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Kinetic study on bastnaesite concentrate mechanochemical decomposition in NaOH solution
Journal Pre-proof The kinetic study on bastnaesite concentrate mechanochemical decomposition in NaOH solution Jiang Liu, Zhihe Dou, Ting-an Zhang PII:
S1002-0721(19)30431-4
DOI:
https://doi.org/10.1016/j.jre.2019.10.002
Reference:
JRE 626
To appear in:
Journal of Rare Earths
Received Date: 12 June 2019 Revised Date:
12 September 2019
Accepted Date: 9 October 2019
Please cite this article as: Liu J, Dou Z, Zhang Ta, The kinetic study on bastnaesite concentrate mechanochemical decomposition in NaOH solution, Journal of Rare Earths, https://doi.org/10.1016/ j.jre.2019.10.002. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © [Copyright year] Published by Elsevier B.V. on behalf of Chinese Society of Rare Earths.
The kinetic study on bastnaesite concentrate mechanochemical decomposition in NaOH solution Jiang Liu, Zhihe Dou, Ting-an Zhang* Key Laboratory of Ecological Metallurgy of Multi-Metal Intergrown Ores of Ministry of Education, School of Metallurgy, Northeastern University, Shenyang 110819, China
Abstract Mechanochemical reaction involves simultaneous chemical reaction and particle crushing; the latter increases the effective reaction area and improves the reactivity, thus enhancing its kinetics. The classical shrinking core model was used to model the kinetics of bastnaesite mechanochemical decomposition in NaOH solution, which showed a questionable result. Mechanochemical reaction is a dynamic process, where the particle shape and concentration in reaction interface undergo constant change. Thus, a physically consistent model was applied to describe the kinetics. The variations in OH− concentration and particle shape were considered in the revision of model. Considering the variation in OH− concentration in solution with time, the model with varying OH− concentration agreed better with the experimental data, improving the regression coefficients to between 0.936 and 0.992. By introducing fractal geometry to deal with the irregular system, the model was further optimized, and the regression coefficients increased to between 0.940 and 0.997. All these models considered shrinking particle approaches and controlling mechanisms for the diffusion and chemical reaction. Finally, the fractal model with varying OH− concentration was selected to describe the mechanochemical decomposition of bastnaesite, which indicated that the process was controlled by chemical reaction. Keywords: bastnaesite concentrate, mechanochemical decomposition, sodium hydroxide, kinetics 1. Introduction Bastnaesite (REFCO3) is mainly found in Mountain Pass in the United States and Bayan Obo, Shandong, and Sichuan in China[1–3]. It is a major source of rare-earth elements and provides 70% production of rare-earth elements in the world[4–6]. Oxidation roasting–hydrochloric acid leaching method is the most typical method for processing bastnaesite concentrate in industry. This method mainly involves four steps: oxidation roasting, prior dissolution with hydrochloric acid, conversion with caustic (NaOH), and the second hydrochloric acid leaching. However, this method suffers from some problems such as complex flows, low recovery of rare-earth elements, high energy consumption, and loss of fluorine[7–9]. Caustic decomposition is a mature method, where rare-earth fluorocarbons are directly transformed into hydroxides using NaOH, followed by HCl leaching to extract rare-earth elements. Thus, the process is simpler and better understood[10]. However, the technology has not been applied in industrial production because direct caustic decomposition has a low decomposition efficiency, causing low recovery efficiency of rare-earth elements, high alkali consumption, and generation of Foundation item: The authors gratefully acknowledge the financial support received from Fundamental Research Funds for the Central Universities (N172506009, N170908001, N182515007, N180725023) and National Nature Science Foundation of China (U1508217). *Corresponding author: Ting-an Zhang (E-mail address: [email protected] )
a large amount of alkaline waste water. Consequently, some special methods such as microwave heating and ultrasound-assisted leaching have been introduced to enhance mineral processing[11–13]. Nowadays, mechanochemical decomposition of minerals has received much attention in hydrometallurgy and achieved good results[14]. It is a high-energy ball milling process, where particle crushing and chemical reaction proceed simultaneously. Particle breakage leads to a decrease in particle size, shape irregularity, and surface defects, which increases the effective reaction area and improves the reactivity. In the mechanochemical decomposition of bastnaesite, NaOH dosage decreases from 80% (relative to the bastnaesite mass) in traditional decomposition to 66%, and at the same time, the decomposition rate significantly improves[15][16]. Consequently, mechanochemical treatment effectively enhances the decomposition of minerals as well as its kinetics. However, it is difficult to model such a dynamical process. 1) Change in ion concentration in reaction interface. A low liquid–solid ratio is required because excessive liquid environment can weaken the milling effect from balls to materials; therefore, reactant ion concentration changes with progressive decomposition. 2) Change in particle shape caused by mechanical milling. The change causes variation in effective reaction area. Thus, it is necessary to apply a physically consistent model to provide a better description for the kinetic process of mechanochemical reaction. In this study, the kinetics on bastnaesite mechanochemical decomposition with NaOH solution was evaluated. The models considered shrinking core approaches, variation in OH− concentration, and fractal dimension. The controlling mechanism of the process was determined; thus, the strengthening mechanism of mechanochemical decomposition was analyzed. 2 Experimental 2.1 Materials The bastnaesite concentrate used in this experiment was obtained from Mianning, Sichuan. The main chemical and phase compositions are shown in Table 1 and Fig. 1, respectively. This indicates bastnaesite has a high purity, and the rare-earth elements exit in the form of REFCO3. The particle size is large, and its distribution is shown in Fig. 2. NaOH used in the experiment was analytical-grade reagent; all the solutions were prepared with distilled water. 2.2 Experimental procedure Experiments of ball milling and alkaline decomposition of bastnaesite concentrate were performed using a homogeneous reactor (DGL-2002). A thermostatic drier box was used as a constant-temperature heating device. The temperature was controlled within ±2 using a thermocouple. Six spherical ball-mill autoclaves were fixed on a stirring shaft in the box, and the stirring shaft was driven using a motor at a given rotational speed. The volume of each ball-mill autoclave is 250 mL; 580 g balls with dimensions of φ 8 mm, φ 10 mm, and φ 12 mm at the same ratio were placed in the ball-mill autoclave. Five sets of kinetic experiments were performed by varying the rotational speed and temperature, and the corresponding experimental conditions are shown in Table 2. In all the experiments, the values of other parameters including the concentration and liquid-to-solid ratio were kept constant at 56 wt% and 0.8:1, respectively. After the mechanochemical decomposition was completed, the slurry gained was discharged into a baker and washed with distilled water at 70 for 20 min to remove the fluorine. The fluorine content in the
washed residue was measured using distillation-EDTA titration method[17]. According to literature[15], bastnaesite decomposition rate can be calculated as follows:
α = 1 − [(W2 × C2 ) (W1 × C1 )]× 100%
(1)
where W1 and W2 are the mass of bastnaesite and washing slag, respectively; C1 and C2 are the mass percent of fluorine in bastnaesite and washing slag, respectively. 3 Results and discussion 3.1 Mechanochemical decomposition Fig. 3 shows the effect of rotational speed on decomposition rate, where the mechanical energy can be increased by increasing the rotational speed. It is observed that the decomposition rate of bastnaesite increases with increasing time and rotational speed, and the reaction can reach equilibrium more quickly at a higher rotational speed. At 20 or 40 r/min, ∼90 wt% of decomposition rate was obtained after 180 min, while the same decomposition rate was achieved after 60 min at 60 r/min. Fig. 4 shows the change in decomposition rate with time as a function of temperature. Temperature has an important influence on the decomposition rate of bastnaesite and reaction kinetics. The decomposition rate of bastnaesite increases with increasing temperature. At 453 K, 97.6 wt% of decomposition rate was achieved with time of up to 180 min. The changes in element content and phase structure of bastnaesite during the mechanochemical decomposition (60 r/min, 453 K, and 180 min) are shown in Table 1 and Fig. 1, respectively. This indicates that REFCO3 is transformed into RE(OH)3 after decomposition; then, the reaction occurs as follows: REFCO3 + 3NaOH = RE(OH)3 + NaF + Na2CO3 (2) Obviously, the fluorine in REFCO3 is converted into soluble fluoride, which can be completely removed by washing. Thus, as shown in Table 1, the fluorine content in decomposition slag obviously decreases, while the contents of other elements slightly change. In addition, the particle size changes after mechanochemical decomposition, as shown in Fig. 2. After the decomposition for only 5 min, the characteristic particle size of D10, D50, and D90 in initial bastnaesite decreased from 65 µm, 125 µm, and 240 µm to 0.75 µm, 7.25 µm, and 24.2 µm, respectively. At the same time, the distribution behavior is transformed from a standard normal distribution to bimodal distribution. This indicates that the particle size would change to a broader and more disordered distribution through mechanochemical treatment. Thus, the initial bastnaesite has a narrow particle-size distribution following the kinetics. 3.2 Shrinking core model The decomposition of bastnaesite in a NaOH solution is a heterogeneous reaction (see Eq. 2). In mechanochemical reaction, considering that the kinetics is similar to classical chemical kinetics, the mechanical force is regarded as a perturbation of thermal dynamics, and the surface area increase caused by particle decrease is superposed to the overall kinetic scheme[18]. The shrinking core model is the most common model to describe a liquid–solid reaction kinetics[19]. Assuming the chemical reaction as the rate-controlling step, Model 1 was used to describe the mechanochemical
decomposition of bastnaesite using Eq. (3): Model 1
kc t = 1 − (1 − α )1/3
(3)
Similarly, when the diffusion through product layer becomes the rate-controlling step, the shrinking core model is described as Eq. (4): 2 23 (4) kd t = 1 − α − (1 − α ) Model 2 3 where α is the fractional conversion, kc is the rate constant for chemical reaction control, kd is the rate constant for product diffusion control, and t is the reaction time. By applying standard linear regression analysis, if the process is controlled by chemical reaction, a plot of 1−(1−α)1/3 against time is a straight line; if the diffusion through product layer becomes the rate-controlling step, a plot of 1−2α/3−(1−α)2/3 versus time shows a liner relationship[20]. A plot of Models 1 and 2 against time is shown in Fig. 5. When all the plots are involved in the fitting, the results of the two models are quite poor, where the regression coefficients obtained are between 0.5 and 0.9 only. Some references[10] have suggested a segmented fitting where the plots limited in the 60 min seem to show a much better linear regression fit. Thus, the plots from 0 to 60 min are selected to fit to the different kinetic models, as shown in Fig. 5. The rate constants (slopes of straight lines) and correlation coefficients are shown in Table 3. The plots of Model 2 with time show a better linear fit, indicating that the mechanochemical decomposition of bastnaesite might be controlled by diffusion through product layer. However, this result seems unreasonable and inconsistent with previous studies[26]. Because a mechanochemical reaction generally removes the product layer and exposes the unreacted surface, the process is more likely to be controlled by chemical reaction, especially at the early stage of reaction. In addition, it is found that the correlation coefficients in the two models decrease from 0.94 to 0.70 with the increase in rotational speed from 20 r/min to 60 r/min. It can be inferred that the deviation between the model and experimental data increases with the enhancement of mechanical effect. Therefore, the linear fitting obtained from shrinking core model is not suitable for describing the mechanochemical reaction process. At this point, the obtained parameters such as rate constant are insignificant. Thus, the classical model should be further developed. The error could be derived from two aspects. First, the model assumes that the solution ionic strength (OH−) remains constant (independent of time), and generally, the kinetic experiments are carried out with a large enough liquid/solid ratio ranging from 20:1 to 100:1, ignoring the effect of variation in solution ionic strength[21][22]. However, a low liquid/solid ratio (0.8:1) was used in the mechanochemical decomposition, because excessive liquid environment would weaken the milling effect of balls to materials. Thus, the assumption is only valid at the beginning of the reaction, and OH− concentration is time-dependent. Second, the shrinking model considers unreacted particles as perfect spheres with smooth surfaces, and the reaction surface moves uniformly towards the center of unreacted ore. The morphology of bastnaesite particles before and after mechanochemical decomposition is shown in Fig. 6. During the mechanochemical decomposition, the particles suffer intense breakage. The particle shape becomes extremely irregular. At the same time, defects and pores are generated on the particle surface and in the product layer. This leads to a change in the
effective reaction area; thus, the change also contributes to the error of model. 3.3 Model with varying OH− concentration The low liquid/solid ratio used in mechanochemical decomposition leads to nonignorable influence on OH− concentration changes. In this case, a physically consistent model with differential expression was found, providing variations in OH− concentration with time[23]. According to Pereira et al., when a chemical reaction is the slowest step, gibbsite leaching in NaOH solution can be described using the following equation: 2
C 3 dCAl = kc 1 − Al0 COH dt C
(5)
where C0 is the initial aluminum concentration in the gibbsite sample, CAl is the Al concentration in solution, and COH is the OH− concentration in solution. However, it is expected to obtain the relationship between decomposition rate α and time t as shown in Table 2; therefore, some modifications were made for Eq. (5), rewritten as Eq. (6): Model 3
dα 23 = kc (1 − α ) COH dt
(6)
Eq. (6) is the kinetic model with variation in OH− concentration, referred to as Model 3, controlled by the chemical reaction for the mechanochemical decomposition of bastnaesite. After such modifications, it can be directly compared with the traditional shrinking core model. However, for the revised model, a rederivation of OH− concentration expression should be carried out. That is modified as follows: With the reaction proceeding, by accompanying the consumption of 3 moles of NaOH, 1 mole of F appears in the solution (see Eq. 2), given as: N OH = 3N F
(7)
where NOH and NF are the mole amounts of used OH− and generated F−, respectively. The relationship between the mole amount of F− NF and the decomposition rate α is: NF =
mF mF0α = MF MF
(8)
where MF is the molar mass of F; mF and mF0 are the mass of F in solution and the mass of F in bastnaesite, respectively. COH is the difference between OH− concentration in the initial solution C0NaOH and the used OH− concentration C△OH. COH can be expressed as follows: 0 COH = CNaOH − C∆OH
C∆OH =
N OH V
(9) (10)
where V is the volume of NaOH solution. Merging Eqs. (7)−(10), 0 COH = CNaOH −
3mF0α M FV
(11)
Notably, if OH− concentration is constant, Eq. (6) can be integrated as Eq. (3). The numerical codes of the model are edited and implemented using the Matlab program. A comparison between the numerical solution of decomposition rate and the experimental data was carried out by nonlinear
regression analysis, and the corresponding parameters were estimated[24]. Model 3 was validated using the experimental data. The nonlinear regression analysis results are shown in Fig. 7, and the parameters are shown in Table 4. Compared with Model 1, the fit of Model 3 to the experimental data has a great improvement. The numerical values of correlation coefficients are improved to between 0.966 and 0.992. When the reaction is controlled by diffusion through product layer, for the gibbsite leaching in NaOH solution kinetics, the physically consistent model with a variation in OH− concentration can be shown as follows[24]: COH dCAl =k −1 3 dt CAl 1 − 0 − 1 Cgibb
(12)
Similarly, some modifications about Eq. (12) were performed to obtain the relationship between decomposition rate α and time t. Eq. (13) can be expressed as follows: Model 4
COH dα = kd −1 3 dt (1 − α ) − 1
(13)
Eq. (13) shows the kinetic model with OH− concentration, referred to as Model 4, with diffusion through product layer being the rate-controlling step for bastnaesite mechanochemical decomposition. A comparison between Model 4 and the experimental data is shown in Fig. 7. The results of model parameters are shown in Table 4. The correlation coefficients on the curves and the experimental values indicate that Model 4 better correlates with the experimental data than Model 2; the numerical values of correlation coefficients range from 0.936 to 0.977. 3.4 Fractal model When the particle is assumed to be a perfect sphere, the surface area of bastnaesite particle and unreacted core follows a proportional relationship with the square of radius. Considering the irregular particles obtained by mechanical milling, fractal geometry was introduced to provide a better description of reaction area[24]. Then, the fractal area is directly proportional to rp, which can be expressed as follows:
Ap = k p' r p
(14)
where p is the fractal dimension between 1 and 3, providing a better description of the reactive surface area. Ap is the fractal area; kp′ is a constant with reactive surface area and fractal dimension. When the reaction is controlled by a chemical reaction, using the fractal area as the reactive area, Model 3 can be reconstructed and converted to Model 5. Therefore, the fractal model with chemical reaction control for the mechanochemical decomposition of bastnaesite can be expressed as follows: dα p 3 Model 5 (15) = kc (1 − α ) COH dt
A comparison of Model 5 with the experimental data is shown in Fig. 8, and the results of nonlinear regression analysis are shown in Table 5. Model 3 is further optimized by the addition of fractal geometry with a reactive area surface, where the correlation coefficient for each group of
experimental data obtained by Model 5 is higher than the correlation coefficient obtained by Model 3. Most of the numerical values obtained for the correlation coefficient are above 0.98, indicating a good agreement between the models and experimental data. At the same time, the numerical values of fractal dimension p are in a reasonable range (1–3). Thus, it can be inferred that the fractal model with chemical reaction control is suitable for modeling the kinetic process of bastnaesite mechanochemical decomposition. Similarly, if diffusion through product layer is the rate-controlling step, the fractal concept is also used to develop Model 4. Therefore, Model 4 can be recast to give Model 6, shown as follows: Model 6
COH dα =k 1− p / 3 dt (1 − α )( ) − 1
(16)
Model 6 describes the fractal model controlled by the diffusion through product layer. Fig. 8 and Table 5 respectively show the fitting results obtained between the model and experimental data and the parameters obtained by nonlinear regression analysis. The figures and correlation coefficient suggest that Model 6 also made a certain progress in comparison with Model 4. The numerical values of correlation coefficients are between 0.940 and 0.977. Among all the models, obviously Model 5 provides the best fitting between the model and experimental data; therefore, it is considered that the mechanochemical decomposition of bastnaesite is controlled by chemical reaction. Some parameters such as fractal dimension and reaction rate constant were obtained using Model 5, as shown in Table 5. The activation energy is calculated using Arrhenius Law. The values of lnk are plotted against 1000/T, as shown in Fig. 9. The activation energy is determined to be 20.36 kJ/mol, further confirming the control step of chemical reaction. In addition, some parameters in Table 5 are analyzed to elucidate the mechanochemical reaction mechanism. Experiments a, b, and e and Experiments c, d, and e are two sets of progressive experimental processes, corresponding to the increase in rotational speed and temperature, respectively. The rate constant kc increases with increasing rotational speed and temperature, indicating that the decomposition is promoted. The fractal dimension reflects the degree of irregularity of particle shape, and a higher numerical value demonstrates more irregularity of particle shape[25]. The fractal dimension increases with the increase in rotational speed. The larger the rotational speed, the greater the mechanical impact, thus causing more intense breakage for reactant particles, i.e., introduction of mechanical energy leads to intense breakage of particles, thus strengthening the reaction process. In addition, owing to the breakage of particles, the product layer is stripped out, and a fresh and unreacted surface is constantly exposed. Consequently, the remaining unreacted bastnaesite particles can be directly reacted with the NaOH solution, and the reaction rate is determined by the chemical reaction. 4 Conclusions In this study, the kinetics of bastnaesite mechanochemical decomposition is evaluated. The decomposition rate of bastnaesite increases with the increase in rotational speed or temperature. Several models considering shrinking particle approaches and controlling mechanisms for the diffusion and chemical reaction are developed and analyzed experimentally.
The classical shrinking core model shows a questionable result. This is due to the low liquid/solid ratio and the actual irregular particle morphology during the mechanochemical decomposition. The model with varying OH− concentration shows a great improvement than the shrinking core model, and the regression coefficients increase to between 0.936 and 0.992. Further, fractal geometry is introduced to the irregular system, and the optimized model with fractal dimension provides the best fitting results with increasing regression coefficients to between 0.940 and 0.997. Thus, the fractal model is selected to model the mechanochemical decomposition of bastnaesite, and the process is controlled by chemical reaction. The mechanochemical treatment effectively strengthens the decomposition process. This can be attributed to the breakage of reactant particles and exposure of unreacted surface. References [1] Jordens A, Cheng YP, Waters KE. A review of the beneficiation of rare earth element bearing minerals. Miner Eng. 2013;41:97. [2] Srinivasan SG, Shivaramaiah R, Kent PRC, Stack AG, Riman R, Anderko A, et al. A comparative study of surface energies and water adsorption on Ce-bastnasite, La-bastnaasite, and calcite via density functional theory and water adsorption calorimetry. Phys Chem Chem Phys. 2017;19(11):7820. [3] Wang LS, Huang XW, Yu Y, Zhao LS, Wang CM, Feng ZY, et al. Towards cleaner production of rare earth elements from bastnaesite in China. J Clean Prod. 2017;165:231. [4] Kanazawa Y, Kamitani M. Rare earth minerals and resources in the world. J Alloys Compd. 2006;408:1339. [5] Zhong CB, Xu CL, Lyu RL, Zhang ZY, Wu XY, Chi RA. Enhancing mineral liberation of a Canadian rare earth ore with microwave pretreatment. J Rare Earths. 2018;36(2):215. [6] Liu J, Zhang TA, Dou ZH, Liu Y, Lv GZ. Study on the decomposition process of bastnaesite concentrate in NaOH-CaO-H2O system. J Rare Earths. 2019;37(7):760. [7] Huang XW, Long ZQ, Wang LS, Feng ZY. Technology development for rare earth cleaner hydrometallurgy in China. Rare Metals. 2015;34(4):215. [8] Jha MK, Kumari A, Panda R, Kumar JR, Yoo K, Lee JY. Review on hydrometallurgical recovery of rare earth metals. Hydrometallurgy. 2016;165:2. [9] Wang LS, Yu Y, Huang XW, Long ZQ, Cui DL. Toward greener comprehensive utilization of bastnaesite: Simultaneous recovery of cerium, fluorine, and thorium from bastnaesite leach liquor using HEH(EHP). Chem Eng J. 2013;215:162. [10] Cen P, Wu WY, Bian X. Study on Kinetic Mechanism of Bastnaesite Concentrates Decomposition Using Calcium Hydroxide. Metall Mater Trans B. 2018;49(3):1197. [11] Huang YK, Zhang TA, Dou ZH, Liu J, Tian JH. Decomposition of the mixed rare earth concentrate by microwave-assisted method. J Rare Earths. 2016;34(5):529. [12] Huang YK, Zhang TA, Dou ZH, Liu J, Tian JH. Influence of microwave heating on the extractions of fluorine and Rare Earth elements from mixed rare earth concentrate. Hydrometallurgy. 2016;162:104.
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Tables Table 1. Chemical compositions of bastnaesite before (1) and after (2) mechanochemical decomposition RE2O3 F Fe SiO2 CaO (1)
77.66
8.01
0.81
0.41
0.14
(2)
79.25
0.82
0.90
0.40
0.10
Table 2. Experimental conditions Experiment
Rotational speed (r/min)
a b c d e
20 40 60 60 60
Table 3. Parameters obtained by Models 1 and 2 Model
1
2
Model
3
4
Experiment
Rate constant k
a b c d e a b c d e
6.42×10−3 7.22×10−3 7.00×10−3 7.70×10−3 9.60×10−3 2.10×10−3 2.31×10−3 2.20×10−3 2.61×10−3 3.62×10−3
Correlation coefficient R2 0.947 0.843 0.983 0.983 0.703 0.993 0.931 0.978 0.979 0.743
Table 4. Parameters obtained by Models 3 and 4 Rate constant Correlation Experiment k coefficient R2 a 1.72×10−3 0.986 b 2.31×10−3 0.978 c 1.54×10−3 0.991 d 1.77×10−3 0.992 −3 e 3.89×10 0.966 a 2.19×10−6 0.977 b 3.46×10−4 0.964 c 2.05×10−4 0.968 −4 d 2.48×10 0.960 e 7.30×10−4 0.936
Table 5. Parameters obtained by Models 5 and 6 Model
5
6
Experiment
Rate constant k
Fractal dimension p
Correlation coefficient R2
a b c d e a b c d e
2.00×10−3 2.71×10−3 1.59×10−3 1.85×10−3 3.70×10−3 3.71×10−7 3.19×10−6 1.65×10−6 4.80×10−6 1.60×10−3
1.519 1.719 2.343 2.999 3.000 1.001 1.005 1.007 1.026 2.695
0.997 0.982 0.992 0.994 0.969 0.977 0.966 0.972 0.965 0.940
Figures 2 2
2
Intensity(a.u.)
(2)
2 2 2 2 2 2 2 222 2 2 22 2
1 1
1-REFCO3
1
2-RE(OH)3
1 1
11 1
(1) 0
20
1 1 1 1 11 1 1 1111
40
60
80
100
2θ/(°)
Fig. 1. XRD patterns of bastnaesite (1) before and (2) after mechanochemical decomposition 12 volume density/vol%
10 8
Bastnaesite Decomposition residue
6 4 2 0 0.1
1
10 100 Particle size/µm
1000
Fig. 2. Particle size distributions of bastnaesite concentrate before and after decomposition
Decomposition rate/wt%
100 80 20 r/min 40 r/min 60 r/min
60 40 20 0
20 40 60 80 100 120 140 160 180 200 Time/min
Fig. 3. Effect of rotational speed on decomposition rate (at 453 K using 56 wt% concentrate of NaOH solution with a liquid/solid ratio of 0.8:1).
Decomposition rate/wt%
100 80 60
393 K 423 K 453 K
40 20 0
0
20 40 60 80 100 120 140 160 180 200 Time/min
Fig. 4. Effect of temperature on decomposition rate (at 60 r/min using 56 wt% concentrate of NaOH solution with a liquid/solid ratio of 0.8:1).
0.20
(a) Model 1
1-2α/3-(1-α)2/3
1-(1-α)1/3
0.6 0.4 0.2 0.0
0
50
100 Time/min
0.15 0.10 0.05 0.00
150
(a) Model 2
0
50
100 Time/min
150
0.25
1-(1-α)1/3
1-2α/3-(1-α)2/3
(b) Model 1
0.6 0.4 0.2
0
1-(1-α)1/3
0.6
50
100 Time/min
150
0.10 0.05 0.00
0
0.2
50
100 Time/min
0.10 0.05
150
0
0.25 1-2α/3-(1-α)2/3
1-(1-α)1/3
Model 1
0.4 0.2 0.0
50
100 Time/min
1-2α/3-(1-α)2/3
1-(1-α)1/3
0.6 0.4 0.2 0.0
150
0.10 0.05 0
0.30
(e) Model 1
100 Time/min
0.15
150
0.8
50
(d) Model 2
0.20
0.00 0
150
(c) Model 2
(d) 0.6
100 Time/min
0.15
0.00 0
50
0.20
(c) Model 1
0.4
0.0
0.15
1-2α/3-(1-α)2/3
0.0
(b) Model 2
0.20
50
100 Time/min
150
(e)
0.25
Model 2
0.20 0.15 0.10 0.05 0.00
0
50
100 Time/min
150
0
50
100 Time/min
150
Fig. 5. Fit of Models 1 and 2 to experimental data: (a)-Experiment a; (b)-Experiment b; (c)-Experiment c; (d)-Experiment d; (e)-Experiment e
Fig. 6. SEM images of bastnaesite particles (a) before decomposition and (b) after decomposition (b) 5 min, (c) 30 min, and (d) 180 min (decomposition conditions: 60 r/min, 453 K, 56 wt% of NaOH concentration).
(a) 0.8 Model 4
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Fig. 9. Arrhenius plot of reaction rate against temperature Graphic abstract:
1. Mechanochemical decomposition of bastnaesite is controlled by chemical reaction. 2. Fractal model gives a best description on the kinetics.
Dear Editor: We submit our manuscript entitled “The kinetic study on bastnaesite concentrate mechanochemical decomposition in NaOH solution” to Journal of Rare Earths for publication. This manuscript has not been published and is not under consideration for publication elsewhere. We have no conflicts of interest to disclose. Sincerely yours, Jiang Liu (E-mail address:[email protected]) Ting-an Zhang (E-mail address: [email protected])
S1002-0721(19)30431-4
DOI:
https://doi.org/10.1016/j.jre.2019.10.002
Reference:
JRE 626
To appear in:
Journal of Rare Earths
Received Date: 12 June 2019 Revised Date:
12 September 2019
Accepted Date: 9 October 2019
Please cite this article as: Liu J, Dou Z, Zhang Ta, The kinetic study on bastnaesite concentrate mechanochemical decomposition in NaOH solution, Journal of Rare Earths, https://doi.org/10.1016/ j.jre.2019.10.002. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © [Copyright year] Published by Elsevier B.V. on behalf of Chinese Society of Rare Earths.
The kinetic study on bastnaesite concentrate mechanochemical decomposition in NaOH solution Jiang Liu, Zhihe Dou, Ting-an Zhang* Key Laboratory of Ecological Metallurgy of Multi-Metal Intergrown Ores of Ministry of Education, School of Metallurgy, Northeastern University, Shenyang 110819, China
Abstract Mechanochemical reaction involves simultaneous chemical reaction and particle crushing; the latter increases the effective reaction area and improves the reactivity, thus enhancing its kinetics. The classical shrinking core model was used to model the kinetics of bastnaesite mechanochemical decomposition in NaOH solution, which showed a questionable result. Mechanochemical reaction is a dynamic process, where the particle shape and concentration in reaction interface undergo constant change. Thus, a physically consistent model was applied to describe the kinetics. The variations in OH− concentration and particle shape were considered in the revision of model. Considering the variation in OH− concentration in solution with time, the model with varying OH− concentration agreed better with the experimental data, improving the regression coefficients to between 0.936 and 0.992. By introducing fractal geometry to deal with the irregular system, the model was further optimized, and the regression coefficients increased to between 0.940 and 0.997. All these models considered shrinking particle approaches and controlling mechanisms for the diffusion and chemical reaction. Finally, the fractal model with varying OH− concentration was selected to describe the mechanochemical decomposition of bastnaesite, which indicated that the process was controlled by chemical reaction. Keywords: bastnaesite concentrate, mechanochemical decomposition, sodium hydroxide, kinetics 1. Introduction Bastnaesite (REFCO3) is mainly found in Mountain Pass in the United States and Bayan Obo, Shandong, and Sichuan in China[1–3]. It is a major source of rare-earth elements and provides 70% production of rare-earth elements in the world[4–6]. Oxidation roasting–hydrochloric acid leaching method is the most typical method for processing bastnaesite concentrate in industry. This method mainly involves four steps: oxidation roasting, prior dissolution with hydrochloric acid, conversion with caustic (NaOH), and the second hydrochloric acid leaching. However, this method suffers from some problems such as complex flows, low recovery of rare-earth elements, high energy consumption, and loss of fluorine[7–9]. Caustic decomposition is a mature method, where rare-earth fluorocarbons are directly transformed into hydroxides using NaOH, followed by HCl leaching to extract rare-earth elements. Thus, the process is simpler and better understood[10]. However, the technology has not been applied in industrial production because direct caustic decomposition has a low decomposition efficiency, causing low recovery efficiency of rare-earth elements, high alkali consumption, and generation of Foundation item: The authors gratefully acknowledge the financial support received from Fundamental Research Funds for the Central Universities (N172506009, N170908001, N182515007, N180725023) and National Nature Science Foundation of China (U1508217). *Corresponding author: Ting-an Zhang (E-mail address: [email protected] )
a large amount of alkaline waste water. Consequently, some special methods such as microwave heating and ultrasound-assisted leaching have been introduced to enhance mineral processing[11–13]. Nowadays, mechanochemical decomposition of minerals has received much attention in hydrometallurgy and achieved good results[14]. It is a high-energy ball milling process, where particle crushing and chemical reaction proceed simultaneously. Particle breakage leads to a decrease in particle size, shape irregularity, and surface defects, which increases the effective reaction area and improves the reactivity. In the mechanochemical decomposition of bastnaesite, NaOH dosage decreases from 80% (relative to the bastnaesite mass) in traditional decomposition to 66%, and at the same time, the decomposition rate significantly improves[15][16]. Consequently, mechanochemical treatment effectively enhances the decomposition of minerals as well as its kinetics. However, it is difficult to model such a dynamical process. 1) Change in ion concentration in reaction interface. A low liquid–solid ratio is required because excessive liquid environment can weaken the milling effect from balls to materials; therefore, reactant ion concentration changes with progressive decomposition. 2) Change in particle shape caused by mechanical milling. The change causes variation in effective reaction area. Thus, it is necessary to apply a physically consistent model to provide a better description for the kinetic process of mechanochemical reaction. In this study, the kinetics on bastnaesite mechanochemical decomposition with NaOH solution was evaluated. The models considered shrinking core approaches, variation in OH− concentration, and fractal dimension. The controlling mechanism of the process was determined; thus, the strengthening mechanism of mechanochemical decomposition was analyzed. 2 Experimental 2.1 Materials The bastnaesite concentrate used in this experiment was obtained from Mianning, Sichuan. The main chemical and phase compositions are shown in Table 1 and Fig. 1, respectively. This indicates bastnaesite has a high purity, and the rare-earth elements exit in the form of REFCO3. The particle size is large, and its distribution is shown in Fig. 2. NaOH used in the experiment was analytical-grade reagent; all the solutions were prepared with distilled water. 2.2 Experimental procedure Experiments of ball milling and alkaline decomposition of bastnaesite concentrate were performed using a homogeneous reactor (DGL-2002). A thermostatic drier box was used as a constant-temperature heating device. The temperature was controlled within ±2 using a thermocouple. Six spherical ball-mill autoclaves were fixed on a stirring shaft in the box, and the stirring shaft was driven using a motor at a given rotational speed. The volume of each ball-mill autoclave is 250 mL; 580 g balls with dimensions of φ 8 mm, φ 10 mm, and φ 12 mm at the same ratio were placed in the ball-mill autoclave. Five sets of kinetic experiments were performed by varying the rotational speed and temperature, and the corresponding experimental conditions are shown in Table 2. In all the experiments, the values of other parameters including the concentration and liquid-to-solid ratio were kept constant at 56 wt% and 0.8:1, respectively. After the mechanochemical decomposition was completed, the slurry gained was discharged into a baker and washed with distilled water at 70 for 20 min to remove the fluorine. The fluorine content in the
washed residue was measured using distillation-EDTA titration method[17]. According to literature[15], bastnaesite decomposition rate can be calculated as follows:
α = 1 − [(W2 × C2 ) (W1 × C1 )]× 100%
(1)
where W1 and W2 are the mass of bastnaesite and washing slag, respectively; C1 and C2 are the mass percent of fluorine in bastnaesite and washing slag, respectively. 3 Results and discussion 3.1 Mechanochemical decomposition Fig. 3 shows the effect of rotational speed on decomposition rate, where the mechanical energy can be increased by increasing the rotational speed. It is observed that the decomposition rate of bastnaesite increases with increasing time and rotational speed, and the reaction can reach equilibrium more quickly at a higher rotational speed. At 20 or 40 r/min, ∼90 wt% of decomposition rate was obtained after 180 min, while the same decomposition rate was achieved after 60 min at 60 r/min. Fig. 4 shows the change in decomposition rate with time as a function of temperature. Temperature has an important influence on the decomposition rate of bastnaesite and reaction kinetics. The decomposition rate of bastnaesite increases with increasing temperature. At 453 K, 97.6 wt% of decomposition rate was achieved with time of up to 180 min. The changes in element content and phase structure of bastnaesite during the mechanochemical decomposition (60 r/min, 453 K, and 180 min) are shown in Table 1 and Fig. 1, respectively. This indicates that REFCO3 is transformed into RE(OH)3 after decomposition; then, the reaction occurs as follows: REFCO3 + 3NaOH = RE(OH)3 + NaF + Na2CO3 (2) Obviously, the fluorine in REFCO3 is converted into soluble fluoride, which can be completely removed by washing. Thus, as shown in Table 1, the fluorine content in decomposition slag obviously decreases, while the contents of other elements slightly change. In addition, the particle size changes after mechanochemical decomposition, as shown in Fig. 2. After the decomposition for only 5 min, the characteristic particle size of D10, D50, and D90 in initial bastnaesite decreased from 65 µm, 125 µm, and 240 µm to 0.75 µm, 7.25 µm, and 24.2 µm, respectively. At the same time, the distribution behavior is transformed from a standard normal distribution to bimodal distribution. This indicates that the particle size would change to a broader and more disordered distribution through mechanochemical treatment. Thus, the initial bastnaesite has a narrow particle-size distribution following the kinetics. 3.2 Shrinking core model The decomposition of bastnaesite in a NaOH solution is a heterogeneous reaction (see Eq. 2). In mechanochemical reaction, considering that the kinetics is similar to classical chemical kinetics, the mechanical force is regarded as a perturbation of thermal dynamics, and the surface area increase caused by particle decrease is superposed to the overall kinetic scheme[18]. The shrinking core model is the most common model to describe a liquid–solid reaction kinetics[19]. Assuming the chemical reaction as the rate-controlling step, Model 1 was used to describe the mechanochemical
decomposition of bastnaesite using Eq. (3): Model 1
kc t = 1 − (1 − α )1/3
(3)
Similarly, when the diffusion through product layer becomes the rate-controlling step, the shrinking core model is described as Eq. (4): 2 23 (4) kd t = 1 − α − (1 − α ) Model 2 3 where α is the fractional conversion, kc is the rate constant for chemical reaction control, kd is the rate constant for product diffusion control, and t is the reaction time. By applying standard linear regression analysis, if the process is controlled by chemical reaction, a plot of 1−(1−α)1/3 against time is a straight line; if the diffusion through product layer becomes the rate-controlling step, a plot of 1−2α/3−(1−α)2/3 versus time shows a liner relationship[20]. A plot of Models 1 and 2 against time is shown in Fig. 5. When all the plots are involved in the fitting, the results of the two models are quite poor, where the regression coefficients obtained are between 0.5 and 0.9 only. Some references[10] have suggested a segmented fitting where the plots limited in the 60 min seem to show a much better linear regression fit. Thus, the plots from 0 to 60 min are selected to fit to the different kinetic models, as shown in Fig. 5. The rate constants (slopes of straight lines) and correlation coefficients are shown in Table 3. The plots of Model 2 with time show a better linear fit, indicating that the mechanochemical decomposition of bastnaesite might be controlled by diffusion through product layer. However, this result seems unreasonable and inconsistent with previous studies[26]. Because a mechanochemical reaction generally removes the product layer and exposes the unreacted surface, the process is more likely to be controlled by chemical reaction, especially at the early stage of reaction. In addition, it is found that the correlation coefficients in the two models decrease from 0.94 to 0.70 with the increase in rotational speed from 20 r/min to 60 r/min. It can be inferred that the deviation between the model and experimental data increases with the enhancement of mechanical effect. Therefore, the linear fitting obtained from shrinking core model is not suitable for describing the mechanochemical reaction process. At this point, the obtained parameters such as rate constant are insignificant. Thus, the classical model should be further developed. The error could be derived from two aspects. First, the model assumes that the solution ionic strength (OH−) remains constant (independent of time), and generally, the kinetic experiments are carried out with a large enough liquid/solid ratio ranging from 20:1 to 100:1, ignoring the effect of variation in solution ionic strength[21][22]. However, a low liquid/solid ratio (0.8:1) was used in the mechanochemical decomposition, because excessive liquid environment would weaken the milling effect of balls to materials. Thus, the assumption is only valid at the beginning of the reaction, and OH− concentration is time-dependent. Second, the shrinking model considers unreacted particles as perfect spheres with smooth surfaces, and the reaction surface moves uniformly towards the center of unreacted ore. The morphology of bastnaesite particles before and after mechanochemical decomposition is shown in Fig. 6. During the mechanochemical decomposition, the particles suffer intense breakage. The particle shape becomes extremely irregular. At the same time, defects and pores are generated on the particle surface and in the product layer. This leads to a change in the
effective reaction area; thus, the change also contributes to the error of model. 3.3 Model with varying OH− concentration The low liquid/solid ratio used in mechanochemical decomposition leads to nonignorable influence on OH− concentration changes. In this case, a physically consistent model with differential expression was found, providing variations in OH− concentration with time[23]. According to Pereira et al., when a chemical reaction is the slowest step, gibbsite leaching in NaOH solution can be described using the following equation: 2
C 3 dCAl = kc 1 − Al0 COH dt C
(5)
where C0 is the initial aluminum concentration in the gibbsite sample, CAl is the Al concentration in solution, and COH is the OH− concentration in solution. However, it is expected to obtain the relationship between decomposition rate α and time t as shown in Table 2; therefore, some modifications were made for Eq. (5), rewritten as Eq. (6): Model 3
dα 23 = kc (1 − α ) COH dt
(6)
Eq. (6) is the kinetic model with variation in OH− concentration, referred to as Model 3, controlled by the chemical reaction for the mechanochemical decomposition of bastnaesite. After such modifications, it can be directly compared with the traditional shrinking core model. However, for the revised model, a rederivation of OH− concentration expression should be carried out. That is modified as follows: With the reaction proceeding, by accompanying the consumption of 3 moles of NaOH, 1 mole of F appears in the solution (see Eq. 2), given as: N OH = 3N F
(7)
where NOH and NF are the mole amounts of used OH− and generated F−, respectively. The relationship between the mole amount of F− NF and the decomposition rate α is: NF =
mF mF0α = MF MF
(8)
where MF is the molar mass of F; mF and mF0 are the mass of F in solution and the mass of F in bastnaesite, respectively. COH is the difference between OH− concentration in the initial solution C0NaOH and the used OH− concentration C△OH. COH can be expressed as follows: 0 COH = CNaOH − C∆OH
C∆OH =
N OH V
(9) (10)
where V is the volume of NaOH solution. Merging Eqs. (7)−(10), 0 COH = CNaOH −
3mF0α M FV
(11)
Notably, if OH− concentration is constant, Eq. (6) can be integrated as Eq. (3). The numerical codes of the model are edited and implemented using the Matlab program. A comparison between the numerical solution of decomposition rate and the experimental data was carried out by nonlinear
regression analysis, and the corresponding parameters were estimated[24]. Model 3 was validated using the experimental data. The nonlinear regression analysis results are shown in Fig. 7, and the parameters are shown in Table 4. Compared with Model 1, the fit of Model 3 to the experimental data has a great improvement. The numerical values of correlation coefficients are improved to between 0.966 and 0.992. When the reaction is controlled by diffusion through product layer, for the gibbsite leaching in NaOH solution kinetics, the physically consistent model with a variation in OH− concentration can be shown as follows[24]: COH dCAl =k −1 3 dt CAl 1 − 0 − 1 Cgibb
(12)
Similarly, some modifications about Eq. (12) were performed to obtain the relationship between decomposition rate α and time t. Eq. (13) can be expressed as follows: Model 4
COH dα = kd −1 3 dt (1 − α ) − 1
(13)
Eq. (13) shows the kinetic model with OH− concentration, referred to as Model 4, with diffusion through product layer being the rate-controlling step for bastnaesite mechanochemical decomposition. A comparison between Model 4 and the experimental data is shown in Fig. 7. The results of model parameters are shown in Table 4. The correlation coefficients on the curves and the experimental values indicate that Model 4 better correlates with the experimental data than Model 2; the numerical values of correlation coefficients range from 0.936 to 0.977. 3.4 Fractal model When the particle is assumed to be a perfect sphere, the surface area of bastnaesite particle and unreacted core follows a proportional relationship with the square of radius. Considering the irregular particles obtained by mechanical milling, fractal geometry was introduced to provide a better description of reaction area[24]. Then, the fractal area is directly proportional to rp, which can be expressed as follows:
Ap = k p' r p
(14)
where p is the fractal dimension between 1 and 3, providing a better description of the reactive surface area. Ap is the fractal area; kp′ is a constant with reactive surface area and fractal dimension. When the reaction is controlled by a chemical reaction, using the fractal area as the reactive area, Model 3 can be reconstructed and converted to Model 5. Therefore, the fractal model with chemical reaction control for the mechanochemical decomposition of bastnaesite can be expressed as follows: dα p 3 Model 5 (15) = kc (1 − α ) COH dt
A comparison of Model 5 with the experimental data is shown in Fig. 8, and the results of nonlinear regression analysis are shown in Table 5. Model 3 is further optimized by the addition of fractal geometry with a reactive area surface, where the correlation coefficient for each group of
experimental data obtained by Model 5 is higher than the correlation coefficient obtained by Model 3. Most of the numerical values obtained for the correlation coefficient are above 0.98, indicating a good agreement between the models and experimental data. At the same time, the numerical values of fractal dimension p are in a reasonable range (1–3). Thus, it can be inferred that the fractal model with chemical reaction control is suitable for modeling the kinetic process of bastnaesite mechanochemical decomposition. Similarly, if diffusion through product layer is the rate-controlling step, the fractal concept is also used to develop Model 4. Therefore, Model 4 can be recast to give Model 6, shown as follows: Model 6
COH dα =k 1− p / 3 dt (1 − α )( ) − 1
(16)
Model 6 describes the fractal model controlled by the diffusion through product layer. Fig. 8 and Table 5 respectively show the fitting results obtained between the model and experimental data and the parameters obtained by nonlinear regression analysis. The figures and correlation coefficient suggest that Model 6 also made a certain progress in comparison with Model 4. The numerical values of correlation coefficients are between 0.940 and 0.977. Among all the models, obviously Model 5 provides the best fitting between the model and experimental data; therefore, it is considered that the mechanochemical decomposition of bastnaesite is controlled by chemical reaction. Some parameters such as fractal dimension and reaction rate constant were obtained using Model 5, as shown in Table 5. The activation energy is calculated using Arrhenius Law. The values of lnk are plotted against 1000/T, as shown in Fig. 9. The activation energy is determined to be 20.36 kJ/mol, further confirming the control step of chemical reaction. In addition, some parameters in Table 5 are analyzed to elucidate the mechanochemical reaction mechanism. Experiments a, b, and e and Experiments c, d, and e are two sets of progressive experimental processes, corresponding to the increase in rotational speed and temperature, respectively. The rate constant kc increases with increasing rotational speed and temperature, indicating that the decomposition is promoted. The fractal dimension reflects the degree of irregularity of particle shape, and a higher numerical value demonstrates more irregularity of particle shape[25]. The fractal dimension increases with the increase in rotational speed. The larger the rotational speed, the greater the mechanical impact, thus causing more intense breakage for reactant particles, i.e., introduction of mechanical energy leads to intense breakage of particles, thus strengthening the reaction process. In addition, owing to the breakage of particles, the product layer is stripped out, and a fresh and unreacted surface is constantly exposed. Consequently, the remaining unreacted bastnaesite particles can be directly reacted with the NaOH solution, and the reaction rate is determined by the chemical reaction. 4 Conclusions In this study, the kinetics of bastnaesite mechanochemical decomposition is evaluated. The decomposition rate of bastnaesite increases with the increase in rotational speed or temperature. Several models considering shrinking particle approaches and controlling mechanisms for the diffusion and chemical reaction are developed and analyzed experimentally.
The classical shrinking core model shows a questionable result. This is due to the low liquid/solid ratio and the actual irregular particle morphology during the mechanochemical decomposition. The model with varying OH− concentration shows a great improvement than the shrinking core model, and the regression coefficients increase to between 0.936 and 0.992. Further, fractal geometry is introduced to the irregular system, and the optimized model with fractal dimension provides the best fitting results with increasing regression coefficients to between 0.940 and 0.997. Thus, the fractal model is selected to model the mechanochemical decomposition of bastnaesite, and the process is controlled by chemical reaction. The mechanochemical treatment effectively strengthens the decomposition process. This can be attributed to the breakage of reactant particles and exposure of unreacted surface. References [1] Jordens A, Cheng YP, Waters KE. A review of the beneficiation of rare earth element bearing minerals. Miner Eng. 2013;41:97. [2] Srinivasan SG, Shivaramaiah R, Kent PRC, Stack AG, Riman R, Anderko A, et al. A comparative study of surface energies and water adsorption on Ce-bastnasite, La-bastnaasite, and calcite via density functional theory and water adsorption calorimetry. Phys Chem Chem Phys. 2017;19(11):7820. [3] Wang LS, Huang XW, Yu Y, Zhao LS, Wang CM, Feng ZY, et al. Towards cleaner production of rare earth elements from bastnaesite in China. J Clean Prod. 2017;165:231. [4] Kanazawa Y, Kamitani M. Rare earth minerals and resources in the world. J Alloys Compd. 2006;408:1339. [5] Zhong CB, Xu CL, Lyu RL, Zhang ZY, Wu XY, Chi RA. Enhancing mineral liberation of a Canadian rare earth ore with microwave pretreatment. J Rare Earths. 2018;36(2):215. [6] Liu J, Zhang TA, Dou ZH, Liu Y, Lv GZ. Study on the decomposition process of bastnaesite concentrate in NaOH-CaO-H2O system. J Rare Earths. 2019;37(7):760. [7] Huang XW, Long ZQ, Wang LS, Feng ZY. Technology development for rare earth cleaner hydrometallurgy in China. Rare Metals. 2015;34(4):215. [8] Jha MK, Kumari A, Panda R, Kumar JR, Yoo K, Lee JY. Review on hydrometallurgical recovery of rare earth metals. Hydrometallurgy. 2016;165:2. [9] Wang LS, Yu Y, Huang XW, Long ZQ, Cui DL. Toward greener comprehensive utilization of bastnaesite: Simultaneous recovery of cerium, fluorine, and thorium from bastnaesite leach liquor using HEH(EHP). Chem Eng J. 2013;215:162. [10] Cen P, Wu WY, Bian X. Study on Kinetic Mechanism of Bastnaesite Concentrates Decomposition Using Calcium Hydroxide. Metall Mater Trans B. 2018;49(3):1197. [11] Huang YK, Zhang TA, Dou ZH, Liu J, Tian JH. Decomposition of the mixed rare earth concentrate by microwave-assisted method. J Rare Earths. 2016;34(5):529. [12] Huang YK, Zhang TA, Dou ZH, Liu J, Tian JH. Influence of microwave heating on the extractions of fluorine and Rare Earth elements from mixed rare earth concentrate. Hydrometallurgy. 2016;162:104.
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Tables Table 1. Chemical compositions of bastnaesite before (1) and after (2) mechanochemical decomposition RE2O3 F Fe SiO2 CaO (1)
77.66
8.01
0.81
0.41
0.14
(2)
79.25
0.82
0.90
0.40
0.10
Table 2. Experimental conditions Experiment
Rotational speed (r/min)
a b c d e
20 40 60 60 60
Table 3. Parameters obtained by Models 1 and 2 Model
1
2
Model
3
4
Experiment
Rate constant k
a b c d e a b c d e
6.42×10−3 7.22×10−3 7.00×10−3 7.70×10−3 9.60×10−3 2.10×10−3 2.31×10−3 2.20×10−3 2.61×10−3 3.62×10−3
Correlation coefficient R2 0.947 0.843 0.983 0.983 0.703 0.993 0.931 0.978 0.979 0.743
Table 4. Parameters obtained by Models 3 and 4 Rate constant Correlation Experiment k coefficient R2 a 1.72×10−3 0.986 b 2.31×10−3 0.978 c 1.54×10−3 0.991 d 1.77×10−3 0.992 −3 e 3.89×10 0.966 a 2.19×10−6 0.977 b 3.46×10−4 0.964 c 2.05×10−4 0.968 −4 d 2.48×10 0.960 e 7.30×10−4 0.936
Table 5. Parameters obtained by Models 5 and 6 Model
5
6
Experiment
Rate constant k
Fractal dimension p
Correlation coefficient R2
a b c d e a b c d e
2.00×10−3 2.71×10−3 1.59×10−3 1.85×10−3 3.70×10−3 3.71×10−7 3.19×10−6 1.65×10−6 4.80×10−6 1.60×10−3
1.519 1.719 2.343 2.999 3.000 1.001 1.005 1.007 1.026 2.695
0.997 0.982 0.992 0.994 0.969 0.977 0.966 0.972 0.965 0.940
Figures 2 2
2
Intensity(a.u.)
(2)
2 2 2 2 2 2 2 222 2 2 22 2
1 1
1-REFCO3
1
2-RE(OH)3
1 1
11 1
(1) 0
20
1 1 1 1 11 1 1 1111
40
60
80
100
2θ/(°)
Fig. 1. XRD patterns of bastnaesite (1) before and (2) after mechanochemical decomposition 12 volume density/vol%
10 8
Bastnaesite Decomposition residue
6 4 2 0 0.1
1
10 100 Particle size/µm
1000
Fig. 2. Particle size distributions of bastnaesite concentrate before and after decomposition
Decomposition rate/wt%
100 80 20 r/min 40 r/min 60 r/min
60 40 20 0
20 40 60 80 100 120 140 160 180 200 Time/min
Fig. 3. Effect of rotational speed on decomposition rate (at 453 K using 56 wt% concentrate of NaOH solution with a liquid/solid ratio of 0.8:1).
Decomposition rate/wt%
100 80 60
393 K 423 K 453 K
40 20 0
0
20 40 60 80 100 120 140 160 180 200 Time/min
Fig. 4. Effect of temperature on decomposition rate (at 60 r/min using 56 wt% concentrate of NaOH solution with a liquid/solid ratio of 0.8:1).
0.20
(a) Model 1
1-2α/3-(1-α)2/3
1-(1-α)1/3
0.6 0.4 0.2 0.0
0
50
100 Time/min
0.15 0.10 0.05 0.00
150
(a) Model 2
0
50
100 Time/min
150
0.25
1-(1-α)1/3
1-2α/3-(1-α)2/3
(b) Model 1
0.6 0.4 0.2
0
1-(1-α)1/3
0.6
50
100 Time/min
150
0.10 0.05 0.00
0
0.2
50
100 Time/min
0.10 0.05
150
0
0.25 1-2α/3-(1-α)2/3
1-(1-α)1/3
Model 1
0.4 0.2 0.0
50
100 Time/min
1-2α/3-(1-α)2/3
1-(1-α)1/3
0.6 0.4 0.2 0.0
150
0.10 0.05 0
0.30
(e) Model 1
100 Time/min
0.15
150
0.8
50
(d) Model 2
0.20
0.00 0
150
(c) Model 2
(d) 0.6
100 Time/min
0.15
0.00 0
50
0.20
(c) Model 1
0.4
0.0
0.15
1-2α/3-(1-α)2/3
0.0
(b) Model 2
0.20
50
100 Time/min
150
(e)
0.25
Model 2
0.20 0.15 0.10 0.05 0.00
0
50
100 Time/min
150
0
50
100 Time/min
150
Fig. 5. Fit of Models 1 and 2 to experimental data: (a)-Experiment a; (b)-Experiment b; (c)-Experiment c; (d)-Experiment d; (e)-Experiment e
Fig. 6. SEM images of bastnaesite particles (a) before decomposition and (b) after decomposition (b) 5 min, (c) 30 min, and (d) 180 min (decomposition conditions: 60 r/min, 453 K, 56 wt% of NaOH concentration).
(a) 0.8 Model 4
0.6
0.6 α
α
1
1 (a) Model 3 0.8
0.4
0.4
0.2
0.2
0 0
50
100 Time/min
150
0 0
200
100 Time/min
150
200
50
100 Time/min
150
200
50
100 Time/min
150
200
50
100 Time/min
150
200
50
100 Time/min
150
200
1
1 (b) Model 3 0.8
(b) 0.8 Model 4 0.6
0.6
α
α
50
0.4
0.4
0.2
0.2
0 0
50
100 Time/min
150
0 0
200
1
1
(c) 0.8 Model 4
0.6
0.6 α
α
(c) 0.8 Model 3
0.4
0.4
0.2
0.2
0 0
50
100 Time/min
150
200
0 0
1
1
(d) 0.8 Model 4
0.6
0.6
α
α
(d) 0.8 Model 3
0.4
0.4
0.2
0.2
0 0
50
100 Time/min
150
200
0 0
1 (e) Model 4 0.8
0.6
0.6
α
α
1 (e) Model 3 0.8
0.4
0.4
0.2
0.2
0 0
50
100 Time/min
150
200
0
Fig. 7. Fit of Models 3 and 4 to experimental data: (a)-Experiment a; (b)-Experiment b; (c)-Experiment c; (d)-Experiment d; (e)-Experiment e.
1
1 0.8
0.6
0.6
0.4
0.4
0.2
0.2
0 0
50
100 Time/min
150
0 0
200
100 Time/min
150
200
50
100 Time/min
150
200
50
100 Time/min
150
200
50
100 Time/min
150
200
50
100 Time/min
150
200
(b) 0.8 Model 6
0.6
0.6 α
α
(b) 0.8 Model 5
0.4
0.4
0.2
0.2
0 0
50
100 Time/min
150
0 0
200
1
1
(c) 0.8 Model 6
0.6
0.6 α
α
(c) 0.8 Model 5
0.4
0.4
0.2
0.2
0 0
50
100 Time/min
150
0 0
200
1
1 (d) Model 5 0.8
(d) 0.8 Model 6 0.6 α
0.6 0.4
0.4
0.2
0.2
0 0
50
100 Time/min
150
0
200
1 (e) Model 5 0.8
1 (e) Model 6 0.8
0.6
0.6 α
α
50
1
1
α
(a) Model 6
α
α
(a) 0.8 Model 5
0.4
0.4
0.2
0.2
0 0
50
100 Time/min
150
200
0 0
Fig. 8. Fit of Models 5 and 6 to experimental data: (a)-Experiment a; (b)-Experiment b; (c)-Experiment c; (d)-Experiment d; (e)-Experiment e.
-5.6
lnk
-5.8 -6.0 -6.2 -6.4 -6.6
2.2
2.3 2.4 1000/T/(1/K)
2.5
Fig. 9. Arrhenius plot of reaction rate against temperature Graphic abstract:
1. Mechanochemical decomposition of bastnaesite is controlled by chemical reaction. 2. Fractal model gives a best description on the kinetics.
Dear Editor: We submit our manuscript entitled “The kinetic study on bastnaesite concentrate mechanochemical decomposition in NaOH solution” to Journal of Rare Earths for publication. This manuscript has not been published and is not under consideration for publication elsewhere. We have no conflicts of interest to disclose. Sincerely yours, Jiang Liu (E-mail address:[email protected]) Ting-an Zhang (E-mail address: [email protected])