Sustainable Metal Recovery from Photovoltaic Waste: A Nitric Acid-Free Leaching Approach Using Sulfuric Acid and Ferric Sulfate

Abstract

In recent years, recovering precious and base metals such as silver and copper from end-of-life products has become a fundamental factor in the sustainable development of many countries. This not only supports environmental goals but is also a profitable economic activity. Therefore, in this study, we investigate the recovery of silver and copper from an end-of-life photovoltaic panel powder using an alternative leaching system containing sulfuric acid and ferric sulfate instead of nitric acid-based leaching systems, which are susceptible to producing hazardous gases such as NO_x. To obtain this goal, a series of experiments were designed with the Central Composite Design (CCD) approach using Response Surface Methodology (RSM) to evaluate the effect of reagent concentrations on the leaching rate. The leaching results showed that high recovery rates of silver (>85%) and copper (>96%) were achieved at room temperature using a solution containing only 0.2 M sulfuric acid and 0.15 M ferric sulfate. Analysis of variance was applied to the leaching data for silver and copper recovery, resulting in two statistical models that predict the leaching efficiency based on reagent concentrations. Results indicate that the models are statistically significant due to their high R² (0.9988 and 0.9911 for Ag and Cu, respectively) and the low p-value of 0.0043 and 0.0003 for Ag and Cu, respectively. The models were optimized to maximize the dissolution of silver and copper using Design Expert software.

1. Introduction

Nowadays, in order to restrict the global temperature rise, there is an urgent need to transition from using fossil fuels to renewable energy sources such as solar energy. The global expansion of using Photovoltaic Panels is raising concerns about the increase in waste generation. Due to the recent European Union targets for PV panel deployment by 2050, fifty percent of energy generation must be from solar panels. It is estimated that the amount of end-of-life PV panel waste will reach 21–35 million tons just in Europe [1,2,3,4]. Since 2012, end-of-life photovoltaic panel modules must be included in the scope of Waste Electrical and Electronic Equipment (WEEE) regulations in the European Union [5]. Based on these regulations, every EU member state is required to achieve a collection rate of 85% and a recycling rate of 80% for materials that are used in these modules. Despite the fact that the recycling rate of PV panels was only 14% in 2019, it is predicted to increase to 35% and 70% by the year 2030 and 2050, respectively [6]. Since end-of-life PV panels contain both hazardous and precious materials, effective recycling of these kinds of waste is critical from both environmental and economic points of view [7,8]. From an environmental aspect, these modules may contain dangerous elements and heavy metals such as lead, tin, and cadmium, which are very dangerous for the environment and human health. On the other hand, the presence of valuable and precious metals, especially silver, makes the recycling process important from an economic point of view [4,9,10]. Lee et al. reported that the main components of a typical PV panel consist of 70.47% glass, 13.42% frame, 6.29% encapsulant, 3.16% back sheet, and 4.63% solar photovoltaic cell. Notably, the majority of valuable metals are concentrated in the photovoltaic cell.

Table 1. Composition of solar photovoltaic cell part of a typical PV panel by weight.

Element	Wt.%
Copper	15.33
Aluminum	6.70
Tin	2.38
Lead	1.73
Silver	0.65
Silicon	65.66
Others	7.56

presents the composition of the solar cell layer in a typical PV panel [11].

Generally, the recycling process of the end-of-life of WEEE, such as PV panels, Printed Circuit Boards, LCDs, HDDs, and batteries, includes three main stages: (1) Delamination, (2) Separation of metallic and non-metallic compounds, and (3) Extraction and Purification [12,13,14,15]. There are various methods, such as mechanical, chemical, and thermal processes, to be used for delamination and separation of metallic and non-metallic compound stages, which can remove glass, silicon, aluminum, and other components [13]. The main goal of the extraction and purification stage is to attain the desired purity level of the metals. To achieve this purpose, only a subset of hydrometallurgical techniques is currently used at a commercial scale for end-of-life PV modules. The most used hydrometallurgical methods are leaching [16,17], solvent extraction [18,19], ion exchange [20,21], precipitation [22,23], and electrowinning [24,25]. Membrane-based approaches such as supported liquid membranes [26,27] and polymer-inclusion membranes [28,29] are still at laboratory or pilot-plant level and have yet to see widespread industrial uptake, either for dedicated PV waste or for mixed WEEE feeds.

Many researchers have employed hydrometallurgical processes to recover valuable elements from PV panels. In 2024, Malumbo Mwase et al. investigated the recovery of silver and aluminum from end-of-life photovoltaic panels using a two-step leaching process. In the first step, 99% of the aluminum was leached using 5% HCl at room temperature for 3 h. The solid residue of the first step of leaching was then leached with 0.5 M HNO₃ at high temperature (85 °C) for 2 h to extract 99% Ag, which was subsequently recovered as metallic Ag with a purity of more than 99.9% using Hydrazine [16]. In 2025, Gajare et al. studied the recovery of silver from solar panel waste using 6 M HNO₃ as the leaching agent for 1 h at a temperature of 60 °C, and, under these conditions, all the silver was dissolved [30]. In 2023, Kastanaki et al. employed the hydrothermal leaching process using HNO₃ to recover silver and aluminum from crystalline silicon panels. The optimal conditions which they reported are 2 N HNO₃, 2 h leaching time, a solid-to-liquid ratio of 10%, and a temperature of 140 °C. Under these conditions, Ag and Al were dissolved completely [10].

In another study, which was conducted by Romano et al., the dissolution mechanism of silver from PV panels using the GOLD-REC1 process was investigated. The leaching system that was used in that study consisted of 20 g/L thiourea, 0.1 M sulfuric acid, and 22 g/L ferric sulfate. They achieved more than 90% silver recovery in 1 h and more than 99% at 2 h reaction time [5].

Due to the fact that using nitric acid as a leaching agent generates toxic wastewater and greenhouse gases such as nitrogen oxides (NO_x), which are known to affect global warming 300 times more than CO₂, Seo et al. suggested using an alternative leaching system containing thiourea and ferric sulfate [31]. Environmental disadvantages of using nitric acid in the leaching process are also mentioned by Li et al. in their study, which was about the leaching of end-of-life PV panels using sulfuric acid as a leaching agent [32].

As reported in the literature, nitric acid has been widely used in most studies due to its strong oxidative properties, which facilitate efficient silver dissolution and high recovery rates. However, the environmental concerns associated with the use of nitric acid must also be considered, as noted by Seo et al. [31]. Therefore, identifying more environmentally friendly alternatives as leaching agents for silver recovery is crucial.

Sulfuric acid offers several compelling advantages over nitric acid: it is inexpensive, widely available, less volatile (thereby avoiding toxic NO_x fumes), and compatible with common, low-cost corrosion-resistant materials. Because sulfate electrolytes are also the industry standard for copper and silver electrowinning, the same leach liquor can be fed directly to the recovery cell, where part of the acid is regenerated cathodically (reducing reagent consumption and safety-related operating costs).

H₂SO₄ is, however, a non-oxidising acid, so an auxiliary oxidant is required to dissolve metallic silver efficiently. Ferric sulfate is particularly well-suited for this role: Fe³⁺ oxidises Ag⁰ (and Cu⁰). At the same time, being reduced to Fe²⁺, the Fe³⁺ can be continuously regenerated by sparging air/oxygen or anodically in the electrowinning circuit. The reagent is low-cost, widely available from iron-sulfate by-streams, and has a long track record in the hydrometallurgical treatment of refractory sulfide concentrates. Consequently, the combined H₂SO₄/Fe₂(SO₄)₃ system delivers economical, internally regenerable, and environmentally preferable leaching conditions compared with nitric acid.

Accordingly, in this paper, we investigated a leaching system using sulfuric acid as the leaching agent and ferric sulfate as an oxidizing agent to recover valuable elements such as silver and copper from end-of-life photovoltaic panel powder. This work represents the optimization of the initial step of a complete recycling process currently under patent application, where leaching and electrowinning constitute the core stages, thus indicating strong technological maturity and near-term potential for industrial implementation. To investigate the effect of sulfuric acid and ferric sulfate concentrations on the recovery rate of Ag and Cu, experiments were designed in three levels with response surface methodology (RSM) using central composite design (CCD). Results were analyzed using Design Expert software, and the process was optimized to maximize Ag and Cu recovery and minimize the consumption of chemical reagents.

2. Materials and Methods

2.1. Materials

The PV panel powder used in this study was provided by a first level plant. This first level plant enables the recovery of the aluminum frame and valuable metals from photovoltaic panels. Glass delamination was achieved using specialized steel tools that removed the glass without contamination. Afterward, the panel was shredded, and the materials were mechanically separated into copper, plastic, and silicon powder [5].

The morphology and elemental distribution of the solar panel powder and the solid residue of the leaching process were investigated using scanning electron microscopy-energy dispersive spectrometer (SEM-EDS; Zeiss Gemini SEM 500, Carl Zeiss Microscopy GmbH, Oberkochen, Germany). Figure 1 shows that the tested solar panel powder contains Si, Al, Na, Ca, Fe, Mg, Pb, Sn, Cu, and Ag. It seems that the observed agglomerate of fine particles is surrounded by larger silica particles (green, on the left) and metallic silicon particles (blue, on the top-right). The metal content of the as-received material was determined via chemical digestion in aqua regia in a 3:1 ratio of analytical grades of HCl (Sigma-Aldrich, St. Louis, MO, USA, 37%) to HNO₃ (Sigma-Aldrich, 65%), followed by analysis using inductively coupled plasma optical emission spectrometry (ICP-OES, Agilent Technologies 5100, Santa Clara, CA, USA). The elemental composition of the sample is presented in

Table 2. Composition of the PV panel powder.

Element	Ag	Cu	Al	Fe	Pb	Sn
Wt. %	0.39	1.01	2.55	0.11	0.57	1.01

. In order to investigate the particle size distribution of the powder, a Mastersizer 2000 (Malvern Instruments Ltd., Malvern, Worcestershire, UK) was used, and the results are given in Figure 2. Analytical-grade reagents were used in all experiments, including sulfuric acid (VWR Chemicals (Radnor, PA, USA), >95%) and ferric sulfate hexahydrate (Fe₂(SO₄)₃·6H₂O, VWR Chemicals), which served as leaching agents.

2.2. Methods

To design the leaching experiments, a full factorial approach was employed using a circumscribed central composite design (CCCD) within the framework of response surface methodology (RSM). The design included two center points and four axial (star) points, aimed at evaluating the individual and interactive effects of two key variables of sulfuric acid concentration and ferric sulfate concentration on silver leaching efficiency. The selection of the experimental factor levels was guided by previous laboratory and pilot-scale studies, which suggested optimal conditions within the experimental space investigated [5].

A total of ten experimental runs were conducted based on this design, allowing for a comprehensive analysis of both main effects and their interactions, as summarized in

Table 3. Independent variables and their levels used in the experimental design.

Variables	X Variable	Variable Levels
		−α	−1	0	+1	+α
H2SO4 (M)	A	0.06	0.1	0.2	0.3	0.34
Fe2(SO4)3 (M)	B	0.03	0.5	0.1	0.15	0.17

. Statistical analysis of the experimental data was carried out using Design-Expert 13 software.

Leaching experiments were conducted in a sulfuric acid medium with ferric sulfate serving as the oxidizing agent. Preliminary investigations showed that reasonable leaching efficiencies for both Ag and Cu could be achieved without elevating the temperature. Therefore, in order to focus on optimizing reagent concentrations, temperature, solid-to-liquid ratio, and leaching time were kept constant throughout this study. All experiments were carried out at room temperature for a duration of 2 h. In each test, 2.5 g of solid PV panel powder was introduced into a glass reactor containing 25 mL pre-prepared leaching solution with a solid to liquid ratio of 10%, composed of defined concentrations of ferric sulfate and sulfuric acid. To prepare the leaching solution, ferric sulfate was first dissolved in deionized water under continuous stirring for 10 min, after which sulfuric acid was added and stirred for 5 min. All leaching experiments were performed under constant agitation at a rotational speed of 250 rpm. Upon completion of the leaching process, solid–liquid separation was achieved using a vacuum filtration system equipped with 0.45 μm nitrate cellulose filters. The resulting filtrates were subsequently diluted at a ratio of 1:10 using a 10% HNO₃ solution prior to ICP-OES analysis. All solutions were analyzed in triplicate using ICP-OES, and the leaching efficiency was calculated based on the average of the three independent measurements, ensuring analytical reliability and minimizing random error, using the following equation:

$$\mathrm{L}\mathrm{e}\mathrm{a}\mathrm{c}\mathrm{h}\mathrm{i}\mathrm{n}\mathrm{g} \mathrm{E}\mathrm{f}\mathrm{f}\mathrm{i}\mathrm{c}\mathrm{i}\mathrm{e}\mathrm{n}\mathrm{c}\mathrm{y}(\mathrm{\%})=100\times {\displaystyle \frac{C_M\times V_f}{M_M}}$$

where C_M is the metal concentration in the leachate (mg/L), V_f is the final volume of the solution (L), and M_M represents the initial mass of the target metal in the solid powder used in the leaching test (mg). To ensure accuracy in the measurements, the filter cake from each test was thoroughly washed with a predetermined volume of deionized water to recover any dissolved metals retained in the residual moisture of the filter cake. After filtration and washing, the total volume of the pregnant leach solution (PLS) was measured using a graduated cylinder. This measured final volume (V_f) was then used in the calculation of leaching efficiency to ensure reliable and consistent data.

3. Results and Discussion

3.1. Leaching Results

As previously mentioned, a full factorial experimental design within the framework of RSM was employed, consisting of ten runs, to investigate the effects of sulfuric acid and ferric sulfate concentrations on the leaching efficiency of silver and copper. The experimental plan and corresponding results, including the leaching efficiency of Ag and Cu as the response variables, are summarized in

Table 4. Experimental design and leaching efficiency of Ag and Cu.

Run	Parameters		Responses
	H2SO4 (M)	Fe2(SO4)3 (M)	Ag (%)	Cu (%)
1	0.1	0.05	1.77	60.37
2	0.3	0.05	1.07	23.13
3	0.1	0.15	68.63	95.76
4	0.3	0.15	85.36	97.33
5	0.2	0.1	68.47	96.05
6	0.34	0.1	0.86	93.86
7	0.06	0.1	62.52	95.25
8	0.2	0.17	85.06	96.81
9	0.2	0.03	2.05	12.80
10	0.2	0.1	63.69	94.32

.

Preliminary analysis of the data confirms that both H₂SO₄ and ferric sulfate concentrations notably influence the leaching efficiency of Ag and Cu. Silver leaching efficiency ranged from 1.07% to 85.36%, with the maximum observed in Run 4 at 0.3 M H₂SO₄ and 0.15 M Fe₂(SO₄)₃. Notably, a comparable efficiency of 85.06% was achieved in Run 8 at a lower sulfuric acid concentration but higher ferric sulfate concentration (0.17 M), corresponding to an axial point outside the central design space. This outcome suggests that both parameters are critical for silver dissolution and highlights the particularly strong positive effect of ferric sulfate concentration, which enhances silver recovery even under lower acid concentration. On the other hand, at lower Fe³⁺ concentrations, silver recovery was minimal, reaching only about 2% in Runs 1, 2, and 9.

These findings underscore the effectiveness of ferric sulfate as an oxidizing agent for silver recovery from PV panel powder, which demonstrated a strong capacity to dissolve Ag and Cu under relatively mild conditions, namely, moderate acid concentration, ambient temperature, and relatively short reaction time. A similar trend was observed for copper, where leaching efficiency notably declined at low ferric sulfate concentrations, as evidenced in the same runs (1, 2, and 9).

Additionally, the reproducibility of the process is supported by the consistent results obtained at the design space center points. Silver leaching efficiencies of 68.47% and 63.93% were obtained in Runs 5 and 10, respectively. The corresponding copper leaching efficiencies were 96.05% and 94.32%, demonstrating both the stability and reliability of the experimental approach.

To statistically validate the observed trends, analysis of variance (ANOVA) was conducted (

Table 5. Analysis of variance (ANOVA) for the efficiency of Ag leaching.

Source	Sum of Squares	df	Mean Square	F-Value	p-Value
Model	12,574.84	7	1796.41	234.1	0.0043	Significant
A-H2SO4	1901.22	1	1901.22	247.76	0.004
B-Fe2(SO4)3	3445.19	1	3445.19	448.96	0.0022
AB	75.91	1	75.91	9.89	0.088
A2	1299.08	1	1299.08	169.29	0.0059
B2	545.91	1	545.91	71.14	0.0138
A2B	142.54	1	142.54	18.57	0.0498
AB2	1332.45	1	1332.45	173.64	0.0057
Residual	15.35	2	7.67
Lack of Fit	5.03	1	5.03	0.4882	0.6117	not significant
Pure Error	10.31	1	10.31
Core Total	12,590.19	9
Fit Statics
Std. Dev.		2.77		R2		0.9988
Mean		43.97		Adjusted R2		0.9945
C.V. %		6.3		Predicted R2		0.9711
				Adeq. Precision		34.5363

and

Table 6. Analysis of variance (ANOVA) for the efficiency of Cu leaching.

Source	Sum of Squares	df	Mean Square	F-Value	p-Value
Model	9649.86	5	1929.97	89.22	0.0003	Significant
A-H2SO4	0.964	1	0.964	0.0446	0.8431
B-Fe2(SO4)3	6520.35	1	6520.35	301.41	<0.0001
AB	376.67	1	376.67	17.41	0.014
B2	2433.82	1	2433.82	112.51	0.0004
AB2	142	1	142	6.56	0.0625
Residual	86.53	4	21.63
Lack of Fit	85.05	3	28.35	19.11	0.1662	not significant
Pure Error	1.48	1	1.48
Core Total	9736.39	9
Fit Statics
Std. Dev.		4.65		R2		0.9911
Mean		76.57		Adjusted R2		0.9800
C.V. %		6.07		Predicted R2		0.9084
				Adeq. Precision		25.1359

). A significance threshold of p-value < 0.05 was used to identify parameters with a meaningful effect on the leaching efficiency [26,33,34]. The ANOVA results indicated that both sulfuric acid and ferric sulfate concentrations, along with their quadratic terms, notably influenced silver leaching efficiency at the 95% confidence level (Table 5).

Based on the ANOVA, which showed a non-significant lack of fit, a regression model was developed to predict silver leaching efficiency within the experimental design space. This model, presented in

Table 7. Models for predicting Ag and Cu leaching efficiency (actual equations).

Response	Mathematical Model	Adjusted R2
Ag (%) =	−316.63 + 2076.98 S + 6092.12 F − 26,531.47 SF − 3374.16 S2 − 25,020.22 F2 + 16,884.16 S2F + 10,3245 SF2	0.9945
Cu (%) =	+59.97 − 536.04 S + 502.42 F + 8681.72 SF − 1598 F2 − 33,704.63 SF2	0.9800

S: H₂SO₄ (M); F: Fe₂(SO₄)₃ (M).

, incorporates both linear and quadratic terms, capturing the non-linear behavior evident in the experimental data. The inclusion of quadratic terms suggests that leaching efficiency improves with increasing concentrations of H₂SO₄ and Fe₂(SO₄)₃ up to an optimum point, beyond which the efficiency may decrease due to curvature effects. Li et al., who used a leaching system containing sulfuric acid and hydrogen peroxide for dissolution of silver and aluminum from PV panels, observed similar trends for the leaching and oxidizing agent’s concentrations [32]. These results suggest that ferric sulfate achieves almost comparable leaching efficiency under milder conditions, which demonstrates its promise as an alternative oxidant.

The model exhibited excellent statistical performance, with a predicted R² of 0.9711, an adjusted R² of 0.9945, and an R² of 0.9988, indicating strong agreement between predicted and observed values (Table 5). The model also demonstrated high statistical reliability, as evidenced by a low standard deviation of 2.77 and a non-significant lack of fit (p = 0.6117). Furthermore, the coefficient of variation (C.V.) was 6.3%, reflecting high precision, while the adequate precision value exceeded the recommended threshold, confirming a strong signal-to-noise ratio [26].

Overall, these results affirm that the developed model is statistically robust and well-suited for predicting and optimizing silver leaching efficiency from the PV panel powder.

To further investigate the influence of process parameters on copper leaching efficiency, ANOVA was performed for the Cu dissolution response. The results, summarized in Table 6, indicate that ferric sulfate concentration, along with its quadratic term and its interaction with sulfuric acid concentration, are statistically significant factors. The model demonstrated strong significance with an overall p-value of 0.0003, confirming excellent fit to the experimental data and an insignificant lack of fit.

Although sulfuric acid concentration was not a statistically significant factor, due to its relatively high p-value, it was retained in the model to maintain model hierarchy. Also, the p-value for the AB² term is 0.0625, slightly above the typical 0.05 threshold for statistical significance. However, this term was retained in the final model to have better model fitting, which improved the overall model performance metrics (R², adjusted R², and predicted R²) and helped capture the curvature observed in the experimental data. Based on the ANOVA results, which confirm a non-significant lack of fit (Table 6), a regression model was developed to predict copper leaching efficiency based on the actual experimental parameters. This model is presented in Table 7.

The final model exhibited strong predictive capability, with a predicted R² of 0.9084, an adjusted R² of 0.9800, and an overall R² of 0.9911, indicating excellent agreement between predicted and observed responses. The model also showed good statistical robustness, with a relatively low standard deviation of 4.65 and a non-significant lack of fit (p = 0.1662). Additionally, the coefficient of variation (C.V.) was 6.07%, and the adequate precision greatly exceeded the recommended threshold of 4, suggesting a high signal-to-noise ratio [26]. These findings confirm that the developed model for predicting copper leaching efficiency is statistically sound and well-suited for process optimization.

The statistical model developed from the experimental data was further evaluated through graphical analysis across the investigated parameter range. Figure 3a presents the normal probability plot of residuals, where the data points closely follow a straight line, indicating that the residuals are normally distributed and that the assumption of normality is satisfied. The correlation between predicted and actual silver leaching efficiency values is shown in Figure 3b. The proximity of the data points to the diagonal line demonstrates strong agreement between experimental and predicted results, further confirming the accuracy of the regression model. Figure 3c illustrates the externally studentized residuals plotted against the run number. The residuals are randomly scattered around the zero line, with no apparent patterns, indicating a good model fit and the absence of systematic error. Figure 3d presents the perturbation plots, which show the sensitivity of silver leaching efficiency to variations in sulfuric acid and ferric sulfate concentrations around the center point.

The three-dimensional response surface plot in Figure 3e illustrates the effect of H₂SO₄ and ferric sulfate concentrations on silver leaching efficiency. The plot reveals that increasing sulfuric acid concentration enhances leaching efficiency up to an optimum point (~0.2 M), beyond which further increases have a detrimental effect, particularly at ferric sulfate concentrations lower than 0.13 M. In contrast, ferric sulfate exhibits a consistently positive influence on silver leaching when sulfuric acid is present in more than 0.2 M concentrations. For enhanced clarity, a corresponding two-dimensional contour plot is provided in Figure 3f, highlighting the regions associated with the highest silver leaching efficiencies.

Overall, these graphical analyses confirm that the developed model is statistically valid and reliable for predicting silver leaching efficiency across the tested ranges of sulfuric acid and ferric sulfate concentrations.

The predictive model for copper leaching efficiency was also evaluated using diagnostic plots. The normal probability plot of residuals (Figure 4a) shows that the data points align closely with the reference line, confirming that the residuals are normally distributed and that the model satisfies the assumption of normality. Figure 4b compares the predicted and actual values for copper leaching efficiency. The close alignment of data points along the diagonal line indicates strong model accuracy and minimal deviation from experimental results. Figure 4c displays the distribution of externally studentized residuals across the experimental runs. All residuals fall within the control limits (±7.45), and no apparent patterns are observed, suggesting random distribution and the absence of systematic bias in the model. Figure 4d presents the perturbation plot based on the model around the center point. The plot reveals a minimal influence of sulfuric acid concentration on copper leaching efficiency, while ferric sulfate concentration exhibits a strong positive effect.

The three-dimensional surface plot in Figure 4e further illustrates the relationship between H₂SO₄ and ferric sulfate concentrations and their effect on copper leaching efficiency. The plot indicates that increasing ferric sulfate concentration significantly enhances copper dissolution, particularly at higher sulfuric acid concentrations. At 0.3 M H₂SO₄, raising the ferric sulfate concentration from 0.05 M to 0.15 M increased the copper dissolution rate from approximately 22% to nearly 100%. At the highest ferric sulfate level of 0.15 M, sulfuric acid concentration has a negligible effect, indicating that ferric sulfate is the dominant factor. For additional clarity, a corresponding two-dimensional contour plot (Figure 4f) highlights the regions associated with the highest copper leaching efficiencies.

Collectively, these diagnostic plots confirm the robustness and predictive reliability of the model. The results demonstrate that copper leaching efficiency is primarily driven by ferric sulfate concentration, and the model is well-suited for use in process optimization. In 2019, Xiaohua Li et al. observed a similar trend when using FeCl₃ (Fe (III)) for the leaching of copper from chalcopyrite [35].

3.2. Characterization of the Leaching Residue

A detailed SEM-EDS analysis of the solid residues obtained after leaching (0.15 M ferric sulfate and 0.3 M sulfuric acid) was performed to better understand the elemental distribution and morphological evolution after leaching. As Figure 5 illustrates, Cu and Ag are no longer visible in the solid residue, and these results confirm that most of the Cu and Ag were leached from the photovoltaic panel. Large silica particles (green) and metallic silicon particles (blue) are still clearly identifiable in the final solid residue.

3.3. Optimization

To determine the most favorable operating conditions, an optimization study was conducted with the objective of maximizing both silver and copper leaching efficiencies. The optimization was performed using the desirability function approach implemented in Design-Expert 13 software. The overall desirability function, which ranges from 0 (least desirable) to 1 (most desirable), was employed as the optimization criterion. The software uses the developed regression models and their interaction terms to predict and optimize conditions that yield the maximum overall desirability.

Figure 6a presents the three-dimensional surface plot of composite desirability as a function of H₂SO₄ and ferric sulfate concentrations. The plot reveals that the maximum desirability value of 1 is achieved at moderate to high sulfuric acid concentrations (0.2–0.3 M) combined with the highest level of ferric sulfate (0.15 M). This region corresponds to an optimal balance, where both Ag and Cu leaching efficiency are simultaneously maximized.

The corresponding two-dimensional contour plot in Figure 6b further highlights the regions of highest desirability. These findings indicate that careful adjustment of reagent concentrations not only enhances metal recovery but also contributes to more sustainable process operations by optimizing chemical usage and reducing excess reagent consumption.

As previously mentioned, Li et al. optimized a leaching system containing sulfuric acid and hydrogen peroxide for the recovery of Ag and Al from PV panels. Their results indicated that achieving a leaching efficiency greater than 90% required using more than 0.8 M sulfuric acid at elevated temperatures (above 60 °C) [32]. In contrast, the system optimized in this study, based on sulfuric acid and ferric sulfate, achieved around 85% silver dissolution at room temperature using a much lower acid concentration (0.2 M) and 0.15 M ferric sulfate. Given the positive effect of ferric sulfate concentration on leaching efficiency, as confirmed by ANOVA, model fitting, and the response surface trend in Figure 3e, it is predicted that even higher leaching efficiency could be achieved simply by increasing the ferric sulfate concentration, without raising the acid concentration or temperature. Since the proposed system does not generate NO_x gases, operates at room temperature, and requires notably lower acid concentrations compared to previous methods, it aligns well with the principles of circular hydrometallurgy as proposed by Binnemans et al. [36].

4. Conclusions

The primary aim of this research was to investigate the potential of sulfuric acid and ferric sulfate as an alternative leaching system, replacing the more commonly studied nitric acid-based methods. This study optimized key process parameters, notably the concentrations of sulfuric acid and ferric sulfate, under ambient conditions using response surface methodology (RSM). The results indicated that high recovery efficiencies (approximately 85% for silver and above 96% for copper) can be achieved with relatively low concentrations of sulfuric acid (0.2 M) and ferric sulfate (0.15 M). ANOVA analysis provided deeper insight into these outcomes, revealing that silver leaching efficiency is significantly influenced by both sulfuric acid and ferric sulfate concentrations and their quadratic terms. In contrast, copper extraction efficiency was primarily influenced by ferric sulfate concentration alone, with a negligible effect from sulfuric acid concentration. This suggests different reaction mechanisms or kinetics for silver and copper dissolution, emphasizing the crucial role of ferric sulfate as an oxidizing agent in copper recovery.

An essential advantage of this system is the potential to implement regeneration steps downstream to recover and recycle sulfuric acid and ferric sulfate, substantially reducing chemical consumption and waste. Unlike nitric acid-based systems, this approach eliminates harmful NOx emissions, positioning it as an environmentally sustainable alternative. Furthermore, the mild operating conditions not only lower operational costs but also enhance worker safety and environmental compliance. Despite the promising outcomes, further investigation into the regeneration efficiency and economics of chemical reuse is necessary. Future research will explore process scalability, economic feasibility in industrial contexts, and detailed environmental lifecycle assessments.

In summary, the sulfuric acid–ferric sulfate leaching system presents a viable, environmentally friendly alternative to conventional nitric acid-based methods, offering significant improvements in sustainability and operational practicality.