study, the reduction mechanism of CS pellets has been carried out at four temperatures of 950 °C, 1000 °C, 1050 °C and 1100 °C for 5, 10, 20, 30, 40, 60, 80, 100 and 120 min by the analysis of kinetic data. As a typical heterogeneous reaction, in which kinetics can be described as the following equation: Z GðaÞ ¼

0

t

  E dt ¼ kt Aexp − RT

ð2Þ

where α is the conversion ratio (reduction degree), %; t is the reaction time, min; k is the rate constant min−1; A is the pre-exponential factor; E is the activation energy (KJ/mol); R is the gas constant; T is the active temperature, K [26,27]. The common isothermal kinetic models were tested with experimental data and are summarized in Table 4. The most appropriate model was selected from that by linear fitting, and the rate constants at different temperatures were applied to calculate the Arrhenius activation energy. Reduction degrees of iron oxides are shown in Fig. 4. As can be seen from that, with an increase in temperature, the reduction degree of iron oxides within booth kinds of pellets was increased significantly, and the equilibrium periods were shortened, which shows good conformity with those obtained by previous researchers [27–29]. In addition, with addition of 15% composite additive, the reduction degree of iron oxide was elevated obviously. To identify the kinetic model and the rate controlling steps in the reduction process of CS pellets, kinetics models in Table 4 were used and the reduction degrees for different time were plotted into G(α).

The experiment dates were analyzed by linearly fitted to determine the appropriate kinetic model, meanwhile the correlation coefficient of reduction degree G(ɑ)-t for the reduced pellets were calculated and the results are shown in Tables 5 and 6. As can be seen from that, the regression coefficient (R2) of model D3(a) was the highest among those models, indicating the reduction kinetic of CS pellets follows three-dimensional diffusion. Fig. 5 shows the plots of [1 − (1 − a)1/3]2 as the reduction time of CS pellets. It can be found from that the test points ([1−(1 − a)1/3]2) consist well with the theoretical curve for D3(a) in the whole reduction process at the various temperatures, which further revels [1−(1 − a)1/3]2 is a preferable linear relationship. In addition, according to the slope of the line of lnk versus 1/T (as seen in Fig. 6), the activation energies for the reduction reaction are obtained. The activation energies for the iron oxides reduction of the CS sample with 15% composite additive was 49.86 KJ/mol, whereas that of the CS sample without additive was increased to 71.27 KJ/mol, indicating that the composite additive is able to decrease the apparent activation energy of iron oxides reduction reaction and speed up the progress of reaction. Combined with kinetic study above, it is inferred that at incubation period, the iron oxides in the CS pellets reduced to metallic iron was

Table 2 Main chemical composition of coal ash (wt%). Fe2O3

SiO2

Al2O3

CaO

MgO

P

S

0.757

1.24

0.36

1.12

0.06

0.0006

0.58

Furnance Controller

Table 3 Proximate and fusibility analysis results of soft coal. Proximate analysis/% Mad 12.98

Aad 4.49

MoSi2 Heating element

Ash fusibility analysis/°C Vad 30.41

FCad 52.12

DT 1332

ST 1376

HT 1450

FT 1470

(Mad: moisture; Aad: ash; Vad: volatile matter; FCad: fix carbon; DT: distortion temperature; ST: soften temperature; HT: hemispherical temperature; FT: flow temperature).

Shaft furnace

Thermocouple

Fig. 3. A schematic illustration of the reduction process.

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The generated CO gas would diffuse into inner of the CS pellets to further participate in the reduction of other iron oxides located inside the ore. Unfortunately, the CS was characterized by the fine size and dense structure, resulting in the difficulty of CO diffusion. However, the composite additive contained some sodium humate, which not only had a role as a kind of binder in the pelletizing process, but also had positive influence on the reduction of iron oxides. The previous studies pointed out the solid solution of alkali metal (such as Li+, Na+, K+) ion in wüsitite results in lattice distortion and structure defects of wüsitite and thus the more microporous would be generated, which is beneficial for diffusion of reduction gas to reaction interface [30–32]. Therefore, the apparent reaction rate was increased and the activation energy was reduced correspondingly with the addition of composition additive.

Table 4 Common used solid reaction mechanism functions [28,29]. Model

Reaction mechanism

Integrated form (G(a))

A1(a)

One-dimensional growth of nuclei (Avrami–Erofeev) n = 1 Two-dimensional growth of nuclei (Avrami–Erofeev) n = 1/2 Three-dimensional growth of nuclei (Avrami–Erofeev) n = 1/3 Chemical reaction control n = 1/4 Chemical reaction control n = 2 Phase-boundary controlled (contracting cylinder) n = 1/2 Phase-boundary controlled (contracting cylinder) n = 1/3 One-dimensional diffusion Two-dimensional diffusion Three-dimensional diffusion (Jander equation) Three-dimensional diffusion (Ginsteing–Brounshtein equation)

−In(1 − a)

A2(a) A3(a) C1(a) C2(a) R2(a) R3(a) D1(a) D2(a) D3(a) D4(a)

[−In(1 − a)]1/2 [−In(1 − a)]1/3 1 − (1 − a)1/4 1 − (1 − a)2 1 − (1 − a)1/2 1 − (1 − a)1/3 a2 (1 − a)In(1 − a) + a [1 − (1 − a)1/3]2

3.2. Phase transformation during reduction

(1– 2/3a) − (1 − a)2/3

mainly hematite (Fe2O3) and Fe3O4, which were gradually reduced to Fe by carbon at the contacted surface of them according to the following reactions: Fe2 O3 þ C → Fe3 O4 þ CO

ð3Þ

Fe3 O4 þ C → FeO þ CO

ð4Þ

FeO þ C → Fe þ CO

ð5Þ

XRD patterns of reduced pellets with or without composite additive are shown in Fig. 7. As can be seen, the huge intensity peak of iron was observed, and its intensity was enhanced obviously with the addition of the composite additive. On the contrary, the gangue minerals, such as augite and fayalite, were also detected in the reduced pellets, and their intensities were reduced rapidly when adding 15% composite additive. Generally, analysis of XRD assumes that the ratio of the peak heights in the XRD patterns is proportional to the mineral content, and that, for the same mineral, the variation in the diffraction intensity can approximately reflect the change in its content [31]. Thus, it means that the content of metallic iron was increased significantly in the reduced pellets with 15% composite additive, leading to an obvious improvement of iron recovery in magnetic separation process.

Fig. 4. Reduction degree vs time (min) for pellets at various temperatures & times.

Table 5 Correlation coefficient of reduction degree G(ɑ)-t from linear fit for the reduced pellets without composite additive. Model

A1(a) A2(a) A3(a) C1(a) C2(a) R2(a) R3(a) D1(a) D2(a) D3(a) D4(a)

950 °C

1000 °C

1050 °C

1100 °C

R

K

R

K

R

K

R

K

0.837 0.572 0.423 0.804 0.544 0.721 0.792 0.541 0.923 0.946 0.948

0.0070 0.0053 0.0045 0.0015 0.0045 0.0033 0.0019 −0.0045 0.0007 0.0007 0.0005

0.866 0.603 0.453 0.829 0.513 0.790 0.816 0.513 0.950 0.977 0.961

0.0087 0.0060 0.0050 0.0018 0.0044 0.0034 0.0023 −0.0046 0.0028 0.0010 0.0007

0.889 0.614 0.456 0.844 0.441 0.541 0.827 0.342 0.958 0.995 0.970

0.0108 0.0066 0.0053 0.0021 0.0046 0.0045 0.0026 −0.0039 0.0036 0.0013 0.0009

0.850 0.557 0.409 0.790 0.342 0.513 0.768 −0.0441 0.924 0.989 0.944

0.0111 0.0065 0.0051 0.0022 0.0039 0.0046 0.0026 −0.004 0.0037 0.0015 0.0010

Z. Guo et al. / Powder Technology 329 (2018) 55–64 Table 6 Correlation coefficient of reduction degree G(ɑ)-t from linear fit for the reduced pellets with 20% composite additive. Model

A1(a) A2(a) A3(a) C1(a) C2(a) R2(a) R3(a) D1(a) D2(a) D3(a) D4(a)

950 °C

1000 °C

1050 °C

1100 °C

R

K

R

K

R

K

R

K

0.851 0.602 0.455 0.812 0.491 0.689 0.798 0.491 0.958 0.972 0.938

0.0095 0.0063 0.0051 0.0019 0.0047 0.0037 0.0024 −0.0047 0.0034 0.0011 0.0008

0.861 0.596 0.447 0.810 0.411 0.696 0.792 0.411 0.923 0.973 0.941

0.0113 0.0068 0.0054 0.0022 0.0043 0.0037 0.0027 −0.0043 0.0038 0.0014 0.0010

0.815 0.563 0.422 0.760 0.329 0.491 0.739 0.269 0.855 0.985 0.878

0.0128 0.0071 0.0055 0.0024 0.0039 0.0047 0.0027 −0.0039 0.0042 0.0017 0.0011

0.853 0.561 0.412 0.778 0.270 0.411 0.740 0.329 0.893 0.981 0.924

0.014 0.0073 0.0056 0.0025 0.0036 0.0043 0.0030 −0.0036 0.0044 0.0018 0.0012

3.3. Growth of metallic iron particles in reduction The microstructure of reduced pellets with different dosages of composite additive is shown in Fig. 8 and the average size of the metallic iron particle size was determined as well. The composite additive exhibited heavily effect on the particle size of the metallic iron in the reduced pellets. As can be seen from Fig. 8(a), many minor metallic iron particles can be observed, but they were very fine and dispersive in reduced briquettes in absence of composite additive. With the addition of the

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composite additive, the metallic iron particles aggregated together and grew obviously. When the level of the composite additive within the pellets was up to 20%, the mean particle size of metallic iron was increased significantly to 38.2 μm. Fig. 9 shows the effect of reduction time on average size of iron grain in the pellets with various dosages of additive. It is found that with prolonging the reduction time, the size of iron particles was increased, and iron particles in the pellets with additive was obviously grew faster than that of the pellets without additive. The process of the particle growth could be divided into two stages: nucleation stage and crystal growth stage. In the first stage, the metallic iron particle nucleation formed, which need to gain energy to overcome the potential barrier of nucleation. The composite additive, containing the hematite and magnetite, was very easily and preferentially to be reduced to metallic iron compared with original CS samples, which could play a role of nucleating agent in this process. Thus, the nucleation method of metallic iron in this system was changed from the homogeneous nucleation to the heterogeneous nucleation [33–35]. As can be seen from Eqs. (6)–(8), this change of nucleation method could reduce the surface energy barrier of nucleation, which was beneficial for the formation of crystal nucleus [34–36].

ΔGs ¼

" # 16πnr3 ð2 þ cosθÞð1−cosθÞ2 4 3ΔG2v

Fig. 5. Relationship between [1 − (1 − a)1/3]2 and time of the CS pellets reduction without (a)/with 15% additives (b).

Fig. 6. Arrhenius plots of ln k vs 104/T of D3 kinetic models for the CS pellets without (a) and with 15% additives (b).

ð6Þ

Z. Guo et al. / Powder Technology 329 (2018) 55–64

/

60

Fig. 9. Effect of reduction time on average size of iron particle in the pellets with various dosages of composite additive.

Fig. 7. XRD patterns of reduced pellets with or without composite additive.

ΔGk ¼

16πnr3

ð7Þ

3ΔG2v

" # ð2 þ cosθÞð1−cosθÞ2 ≪1→ ΔGs ≪ ΔGk 4

ð8Þ

where ΔGs is the barrier of heterogeneous nucleation, n is the number of crystal grey, r is the radii of crystal grey, ΔGv is the free energy diversification, θ is the contact angle between crystal nucleus and matrix, ΔGk is the barrier of homogeneous nucleation. In second stage, the driving force to promote crystal growth is the principle of minimum free energy and larger grain size tending to decrease surface free energy. The nucleating particles, generated on surface of the composite additive, strongly absorb around fine particles

by interfacial tension and thus induce the growth of the iron particles. As a result, tiny iron particles decreased and disappeared, while large particles reunited and grew up. Generally, the larger size of the minerals responds very superiorly to sufficient liberation in milling process and subsequent physical separation. Therefore, the composite additive essentially played a role of nucleating agent during direct reduction, which can significantly promote nucleation, improve migration of metallic ferrous grains, facilitate the growth and coalescence of particles, effectively enhance the iron grains liberation in grinding, upgrading the iron degree and iron recovery in magnetic separation process. 3.4. Main elements distribution behaviors Fig. 10 shows the microstructures of reduced pellets and chemical compositions under SEM and EDS·As can be seen from that, the metallic

Fig. 8. Microstructures of reduced pellets with various dosages of composite additive and the metallic iron size.

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Fig. 10. SEM-EDS of the reduced pellets.

iron particles within two kinds of reduced pellets were very pure and contain some of Cu, indicating that the copper-bearing minerals in the ore was reduced and the generated metal copper entered into the metallic iron grains. In addition, for the slag, the Fe content of point 4 was still higher than 28% and the Cu content was also reached 0.30%, which reveals that the many superfine metallic iron grains may not grow up and were trapped in the slag phase, meanwhile many copper was lost in the slag as well in the absence of composite additive. On the contrary, from Fig. 10A, the Fe content of point 2 was only 14.39% as well as corresponding Cu content was 0.12%. Furthermore, the iron and copper content of different micro-zones randomly selected in the slag was detected by EDS point analysis, and the results are displayed in Fig. 11. As the dosage of the composite additives was increased, both iron and copper content in the slag matrix were decreased. Based on the variation tendency, it is inferred that iron and copper gradually emigrated and transformed into metallic iron

phase with the addition of composite additives during the carbothermic reduction process of CS sample, which further confirms that the composite additive is favorable to beneficiation of iron and copper. The distribution characteristics of iron, copper, silica, aluminum and calcium elements in the reduced pellets with 15% composite additive can be further revealed from Fig. 12. In the reduced pellets, most of the iron element were enriched in the metallic iron phase, which aggregated together and clearly was separated from the other elements, such as Si, Al and Ca. However, the distribution characteristic of copper element was not obvious due to the low content of copper in the reduced pellets. Fig. 13 presents a typical analysis for the line scanning of the reduced pellets; the presence of Cu shows likelihood of being tracked with Fe and their existence in metallic iron phase, whereas Si exhibits the reverse behavior. The result shows that iron with some copper are present in the metallic iron particles.

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0.45

EDS of Fe content in the slag matrix/%

EDS of Cu content in the slag matrix/%

28

Iron phase

0.40 0.35 0.30

Slag matrix

0.25 0.20 0.15 0.10 0

5

10

15

20

Dosage of the compound additive/%

26 24 22 20 18 16 14 12 10 0

5

10

15

20

Dosage of the compound additive/%

Fig. 11. Copper and iron content in the slag matrix of samples subjected to reduction with different dosages of composite additive.

Fe

100μm

Cu

Si

Al

Ca

Fig. 12. Element map scanning of the reduced pellets with 15% composite additive.

Z. Guo et al. / Powder Technology 329 (2018) 55–64

63

50μm Cu k

Si k Fe k Distance/­P 0

20

40

60

80

100

120

140

Fig. 13. SEM image and EDS line scanning of the reduced pellets with 15% composite additive.

4. Conclusions Reduction behaviors of the CS pellets were investigated under isothermal conditions, and the growth characteristics of the iron particles as well as main elements distribution behaviors were explored to disclose the mechanism of composite additive in promoting reduction of copper slag to produce directly reduced iron for weathering resistant steel. The following conclusions can be drawn as follows: 1) Reduction of iron oxide within CS was controlled by Threedimensional diffusion (Jander equation). The composite additive could reduce the active energy of reduction and thus accelerate the reaction rate. The activation energies for the iron oxides reduction of the CS sample without composite additive was 71.27 KJ/mol, while with 15% additive, the apparent activation energy was reduced to 49.86 KJ/mol. 2) The composite additive played a role of nucleating agent during direct reduction, which can significantly facilitate growth and coalescence of metallic iron particles. With the addition of composite additive, the mean particle size of metallic iron was increased from 9.2 μm to 35.2 μm. Acknowledgements The authors wish to express their thanks to the National Key Technology R&D Program of China (NO. 2013BAB03B04) for the financial support of this research, and also would like to thank Co-Innovation Center for Clean and Efficient Utilization of Strategic Metal Mineral Resources of Hunan Province, which supplied us the facilities and funds to fulfill the experiments. References [1] B. Gorai, R. Jana, M. Premchand, Characteristics and utilization of copper slag—a review, Resour. Conserv. Recycl. 39 (2003) 299–313. [2] S. Gyurov, Y. Kostova, G. Klitcheva, A. Ilinkina, Thermal decomposition of pyrometallurgical copper slag by oxidation in synthetic air, Waste Manag. Res. 29 (2011) 157–164. [3] C. Shi, C. Meyer, A. Behnood, Utilization of copper slag in cement and concrete, Resour. Conserv. Recycl. 52 (2008) 1115–1120. [4] I. Alpa, H. Deveci, H. Sungun, Utilization of flotation wastes of copper slag as raw material in cement production, J. Hazard. Mater. 159 (2008) 390–395. [5] H. Wang, J. Recovery of copper and iron in the converter slag from a copper smelter, Guangdong Non-ferrous Met. 13 (2003) 83–88 (In Chinese). [6] T. Deng, Y. Ling, Processing of copper converter slag for metals reclamation: part II: mineralogical study, Waste Manag. Res. 22 (2004) 376–382. [7] H. Shen, E. Forssberg, An overview of recovery of metals from slags, Waste Manag. 23 (2003) 933–949. [8] A. Taeb, S. Faghihi, Utilization of copper slag in the cement industry, ZKG Int. 55 (2002) 98–100.

[9] S. Roy, S. Rehani, Flotation of copper sulphide from copper smelter slag using multiple collectors and their mixtures, Int. J. Miner. Process. 43 (2015) 43–49. [10] A. Sarrafi, B. Rahmati, H.R. Hassani, Recovery of copper from reverberatory furnace slag by flotation, Miner. Eng. 7 (2014) 457–459. [11] W.J. Bruckard, M. Somerville, F. Hao, The recovery of copper, by flotation, from calcium-ferrite-based slags made in continuous pilot plant smelting trials, Miner. Eng. 17 (2004) 495–504. [12] J. Zheng, K. Xiao, The research on using dispersant agent to iron recovery in copper slag, Non-Ferrous Met. Sci. Eng. 16 (2011) 71–73 (In Chinese). [13] P. Anna, L. Piet, V.D. Vossenberg, R. Eldon, Comparison of Cu, Zn and Fe bioleaching from Cu-metallurgical slags in the presence of Pseudomonas fluorescens and Acidithiobacillus thiooxidans, Appl. Geochem. 68( (2016) 39–52. [14] D. Urosevic, M. Dimitrijevic, Z. Jankovic, D. Antic, Recovery the copper from copper slag and copper slag flotation tailing by oxidative leaching, Physicochem. Probl. Miner. Process 51 (2015) 71–82. [15] I. Muravyov, V. Fomchenko, V.A. Usoltsev, F.K. Vasilyev, Leaching of copper and zinc from copper converter slag flotation tailings using H2SO4 and biologically generated Fe2(SO4)3, Hydrometallurgy 119 (2012) 40–46. [16] R. Subrata, S. Sanjay, D. Amlan, Importance of mineralogy and reaction kinetics for selecting leaching methods of copper from copper smelter slag, Sep. Sci. Technol. 51 (2016) 135–146. [17] F. Yong, E. Shibata, A. Izuka, T. Nakamura, Crystallization Behavior of Copper Smelter Slag During Molten Oxidation, 46, MMTB, 2015 2158–2164. [18] J.H. Heo, B.S. Kim, J.H. Park, Effect of CaO Addition on Iron Recovery From Copper Smelting Slags by Solid Carbon, 44, MMTB, 2013 1352–1363. [19] K. Mawejaa, T. Mukongob, I. Mutomboc, Cleaning of a copper matte smelting slag from a water-jacket furnace by direct reduction of heavy metals, J. Hazard. Mater. 164 (2009) 856–862. [20] O. Yucel, F. Sahin, B. Sirin, O. Addemir, A reduction study of copper slag in DC arc furnace, Scand. J. Metall. 28 (1999) 93–99. [21] Z.Q. Guo, D.Q. Zhu, J. Pan, T.J. Wu, F. Zhang, Improving Beneficiation of Copper and Iron from Copper Slag by Modifying the Molten Copper Slag Metals, 6, 2016 75–82. [22] Z.Q. Guo, D.Q. Zhu, J. Pan, F. Zhang, Mechanism of mineral phase reconstruction for improving the beneficiation of copper and iron from copper slag, JOM 48 (2016) 2341–2348. [23] B. Kim, S.K. Jo Su, D. Shin, J.C. Lee, S.B. Jeong, A physico-chemical separation process for upgrading iron from copper slag, Int. J. Miner. Process. 143 (2015) 43–49. [24] D. Busolic, F. Parada, R. Parra, M. Sanchez, J. Palacios, M. Hino, Recovery of iron from copper flash smelting slags, Miner. Process. Ext. Metall. 120 (1) (2014) 32–36. [25] X.L. Zhou, D.Q. Zhu, J. Pan, T.J. Wu, Utilization of copper slag to produce directly reduced iron for weathering resistant steel, ISIJ Int. 55 (2015) 1347–1352. [26] S. Biswas, S. Chakraborty, M.G. Chaudhuri, P.C. Banerjee, S. Mukherjee, R. Dey, Optimization of process parameters and dissolution kinetics of nickel and cobalt from lateritic chromite overburden using organic acids, J. Chem. Technol. Biotechnol. 89 (2014) 1491–1500. [27] A.K. Vaish, R.C. Gupta, S.P. Mehrotra, Solid-state kinetic models: basics and mathematical fundamentals, J. Metall. Mater. Sci. 48 (2006) 1–12. [28] S. Nasr, K.P. Plucknett, Energ Fuel, Kinetics of Iron Ore Reduction by Methane for Chemical Looping Combustion, 28, 2014 1387–1395. [29] J. Sharp, G. Brindley, B.N. Achar, Numerical data for some commonly used solid state reaction equations, J. Am. Ceram. Soc. 49 (1966) 379–382. [30] M. Liu, T. Jiang, G. Li, Effect of Na2CO3 and Na2SO4 on sodium-reduction dynamic law of high aluminum iron ores, Chin. J. Nonferrous Met. 25 (2015) 221–226. [31] L. Zhang, P. Guo, P. Zhang, Study on catalytic mechanism of gas–based reduction of iron ore, Iron Steel Vanadium Titan. 29 (2018) 1–5. [32] Y. Zhang, X. Guo, H. Tang, S. Zhang, Effect of catalysts on additive containing li on the reduction of hematite by carbon monoxide, J. Univ. Sci. Technol. Beijing 24 (2002) 194–196.

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Z. Guo et al. / Powder Technology 329 (2018) 55–64

[33] T.Q. Li, C.Y. Wang, X.J. Liu, Similarities and differences of carbonaceous mesophases derived from homogenous and heterogeneous systems, Carbon Technol. 27 (2008) 5–9. [34] X.G. Mei, M.L. Yan, W.L. Zuo, Kinetics of the nucleation and grain growth of metallic phase in direct reduction of high iron red mud with coal base, J. Cent. S. Univ. Sci. Technol. 27 (1996) 159–163.

[35] T.J. Chun, Study on Process and Mechanism of Effect Beneficiation of Superfine Low Grade Hematite, Central South University, Changsha, 2010. [36] Y. Sun, P. Gao, Y. Han, D. Ren, Reaction behavior of iron minerals and metallic iron particles growth in coal-based reduction of an oolitic Iron ore, Ind. Eng. Chem. Res. 52 (2013) 2323–2329.