Dissolution Behavior and Kinetics of Copper Sulfide Concentrate in Choline Chloride DES

Abstract

This study presents a comprehensive investigation of copper extraction from chalcopyrite concentrate using choline chloride–malonic acid (ChCl:Ma) deep eutectic solvent (DES) through an integrated experimental and modeling approach. The work began with determination of the deep eutectic temperature (38 °C) for the ChCl:Ma system, which guided the selection of the optimal 1:1 molar ratio to ensure minimal viscosity and maximum solvent stability. The operating temperature range (50–80 °C) was strategically chosen based on TGA analysis confirming the solvent’s thermal stability below 120 °C, ensuring no solvent degradation during leaching experiments. Response Surface Methodology (RSM) with Central Composite Design (CCD) optimization revealed temperature and leaching time (24–72 h) as statistically significant parameters affecting copper recovery, with a highly predictive quadratic model (R² = 0.99, p < 0.0001). Kinetic analysis using the shrinking core model identified a diffusion-controlled mechanism through a sulfur layer, supported by low activation energies (Cu = 29.09 kJ/mol, Fe = 38.16 kJ/mol). Comprehensive characterization showed preferential chalcopyrite dissolution with direct conversion to elemental sulfur (XRD), formation of metalchlorocomplexes (UV-Vis), and excellent solvent thermal properties (TGA). These findings demonstrate ChCl:Ma DES as an effective medium for chalcopyrite processing, with a systematic methodology providing insights for sustainable non-aqueous metal recovery systems.

1. Introduction

Copper is a vital metal extensively employed in industries due to its outstanding thermal and electrical conductivity [1,2,3]. Its applications span electronics, machinery, and transportation [4]. Globally, 70–90% of copper resources are found in sulfide ores, predominantly chalcopyrite (CuFeS₂) [5,6]. However, conventional extraction methods, including those of pyrometallurgical and hydrometallurgical processes, pose significant challenges [7,8]. Pyrometallurgy, the dominant production method, is energy-intensive and environmentally detrimental, emitting pollutants like SO₂ [2,9,10]. High-temperature smelting, roasting, and converting processes demand substantial energy and generate harmful waste, raising sustainability concerns [11,12]. Hydrometallurgy, though operating at lower temperatures, suffers from slow kinetics and passivation layers that impede copper recovery [13,14]. These limitations highlight the need for greener and more efficient extraction methods [15,16].

Conventional processing of copper sulfide ores typically relies on froth flotation, a critical beneficiation step to separate valuable minerals from gangue, yielding a high-grade concentrate suitable for subsequent extraction processes like smelting or leaching [17]. The efficiency of flotation hinges on the surface properties of minerals, and extensive research focuses on using activators and collectors to enhance selectivity and recovery [3]. For instance, mechanistic studies reveal how stepwise surface activation can significantly improve the flotation performance of oxide minerals [18]. Similarly, molecular dynamics simulations provide profound insights into reagent interactions at mineral surfaces, such as in dual activation systems, guiding the optimization of flotation processes for complex ores [19]. The chalcopyrite concentrate used in this study was produced through such industrial flotation, providing the high-grade feed material essential for investigating novel solvometallurgical routes [20].

Deep Eutectic Solvents (DESs) have recently emerged as sustainable alternatives for mineral processing [21,22,23]. Composed of a hydrogen bond acceptor (HBA; e.g., choline chloride, ChCl) and a hydrogen bond donor (HBD), DESs form eutectic mixtures with depressed melting points [24,25]. Their advantages include low cost, ease of preparation, biodegradability, and tunable properties [26,27]. Crucially, for sulfide mineral processing, certain DESs can act as both lixiviants and complexing agents, selectively dissolving target metals while leaving gangue minerals largely unaffected [28,29,30]. Unlike conventional aqueous systems, DESs can dissolve metals while forming stable complexes, offering a scalable and eco-friendly approach [31,32]. Water content adjustment further enhances mass transfer without destabilizing the system [33,34].

The Response Surface Methodology (RSM) plays a pivotal role in optimizing copper dissolution from chalcopyrite in deep eutectic solvents (DESs) [35]. As a statistical and mathematical approach, RSM enables systematic process optimization by evaluating the interactions between key variables (e.g., temperature, time, solvent composition, and oxidant concentration) while minimizing experimental effort [36]. This methodology offers critical insights into dissolution kinetics, chemical equilibria, and reaction mechanisms, enabling the identification of optimal conditions for maximizing copper recovery. By integrating RSM with DES-based leaching, researchers can efficiently model and predict the effects of process parameters on dissolution efficiency. For instance, recent studies have employed RSM to assess the influence of water content, HBD/HBA ratios, and oxidant additives in DES systems, revealing non-linear relationships that traditional one-factor-at-a-time experiments might overlook [37]. Such optimization is particularly valuable in overcoming challenges like passivation layer formation or DES degradation, ensuring both high extraction yields and solvent stability [38]. Furthermore, RSM facilitates kinetic analysis by correlating experimental data with mechanistic models (e.g., shrinking core or diffusion-controlled models). This approach not only refines process parameters but also contributes to the scalability and sustainability of DES-based copper extraction, aligning with the broader goals of green metallurgy [39].

DES applications for refractory minerals such as chalcopyrite demonstrate promise in replacing hydrometallurgy [31,40]. Recent studies optimize parameters (e.g., temperature and water content) to improve efficiency [6,41]. However, challenges such as solvent degradation via esterification necessitate more stable formulations. For instance, Li et al. [42] extracted copper from chalcopyrite using FeCl₃ in ethylene glycol, achieving high leaching rates and direct electrodeposition. Similarly, Teimouri et al. [43] studied pyrite dissolution in ChCl/EG with H₂O₂, while Lu et al. [44] recovered metals from lithium-ion batteries using ChCl/malonic acid DES. Water dilution was found to enhance metal recovery, though thermal degradation remains a concern [45,46,47].

This study aims to develop a sustainable solvometallurgical process for copper extraction from chalcopyrite concentrate using a choline chloride–malonic acid (ChCl:Ma) deep eutectic solvent (DES). The chemical composition of the concentrate was precisely determined using X-ray fluorescence (XRF) analysis. The work systematically integrates experimental optimization, kinetic analysis, and advanced characterization to address key challenges in metal recovery. Beyond conventional approaches, this research specifically determines the experimental eutectic temperature of the ChCl:Ma system and provides a detailed investigation into the chemical mechanisms and reaction kinetics governing the dissolution process. Specifically, we seek to optimize leaching parameters (temperature and time) via Response Surface Methodology (RSM), identify the rate-controlling mechanism through shrinking core kinetics, and elucidate dissolution pathways and solid-phase transformations using XRD, XRF, TGA/DTG, ICP-OES, and UV-Vis spectroscopy. The findings are intended to provide fundamental insights into the reaction mechanisms and practical strategies for enhancing metal recovery in non-aqueous systems, contributing to the advancement of green hydrometallurgical alternatives for processing refractory sulfide ores.

2. Materials and Methods

2.1. Materials

The chalcopyrite concentrate used in this study was sourced from the Sarcheshmeh Copper Complex located in Kerman Province, Iran. The chemical composition of the concentrate, as determined by X-ray fluorescence (XRF) analysis, is presented in

Table 1. Chemical composition of the chalcopyrite concentrate used in this study.

Fe	S	Cu	SiO2	Al2O3	CaO	TiO2	MgO
32.52	36.4	22.46	4.74	1.17	0.49	0.41	0.48

. The major elements consisted of copper, iron, and sulfur, constituting the chalcopyrite (CuFeS₂) phase. Gangue minerals, primarily in the form of silicates and oxides, were present as minor components. For the synthesis of deep eutectic solvents (DES), high-purity choline chloride (≥98%, Loba Chemie, India) and malonic acid (≥99%, Merck) were utilized.

2.2. Synthesis of Deep Eutectic Solvents

The binary deep eutectic solvent was prepared by mixing choline chloride (HOC₂H₄N(CH₃)₃Cl), serving as the hydrogen bond acceptor, with malonic acid, serving as the hydrogen bond donor, in a 1:1 molar ratio (ChCl:Ma). The synthesis procedure involved heating the mixture at 80 °C under continuous magnetic stirring until a clear, homogeneous liquid was obtained. This temperature was optimized to ensure efficient hydrogen bonding interactions while avoiding thermal decomposition of malonic acid, which is sensitive to excessive heat.

The formation of an extensive hydrogen bond network between choline chloride (a quaternary ammonium salt) and malonic acid (a dicarboxylic acid) was essential for achieving the desired eutectic behavior. The transparency and low viscosity of the resulting solvent confirmed the successful disruption of crystalline structures and the formation of a homogeneous liquid phase. The 1:1 molar ratio was selected based on prior optimization studies, which demonstrated favorable physicochemical properties, including high solubility for metal oxides and moderate viscosity (see Table 1). The synthesis temperature was carefully controlled to ensure complete miscibility without degrading the organic acid component.

The selection of the key independent variables for leaching, temperature and time, and their respective ranges was likewise based on a critical review of the existing literature on metal dissolution in DESs and the known thermal behavior of the individual solvent components. The upper temperature limit (80 °C) was selected to remain safely below the reported onset decomposition temperature of similar ChCl-based DESs (<120 °C) to ensure solvent stability throughout the experiments. The lower limit (50 °C) was chosen to provide sufficient thermal energy to enhance kinetics significantly above ambient conditions. The extended time range (24–72 h) accounts for the slower diffusion rates inherent to viscous DES media compared to conventional aqueous solutions, as consistently reported in the literature [48].

2.3. Characterization

2.3.1. Chemical Composition Analysis (XRF)

The elemental composition of the initial chalcopyrite concentrate was determined using X-ray fluorescence spectroscopy (XRF). This analysis provided the mass fractions of all major and minor elements, which were essential for the subsequent calculation of leaching efficiencies.

2.3.2. Mineralogical and Phase Analysis (XRD)

The crystalline phases and structural evolution of the samples were characterized using an Italstructure APD2000 X-ray diffractometer (XRD) with Cu Kα radiation (λ = 1.54060 Å). Measurements were conducted at 40 kV and 300 mA, scanning from 10° to 100° (2θ) with a step size of 0.05°. This enabled detailed identification of mineral phases in both the raw materials and post-leaching residues, clarifying any phase transformations induced by the ChCl:Ma solvent system.

2.3.3. Elemental Analysis of Leachates (ICP-OES)

Complementary elemental analysis, particularly targeting metal ions (e.g., Cu²⁺, Fe²⁺/Fe³⁺), was performed via inductively coupled plasma-optical emission spectrometry (ICP-OES; Perkin Elmer DV7300 Optima, Waltham, MA, USA). The axially viewed plasma configuration ensured high sensitivity, with detection limits in the ppm range, allowing precise quantification of dissolved metals in the DES leachates.

2.3.4. Optical Properties and Complexation (UV-Vis Spectroscopy)

The ultraviolet-visible (UV-Vis) absorption spectra of the leachates were recorded using a UV-160 A spectrophotometer over a wavelength range of 200–800 nm. This technique was used to monitor the potential formation of metal-complex species in solution (e.g., Cu-DES complexes) by identifying characteristic absorption bands, providing insights into the dissolution mechanism.

2.3.5. Thermal Stability Analysis (TGA/DTG)

Thermogravimetric analysis (TGA) coupled with differential thermogravimetry (DTG) was employed to evaluate the thermal stability of the ChCl:Ma solvent. Experiments were conducted under a nitrogen atmosphere at a heating rate of 10 °C/min (25–800 °C). The TGA profiles delineated weight loss steps associated with solvent decomposition, while DTG curves pinpointed the maximum temperature of each degradation stage. These data were critical for determining the operational temperature limits of the DES, especially for high-temperature leaching applications.

The combined use of XRF, XRD, ICP-OES, UV-Vis, and TGA/DTG provided a comprehensive multiscale understanding of the interactions between the ChCl:Ma solvent and the target materials. This integrated characterization approach encompassed elemental composition (XRF), crystallographic evolution (XRD), quantitative metal dissolution (ICP-OES), metal-complex formation in solution (UV-Vis), and solvent thermal behavior (TGA/DTG), offering complete insights into the leaching mechanism from bulk to molecular level.

2.3.6. Calculation of Leaching Efficiency

A solid–liquid ratio of 1:20 (50 g/L) was chosen for all experiments to ensure sufficient solvent availability for complete reaction, maintain manageable slurry viscosity for effective mixing, and provide a concentration of dissolved metals suitable for precise analysis by ICP-OES. The leaching efficiency of copper and iron was quantified based on the mass of metal dissolved into the lixiviant relative to its original mass in the solid concentrate. The recovery percentage for each metal was calculated using the formula:

Recovery (%) = (C × V)/(m × w) × 100

(1)

where C is the concentration of the metal (Cu or Fe) in the leachate (measured by ICP-OES, in mg/L), V is the volume of the leachate (in L), m is the mass of the concentrate sample (in g), and w is the mass fraction of the metal in the concentrate (as determined by XRF analysis). After each leaching test, the slurry was filtered, and the leachate was diluted with water for ICP-OES analysis to ensure accurate quantification of dissolved metals.

3. Results

3.1. Determination of Eutectic Temperature

To optimize the dissolution of sulfide concentrates in deep eutectic solvents (DESs) and accurately establish their theoretical and experimental eutectic temperatures, constructing a detailed phase diagram is essential. As previously mentioned, DESs are synthesized by combining a hydrogen bond donor (HBD) and a hydrogen bond acceptor (HBA) at a specific molar ratio. The strong hydrogen bonding interactions between these components result in a substantial freezing point depression. A notable example is the choline chloride/urea (ChCl:2U) system, which exhibits a melting point of −12 °C, significantly lower than those of its constituents (302 °C for choline chloride and 133 °C for urea). This depression allows the mixture to remain liquid at room temperature, rendering it highly effective as a solvent [49]. The formation of an extensive hydrogen bond network between choline chloride (a quaternary ammonium salt) and a dicarboxylic acid was essential for achieving the desired eutectic behavior. The transparency and low viscosity of the resulting solvent confirmed the successful disruption of crystalline structures and the formation of a homogeneous liquid phase.

In this study, the phase diagram of the ChCl:Ma (Choline chloride–malonic acid) binary system was constructed using both theoretical predictions and experimental measurements. The theoretical curve was generated using Equation (2), incorporating the following thermodynamic parameters:

-

Choline chloride (ChCl): Enthalpy of fusion (ΔH_m,ChCl) = 4300 kJ/mol, melting point (T_m) = 324 °C.

-

Malonic acid (Ma): Enthalpy of fusion (ΔH_m,Ma)= 23,100 kJ/mol, melting point (T_m) = 134 °C.

ln x_iγ_i = − ΔH_m,i/R (1/T − 1/T_i^*)

(2)

The theoretical eutectic temperature was determined to be 89 °C, whereas experimental measurements yielded a value of 38 °C (Figure 1). This significant discrepancy arises from non-ideal interactions in the real system, highlighting the importance of empirical validation in DES studies. For precise determination of the eutectic temperature, a high-precision temperature data logger was used, coupled with a sensitive thermocouple (operational range: −40 to +400 °C). During the cooling process, temperature changes were continuously recorded by the data logger.

Importantly, the experimental eutectic point was confirmed at a 1:1 molar ratio of ChCl:Ma. This composition was strategically selected for the leaching studies as it represents the solvent’s thermodynamically most stable state with minimized viscosity. The lower viscosity at the eutectic point is a crucial factor, as it enhances mass transfer, improves diffusion of reactants and products, and facilitates better interaction with the solid concentrate particles. Consequently, performing the leaching process near this optimized composition is scientifically justified and was essential for achieving the high dissolution efficiencies and reproducible kinetic results reported in this study.

3.2. The Thermal Stability of DESs

The thermogravimetric analysis (TGA) results for the choline chloride–malonic acid (ChCl:Ma) deep eutectic solvent (Figure 2a) reveal three distinct thermal degradation stages. The solvent demonstrates excellent thermal stability below 120 °C, showing negligible mass loss (<2%), which confirms its suitability for low-temperature applications. The first major decomposition event occurs between 120 and 170 °C with a rapid 31% mass loss, attributed primarily to malonic acid decarboxylation. A subsequent gradual decomposition (170–260 °C) accounts for an additional 12% mass loss, likely involving intermediate decomposition products. Complete solvent decomposition is achieved by 310 °C.

The derivative thermogravimetric (DTG) curve (Figure 2b) resolves these events, showing two characteristic peaks:

• A peak at 130–160 °C (malonic acid decomposition)
• A peak at 270–300 °C (choline chloride degradation)

The observed thermal behavior provides important insights into the solvent’s structural stability and potential applications. The initial stability plateau (<120 °C) indicates a strong hydrogen bonding network integrity at moderate temperatures, making this DES suitable for processes like metal extraction, which require thermal stability up to 120 °C.

The two-stage decomposition pattern reflects the different thermal stabilities of the components. Malonic acid’s lower decomposition temperature is characteristic of organic acids. The 42% total mass loss in this phase corresponds well with malonic acid’s theoretical mass fraction (44.6% in 1:1 molar ratio ChCl:Ma), supporting this assignment. The higher-temperature choline chloride decomposition agrees with literature reports for quaternary ammonium salts [50].

It is important to note that the thermal degradation onset temperature (~120 °C) was determined at a heating rate of 10 °C/min under dynamic conditions. However, considering the significantly longer duration of leaching experiments (up to 72 h), the possibility of solvent degradation at lower temperatures cannot be entirely ruled out due to prolonged thermal exposure. Therefore, to ensure solvent stability and avoid potential decomposition during extended leaching operations, a conservative upper temperature limit of 80 °C was selected for all experiments. This provides a sufficient safety margin and confirms that the observed metal dissolution is solely attributable to the non-degraded DES system.

3.3. Response Surface Methodology Studies

This research aimed to optimize copper extraction from chalcopyrite concentrate using a choline chloride–malonic acid (ChCl:Ma) deep eutectic solvent. The effects of key operational parameters, including dissolution temperature (50 °C, 65 °C, and 80 °C) and time (24 h, 48 h, and 72 h), were systematically evaluated. A Central Composite Design (CCD) was employed to identify optimal conditions for maximizing copper recovery efficiency. To optimize these parameters, RSM, a highly effective statistical and mathematical approach, was employed to examine multiple factors as a multivariate statistical approach. This method enabled efficient experimental design by considering parameter interactions while minimizing the number of required tests. The design included eleven experimental runs at the levels represented in

Table 2. The independent variables, along with their coded and actual levels, used in the CCD.

Variables	Levels
	Low Actual	High Actual	Low Coded	High Coded	Mean
Temperature (A)	50 °C	80 °C	−1	1	65 °C
Time (B)	24 h	72 h	−1	1	48 h

.

For each experimental run in the CCD matrix, the leaching process was conducted. A specific mass of the chalcopyrite concentrate, corresponding to the fixed solid-to-liquid ratio of 1:20 g/mL, was added to the pre-synthesized ChCl:Ma DES in a sealed glass vessel. The mixture was magnetically stirred at 500 rpm and maintained at the target temperature (50–80 °C) for the predetermined duration (24–72 h) using an incubator shaker for precise thermal and agitation control. After the leaching period, the entire slurry was centrifuged to separate the solid residue from the leachate. The solid residue was washed with distilled water, dried, and prepared for mineralogical analysis by XRD. For metal quantification, the leachate was diluted with distilled water and analyzed by ICP-OES to determine the recovery efficiency. The RSM approach provided comprehensive optimization while significantly reducing the number of experimental runs compared to conventional one-variable-at-a-time methods, ensuring both economic and technical efficiency in process development.

Table 3. Experimental dissolution data of Central Composite Design (CCD) technique for copper and iron recovery values determined by ICP-OES.

Run	Factor 1	Factor 2	Response	Response
	A: Temperature (°C)	B: Time (h)	Efficiency of Cu Recovery (%)	Efficiency of Fe Recovery (%)
A: Choline Chloride–Malonic Acid
1	80	24	33.1	31.9
2	50	24	21.3	12
3	65	48	37.9	36.2
4	65	24	27.4	24.7
5	65	72	45.2	43.7
6	65	48	36.3	36.8
7	50	72	35.2	23.9
8	65	48	38.1	35.1
9	80	72	51.4	54.3
10	50	48	30.1	19.8
11	80	48	41.6	46.5

displays the results of the copper and iron dissolution process on the concentrate. The experimental design consisted of 8 factorial points and 3 center points, resulting in a total of 11 experiments. The three replicated experiments at the center point (65 °C, 48 h; Runs 3, 6, and 8) were specifically included to evaluate the pure error and the reproducibility of the experimental process. The slight variations in the extraction efficiency values for copper (37.9%, 36.3%, 38.1%) and iron (36.2%, 36.8%, 35.1%) observed in these replicates are attributed to inherent experimental variability.

With a total of 11 experiments, a linear model equation was developed by analysis of variance (ANOVA). The analysis of variance was employed to assess the significance of the model and its terms. A significance threshold of p-value < 0.05 was used to identify influential factors. For the ChCl:Ma system, the high F-value (278.34) and a very low p-value (<0.0001) for the model confirm its high statistical significance. The initial model included all linear, interaction, and quadratic terms (A, B, AB, A², B²). However, to develop a more precise and parsimonious predictive model, non-significant terms (AB and A²) were excluded from the final model. The refined model, containing only the significant terms (A, B, and B²), was used for all subsequent predictions and is presented as Equation (3). This step of model refinement is a standard practice in RSM to enhance the model’s predictive accuracy and reliability.

The Lack of Fit test resulted in an F-value of 1.42 and a p-value of 0.43. The non-significant Lack of Fit indicates that the selected model is adequate to describe the observed data, and any residual error can be attributed to pure experimental noise rather than a deficiency in the model form. The derived fitted model (Equation (3)) demonstrates that copper recovery efficiencies are significantly influenced by both main parameters of temperature and reaction time.

The second-order polynomial equation to predict Cu leaching efficiency in the ChCl:Ma system is expressed as follows:

Cu Recovery (%) = 13.4 + 2.78 A + 5.83 B − 1.01 B²

(3)

Table 4. Obtained results of ANOVA for the dissolution of copper from chalcopyrite concentrate by A.

A: Choline Chloride–Malonic Acid
Source	Sum of Squares	df	Mean Square	F-Value	p-Value
Model	1561.05	5	312.21	278.34	<0.0001	significant
A—temp.	596.34	1	596.34	486.46	<0.0001
B—time	834.12	1	834.12	678.57	<0.0001
AB	0.0361	1	0.0361	0.0286	0.8724
A2	1.05	1	1.05	0.875	0.3925
B2	46.12	1	46.12	37.59	0.0017
Residual	6.1	5	1.22
Lack of Fit	4.1533	3	1.3844	1.422	0.43

Std. Dev. = 1.57; R2 = 0.9961; Mean = 55.73; Adjusted R2 = 0.9922; C.V. % = 2.81; Predicted R2 = 0.9631; Adequate Precision = 53.2624.

presents the ANOVA analysis results used to evaluate the significance of both main and interaction effects of the variables. Using a significance threshold of p < 0.05, the analysis confirms the statistical relevance of the predictive models and their parameters. For the ChCl:Ma quadratic models, the high F-value (278.34) and extremely low p-value (<0.0001) demonstrate that the models are statistically highly significant.

The F-values in the ANOVA results play a key role in assessing the importance of independent variables and their interactions within the proposed regression model. The F-value represents the ratio of explained variance (regression sum of squares) to unexplained variance (error sum of squares). A larger F-value suggests that the model effectively captures a substantial portion of the variability in the dependent variable, reinforcing the reliability of the predictors [51].

These findings confirm that the developed models are statistically robust, with the independent variables significantly influencing the response. The exceptionally low p-values further validate the models’ adequacy, ensuring their suitability for predictive analysis in this experimental framework [52].

Figure 3a presents a 3D visualization of the interactive effects of temperature and time on the dissolution rate of copper in the ChCl:Ma deep eutectic solvent. Within the selected temperature and time ranges, it is evident that these two parameters exhibit nearly identical influences on the dissolution process in the studied eutectic system.

Furthermore, Figure 3b compares the predicted values from the statistical model with the actual experimental data obtained for copper dissolution in the ChCl:Ma deep eutectic solvent. The high correlation coefficient (R² = 0.99) confirms an excellent agreement between the predicted and experimental results, demonstrating the model’s strong predictive accuracy.

These findings highlight the consistent impact of temperature and time on copper dissolution, as well as the reliability of the statistical model in estimating dissolution behavior within this deep eutectic solvent system. The close alignment between predicted and experimental data further validates the robustness of the proposed approach.

3.4. Mineralogical Studies on Chalcopyrite

X-ray diffraction analysis was employed to investigate the phase transformations occurring during the leaching of sulfide concentrate in ChCl:Ma deep eutectic solvent at 80 °C. The comparative XRD patterns before and after 72 h of leaching revealed three distinct transformation processes that provide critical insights into the leaching mechanism (Figure 4).

The analysis showed a substantial reduction in diffraction peak intensities corresponding to both chalcopyrite and pyrite phases, with chalcopyrite exhibiting more pronounced dissolution compared to pyrite. This differential dissolution behavior suggests preferential attack of the solvent on the chalcopyrite structure. Several characteristic sulfide peaks completely disappeared after the leaching process, confirming extensive breakdown of the original sulfide mineral framework.

Concurrently, new diffraction peaks emerged that were identified as elemental sulfur, demonstrating its formation as the primary crystalline byproduct. Notably, no intermediate crystalline phases were detected, suggesting direct conversion of sulfides to elemental sulfur without stable intermediate compounds. The gangue minerals, particularly quartz and silicates, displayed remarkable stability under the leaching conditions, with their diffraction patterns remaining essentially unchanged.

This selective behavior confirms the solvent’s specific action on sulfide phases while leaving the non-sulfide matrix intact. These observations collectively support a reaction mechanism beginning with rapid surface decomposition at sulfide-solvent interfaces, followed by gradual inward progression of the dissolution front. As the reaction advances, the accumulating sulfur product layer forms a porous barrier that eventually governs the kinetics through diffusion control. The differential dissolution between chalcopyrite and pyrite, coupled with exclusive sulfur formation, provides valuable insights for optimizing metal recovery processes. The stability of gangue minerals suggests potential for simplified downstream processing, as these components remain inert throughout the leaching operation. These findings significantly advance our understanding of phase evolution in solvometallurgical processing of sulfide ores using deep eutectic solvents.

3.5. Kinetics of Dissolution for Cu and Fe

This study systematically examined the dissolution behavior of chalcopyrite (CuFeS₂) in solvometallurgical systems using the shrinking core model as the fundamental kinetic framework. Leaching, as a heterogeneous solid–liquid interfacial reaction, is most accurately described by the shrinking core model for chalcopyrite systems [53]. This model depicts the progressive retreat of the reaction interface as reactants penetrate the mineral matrix, with the unreacted core gradually diminishing over time [54]. Three fundamental rate-controlling mechanisms were evaluated to determine the limiting steps in the leaching process:

(1)

Chemical reaction control (Equation (4)), representing surface-controlled kinetics.

(2)

Diffusion control (Equation (5)), governing ash-layer mass transfer limitations.

(3)

Mixed control (Equation (6)), accounting for combined surface reaction and diffusion effects.

It relates the fractional conversion of the reactant before time t (X), the rate constant of the reaction (K_r, K_d, K), the diffusivity constant (D), and time (t) in a chemical reaction under kinetic control.

The applicability of each model was systematically assessed through regression analysis of experimental leaching data under varying conditions. This approach provides fundamental insight into the rate-determining steps governing chalcopyrite dissolution in the studied deep eutectic solvent systems.

1 − (1 − X)^1/3 = K_rt

(4)

1 − (2/3 X) − (1 − X)^2/3 = K_dt

(5)

−Ln(1 − X) = Kt

(6)

Equation (7) for Arrhenius’s law is expressed as (K_p) equals (A) times e to the power of negative (E_a) divided by RT, where K represents the rate constant, A is the Arrhenius pre-exponential factor, (E_a) is the activation energy, (R) is the gas constant (8.314 J/(mol.K)), (T) is the temperature in Kelvin, and e denotes the base of natural logarithm [55].

K_p = A × exp(−E_a/RT)

(7)

To investigate the dissolution kinetics of copper sulfide concentrate in ChCl:Ma deep eutectic solvent, experiments were conducted at three different temperatures (50, 65, and 80 °C) with a solid to liquid ratio of 50 g/L These conditions were carefully selected to evaluate the effects of temperature and rate-controlling mechanisms on copper and iron dissolution. Three kinetic models were evaluated:

• Chemical control model (Equation (4), Figure 5a): The results showed poor correlation with experimental data, indicating that surface chemical reactions were not rate-limiting.
• Mixed control model (Equation (6), Figure 5b): While this model showed better agreement than the chemical control model, it still could not fully describe the experimental data.
• Diffusion control model (Equation (5), Figure 5c): This model provided the best fit to the experimental data (with acceptable R² values), suggesting that the reaction was controlled by ash layer diffusion.

To complement the dissolution results, activation energy calculations were performed using the Arrhenius equation, as shown in Figure 5d; the calculated activation energy was 29.09 kJ/mol. Since diffusion-controlled reactions typically exhibit lower activation energies than chemically controlled reactions, this value further confirms that the leaching process is controlled by diffusion through the ash layer.

The comprehensive analysis demonstrates that chalcopyrite leaching in the studied deep eutectic solvent system follows diffusion-controlled kinetics through the ash layer, with an activation energy characteristic of mass transfer limitations. These findings provide important insights for optimizing leaching processes in deep eutectic solvent systems.

In the initial stages of the leaching process, copper and iron partially dissolve into the DES, leading to the selective dissolution of chalcopyrite particles, which results in the formation of sulfur, as confirmed by XRD results. The sulfur particles formed due to bonding with residual chalcopyrite hinder further leaching by obstructing the diffusion pathways. This phenomenon prevents the solvent from effectively penetrating the mineral structure and reaching the trapped copper. Consequently, a passivating sulfur layer forms on the mineral surface, acting as a physical and chemical barrier that controls the leaching kinetics predominantly by diffusion [56,57].

The dissolution kinetics of iron from the sulfide concentrate were systematically evaluated using different kinetic models, as presented in Figure 6. In the studied concentrate, iron exists both as a primary constituent of chalcopyrite (CuFeS₂) and as a key component of pyrite (FeS₂). The kinetic analysis revealed:

• Chemical reaction control model (Figure 6a): The experimental data showed poor correlation (R² = 0.93), indicating that surface chemical reactions were not rate-limiting.
• Mixed control model (Figure 6b): While showing slightly better fit (R² = 0.95), this model still failed to adequately describe the dissolution behavior.
• Diffusion control model (Figure 6c): Demonstrated excellent agreement with the experimental data (R² = 0.99), confirming ash layer diffusion as the rate-controlling mechanism through Equation (5).

The calculated activation energy for iron dissolution was determined to be 38.16 kJ/mol. This value, falling within the characteristic range for diffusion-controlled processes, further supports the conclusion that iron dissolution is primarily governed by Ash-layer diffusion.

3.6. Proposed Dissolution Mechanism

The integration of XRD, XRF, and UV-Vis analytical data allows for the elaboration of a comprehensive dissolution mechanism for chalcopyrite in the ChCl:Ma DES system, which aligns perfectly with the diffusion-controlled kinetics identified earlier. The process is initiated by the action of protons (H⁺) derived from the dissociation of malonic acid within the DES network (Equation (8)). Chloride ions (Cl⁻) from choline chloride play a dual role as a catalyst and complexing agent, weakening the metal-sulfur bonds in the chalcopyrite matrix (CuFeS₂). The primary reaction can be summarized as:

CuFeS₂ + 4H⁺ → Cu²⁺ + Fe²⁺ + 2H₂S

(8)

The generated hydrogen sulfide (H₂S) is unstable in the oxidative environment and rapidly undergoes oxidation to elemental sulfur (S⁰), which subsequently polymerizes to form the stable cyclic octatomic molecule (S₈), as unequivocally identified by the distinct diffraction peaks in the XRD pattern of the leach residue (Figure 4). The formation of this solid S₈ layer is the primary cause of the passivation effect.

Concurrently, the dissolved Cu²⁺ and Fe²⁺ ions interact with the high concentration of Cl⁻ in the medium to form stable soluble chlorocomplexes. UV-Vis spectroscopic analysis confirmed the presence of these complexes in the solution phase (Figure 7), showing characteristic absorption bands for tetrachlorocuprate (II) ([CuCl₄]²⁻) at approximately [415, 280 nm] and for tetrachloroferrate (II) ([FeCl₄]²⁻) at [280, 240 nm], in agreement with literature reports for concentrated chloride media [24,26]. The high complexing ability and solvation power of the chloride-rich DES medium effectively stabilize these complexes in solution, ensuring high metal extraction efficiency.

Therefore, the final overall reaction accounts for the products in their predominant states:

CuFeS₂ + 4Cl⁻ + 2H⁺ → [CuCl₄]²⁻(sol) + [FeCl₄]²⁻(sol) + 2S⁰ + H₂(g)

(9)

8S⁰ → S₈↓

(10)

The convergence of evidence from all techniques, XRD (identification of S₈) and UV-Vis (identification of soluble [CuCl₄]²⁻ and [FeCl₄]²⁻ complexes), provides strong support for this mechanism. The formation of a passivating layer predominantly composed of elemental sulfur (S₈) rationally explains the diffusion-controlled kinetics governed by ash layer diffusion, as determined by the shrinking core model. The low activation energies calculated are characteristic of a process limited by the diffusion of reactants and products through this sulfur product layer.

4. Conclusions

This study successfully developed a scientifically grounded approach for copper extraction from chalcopyrite using choline chloride–malonic acid deep eutectic solvent, with several key achievements:

First, the research established fundamental solvent characteristics by determining the deep eutectic point (38 °C at 1:1 molar ratio), which directly guided the selection of the optimal solvent composition. This rational selection ensured minimal viscosity and enhanced mass transfer properties. Furthermore, TGA analysis provided critical thermal stability data, enabling the strategic selection of an operational temperature range (50–80 °C) safely below the decomposition threshold (120 °C), thus maintaining solvent integrity throughout extended leaching operations. The experimental optimization using RSM-CCD successfully identified temperature and time as the most influential parameters, generating a highly reliable predictive model (R² = 0.99) for copper recovery. This addresses the first objective of process parameter optimization with statistical rigor.

Kinetic analysis revealed that the leaching process follows diffusion-controlled kinetics through a sulfur-rich product layer, with activation energies of 29.09 kJ/mol (Cu) and 38.16 kJ/mol (Fe) characteristic of ash-layer diffusion control. This fundamental understanding of the rate-limiting mechanism fulfills the second key objective of identifying the dissolution kinetics. Advanced characterization techniques provided comprehensive mechanistic insights: XRD analysis confirmed preferential chalcopyrite dissolution with direct conversion to elemental sulfur, while UV-Vis spectroscopy identified the formation of soluble chlorocomplexes ([CuCl₄]²⁻ and [FeCl₄]²⁻), explaining the high extraction efficiency. These findings collectively address the third objective of elucidating dissolution pathways.

The integrated methodology, from fundamental solvent characterization (eutectic temperature determination, TGA) to process optimization (RSM) and mechanistic analysis (kinetics, XRD, and UV-Vis), provides a robust scientific framework for DES-based metal recovery. The demonstrated relationship between solvent properties (eutectic composition and thermal stability) and process performance offers valuable general principles for developing sustainable solvometallurgical technologies. Future work should focus on strategies to overcome sulfur passivation and enhance selective metal recovery to advance practical applications of DES systems in mineral processing.