Optimization of combined microwave pretreatment–magnetic separation parameters of ilmenite using response surface methodology

Powder Technology 232 (2012) 58–63

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Optimization of combined microwave pretreatment–magnetic separation parameters of ilmenite using response surface methodology Guo Chen a, b, Jin Chen a, b, 1, Jun Li a, b, Shenghui Guo a, b, C. Srinivasakannan c, Jinhui Peng a, b,⁎ a b c

Key Laboratory of Unconventional Metallurgy, Ministry of Education, Kunming University of Science and Technology, Kunming 650093, PR China Faculty of Metallurgical and Energy Engineering, Kunming University of Science and Technology, Kunming 650093, PR China Chemical Engineering Program, The Petroleum Institute, Abu Dhabi, P.O. Box 253, United Arab Emirates

a r t i c l e

i n f o

Article history: Received 2 June 2011 Received in revised form 10 June 2012 Accepted 13 August 2012 Available online 21 August 2012 Keywords: Microwave pretreatment Ilmenite Magnetic separation Response surface methodology

a b s t r a c t The paper addresses the effect of three major influencing parameters, microwave power, time and mass of sample on the combined microwave pretreatment and magnetic separation of ilmenite through application of process optimization technique response surface methodology. The experimental data obtained were fitted into a quadratic polynomial model using multiple regression analysis and were analyzed by the method of least squares. It was found that microwave power and time were the most significant factors affecting the recovery ratio while the mass of sample was found to be an insignificant parameter. The optimum process conditions were determined by analyzing response surface plots and by solving the regression model equation. Based on the analysis of variance (ANOVA) and the coefficient of determination (R2 = 0.9410), the model was found to be in good agreement with the experimental data. The optimum experiment conditions were found to be 2400 W of microwave power, 30.11 min of time and 44.80 g of sample mass, resulting in an experimental recovery ratio of 68.73%, as compared to the model prediction of 69.15%. The crystal structures of the samples were characterized before and after microwave pretreatment using X-ray diffraction (XRD). © 2012 Elsevier B.V. All rights reserved.

1. Introduction Traditional comminution processes consumes a large amount of energy to liberate minerals from ores. The high energy consumption of comminution process is a major economic and environmental concern [1–3], which necessitates development of new processing technologies with low energy consumption and less pollution to the environment [4–7]. The ore pre-treatment is one of the most important stages of comminution [8,9]. Whittles et al. [10] have reported that the microwave power density is an important factor which contributes toward decreasing energy consumption and improving recovery efficiency. Kingman et al. [11] have reported significant reduction in the iron ore strength in a very short exposure time of high electric field strength microwave energy on copper carbonatite ore. The use of microwave treatment to enhance the liberation of gold for subsequent recovery by gravity separation techniques has been reported by Amankwah et al. [12]. Microwaves are a specific category of radio waves that cover the frequency range of 300 MHz to approximately 300 GHz [13,14].

⁎ Corresponding author at: Key Laboratory of Unconventional Metallurgy, Ministry of Education, Kunming University of Science and Technology, Kunming 650093, PR China. Tel./fax: +86 871 5138997. E-mail address: [email protected] (J. Peng). 1 These authors contributed equally to this work and should be regarded as co-first authors. 0032-5910/$ – see front matter © 2012 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.powtec.2012.08.009

Compared to conventional heating methods, the major advantages of using microwave heating for industrial processing are rapid heat transfer, volumetric and selective heating, compactness of equipment, speed of switching on and off and pollution-free environment [15–17]. Hence, microwave energy is used in industry for various processes such as drying, calcining, roasting, and smelting [18–22]. Compared with the conventional ore pre-treatment methods, the microwave pretreatment consumes much less energy, improves mineral recovery, reduces the processing time and is suitable for commercial-scale operation [23–26]. The single-variable optimization methods cannot explain the interactions of the parameters of the experimental data, because interaction between different factors is easily overlooked, leading to a misinterpretation of the experimental results [27,28]. Recently, many statistical experimental design methods have been developed for process optimization. Among them, response surface methodology stands out as a popular method utilized in many fields [29,30]. Response surface methodology, includes factorial design and regression analysis, which helps in evaluating the effective factors and selecting the optimum experimental conditions [31,32]. Although the optimization of experimental conditions using response surface methodology is widely applied to mineral process optimization, its specific application to microwave pretreatment process is seldom reported. The main objective of this study is to investigate the influence of microwave pretreatment on magnetic separation of ilmenite using response surface methodology. Microwave power, time, and mass of sample are the main three dominant factors selected as independent

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Table 1 Chemical compositions of Panzhihua ilmenite ore (wt.%). ΣFe

TiO2

SiO2

CaO

MgO

Al2O3

Others

30.67

15.71

20.38

6.48

7.12

3.33

16.28

variables while recovery ratio of ilmenite is selected as a dependent variable. The optimum process conditions that result in highest ilmenite recovery are identified using the Design Expert software package. 2. Experimental 2.1. Materials The ilmenite utilized in the present study was obtained from Panzhihua City, Sichuan Province, China. The chemical compositions of ilmenite were shown in Table 1. The mineralogical analysis of the ilmenite was performed using X-ray diffraction. Fig. 1 shows the XRD pattern of the ilmenite. It was observed that magnetite (Fe3O4) and ilmenite (FeTiO3) were the main crystalline compounds in the ore; in addition, a minor amount of SiO2, CaO, TiO2, MgO and Al2O3 was also present. 2.2. Characterization The raw and microwave pretreated ilmenite was characterized by X-ray diffractometer (D/Max 2200, Rigaku, Japan) at a scanning rate of 0.25°/min with 2θ ranging from 5° to 100° using CuKα radiation (λ =1.5418 Å) and a Ni filter. The voltage and anode current operated were 35 kV and 20 mA, respectively. 2.3. Instrumentation The microwave pretreatment experiments were carried out in a lab-made microwave muffle furnace (Fig. 2). Typical industrial microwave muffle furnace consists of a magnetron to produce the microwaves, a waveguide to transport the microwaves, a resonance cavity to manipulate microwaves for a specific purpose, and a control system to regulate the temperature and microwave power. The power supply of the microwave muffle furnace was two magnetrons at 2.45 GHz frequency and 1.5 kW power, which was cooled by water circulation. The inner dimensions of the multi-mode microwave resonance cavity were 260 mm in height, 420 mm in length and 260 mm in width. The temperature was measured using a Type K thermocouple with a thin layer of aluminum shielding, placed at the closest proximity to the

Intensity/CPS

1-Ilmenite 2-Fe3 O4 1 3-Magnesium alumosilicate 4-Rutile TiO2 5-Aluminum silicate

2 11

1500

1000

2 1

500

3 3

5

sample. The thermocouple provides feedback information to the control panel that controls the power to the magnetron, controlling the temperature of the sample during the microwave pretreatment process in order to prevent the sample from overheating.

2

4 4

Fig. 2. Schematic diagram and picture of microwave reactor of multi-mode with continuous controllable power. 1—Oven door; 2—Observation door; 3—Microwave multi-mode cavity; 4—Time; 5—Power controller; 6—Fireproof materials; 7—Raw materials; 8—Ventilation hole; 9—Temperature.

22 1 5

2.4. Procedure

0 0

20

40

60

80

2-Theta/deg Fig. 1. The X-ray diffraction pattern of the ilmenite.

100

Ilmenite (16.36–83.64 g) was weighed and placed in the microwave muffle furnace which was irradiated for varying exposure times (6.48–48.52 min) at different power levels (522.75–2877.25 W). After irradiation the sample was naturally cooled in the furnace to the room

60

G. Chen et al. / Powder Technology 232 (2012) 58–63

temperature. After microwave pretreatment, the treated samples were ground for 60 s by using a laboratory crusher (XMQ 240 × 90, conical ball mill, China). Subsequently, magnetic separation trials were carried out to determine the liberation. Magnetic separations were realized on the electromagnetic separator (XCGS-73, Magnetic tube, China) with a magnetic field intensity of 3.0KOe, which is specified to the wet mode of separation. At the end of the experimental, the recovery ratio was calculated based on the following equation: Recovery ratioð% Þ ¼

m  100 m0

ð1Þ

where m and m0 were the metal weight separated using magnetic separator (g) and the total metal weight of sample (g), respectively. 2.5. Experimental design Microwave power (χ1), time (χ2), and mass of sample (χ3) were chosen as independent variables, while recovery ratio (Y) was the response (dependent variable). The range and the levels of the independent variables investigated in this study are given in Table 2. On the basis of preliminary experiments the levels of independent variables were chosen to be 1000 to 2400 W, 15 to 40 min and 30 to 70 g, respectively. The design matrix was generated using the design expert software (version 7.1.5, STAT-EASE Inc., Minneapolis, USA), which depicts the experimental conditions and the resultant output variable (recovery ratio) as shown in Table 3. As seen from Table 3, the complete design consisted of 20 experimental points (8 factorial points, 6 axial points and 6 center points), covering all combinations of the independent variables along with the repeat experimental runs. For the purpose of statistical calculations, the chosen independent variables were coded according to Eq. (2) [33,34]:

Table 3 Experimental design matrix and results. Run

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

Variables Microwave power (W)

Time (min)

Mass of sample (g)

1000.00 2400.00 1000.00 2400.00 1000.00 2400.00 1000.00 2400.00 522.75 2877.25 1700.00 1700.00 1700.00 1700.00 1700.00 1700.00 1700.00 1700.00 1700.00 1700.00

15.00 15.00 40.00 40.00 15.00 15.00 40.00 40.00 27.50 27.50 6.48 48.52 27.50 27.50 27.50 27.50 27.50 27.50 27.50 27.50

30.00 30.00 30.00 30.00 70.00 70.00 70.00 70.00 50.00 50.00 50.00 50.00 16.36 83.64 50.00 50.00 50.00 50.00 50.00 50.00

Recovery ratio (%) 58.00 66.00 60.00 66.00 57.00 62.00 60.00 65.00 61.00 72.00 60.00 64.00 62.00 61.00 66.00 65.00 66.00 68.00 65.00 65.00

3. Results and discussion The objective of the present work is to assess the effect of operating variables such as microwave power, time and sample mass on recovery ratio of ilmenite using central composite design of the response surface methodology and to identify the optimal experimental conditions to maximize the recovery ratio of ilmenite [37]. Table 3 also provides the results of the experiments in terms of percentage recovery of ilmenite, which was found to vary from 57.00 to 72.00%. 3.1. Statistical analysis

ðχ −χ 0 Þ Xi ¼ i Δχ

ð2Þ

where Xi is a coded value of the variable, χi is the actual value of variable, χ0 is the actual value of the Xi at the center point level, and Δχ is the step change of variable. The quadratic equation for predicting the optimal conditions can be expressed according to Eq. (3) [35,36]:

Y ¼ β0 þ

k X

βi χ i þ

i¼1

k X

2

n −1 X

βii χ i þ

i¼1

n X

βij χ i χ j

ð3Þ

i¼1 j¼iþ1

where β0 is a constant coefficient, βi is the linear coefficient, βii is the quadratic coefficients and βij is the interaction coefficients, k is the number of factors studied and optimized in the experiment, χi, χj are the coded values of independent variables, and the terms χiχj and χi2 represent the interaction and quadratic terms, respectively. The software ‘Design Expert’ was used for the central composite design, experimental data analysis, quadratic model buildings, polynomial equations evaluation, and three dimensional response surface and contour plotting.

Table 2 Coded value of the independent variables and experimental ranges. Independent variables

Microwave power (W) Time (min) Mass of sample (g)

Coded parameters −1.682

−1

0

1

1.682

522.75 6.48 16.36

1000.00 15.00 30.00

1700.00 27.50 50.00

2400.00 40.00 70.00

2877.25 48.52 83.64

The ANOVA results of the quadratic model for recovery ratio are summarized in Table 4. According to Joglekar and May [38], the correlation coefficient of a good fit of a model should be at a minimum of 0.80, while an high R 2 value illustrates better agreement between the calculated and observed results within the range of experiments [33,39]. The correlation coefficient (R 2 = 0.9410) clearly indicates the proximity of the model equation with the experimental data. The adjusted determination coefficient (R 2 = 0.8879) is also high advocating the significance of the model [6,17]. The closer the value of adjusted R 2 to 1, the better is the correlation between the experimental and predicted values [40]. The lack-of-fit F-value of 1.18 implies that it is not significant relative to the pure error. There is a 42.90% chance that a large lack-of-fit F-value could occur due to noise. The coefficient of variation (CV) indicates the degree of precision with which the experiments were conducted and is a good index of the reliability of the experiment [17,29]. A lower CV means a higher reliability

Table 4 Analysis of the variance (ANOVA) for response surface quadratic model for recovery ratio. Source of variation

Degrees of freedom

Sum of squares

Mean square

F-value

p-value

Linear 2FI Quadratic Cubic Residual error Lack-of-Fit Pure error Total

11 8 5 1 10 5 5 19

93.66 89.16 8.09 6.55 14.92 8.09 6.83 252.95

8.51 11.14 1.62 6.55 1.49 1.62 1.37

6.23 8.15 1.18 4.79

0.0280 0.0167 0.4290 0.0802

1.18

0.4290

R2 = 0.9410; adj. R2 = 0.8879; CV = 1.93%; Adequate precision = 15.754 (>4.0).

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Table 5 Regression coefficients of predicated second-order polynomial model for the response variable. Source Regression analysis Degrees of Sum of Coefficient Standard freedom squares error of coefficient Model χ1 χ2 χ3 χ1 χ2 χ1 χ3 χ2 χ3 χ12 χ22 χ32

65.88 3.11 1.08 −0.56 −0.066 −1.66 −1.83 −0.25 −0.50 0.50

0.50 0.33 0.33 0.33 0.32 0.32 0.32 0.43 0.43 0.43

9 1 1 1 1 1 1 1 1 1

Mean squares

238.03 26.45 132.26 132.26 15.88 15.88 4.32 4.32 0.064 0.064 39.59 39.59 48.48 48.48 0.50 0.50 2.00 2.00 2.00 2.00

F-value p-value

17.73 88.65 10.64 2.90 0.043 26.53 32.50 0.34 1.34 1.34

b0.001 b0.001 0.0085 0.1196 0.8406 0.0004 0.0002 0.5755 0.2738 0.2738

of the experiment. The lower value of CV (1.93%) demonstrates that the performed experiments were highly reliable. Adequate precision measures of the signal-to-noise ratio greater than 4 are generally desirable [6,17,29]. The signal to noise ratio of 15.754, clearly indicates the suitability of the model to navigate the design space [29,34]. Multiple regression coefficients obtained by employing a least square technique for second-order polynomial model are summarized in Table 5. The quadratic model F-value of 17.73 implies that the model is significant for recovery ratio. The values of Prob>F>0.0500 indicate that the model terms are significant [17,33]. Table 5 presents the linear termsχ1, χ2, and the interaction terms χ1χ3 and χ2χ3 to be significant model terms based on the values of “Prob>F” less than 0.050. The quadratic model equation developed relating to the dependent and independent variables is presented in Eq. (4) Y ¼ 65:88 þ 3:11χ 1 þ 1:08χ 2 −0:56χ 3 −0:07χ 1 χ 2 −1:66χ 1 χ 3 2

2

ð4Þ

2

−1:83χ 2 χ 3 −0:25χ 1 −0:50χ 2 þ 0:50χ 3 where χ1, χ2 and χ3 corresponds to independent variables of microwave power (W), time (min) and mass of sample (g), respectively. Fig. 3 shows the proximity of the model prediction with the experimental data validating the goodness of the fit. In addition the standardized residuals were found to be small, which authenticate the

Fig. 3. Predicted values versus experimental values of recovery ratio.

Fig. 4. Normal probability versus internally studentized residuals.

appropriateness of the model. The normal probability plot of the standardized residuals shown in Fig. 4 demonstrates that there were no abnormalities.

3.2. Process analysis Figs. 5 through 7 show the response surface curves of the independent variables on the dependent variable. The response surface curves are easy and convenient way to understand the interaction effects between two independent variables and to locate the optimum levels. Fig. 5 shows the effect of microwave power and time on the recovery ratio at a fixed mass of sample of 50 g. An increase in microwave power as well as time shows an increase in recovery ratio; however the rate of increase is higher at lower levels as compared to higher levels of microwave power and time. An increase in the microwave power possibly increases inter granular fracture, which usually occurs in the weak and brittle grain boundary under microwave irradiation. An increase in the recovery ratio with time was well understood, as

Fig. 5. Response surface plot for the interactive effect of microwave power and time: fixed mass of sample at optimum point of 50 g.

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G. Chen et al. / Powder Technology 232 (2012) 58–63 Table 6 Validation of the model. Microwave power (W)

Time (min)

Mass of sample (g)

Recovery ratio Predicted

Experimental

2400

30.11

44.80

69.15

68.73

3000

1

1-Fe3O4 2-Ilmenite

Intensity/CPS

2500 2000 1500 1000

1

1 2

Fig. 6. Response surface plot for the interactive effect of microwave power and mass of sample: fixed time at optimum point of 27.5 min.

1

1 1

500

2

2

2

0

the number of intergranular fracture increases with increase in the microwave exposure time. However the increase in recovery ratio, with both the microwave power as well as the time seems to reach an asymptote indicating the optimum conditions. Fig. 6 shows the effect of microwave power and mass of sample on the recovery ratio at the time of 27.5 min. As can be seen, the recovery ratio increases with increase in microwave power and mass of sample, however the effect of mass of sample is not as significant as the microwave power. It is also evident from the low p value of this parameter through the ANOVA analysis indicating the insignificance of the mass sample on the recovery ratio. Fig. 7 shows the effect of time and mass of sample on the recovery ratio at the microwave power of 1700 W. The effect of time is found to be significant while the effect of mass of sample is found to be insignificant on the recovery ratio. 3.3. Process optimization The optimized conditions were calculated by using ‘Design Expert’ software package and were identified to be 2400 W microwave power,

0

20

40

60

80

2-Theta/deg Fig. 8. The X-ray diffraction patterns of the magnetic separation concentrates.

30.11 min time, and 44.80 g mass of sample, with an estimated recovery ratio of 69.15%. Experiments were repeated at the optimized conditions to check its validity of the model and results were summarized in Table 6. A yield of 68.73% clearly indicates that the optimized conditions generated using the Design Expert software was sufficiently accurate. The magnetically separated samples under the optimum experimental conditions were characterized by XRD, and the results were shown in Fig. 8. It can be found from Fig. 8 that the diffraction peaks of magnetite (Fe3O4) and ilmenite (FeTiO3) gradually broadened and their intensities increased under microwave pretreatment followed by magnetic separation processes [41]. All the X-ray diffraction peaks of magnetite (Fe3O4) and ilmenite (FeTiO3) matched well with those of the standard XRD pattern. The chemical compositions of ilmenite concentrate and gangue at optimum conditions were shown in Tables 7 and 8, respectively. The demonstration of microwave irradiation techniques can be applied effectively and efficiently to the treatment processing of ilmenite. The comparison of recovery rate of ilmenite between conventional and microwave conditions is shown in Fig. 9. It can be seen that the recovery rate of ilmenite increases with increasing microwave power. And the recovery rates of microwave treated ilmenite were higher than that of the conventional treated sample.

Table 7 Chemical compositions of ilmenite concentrate under optimized conditions (wt.%). TiO2

ΣFe

SiO2

CaO

MgO

Al2O3

45.35

14.23

15.38

8.48

8.12

4.33

Table 8 Chemical compositions of gangue under optimized conditions (wt.%).

Fig. 7. Response surface plot for the interactive effect of time and mass of sample: fixed microwave power at optimum point of 1700 W.

ΣFe

TiO2

SiO2

CaO

MgO

Al2O3

51.87

11.89

17.56

5.78

6.34

4.23

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63

Recovery rate of magnetite/%

Acknowledgments 70

Financial supports from the National Natural Science Foundation of China (No: 51090385), and the National Basic Research Program of China (No: 2007CB613606) were sincerely acknowledged.

60

References

50

40

0

1.0

1.5

2.0

2.5

3.0

Microwave power/kW Fig. 9. The recovery rate of ilmenite at conventional and microwave conditions.

4. Conclusion The response surface methodology was applied to assess the effect of microwave power, time and mass of sample on recovery ratio of ilmenite and to identify the optimized experimental conditions in order to maximize the recovery ratio. The optimum conditions were identified to be a microwave power of 2400 W, time of 30.11 min and mass of sample of 44.80 g resulting in a maximum recovery ratio of 68.73%. The statistical analysis identified only the microwave power and time to be significant parameters while the mass of sample was found to be insignificant. The results show that response surface methodology is one of the suitable methods to optimize the best operating conditions in a multi-factor operating environment for the purpose of obtaining maximum recovery ratio of ilmenite. It can be concluded that microwave pretreatment can turn out to be a potential pre-treatment to enhance magnetic separation of ilmenite and improve recovery ratio of magnetite (Fe3O4) and ilmenite (FeTiO3). Nomenclature m the metal weight of magnetic separation concentrates (g) defined by Eq. (1) m0 the total metal weight of sample (g) defined by Eq. (1) χ1 Microwave power (kW) χ2 time (min) χ3 mass of sample (g) Y recovery ratio (%) k the number of factors

Greek symbols Xi the coded value of the variable defined by Eq. (2) χ0 the actual value of the Xi defined by Eq. (2) Δχ the step change of variable defined by Eq. (2) β0 the constant coefficient defined by Eq. (3) βi the linear coefficient defined by Eq. (3) βii the quadratic coefficients defined by Eq. (3) βij the interaction coefficients defined by Eq. (3)

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