Kinetics of malachite leaching in alkaline glycine solutions

Abstract

Aqueous alkaline glycine solutions present technical advantages over acidic solutions for leaching oxidised copper minerals hosted in carbonate mineral matrix phases. In this study, the leaching and kinetics of malachite in alkaline glycine solutions have been studied. The influence of process variables such as glycine concentration, temperature, particle size and stirring speed on leaching kinetics was evaluated. The results show that temperature has a significant effect on copper dissolution rates. A temperature increase from 25°C to 50°C resulted in a copper extraction of 32.3–83.6% respectively over 5 min. Increasing glycine concentration and reducing particle size led to an increase in copper extraction rates while no significant influence was observed with stirring speeds above 350 rpm.

Keywords

Malachite alkaline glycine kinetics leaching

Introduction

Malachite is a basic carbonate mineral of copper with a chemical formula of CuCO₃.Cu(OH)₂ occurring as a secondary copper mineral in the oxidised upper zone of copper deposits. Malachite is the most common oxidised mineral of copper with deposits in the Democratic Republic of the Congo, Gabon, Zambia, Namibia, Mexico, Australia (Broken Hill, New South Wales), France (Lyon), Israel (Timna Valley), and the Southwestern United States, most notably in Arizona (Anthony et al. 2001; Mindat.org 2016).

Being one of the most common copper oxide minerals, malachite has been leached with a variety of leaching agents. Although sulfuric acid is widely used in industrial leaching operations, the predominance of gangue carbonates in certain ore deposits can result in uneconomic acid consumption (Habashi 1970; You-Cai et al. 2013). Acid leaching also causes the dissolution of impurity elements such as iron, aluminium, magnesium and silica gels which may be detrimental to downstream processes such as solvent extraction and water balance management. Alkaline lixiviants; such as ammonia and its derivatives, have been considered for the leaching of such carbonaceous copper oxide ores and investigated as an alternative to acid with extensive research publications on the leaching kinetics in these systems. Oudenne and Olson (1983) conducted experiments to investigate the leaching kinetics of malachite in ammonium carbonate solutions and found that the leaching process occurs in two reaction stages. In the first stage, malachite leaches rapidly in the first 10 percent of the first stage, after which the formation of a needle-like-structured Cu(OH)₂ intermediate phase leads to a retardation of the dissolution rate. Stage two reactions, which only start after pure malachite has been leached, involve the dissolution of the intermediate product. They estimated the activation energies for the first and second stages to be 64 and 75 kJ/mol respectively. On the other hand, Künkül et al. (1994) observed that the kinetics of malachite leaching in ammonia solutions is controlled by the diffusion of through the product layer with the calculated activation energy of 22.4 kJ/mol. On evaluating the leaching kinetics of a low-grade copper ore containing Ca-Mg carbonate in ammonia-ammonium sulfate with persulfate using the shrinking core model, Liu et al. (2012) showed that the leaching rate is influenced by both interfacial transfer and diffusion across the product layer requiring an activation energy of 22.9 kJ/mol. The contribution of process variables on the dissolution kinetics of malachite ore in ammonium chloride solution was studied by Ekmekyapar et al. (2003). The results indicated an increase in the dissolution kinetics when reaction temperature, ammonium chloride concentration, and stirring speeds were increased. The activation energy for the process was stated as 71 kJ/mol and the dissolution model was established to be mixed kinetics represented by:

where x is reaction conversion, c is ligand concentration, dp is the mean particle size, ρ is slurry density, n is the rotational velocity, T is the absolute temperature and t is the reaction time. According to (Bingöl et al. 2005), the controlling steps during the leaching of copper oxides containing malachite in ammonia/ammonium carbonate are the interface transfer and diffusion across the product layer with an activation energy of 15 kJ/mol. Copper dissolution from a malachite ore in ammonium nitrate solutions was reported by Ekmekyapar et al. (2012) to be a mixed kinetic model, including both surface chemical control (30–50°C) and diffusion through a porous product layer (50–70°C). It was noted that the sequential stages had activation energies of 95.1 and 29.5 kJ/mol respectively. A kinetic study performed by Künkül et al. (2013) on the dissolution of malachite in ammonium acetate reported the leaching process follows a mixed kinetic control model with a calculated activation energy of 59.6 kJ/mol.

Alkaline glycine solutions have been reported to be a potentially suitable lixiviant for the leaching of base and precious metals from their native and mineralised forms (Oraby and Eksteen 2014a, 2014b, 2015; Eksteen and Oraby 2015; Eksteen, Oraby, Tanda 2017; Eksteen, Oraby, Tanda, Tauetsile, et al. 2017; Oraby et al. 2017; Tanda, Eksteen, Oraby 2017; Tanda, Eksteen, Oraby and O'Connor 2017; Tanda et al. 2017b). Just as in alkaline ammonia/ ammonium derivatives solutions, leaching of copper minerals in alkaline glycine is selective with the rejection of impurities such as Fe, Ca, Mg, Si in the leached residue (Eksteen et al. 2016; Tanda, Eksteen, Oraby 2017). Unlike ammonia, the use of glycine has little cause for environmental concern and can thus be employed in environmentally open systems such as heap leaching or in situ leaching approaches which are particularly suitable for processing low-grade ores (National Institute for Occupational Safety and Health 1992; Drauz et al. 2007). Unlike ammonia, glycine is non-volatile, non-toxic, non-flammable and non-explosive, and can be easily transported as a crystalline solid. Additionally, Cu-glycinate complex is stable over a wider pH-Eh region as compared to that of Cu- ammonia complex (Tanda, Eksteen, Oraby 2017). Glycine, or aminoacetic acid, is the simplest amino acid. As indicated by their name, amino acids are organic compounds containing both a carboxyl group (–COOH) and an amino group (–NH₂) bonded to the same carbon atom in α position. It is a colourless, odourless, sweet crystalline solid that is soluble in water (25 g/100 mL at 25°C), acids, and alkalis but not soluble in organic solvents (0.038 g/100 mL) (Fleck and Petrosyan 2014). Glycine is used as a taste enhancer and sweetener in food industries and a levelling agent in acidic copper plating baths. Glycine can be industrially produced in bulk through chemical synthesis or from the hydrolysis of natural compounds (Couriol et al. 1999). Glycine leaches copper from its ores by forming a stable water soluble copper-glycinate complex (Aksu and Doyle 2001, 2002; Tanda, Eksteen, Oraby 2017; Tanda, Eksteen, Oraby and O'Connor 2017; Tanda et al. 2017a). Tanda et al. (2017b) have also shown that the copper in alkaline pregnant leach solutions derived from malachite leaching can be effectively extracted using conventional diketone and ketoxime extractants, leaving a raffinate that can be recycled to the leach after pH adjustment.

The authors have investigated the dissolution behaviour of copper oxides in alkaline glycine solutions under various process conditions (Tanda, Eksteen, Oraby 2017). Under optimum conditions of glycine to copper ratio of 4:1, pH 11 and ambient temperature and pressure 95, 91, 84, and 17% copper was leached from azurite, malachite, cuprite, and chrysocolla respectively after 24 h. However studies are yet to be conducted in order to determine the rate limiting steps during the leaching any of the copper oxides in alkaline glycine. With malachite being the most prevalent oxidised copper mineral (Ata et al. 2001), this current work has therefore focused on the effects of process variables on the leaching kinetics of malachite in alkaline glycine solutions.

Experimental

Material

The malachite specimen used in these investigations was obtained from GEODiscoveries Pty Ltd, Australia. Quantitative X-ray diffraction (Q-XRD) analysis to determine the mineralogy of the sample indicated that 99% of the sample is malachite and the remaining 1% is quartz. Chemical composition analysis of the sample was performed by X-ray fluorescence spectrometry and the results showed the copper content to be 56%. The mineral sample was crushed, ground and then sieved using standard test sieves to divide into four size fractions (+20–38, +38–53, +53–75 and +75–106 µm). Apart from experiments investigating the effect of particle, all other experiments were carried out with +53–75 µm size fraction. Analytical grade glycine reagent, with 99% purity was mainly used as a lixiviant for leaching. Analytical grade NaOH was used to adjust the leaching solution pH. An Agilent 55B AAS spectrometer was used to determine the concentration of copper ions in solutions.

Procedure

All experiments were conducted in a thermally controlled 500 mL jacketed glass reactor fitted with a condenser, a mercury thermometer, an overhead Teflon stirrer with an anchor-shaped impeller, and rubber stopper for the sampling inlet. The reactor was filled with a 500 mL solution of the desired reagent concentration, pH 10 and the required temperature was maintained with a digitally controlled heated circulating water bath. At the desired temperature, a charge of 1.8 g malachite was added to the solution and stirring started. After a specific leaching time, the stirring was stopped, a 10–15 s interval was allowed for the particles to settle and 3 mL solution was extracted for copper concentration determination. The percentage of copper leached was calculated on the basis of copper released into solution relative to the copper content of the original mineral.

Kinetic model

Leach kinetic models are essential for process modelling, simulation and design (Crundwell 2013). Leaching reactions are generally heterogeneous in which reactions occur at the interface of solid phase and a solute in an aqueous solution. A simplified representation of such reactions is as follows: (1)

To study the reaction kinetics of the malachite leaching process, the shrinking core model seen to reasonably represent reality in a broad variety of situations (Levenspiel 1999) and which has been used extensively to describe leaching kinetics of most minerals (Li et al. 2013) has been employed. The model as first developed by Yagi and Kunii in 1955 visualised that the leaching process progresses in five successive steps for particles of unchanging size (Parker et al. 1975): (1) diffusion of reactant A through the liquid film surrounding the particle to the surface of the solid, (2) diffusion of A through the blanket of a solid product phase to the surface of the unreacted core, (3) reaction of reactant A with solid at the reaction surface, (4) diffusion of products through the solid product layer back to the exterior surface of the solid, and (5) diffusion of products through the liquid film back into the main body of fluid. The slowest step controls the leaching process. Levenspiel (1999) used the shrinking core model to develop mathematical expressions for when the various steps are rate controlling. In the case of spherical particles of unchanging size, the integrated expressions are as follows: (2) (3) (4)

Where x is the conversion fraction of the solid particles, k_l, k_d and k_r are the apparent rate constants for the different controlling steps and t is the reaction time.

In reactions in which no solid product layer is formed, i.e. particle size changes during leaching, only the following three steps are assumed to occur: diffusion of reactant A from the main body of the solution through the liquid film to the solid surface, the reaction at the surface between solid and reactant A and thirdly, the diffusion of the reactant products from the solid surface through the film into the main body of the solution. If the process is surface chemical reaction controlled, the behaviour is alike that of unchanging size implying Equation (4) is applicable. When the film diffusion controls the rate in the absence of a product layer, the integrated rate expression is (Wen 1971): (5)

In the cases above, reactant A would refer to dissolved glycine (or glycinate anion).

Tanda (2017) has proposed that the overall leach reaction of malachite happens according to the following stoichiometric reaction:. (6)

Results and Discussion

Effect of glycine concentration

The effect of glycine concentration on the leaching kinetics of malachite was studied by varying the initial glycine concentration from 0.1, 0.2, 0.4, and to 0.8 M in 500 mL of solution at pH 10. Other process variables such as stirring speed (SS), temperature, and particle size (PS) were fixed at 350 rpm, 25°C, and 53–75 µm respectively. Since the formation of the copper-glycine complex needs two moles of glycine for every one mole of copper (Tanda, Eksteen, Oraby 2017) the minimum glycine concentration of 0.1 M ensured that the required glycine to copper ratio of 2:1 in solution is obtainable if complete copper dissolution occurs. Figure 1 shows that copper dissolution increases with increasing glycine concentration. When glycine concentration is increased from 0.1 to 0.2 M, the percentage copper dissolved after three hours increased from 67.6 to 91.3%. At a glycine concentration of 0.4 M, 98.0% Cu was occurred under 2 h of leaching. At 0.8 M glycine concentration copper extraction was similar to the copper extracted at 0.4 M, indicating a plateau is reached in the effect of glycine concentration on the leaching rate.

Effect of temperature

The relationship between temperature and copper dissolution rate is shown in Figure 2. During this investigation, the initial glycine concentration, stirring speed, particle size was maintained at 0.4 M, 350 rpm and 53–75 µm respectively while the solution temperature was varied from 25 to 50°C. The results indicate that temperature has a significant effect on the copper dissolution rate. At 50°C, 83.6% copper dissolution occurs in 5 min while 22.3% copper is dissolved at 25°C, over the same time. Complete copper dissolution was noted in under 30 min of leaching at 50°C, after 2 h at 40°C and after 3 h at 25°C. Although higher temperatures significantly improve malachite leaching rates, raising the leaching temperature may be limited by increased capital and operating costs. Thus, 25°C was maintained during the evaluation of the other parameters.

Effect of stirring speed

In order to examine the influence of stirring speed on the leaching rate of malachite, experiments were carried out at various stirring speeds (150, 350, 550 and 800 rpm) at 25°C in solutions containing 0.4 M Gly and at pH 10. The results as shown in Figure 3 indicate that leaching rate increases as stirring speed is increased from 150 to 350 rpm. However, increasing the stirring speed from 350 to 800 rpm does not result in significant improvement in copper dissolution. This observation suggested that the leaching kinetics might not be controlled by diffusion through the liquid film. However, the result still indicates that fluid turbulence is important at lower agitation rates. This is particularly significant in vat, heap and in-situ leaching where an optimum leaching solution flow rate is required to carry reagents to and products from the mineral surface.

Effect of particle size

The influence of particle size on the leaching of malachite in 0.4 M glycine at pH 10 and 25°C was investigated and the results are shown in Figure 4. The particle size ranges of +20–38 µm, +38–53 µm, +53–75 µm, +75–10 µm were leached for 180 min. Rapid dissolution rates were obtained at smaller particle sizes although no noticeable difference was obtained between +20–38 and +38–53. After 60 min of leaching, copper extraction for +75–100 and+53–75 µm was 82.8 and 89.5% respectively while 99.0% copper was extracted at +20–38 and +38–53 µm fractions. Leaching fine particles increases the leaching rate by providing larger contact surface areas for contact with the leaching solution. Li et al. (2013), mentioned that if the leaching rate is significantly dependent on particle size, then it is an indication that the kinetics is sensitive to diffusion through the product layer. Thus, the insignificant difference between the copper leaching rates from +20–38 and +38–53 µm size fractions even though the surface area was increased by finer grinding can be explained by assuming that below a particular particle size (−53 µm in this case), malachite leaching rate is predominantly influence/limited by chemical reaction rather than by diffusion phenomena.

Kinetic analysis

To Determine of the rate controlling step or steps in the leaching of malachite in alkaline glycine solution, the experimental data were analysed based on Equations (2)–(5). The inclusion of shrinking core model involving film diffusion when no product layer is formed was due to the observation that malachite particles completely disappeared when total copper dissolution was obtained.

As malachite leaching at 50°C is completed within 30 min, the leaching kinetics has been investigated for the initial 30 min. According to the shrinking model equations (Equations (2)–(5)), if the leaching is controlled by any of the kinetic models, plotting the right hand side of the equation against time should give a straight line with the regression correlation coefficient values close to 1. The slope of the straight line represents the apparent rate constant. The regression correlation coefficient values from the plotted kinetic models have been determined and shown in Table 1.

Table 1

Correlation coefficient values for kinetic models.

Variables	Coefficient of Variation for the Evaluated Models: R²
	Diffusion through Film Controls	Diffusion through Product Layer Controls	Chemical Reaction Controls	No Product Layer Formation- Film Diffusion controls
	x
Glycine concentration
0.1	0.9824	0.9710	0.9878	0.9852
0.2	0.9553	0.9898	0.9731	0.9647
0.4	0.9581	0.9753	0.9906	0.9774
0.8	0.9336	0.9803	0.9766	0.9579
Temperature
25	0.9581	0.9753	0.9906	0.9774
30	0.8476	0.9754	0.9245	0.8880
40	0.7970	0.9909	0.9592	0.8833
50	0.5218	0.8161	0.7659	0.6200
Stirring speed
150	0.9539	0.9868	0.9782	0.9671
350	0.9581	0.9753	0.9766	0.9766
550	0.9282	0.9847	0.9906	0.9564
800	0.9166	0.9887	0.9633	0.9395
Particle size, µm
20–38	0.857	0.9995	0.9878	0.9821
38–53	0.8351	0.9996	0.9422	0.9770
53–75	0.9581	0.9753	0.9906	0.8931
75–106	0.9737	0.9576	0.9915	0.9119

Upon comparing the correlation coefficients values for the fitted rate controlling models, it can be observed that it is difficult to predict which model controls the leaching rate of malachite given that the R² values for all models under different process conditions are very similar. It has been suggested that this generally occurs when metal dissolution rates predominantly dependent upon reagent concentrations and temperature (Saxena and Mandre 1992). According to Levenspiel (1999), when more than a single step controls the leaching rate, the shrinking core rate equations can be combined to estimate the contribution of individual rate controlling steps to overall leaching kinetics. Nazemi et al. (2011) applied a constrained multi-linear regression using the least square technique to estimate the contribution of each model on limiting the leaching process. The technique avoids comparing the correlation coefficients from experimental data and rate model equation testing. The combination of the individual rate controlling models is illustrated by Equation (7): (7)

The constants k_l, k_d, and k_r can be determined by a multi-linear regression analysis using the least square method. To avoid negative values for the constants, a constrained least square technique as expressed in Equations (8) and (9) is used: (8) (9)

Equation (9) can then be solved by any optimisation technique to determine the values of k_l, k_d and k_r. The results from the solved equation will estimate the time needed to complete a leaching process controlled by any limiting mechanism/step.

The new approach of a constrained multi-linear regression analysis using the least square technique as proposed by Nazemi et al. (2011) was then applied to determine the rate controlling step(s) for malachite in alkaline glycine solution. Table 2 shows the calculated results of fitted experimental data to Equation (8) and solving Equation (9) by the constraint least square technique. It can be deduced from the results that the leaching rate (first 3 h) of malachite is controlled only by diffusion through the product layer.

Table 2

Data showing the rate-controlling model of malachite at different temperatures using the least square technique of constrained multi-linear analysis.

Temperature °C	k_d (min)	R ²
25	162.15	0.9777
30	137.18	0.9115
40	38.27	0.9954
50	25.73	0.9035

The apparent rate constant, k, at various leaching temperatures were obtained from linearised plots. The apparent rate constant values were then plotted against temperature according to the Arrhenius equation (Equation (10)). (10) The plot of lnk vs. 1/T was a straight line with its gradient being –E_a/R from which the apparent activation energy could be estimated. The apparent activation energy was determined to be 48.3 kJ/mol. Although it is generally accepted that reactions with activation energies more than 40 kJ/mol are chemically controlled and those with activation energies lower than 40 kJ/mol are diffusion controlled, diffusion controlled leaching reactions have been reported to have an activation energy value higher than 40 kJ/mole (Vračar et al. 2000; Baba et al. 2009) (Figure 5).

Activation energy does not give any more information on the reaction mechanism, but the reaction order on the other hand describes the dependency of the reaction rate on the reagent concentration. These two factors in terms of kinetic parameters; the order of the reaction and the activation energy are linked to the reaction rate as described Equation (11) (Crundwell 2013). (11) Where K represents the rate constant, [c] is the concentration of reagent, n the order of the reaction, E_a the activation energy, R the gas constant and T the temperature (kelvin).

Using K_d values obtained for each investigated process variable, plots of K_d versus ln[Gly], ln[n], ln[dp] were obtained. The slope of the straight line in each plot shows the calculated order of the reaction with respect to glycine, stirring speed and geometric mean particle size. The order of the reaction with respect to glycine concentration, stirring speed, particle size were found to be 1.36, 0.64, and −0.96, respectively. Leaching kinetics of malachite in alkaline glycine solution can thus be represented by Equation (12). (12)

In order to test the agreement between experimental data and theoretical data calculated from the empirical equation, experimental rates were plotted against calculated rates as shown in Figure 6. The results show a good agreement between the experimental and calculated diffusion rate values as indicated by a Coefficient of Variation of 0.93.

Conclusions

The leaching kinetics of malachite in alkaline glycine solutions was investigation and the effects of process variables on the leaching kinetics evaluated. Temperature was noted to have the most significant effect on the leaching rate with 100% copper dissolution in just less than 30 min at 50°C while at 25°C, complete copper dissolution was only obtained after 3 h. Reduction in particle size and increase in glycine concentration improve the leaching rate whereas an increase in stirring speed above 350 rpm only slightly improves copper leaching rates.

Kinetic analysis using the shrinking core model indicated that the initial leaching rate of malachite in alkaline glycine solution is controlled by diffusion through the product layer. The apparent activation energy was found to be 48.3 kJ/mol.

Although alkaline glycine leach rates are slower than acid leaching, for example using sulphuring acid, the rates are practical for all leach modes and alleviates the downstream problems with the co-dissolution of other impurities. The inherent recyclability after the copper recovery from solution, lowers the reagent costs significantly as the reagents are retained in the recycle to the leach.

Footnotes

Acknowledgements

The financial support of Curtin University is gratefully acknowledged.

Disclosure statement

No potential conflict of interest was reported by the authors.

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