Alternative Leaching Agents for Selective Recovery of Gold and Copper from Computer Waste Printed Circuit Boards

Abstract

Recent studies focus on recovering materials from Waste Electrical and Electronic Equipment (WEEE). Printed Circuit Boards (PCBs) are promising due to their heterogeneous composition, which includes precious metals, ceramics, and polymers. This research analyzes the leaching process of computer PCB waste to recover valuable metals such as copper and gold. The study involved physical-mechanical processing of PCB samples followed by chemical composition characterization. Metal extraction was performed through a three-stage leaching process. The first two stages used 2 M and 3 M sulfuric acid with hydrogen peroxide as leaching agents, achieving about 75% copper extraction. In the third stage, parameters for gold leaching using thiosulfate were evaluated, including concentrations of ammonium hydroxide and copper sulfate, reaction times (1–4 h), and temperatures (30, 40, and 50 ${\phantom{­}}^{\circ }$C). The leaching solution comprising 0.12 M sodium thiosulfate, 0.2 M ammonium hydroxide, and 20 mM copper sulfate yielded maximum gold extractions of 14.76% for fine and 15.73% for coarse fractions at 40 ${\phantom{­}}^{\circ }$C. In conclusion, the proposed method for recovering metals from PCBs can reduce the environmental impact of improper WEEE disposal while promoting a circular economy of secondary raw materials.

1. Introduction

The increasing generation of Waste Electrical and Electronic Equipment (WEEE) due to the rapid development of the electronic industry has raised environmental concerns [1,2]. The diverse composition of WEEE, including polymeric, ceramic, and metallic materials, requires efficient recovery and recycling to prevent environmental and health issues associated with the toxicity of its components. Enhancing recycling technologies and processes, especially in recovering valuable materials, is crucial to minimize environmental impacts and promote sustainability. For instance, a multi-decisional modeling approach has shown that although WEEE treatment plants can achieve substantial environmental gains, their economic viability depends on the scale and policy incentives [3]. Additionally, adopting a systematic approach like material flow analysis can significantly enhance the management of WEEE by thoroughly quantifying economic, social, and environmental dimensions, supporting more comprehensive decision-making aligned with sustainability and circular economy goals [4]. Effective WEEE recycling is critical not only due to its environmental implications but also because of its economic and social impacts. In this sense, a structured literature review highlighted how circular economy principles can address these multidimensional sustainability aspects in the WEEE sector by promoting resource efficiency, minimizing waste generation, and creating socioeconomic value through recycling practices [5].

Extractive metallurgy processes represent the primary industrial-scale technologies when the focus is on metal recovery from WEEE [6,7]. Compared to conventional mining, this urban mining process tends to be shorter and yields higher results, coupled with a lower volume of waste and rejects [8]. Another essential point to consider is that mineral resources are finite, and reserves are depleting at an accelerating rate, especially concerning valuable metals [9]. The trend indicates that by 2070, economically exploitable reserves of gold (Au), silver (Ag), and copper (Cu) may be depleted [10]. In this perspective, reducing the demand for virgin raw materials and enhancing the recovery of metals from secondary sources is crucial.

Integrated approaches have been investigated to enhance the sustainability of metal recovery from WEEE, aiming to address the challenges associated with the imminent scarcity of mineral resources. In this context, the integration of material flow analysis with complementary tools such as life cycle assessment and circular economy principles is considered essential for capturing the full sustainability dimensions—economic, social, and environmental—inherent to WEEE management [4]. Moreover, the optimization of reverse-logistics networks via mathematical programming can significantly reduce WEEE management costs by minimizing transportation expenses [11]. In addition, recycling automotive PCBs can be economically viable with proper material characterization, highlighting the importance of integrating technical and economic approaches in WEEE recovery [12].

In addition to integrated analytical approaches, the choice of metallurgical processes also significantly influences the sustainability of metal recovery from WEEE. In particular, hydrometallurgy has gained prominence as it represents a less environmentally damaging alternative than other metallurgical routes [13]. For instance, high recovery efficiencies for copper, gold, and silver have been achieved through multi-step hydrometallurgical methods, significantly reducing reagent consumption and environmental impact [14]. Additionally, hydrometallurgy offers advantages such as high recovery rates and relatively low operational costs, reinforcing its viability for sustainable metal extraction from WEEE [15]. Furthermore, mechanical pre-treatment methods such as zig-zag classification can efficiently concentrate metals, simplifying subsequent recovery steps [16], and hydrometallurgy can effectively reclaim critical metals like rare earth elements, enhancing sustainability in urban mining [17]. Nonetheless, despite these promising results, literature reviews indicate that no single metallurgical route has yet proven fully efficient and sustainable for metal recovery, suggesting that hybrid approaches currently represent the most practical pathway toward achieving comprehensive recycling [18,19,20,21].

The study highlights the value of PCBs in WEEE due to their composition. PCBs stand out in almost all electrical and electronic equipment due to their primary role in operating such devices [22]. Thus, this work presents state-of-the-art gold recovery processes from WEEE in PCBs, employing different methodologies. It evaluates a hydrometallurgical route involving two leaching steps with H₂SO₄ and H₂O₂ solutions to extract base metals, especially copper (Cu) [14,15,23,24]. Additionally, there is a gold (Au) leaching step using solutions with different concentrations of sodium thiosulfate, copper sulfate, and ammonium hydroxide [25,26]. Compared to conventional cyanide-based gold recovery and highly acidic leaching routes, the approach proposed in this study presents significant innovations. The sequential use of sulfuric acid (H₂SO₄) and hydrogen peroxide (H₂O₂) in the first two leaching stages maximizes copper extraction while reducing environmental toxicity. Additionally, the employment of sodium thiosulfate as a lixiviant for gold extraction represents a safer and more sustainable alternative to cyanide, which is traditionally used despite its severe environmental risks.

Recent advances in hydrometallurgical processes, such as the use of ionic liquids [27], bioleaching approaches [28], and closed-loop systems [29], have demonstrated high selectivity and lower reagent consumption for metal recovery from WEEE. However, these emerging technologies often require specialized reagents, complex operational controls, or longer processing times, which may pose scalability and economic challenges for immediate application in industrial settings. In contrast, the methodological choices in this study aim to use circular economy principles and provide a viable alternative for industrial applications that reduce hazardous waste generation while identifying opportunities for future improvements in recovery efficiency. The three-stage leaching process employed in this study was designed to target specific metals present in PCBs incrementally, enhancing process control and selectivity. The initial H₂SO₄/H₂O₂ stage effectively removes base metals such as copper, which could otherwise interfere with the subsequent gold leaching step by consuming lixiviant or forming passivating layers. Furthermore, this multi-step strategy reduces reagent consumption and ensures stable copper dissolution, improving process consistency [14]. The effective removal of copper also decreases thiourea consumption during gold leaching, enhancing both the process’s economic viability and environmental sustainability.

While the use of sulfuric acid and hydrogen peroxide for copper extraction and thiosulfate for gold leaching is well documented in the literature [14,23,24], this study contributes to the field by adapting these conventional reagents into a safer and more accessible process specifically tailored for post-consumer PCB waste. Compared to cyanidation, the proposed method significantly reduces environmental risks by eliminating highly toxic reagents and the associated need for complex detoxification treatments [30]. This study prioritizes operational safety and environmental responsibility, providing a practical alternative for decentralized recycling applications. Additionally, by incrementally targeting base and precious metals, the sequential process enhances selectivity, optimizes reagent usage, and opens pathways for future improvements in process scalability and efficiency. Therefore, this study proposes a metallurgical recycling approach that prioritizes environmental responsibility and operational simplicity while critically acknowledging the challenges of optimizing efficiency and economic viability. By exploring non-cyanide-based leaching routes and assessing reagent choices and process conditions, this work aims to advance sustainable recovery strategies from electronic waste and provide a safer foundation for future process scaling and performance improvements.

2. Materials and Methods

This section will detail the methods for sample selection and physical-mechanical processing. The methodological foundation of this work is based on experimental procedures from research groups that have been active in this area for several years [14,23,24,25,26,31,32].

2.1. Sample Selection

In the southern region of Bahia, where this study was conducted, a factory in the Industrial District of Ilhéus specializes in manufacturing, marketing, leasing, and providing technical support for personal computers. Daten Tecnologia LTDA (Ilhéus, Brazil), the company in question, volunteered to contribute to the research by supplying residual computer PCBs. This waste was considered the most economically interesting among the options available at the factory and aligns with the findings in the literature survey on this topic [22,33,34,35]. As described in the literature by [36,37], the mass for each PCB varies according to factors such as brand, model, and year of manufacture.

2.2. Sample Preparation

The sample preparation involved a two-phase mechanical processing of PCBs. In the initial stage, the samples were cut into 1 × 1 cm fractions using a manual guillotine in the Laboratory of Materials and Environment (LAMMA) at the State University of Santa Cruz (UESC). Subsequently, the samples were fragmented in a knife mill [SEIBT LTDA, model MGVS-1 (4 HP, 380 V, 60 Hz, 1160 rpm)] by Recicla Brasil—Environmental Management and Reverse Logistics. The initial grinding was coarse, requiring a secondary grinding in a bench knife mill (SOLAB–Wyllie macro–CE 430) available at LAMMA/UESC to standardize the particle size. Particle size analysis employed Tyler series sieves (BERTEL) with a 24-mesh (0.71 mm) screen, resulting in two fractions, fine and coarse, through a sieve shaker (BERTEL) with the potentiometer set at factor 5. An additional sieve with a 7-mesh (2.83 mm) screen ensured that all sample particles had a diameter of less than 1.0 mm.

2.3. Acid Digestion for Sample Characterization

Acid digestion using aqua regia was performed to determine metal concentrations in fine and coarse material samples derived from comminuted computer-PCBs. The digestion involved mixing nitric acid (HNO₃, 65% P.A.) and hydrochloric acid (HCl, 37% P.A.) at a volumetric ratio of 1:3. This mixture was maintained at 70 ${\phantom{­}}^{\circ }$C with constant stirring at 200 rpm for four hours. Figure 1 presents a flowchart detailing each procedural step of this acid digestion process.

Upon completion of the acid digestion, the remaining solid material collected on filter paper was transferred to a clean, dry beaker. This sample was then dried in an oven at 60 ${\phantom{­}}^{\circ }$C for 12 h. After drying, the beaker containing the dried sample was promptly moved to a desiccator and cooled to room temperature to prevent moisture absorption. The final mass of the dried sample was determined by weighing both the system (beaker, filter paper, and sample) and separately weighing the beaker and filter paper. Finally, chemical characterization was conducted on the filtered digestion solution using an Agilent Technologies 5110 Inductively Coupled Plasma Optical Emission Spectrometer (ICP-OES). The dried solid material was characterized by X-ray Fluorescence (XRF) using a Thermo Scientific™ Niton™ XL3t analyzer. Both analyses were performed at the Laboratory of Corrosion, Protection, and Materials Recycling (LACOR) of the Universidade Federal do Rio Grande do Sul (UFRGS).

2.4. Leaching of Base Metals

This study aimed to enhance the copper extraction rate using the same leaching agents while varying their concentrations. The leaching process was carried out in two steps using 150 mL of H₂SO₄ solution and 30 mL H₂O₂ (30%). In the first step, a 2 mol·L⁻¹ acid solution was applied with a solid-to-liquid (S/L) ratio of 1/10. In the second step, the acid concentration was increased to 3 mol·L⁻¹, while the S/L ratio was reduced to 1/15. Hydrogen peroxide was introduced in two stages: 15 mL was added at the beginning of the experiment, followed by an additional 15 mL after 30 min. The reaction mixture was placed in a beaker with a magnetic stir bar and stirred continuously on a hotplate stirrer to ensure constant agitation. After leaching, the solution was filtered using a Büchner funnel, vacuum pump, Kitasato flask, rubber tubing, filter paper, and a glass rod. The resulting filtrate was transferred for chemical analysis via ICP-OES. At the same time, the solid residue was dried and weighed using an analytical balance to determine the final mass by differential calculation. These procedures are consistent with standard laboratory protocols and emphasize the importance of supplementary leaching in enhancing copper extraction, thereby minimizing interference during subsequent gold recovery, as supported by previous studies [14,23,24].

2.5. Gold Leaching

In this third leaching step, a sodium thiosulfate (Na₂S₂O₃) solution at a concentration of 0.12 M was employed, based on methodologies previously described by [25,31,38]. Variations in ammonium hydroxide (NH₄OH) and copper sulfate II (CuSO₄) concentrations, as well as different temperature conditions and reaction times, are detailed in

Table 1. Experiments to evaluate process variables in gold leaching.

Experimental Conditions				Analyzed Variables
Concentration of Reagents			Temperature (${\phantom{­}}^{\mathbf{\circ }}$C)
Na2S2O3 (M)	NH4OH (M)	CuSO4 (mM)
0.12	0.2	20	30	Temperature
			40
			50
		0	40	Concentration CuSO4 e NH4OH
	0.15	20		Concentration de NH4OH
	0.10
	0.06	10		Concentration de CuSO4
		0

.

For each leaching test, the solution volume was calculated based on a solid-to-liquid (S/L) ratio of 1:25. Solid residues from the second leaching step were weighed, labeled, dried, and stored in a desiccator. The corresponding leaching solution volumes were determined for each experimental condition using the recorded mass of these solid samples.

The solid samples from the second acid leaching step were individually placed in reaction flasks with a capacity of 400 mL. Each flask was filled with the calculated volume of leaching solution, maintaining the S/L ratio of 1:25, and was set up as an open system. The flasks were then placed on hotplate stirrers inside a fume hood. Experimental parameters such as stirring speed (200 rpm), temperature, and duration (4 h) were standardized according to previously published literature [25]. The pH of each solution was carefully maintained between 10.0 and 10.5 through periodic adjustments using either 1 M sodium hydroxide (NaOH) or 1 M sulfuric acid (H₂SO₄).

After completing the leaching process, the resulting mixtures were transferred into clean, dry Falcon tubes. These samples underwent centrifugation, filtration, and dilution and were finally characterized chemically. A schematic representation of the sequential leaching steps performed in this study is provided in Figure 2, facilitating a clearer understanding of the overall methodology.

3. Results and Discussion

This section will first present the types of processed samples and the mass of each resulting fraction after the grinding and particle size separation stage. The qualitative and quantitative characterization results of WEEE PCBs will be discussed, along with the chemical analyses of leaching solutions for base metals such as copper and gold. Finally, the gold leaching efficiency rates using sodium thiosulfate will be calculated for comparison with other leaching agents reported in the literature.

3.1. Evaluation of the Physical-Mechanical Processing of PCBs

Table 2. Particle size classification of PCBs after comminution.

Sample	Mesh	Granulometry (mm)	Mass (g)	Percentage (%)
Fines	$x<24$	$x<0.710$	1500	39.0
Coarses	$24\le x<7$	$0.710\le x<2.84$	2350	61.0
Total	$x<7$	$x<2.84$	3850	10.0

presents the particle size classification of the 14 PCBs after comminution and fractionation into fine and coarse materials. It is observed that there is a loss of material in the comminution process; from a total of 4 kg of intact PCBs, 3850 g of ground material was obtained. A lower mass of the fine fraction was also observed compared to the coarse fraction.

The variation in sample quantity after the comminution process of electronic waste (150 g) is related to the complexity of the composition, involving mixtures of metals, polymers, and ceramics with varying hardness levels. This complexity complicates comminution, resulting in sample loss, especially when using a guillotine and two mills. The industrial processing of residual PCBs may require specialized equipment, such as shredding machines or impact mills.

3.2. Chemical Composition Analysis of PCBs

This section will present the results obtained through the XRF technique applied to the solid samples of initial fine and coarse materials (after particle size classification), the residues from the acid digestion process, and the final solid samples after the three leaching stages. The chemical analyses of the solutions obtained after leaching will be presented using the ICP-OES technique.

3.2.1. Characterization of Ground PCB via XRF

The purpose of characterizing the solid sample by XRF is to obtain information about the sample’s elemental composition.

Table 3. Characterization of fine and coarse fractions of PCBs by XRF.

Metal	Sample Concentration
	Fines	Coarses
Au (ppm)	1154.78	487.31
Ag (ppm)	628.79	22.36
Pd (ppm)	≈0	≈0
Cu (%)	13.21	12.47
Fe (%)	8.84	0.44
Ni (%)	0.36	0.05
Pb (%)	0.04	0.02
Zn (%)	0.40	0.18
Al (%)	6.41	10.20
Cr (%)	0.10	0.02
Si (%)	8.25	5.92
Sn (%)	1.91	0.15

presents the results of this analysis for the solids of fine and coarse materials from PCBs.

Table 3 indicates that the estimated higher quantities of elements such as copper and silicon align with findings in the literature [39] on the composition of microcomputer PCBs. For instance, copper is preferred among other elements due to its notable electrical and thermal conductivity and its resistance to oxidation. Conversely, silicon is found in microcomputer transistors, the main building blocks of electronic circuits in these devices. These transistors facilitate the amplification and control of electric current, enabling the operation of processors, memory, controllers, and other electronic components [39].

Considering that the electronic components soldered to the PCB bases used in this study were not separated, the relevant silicon values in the sample analyses are justified.

3.2.2. The Effectiveness of Acid Digestion in Determining the Composition of PCBs

Aqua regia is known for its non-selective leaching in WEEE, as it can dissolve various metals simultaneously. [40]. This lack of selectivity is attributed to its strongly oxidizing, complexing, and highly acidic properties, enabling the digestion of a wide variety of metals and compounds indiscriminately. Although these physicochemical characteristics make aqua regia ideal for total digestion, they render it unsuitable for selective analytical methods [7].

The results of tests with duplicates of 5 g of fine and coarse material samples at 70 ${\phantom{­}}^{\circ }$C and 100 mL of aqua regia are of the concentration of the metals present in the samples and are presented in

Table 4. Average concentration (%) of the metals after acid digestion and analysis chemistry (by ICP-OES).

Metal	Sample	Average Concentration (%)		Relative Standard Deviation (%)	Total Concentration (%)	Literature Concentration (%)
		Sample 01	Sample 02
Cu	Fines	0.233	0.219	0.010	22.57	13.70
	Coarses	0.265	0.262	0.033	24.19
Fe	Fines	0.139	0.130	0.006	13.45	4.90
	Coarses	0.123	0.166	0.030	14.47
Ni	Fines	0.007	0.007	0.000	0.73	1.10
	Coarses	0.008	0.010	0.001	0.99
Pb	Fines	0.001	0.001	0.000	0.10	2.20
	Coarses	0.002	0.001	0.004	0.14
Zn	Fines	0.017	0.022	0.004	1.92	4.70
	Coarses	0.038	0.035	0.002	3.69
Al	Fines	0.035	0.034	0.001	3.42	4.60
	Coarses	0.043	0.037	0.005	4.00
Cr	Fines	0.002	0.002	0.000	0.18	1.20
	Coarses	0.003	0.003	0.000	0.30
Sn	Fines	0.044	0.048	0.003	4.60	2.30
	Coarses	0.066	0.075	0.006	7.07

(concentration in percentage) and

Table 5. Average concentration (ppm) of the metals after acid digestion (ICP-OES).

Metal	Sample	Average Concentration (ppm)		Relative Standard Deviation (ppm)	Total Concentration (ppm)	Literature Concentration (ppm)
		Sample 01	Sample 02
Au	Fines	0.53	0.96	0.30	74.50	150
	Coarses	0.59	1.02	0.30	80.50
Ag	Fines	3.09	1.94	0.81	251.50	300
	Coarses	2.92	2.73	0.13	282.50
Pd	Fines	40.69	38.06	1.86	3937.50	124
	Coarses	78.56	43.15	25.04	6085.50

(concentration in ppm).

The results indicate that metal concentrations in fine and coarse fractions did not closely match the concentrations reported in the literature [15,41]. The lower extraction efficiencies may result from the absence of dissolved oxygen in the reaction system, typically introduced by bubbling compressed air—a notable methodological difference compared to previous studies. Furthermore, the coarse fraction exhibited unexpectedly higher extraction efficiencies for specific metals, notably copper, than the fine fraction. Palladium extraction was also higher than anticipated, likely due to the presence of components soldered onto PCBs, such as ceramic capacitors and carbon film resistors, which are challenging to fragment into finer granulometries because of their considerable hardness [33,39].

Furthermore, XRF analysis suggests partial solubilization of components by aqua regia due to the presence of gold and other elements in the fine and coarse fractions. Estimates of the average remaining mass of metals were made using masses of 2.2 g and 2.4 g for the fine and coarse fractions, respectively, to assess the presence of gold. Masses of 2.5 g and 1.9 g were also used to estimate the other elements in the fine and coarse fractions. Results are presented in

Table 6. Estimated remaining mass of elements in solid samples after acid digestion at 70 ${\phantom{­}}^{\circ }$C (5 g of sample).

Metal	Estimated Average Remaining Mass (mg)
	Fines	Coarses
Au	2.35	3.48
Ag	0.04	0.10
Pd	≈0	≈0
Cu	3.27	1.82
Fe	70.86	25.51
Ni	3.73	1.17
Pb	0.82	0.35
Zn	7.35	3.03
Al	70.86	61.67
Cr	1.04	≈0
Sn	3.39	0.27

.

The XRF results indicate that the coarser granulation fraction has a higher estimated remaining mass for gold, silver, strontium, and antimony. Despite the finer material samples having a larger surface area, extraction proved to be more effective in the coarser samples for copper and other elements. This finding aligns with the work of Bilesan (2021), who reported that a portion of the gold (73%), palladium (66%), and silver (33%) in his samples was recovered from the fine fraction (<75 µm), while part of the copper (70%) was in the coarse fraction (>75 µm).

3.2.3. Efficiency of Sequential Leaching Stages with Sulfuric Acid and Hydrogen Peroxide for Base Metals Extraction

The results obtained from the first leaching stage, conducted with a sulfuric acid concentration of 2 M, are presented in Figure 3, illustrating the evolution of extraction rates for fine and coarse material samples analyzed via ICP-OES. For this scenario, higher extraction efficiency was observed in fine materials (particles < 0.71 mm), achieving a recovery rate of up to 71% copper. In contrast, the extraction rate for coarse materials (particles between 0.71 mm and 2.8 mm) reached a maximum value of 45%.

The progression of copper extraction rates during the second leaching stage is illustrated in Figure 4. It is observed that the percentage of copper recovered at this stage is lower compared to the first leaching, as expected, given the reduced amount of metal in the solid sample following the initial leaching stage. However, it is noteworthy that copper extraction rates reached values close to 41% for fine materials and 56% for coarse materials when considering the residual copper concentration in the samples after the first leaching step. These values correspond to approximately 12% and 31% for fine and coarse materials, respectively. It is also important to note that, according to the literature [24,36,42], typical copper extraction rates in the second leaching stage are generally lower, ranging from 14% to 19%. The obtained results highlight the importance of performing a complementary leaching stage to achieve significant metal extraction levels, thus preventing interferences in subsequent gold separation processes, a conclusion also supported by previous studies [14,23,24].

Table 7. Copper concentration and extraction in the first leaching stage with 2 M H₂SO₄ and H₂O₂.

	Concentration (mg/L)			Relative Standard Deviation (mg/L)	Average Extraction Percentage (%)
	Sample 1	Sample 2	Average
Fines	6033.82	6005.26	6019.54	20.19	53.33
	5378.07	5427.34	5402.70	34.84	47.87
Coarses	6213.07	6083.48	6148.27	91.63	46.66
	3780.75	3999.84	3890.29	154.92	49.20

summarizes the estimated remaining mass of elements in solid PCB samples following acid digestion conducted at 70 ${\phantom{­}}^{\circ }$C, initially containing 5 g of sample material. The data, obtained through ICP-OES chemical analysis, highlight the copper extraction percentages for fine and coarse particle fractions after the initial leaching stage using a mixture of 2 M H₂SO₄ and 30% (v/v) H₂O₂. These quantitative findings clearly compare extraction efficiencies between different particle sizes.

The results reveal a copper extraction rate ranging from 46% to 53%, falling below the efficiency of 76.12% reported under similar conditions [24]. The intrinsic heterogeneity of coarse materials may explain the variation in copper concentration in the samples. Different exposure to leaching solutions could have impacted the concentration, with fine samples (<0.71 mm) demonstrating higher efficiency due to a larger surface area. In the second leaching step, the concentration of H₂SO₄ was modified to 3 M, resulting in a copper extraction rate of 15% to 34%, consistent with literature values (14–19%) [24,36,42]. One factor justifying this is the high extraction achieved in the first step, making copper less available in the subsequent step [23,43].

Table 8. Copper concentration and extraction in the second leaching stage with 3 M H₂SO₄ and H₂O₂.

	Concentration (mg/L)			Relative Standard Deviation (mg/L)	Average Extraction Percentage (%)
	Sample 1	Sample 2	Average		2nd Leaching	1st + 2nd Leaching	Accumulated
Fines	2790.39	1514.34	2152.36	902.30	31.78	85.12	77.95
	1493.26	1608.74	1551.00	81.66	22.90	70.77
Coarses	1351.92	1020.77	1186.34	234.16	15.00	61.66	72.57
	2684.62	2736.99	2710.80	37.03	34.28	83.49

presents the results from the second copper leaching step using the ICP-OES technique on fractions of fine and coarse materials from computer PCBs.

The copper extraction rate reaches up to 85% in two leaching steps with H₂SO₄ and H₂O₂, aligning with previous studies [23,24]. The average efficiency for the fine fractions (78%) is slightly higher than the coarse fractions (72%). Comparative studies indicate higher efficiencies in two consecutive leachings using particles smaller than 3 mm, such as 90% [23] and 99% [44]. The overall process efficiency was satisfactory, considering the results, particle size, and environmental aspects. Removing most copper will enable gold extraction in the subsequent step.

3.2.4. Effects of Different Experimental Conditions for Gold Leaching in PCBs

This section addresses the gold extraction from PCBs under different experimental conditions, considering parameters such as reaction temperature and leaching solution composition based on state-of-the-art [24,26]. The solid sample of PCBs for this stage is the residue from the first two leaching steps after drying, aiming for a composition with low copper content to avoid interference in the gold separation process. The quantitative results obtained by ICP-OES for all experimental conditions are summarized in

Table 9. Results after 4 h of testing all experimental conditions in gold leaching.

Experimental Conditions	Time (h)	Sample	Concentration Au (ppm)			Average Mass Extracted (mg)	Average Extraction Percentage (%)
			Sample 1	Sample 2	Average
0.12 M Na2S2O3 + 0.2 M NH4OH + 20 mM CuSO4 − 30 ${\phantom{­}}^{\circ }$C	4	Fines	0.050	0.060	0.055	0.017	2.46
	4	Coarses	0.000	0.600	0.300	0.074	6.09
0.12 M Na2S2O3 + 0.2 M NH4OH + 20 mM CuSO4 − 40 ${\phantom{­}}^{\circ }$C	4	Fines	0.620	0.040	0.330	0.165	14.77
	4	Coarses	0.570	0.190	0.380	0.190	15.73
0.12 M Na2S2O3 + 0.2 M NH4OH + 20 mM CuSO4 − 50 ${\phantom{­}}^{\circ }$C	4	Fines	0.445	0.530	0.488	0.174	15.54
	4	Coarses	0.220	0.350	0.285	0.143	11.80
0.12 M Na2S2O3 + 0.06 M NH4OH − 40 ${\phantom{­}}^{\circ }$C	4	Fines	0.330	0.230	0.280	0.046	4.22
	4F *		0.040	0.160	0.100	0.058	4.13
	4	Coarses	0.040	0.030	0.035	0.008	0.64
	4F *		0.020	0.530	0.020	0.010	0.83
0.12 M Na2S2O3 + 0.2 M NH4OH − 40 ${\phantom{­}}^{\circ }$C	4	Fines	0.320	0.050	0.185	0.033	2.67
	4F *		0.040	0.030	0.035	0.018	1.57
	4	Coarses	0.030	0.040	0.035	0.007	0.57
	4F *		0.040	0.050	0.045	0.023	1.86
0.12 M Na2S2O3 + 0.06 M NH4OH + 10 mM CuSO4 − 40 ${\phantom{­}}^{\circ }$C	4	Fines	0.250	0.000	0.250	0.042	3.72
	4F *		0.070	0.060	0.065	0.033	2.91
	4	Coarses	0.120	0.210	0.165	0.036	2.94
	4F *		0.060	0.080	0.070	0.035	2.90
0.12 M Na2S2O3 + 0.10 M NH4OH + 20 mM CuSO4 − 40 ${\phantom{­}}^{\circ }$C	4	Coarses	0.500	0.000	0.500	0.101	8.33
0.12 M Na2S2O3 + 0.15 M NH4OH + 20 mM CuSO4 − 40 ${\phantom{­}}^{\circ }$C	4	Coarses	0.250	0.470	0.360	0.072	6.00

* Samples were collected after 4 h of leaching and then filtered and brought to a volume of 500 mL with distilled water.

.

Upon analyzing the compiled results in Table 9, it is observed that the most effective leaching solution was composed of 0.12 M Na₂S₂O₃ + 0.2 M NH₄OH + 20 mM CuSO₄, particularly noteworthy in experiments conducted at 40 ${\phantom{­}}^{\circ }$C.

Table 10. Estimated remaining masses for metals in fine and coarse materials of PCBs.

Experimental Conditions				Estimated Average Remaining Mass
Concentration of Reagents			Temperature ( ${\phantom{­}}^{\mathbf{\circ }}$C)	Au (mg)
Na2S2O3 (M)	NH4OH (M)	CuSO4 (mM)		Fines	Coarses
0.12	0.20	20	30	8.35	11.01
			40	6.34	8.68
			50	7.29	11.17
		0	40	7.94	8.82
	0.15	20		7.24	12.24
	0.10			8.11	9.20
	0.06	10		7.59	7.43
		0		10.03	10.73

further summarizes the XRF analysis of the final solids after the three leaching steps.

Significantly, gold and copper are present in the chemical analyses of samples after the experimental steps in both fractions (fine and coarse), underscoring that the leachings performed did not achieve maximum efficiency.

Evaluation of the Effect of Sample Granulometry

The coarse samples exhibit a higher residual copper mass, suggesting that fine particles contribute to higher extraction efficiency due to increased surface area. The most effective condition was the one that left the least amount of remaining mass. In this case, the solution containing 0.12 M Na₂S₂O₃, 0.20 M NH₄OH, and 20 mM CuSO₄, showed the best efficiency for extracting the metals of interest. The estimated average remaining mass of gold is higher (12.24 mg) in coarse samples leached with 0.12 M Na₂S₂O₃, 0.15 M NH₄OH, and 20 mM CuSO₄, indicating that larger particles resist leaching more [45]. However, the condition with 0.12 M Na₂S₂O₃ and 0.06 M NH₄OH, without CuSO₄, results in higher amounts of remaining mass in both samples (~10 g).

Evaluation of the Effect of Temperature on Gold Extraction

Quantitative analysis revealed a higher average gold extraction rate in experiments conducted at 40 ${\phantom{­}}^{\circ }$C, reaching 14.8% for the fine fraction and 15.7% for the coarse fraction. Extraction rates at 30 ${\phantom{­}}^{\circ }$C were considerably lower. In comparison to a previous study that obtained 70% gold extraction from mobile phone PCBs in a 4-h leaching at 30 ${\phantom{­}}^{\circ }$C using similar reagents, the results of this research cannot be directly compared. The possible lower extraction efficiency may be attributed to the absence of dissolved oxygen in the reaction system (by bubbling compressed air), a significant methodological difference between the studies.

Evaluation of the Effect of Copper Sulfate and Ammonium Hydroxide Concentration on Gold Extraction

In a sodium thiosulfate solution, the ammonium hydroxide and copper sulfate reagents trigger an electrochemical reaction, favoring gold extraction [25]. The ability of copper ions to catalyze gold dissolution in thiosulfate media is firmly supported by existing research [26,30]. In the presence of copper(II) (Cu${\phantom{­}}^{2+}$) as a catalyst and ammonia (NH${\phantom{­}}_3$) as a stabilizer, gold leaching occurs through a series of redox and complexation reactions. The key reaction is as follows:

$$\mathrm{Au}+4{\mathrm{S}}_2{\mathrm{O}}_3^{2-}+{\mathrm{Cu}(\mathrm{NH}}_3{)}_4^{2+}\to {\mathrm{Au}(\mathrm{S}}_2{\mathrm{O}}_3{)}_2^{3-}+{\mathrm{Cu}(\mathrm{S}}_2{\mathrm{O}}_3{)}_2^{3-}+4{\mathrm{NH}}_3$$

Gold (Au) is oxidized by the Cu${\phantom{­}}^{2+}$-NH${\phantom{­}}_3$-thiosulfate system, forming a soluble gold-thiosulfate complex. Cu${\phantom{­}}^{2+}$ mediates electron transfer from Au to thiosulfate, enabling dissolution. Without Cu${\phantom{­}}^{2+}$, the reaction would be extremely slow because thiosulfate alone is a weak oxidant. The Cu${\phantom{­}}^{2+}$/Cu${\phantom{­}}^{+}$ cycle accelerates the process by facilitating electron transfer. The presence of CuSO₄ as a catalyst proved crucial, with the highest concentration (20 mM) providing the best results, achieving 14.8% and 15.7% gold extraction for fine and coarse fractions, respectively. Experiments without CuSO₄ sought to compensate for this absence by increasing the presence of NH₄OH, as this reagent prevents the formation of elemental sulfur on the surface of gold, making it more available. However, ammonia also stabilizes copper in the cupric form [46]; therefore, according to [47], the loss or excess of ammonia within the system can be considered a limiting factor in gold extraction.

The highest tested concentration of NH₄OH (0.20 M) in leaching solutions showed the best results, with an index of 15.7% for gold extraction, compared to 8.3% (0.10 M) and 6.0% (0.15 M). These results corroborate previous studies in the literature that used similar methodological approaches [25,26,32,47]. Interestingly, the ammonia condition 0.20 M was the most effective; however, the assay with 0.15 M was the least effective considering gold extraction (Table 8). Ammonia in the leaching solution tends to improve metal dissolution rates; however, maintaining an appropriate concentration is crucial to prevent undesirable behaviors such as excessive stabilization of metal complexes, which can significantly decrease the availability of free copper(II), which is necessary for efficient metal dissolution. An improper ammonia ratio can also lead to unwanted precipitation reactions, potentially hindering subsequent recovery processes [46,47].

3.2.5. The Optimal Experimental Condition for Gold Leaching in PCBs

Gold recovery through thiosulfate leaching in the fine and coarse fractions achieved the best results under the condition 0.12 M Na₂S₂O₃ + 0.2 M NH₄OH + 20 mM CuSO₄, with an efficiency of about 15% (equivalent to 12 g Au/t of computer PCBs) and a remaining gold mass of approximately 7.5 mg. This condition presented the highest efficiency in the study, reaching 30% compared to the concentration of acid digestion. The masses of 0.187 mg and 0.201 mg of gold for fine and coarse fractions obtained in the acid digestion solution correspond to 38.8 g Au/t of computer PCBs. Compared to traditional mining, recycling one ton of cell phones can produce up to 340 g of gold [48], in contrast to average contents of 5 g Au/t in underground mines and 1.2 g Au/t in open-pit mines [49]. The largest gold mine in Brazil, Morro do Ouro, extracts approximately 0.4 g Au/t of ore [50].

The use of sodium thiosulfate as a leaching agent for gold extraction from computer PCBs is less common in the literature compared to thiourea [7,23,44,51]. According to the literature, gold extraction rates of 15% [31], 70% [26], and 81% [52] were achieved using leaching solution concentrations close to those used in this study and temperatures between 25 and 30 ${\phantom{­}}^{\circ }$C. However, differences in experimental parameters, such as particle size, the presence of dissolved oxygen, and the use of PCBs from different models and brands, make it challenging to make direct comparisons with the results of this study.

4. Final Considerations

This study evaluated a hydrometallurgical method for recovering valuable metals, particularly copper and gold, from PCBs in WEEE. Initially, PCB samples underwent physical-mechanical pre-treatment and chemical characterization through XRF and ICP-OES to identify metal composition. Subsequently, metal extraction was performed in three leaching stages. The first two stages involved copper extraction using sulfuric acid and hydrogen peroxide, achieving approximately 75% extraction efficiency. In the third stage, gold recovery conditions were optimized using sodium thiosulfate solutions containing copper sulfate and ammonium hydroxide at different concentrations and temperatures. This environmentally friendly hydrometallurgical route was demonstrated to be a viable alternative to cyanide-based processes. However, generating certain by-products, such as sulfur-containing residues, must be appropriately managed to maintain ecological benefits. The main conclusions drawn from this study are as follows:

• Characterization of PCB samples through chemical analyses (XRF and ICP-OES) confirmed significant concentrations of valuable metals, primarily copper and gold, aligning with previous literature.
• Elevated palladium concentrations were detected, likely due to specific components soldered to the PCB base.
• Sodium thiosulfate was used as an alternative lixiviant to cyanide, achieving gold recovery after two preceding copper leaching stages. Although the gold recovery (~15%) is still limited, the process demonstrates the potential for environmentally friendlier practices. Further optimization is required to improve efficiency.
• Optimal conditions for gold recovery were identified as higher copper sulfate and ammonium hydroxide concentrations at 40 ${\phantom{­}}^{\circ }$C.
• The presented hydrometallurgical method proved environmentally safer and economically viable compared to cyanide-based processes, supporting sustainable recycling of WEEE.

Future research should build upon the findings of this study, addressing key limitations and extending its practical applicability. Specific directions to pursue include evaluating process scale-up with large PCB feedstocks under continuous-flow conditions, as previously indicated in the literature [53]; exploring alternative, lower-impact lixiviants and selective separation methods for recovering other valuable metals, such as palladium; investigating valorization strategies for non-metallic residues derived from PCB recycling; performing comprehensive life-cycle assessments (LCA) to thoroughly evaluate the environmental and economic impacts associated with the recycling processes developed; and conducting dedicated studies to quantify the role of residual copper from prior leaching stages in gold extraction, including solution chemistry analysis and kinetic monitoring to clarify its potential catalytic or redox-modifying effects.