# Combination of mineral processing and leaching steps to produce a Pd-concentrate from spent electronic components

Agathe Hubau, Anne-Gwénaëlle Guezennec, Marion Erard, Damien Bourgeois, Solène Touzé

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## To cite this version:

Agathe Hubau, Anne-Gwénaëlle Guezennec, Marion Erard, Damien Bourgeois, Solène Touzé. Com-bination of mineral processing and leaching steps to produce a Pd-concentrate from spent electronic components. Waste Management, 2025, 209, 10.1016/j.wasman.2025.115198. hal-05317291

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Submitted on 16 Oct 2025

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Research Paper

# Combination of mineral processing and leaching steps to produce a Pd-concentrate from spent electronic components

Agathe Hubau<sup>a, *</sup> <sup>□</sup>, Anne-Gwénaëlle Guezennec<sup>a</sup>, Marion Erard<sup>a</sup>, Damien Bourgeois<sup>b, □</sup>, Solène Touzé<sup>a, □</sup>

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## ARTICLE INFO

### Keywords:

- Electronic waste
- Mineral processing
- Leaching
- Recycling
- Palladium
- Integrated circuits

## ABSTRACT

In a context of depletion of resources and tensions on supplies, it is now becoming necessary to develop recycling methods for end-of-life wastes that may contain high metal contents. With this objective, the CAREME project aims to produce new Pd and Au catalysts from electronic waste via short routes without intermediate production of pure metals. In this project, the first step consists in the production of a Pd concentrate from electronic waste in order to increase Pd content together with the removal of less valuable fractions. The waste targeted was spent integrated circuits (IC) and particularly Plastic Leaded Chip Carrier (PLCC). After characterizing the waste, this article presents different stages of mineral processing (grinding, sieving and gravimetric separation) in order to produce a Pd pre-concentrate. Afterwards, a leaching step of the pre-concentrate using Fe(III) in acidic medium (H₂SO₄) was performed to reduce the base metal content. The Pd content was increased by 23.4 between the initial waste and the final concentrate (Pd content of 4 890 mg.kg⁻¹) while the base metal content (Al, Co, Cu, Fe, Mn, Ni, Pb and Zn) was reduced to 6.55 wt%. From this data, a theoretical flowsheet was established. Pd content, enrichment ratio and recovery yield were estimated.

## 1. Introduction

Palladium is an element of the platinum group (along with ruthenium, rhodium, osmium, iridium and platinum). These elements are among the rarest in the earth's crust (Labbé, 2014). Palladium is produced in limited quantity, 293 t in 2025 (Johnson Matthey, 2025). More than 85 % of the metal produced was used for catalysis (particularly in automobile catalytic converters) (Johnson Matthey, 2025). Russia is one of the main mining producers (43 % in 2025) with South Africa (36 % in 2025) (Johnson Matthey, 2025). Until 2016, platinum group metals (PGM) prices were relatively stable. Since 2016, prices have varied considerably, including a 4-fold increase in the price of Pd between 2016 and 2020 before a drop since 2022 to reach around 900 US$/oz at the beginning of 2025 (Johnson Matthey, 2025). High prices encourage recycling. In 2025, recycling contributed around 32 % of market supply, with around 78 % of recycled Pd coming from automobile catalytic converters recycling (Johnson Matthey, 2025). However, in the recent years, the production of secondary Pd from automotive waste declined, mainly because of a decrease of waste collection (Johnson Matthey, 2025).

In this context, the development of new processes for the recovery of Pd from end-of-life wastes, other than converters, may be of interest. In 2012, Pd recovery from electrical and electronic equipment (EEE) reached 13.3 t (Labbé, 2014). The Pd recycling rate from end-of-life EEE is of 5 to 10 % only (Bourgeois et al., 2020) and has to be improved.

In EEE, Pd is employed for the manufacturing of specific components. Large amounts of Pd can be found in multi-layer ceramic capacitors (MLCC; Bourgeois et al., 2020; Morales et al., 2023). Another resource of interest, although less rich in Pd, lies in Plastic Leaded Chip Carrier (PLCC). Waste PLCC can be either collected directly from electronics companies as production scraps, or after sorting of components after waste printed circuit boards reprocessing (Lu et al., 2022). PLCC is composed with an integrated circuit that is attached to a leadframe and encapsulated in a plastic material. It is soldered onto a printed circuit board (PCB) thanks to its leads, curved and placed all around the PLCC. Different types and sizes of PLCC exist. They are commonly used as cost-effective and easy-to-assemble packages for various electronic applications (Nextpcb website, 2024). Fig. 1 gives a schematic diagram of PLCC

<footnote><sup>a</sup> BRGM, F-45060 Orléans, France</footnote>

<footnote><sup>b</sup> ICSM, CEA, CNRS, Université de Montpellier, BP 17171, 30207 Bagnols-sur-Cèze, France</footnote>

<footnote>* Corresponding author.</footnote>

<footnote>E-mail address: a.hubau@brgm.fr (A. Hubau).</footnote>
and the materials they are made of.

There are few data available in the scientific literature on the composition of PLCC waste. However, there are extensive data from electronic suppliers on PLCC manufacturing processes. From a document from a manufacturer, the composition of 18 different circuits was studied and reported in the table of the Fig. 1 (Mouser electronics website, 2014). Even though this may not be exhaustive on the composition of all the PLCC that are on the market, it gives general indication on PLCC composition. Pd is used to externally cover the leadframe, in a Ni, Pd, Au and Ag plating. This plating generally contains fine films of Pd and Au (reported to be of 0.05 to 0.2 µm by Lee et al., 2020) deposited on a film of Ni of more than 5 µm. It may also be used in wires (composed of Cu and/or Au, Pd) that interconnect the circuit with the leads. The total metal content varies from 11 wt% to more than 63 wt % (Fig. 1). Whatever Pd uses (for external plating and/or bonding wire), Pd is in the form of Pd on carbon (pure Pd in zero oxidation state).

This study is part of a project funded by the French research agency (CAREME project – ANR-21-CE07-0057-02). The aim of CAREME is to bridge the gap between growing needs for precious metals and difficulties to valuate e-waste, through the use of precious metal-based catalysts directly prepared from e-waste, by-passing all final isolation and purification steps (ANR, 2023). The scientific purpose of the project is to study the impact of impurities (organic and inorganic) originating in the processing of e-waste on the activity of catalysts. The presence of impurities may affect the performances of the catalysts (Morales et al., 2023) but also increase reagent consumptions during the upcycling chain. Furthermore, when working on a waste with low Pd content, will hamper the strategy previously proposed, relying on the use of the waste leachate to prepare directly supported catalysts (Morales et al., 2023). The study presented in this article is on the upstream part of the process; that is the production of a concentrate of Pd with a minimal presence of impurities before its use for the synthesis of new catalysts. This concentrate meets the specifications for the preparation of catalysts after leaching, i.e. a Pd concentration higher than 1.5 g.kg⁻¹. The chosen waste comes from a batch of used PLCC collected by a recycling company. These PLCC exhibit a low Au content and are thus difficult to valuate in comparison with classical PLCC waste, which are rather rich in Au (see Fig. 1). Typical processing relies on a calcination, which is hindered by the high content in silica, and delivers here an ash of low average content in precious metals. The proposed approach opens the door towards a better valuation of this waste.

First, PLCC wastes were grinded to make metals (Pd in particular) accessible prior to concentration steps. After this grinding step, the goal was to separate particles of different nature with physical processes. Two objectives were pursued: the enrichment of a fraction with an element of interest (i.e. removal of non-valuable particles) together with limiting losses in the eliminated fraction. Yamane et al. (2011) combined magnetic separation with electrostatic separation to concentrate precious metals from e-waste (two PCBs samples from mobile phones and computers). Pd was not analysed in their study, but Ag, Au and Ni contents were determined in all the fractions that were produced.

Results were therefore not convincing. Pd has a high density of 12.0 g.cm⁻³ which makes it a good candidate for gravity separation, in order to separate it from lighter particles (plastics, resins, fiberglass epoxy composite, glass fibres and even lighter metals) (Forsythe, 1954). This study thus focused on the gravity separation only. It is expected that, if, after grinding, Pd is still associated with Au, Ni and Ag (as these metals are associated for external plating and bonding wire), gravity separation would still be efficient because the densities of these metals are between 8.8 and 19.3 g.cm⁻³ (Forsythe, 1954).

After physical concentration, this study explored the selective leaching of base metals (Cu, Ni, Co, Pb, etc) from the pre-concentrate. By removing base metals, precious metals were expected to remain in the solid phase, as they should not be leached. They should be highly concentrated in the residue, which can then be considered as a Pd concentrate. In order to carry out the leaching step, ferric sulphate leaching was chosen. As base metals are mainly in zero-oxidation state in e-waste, leaching of base metals is expected to be mediated by Fe(III), following Eq.(1), which has greater kinetics compared to dioxygen mediated oxidation (Eq.(2)):

$$M^0 + zFe^{3+} \rightarrow M^{2+} + zFe^{2+} \quad (1)$$

$$M^0 + \frac{z}{4}O_2 + zH^+ \rightarrow M^{2+} + \frac{z}{2}H_2O \quad (2)$$

Addition of H₂O₂ and dissolved oxygen (through air injection) was performed in order to maintain the presence of Fe(III), following the reactions Eq.(3) and Eq.(4):

$$2Fe^{2+} + H_2O_2 + 2H^+ \rightarrow 2Fe^{3+} + 2H_2O \quad (3)$$

$$2Fe^{2+} + 0.5O_2 + 2H^+ \rightarrow 2Fe^{3+} + H_2O \quad (4)$$

The use of oxidizing conditions enabled avoiding the presence of a large excess of ferric iron at the beginning of the leaching experiment, as side reactions (such as jarosite precipitation, Eq.(5)) may consume the ferric iron in the leaching conditions (Kaksonen et al., 2014):

$$K^+ + 3Fe^{3+} + 2SO_4^{2-} + 6H_2O \rightarrow KFe_3(SO_4)_2(OH)_6 + 6H^+ \quad (5)$$

Amongst the numerous strategies developed to process waste PCBs, few rely on a physical concentration followed by a mild acidic treatment (Cui and Anderson, 2016; Silvas et al., 2016). The combination of mineral processing and bio-leaching for the valorisation of e-waste was reported in the literature for PCBs (Mäkinen et al., 2015). To our knowledge there is no data on the use of ferric sulphate system to dissolve metals from PLCC. Some studies reported the use of an oxidative sulphate system (using H₂O₂) on pins from central processing units (CPUs). Birloaga (2013) performed CPUs concentration by magnetic separation and recovered base metals with high dissolution yields for Ni, Fe and Sn. Chen et al. (2023) investigated the same leaching reagent with slurry electrolysis for Cu recovery, which reached around 70 %, together with Sn and Ni.

<figure><img src="image_5.png" /><figcaption>Fig. 1. Schematic diagram of PLCC composition (adapted from (Shinko Electric Industries Co. Ltd., 2024) and metal content range (authors data compilation).</figcaption></figure>
The present study focused on the combination of grinding, sieving, gravity separation and leaching with Fe(III) and H₂O₂ in H₂SO₄ medium, to produce a Pd concentrate from chip carriers waste (PLCC waste). A large range of metals were monitored during the experiments. This study reports Pd recovery yield and enrichment ratio at the different level of the process. As PLCC waste are rich in Au and Cu, recovery yields and enrichment ratios for these two metals were also discussed. The contents of other metals are detailed in *Supplementary material*.

## 2. Material and methods

### 2.1. Spent PLCC

A sample of 6 kg of spent PLCC were recovered from a recycling company (Sovamep, France). They were provided by an electronic materials producer. For confidentiality reasons, the electronic components were roughly shredded by the producer before being sent to the recycler.

### 2.2. Mineral processing

Mineral processing (shredding, grinding, sieving and gravity separation) was performed to produce Pd and Au pre-concentrate (Fig. 2).

The sample was first shredded with an industrial 2-axis shredder (slow rotating shredder Mecaroanne) to a particle size around or below 10 mm. The particle size was then further reduced using a laboratory knife mill (Pulverisette 19 from Fritsch) with a bottom sieve mesh size of 750 µm. Intermediary bottom sieves with mesh sizes of 10 mm, 4 mm, 2 mm and 1 mm were used for this step. At each reduction stage, the particles retained on the bottom sieve of the mill were added to the milled sample to ensure representativeness. It caused the presence of particles larger than 750 µm despite the use of a bottom sieve mesh size of 750 µm.

The sample of grinded PLCC was divided in two smaller subsamples by quartering. This operation was carried out with a riffle-divider with openings more than three times the particle size. (i) The first sample was a sample of around 500 g that was used for characterization. This sample was further reduced using a laboratory knife mill (SM2000 from Retsch) with bottom sieve mesh sizes of 500 µm and 250 µm. Riffle-divider was used to sub-sample it in 5 g samples in order to perform chemical characterization. (ii) The second sample weighed 5.5 kg. Particle size classification was performed by wet sieving to 800 µm, 500 µm, 250 µm and 63 µm. Each size fraction was dried at 40 °C before weighing. Riffle-divider was used to sub-sample the fractions in order to perform chemical characterization.

The intermediate and coarsest fractions ('63 µm-250 µm', '250 µm-500 µm', '500 µm-800 µm' and '> 800 µm') were concentrated with a gravity separation step. A shaking table (from Wilfley, with a surface of 1 m²) was used.

The three coarsest fractions were introduced as dry fractions in the shaking table, using a vibrating feeder, while the 63–250 µm fraction was added as a pulp (5.5 %w/v, previously stirred for some hours) using a volumetric pump. For all of them, the feed solid flow was set to 3.5 kg·h⁻¹. The operating parameters were chosen to obtain a visual separation of metals and non-metallic particles. Details are given in Table S1 (Supplementary material). Only two fractions (light and heavy) were recovered for each size fraction. Finally, riffle-divider was used to sub-sample the fractions in order to perform chemical characterization.

### 2.3. Leaching experiments

Leaching was performed on one of the heavy fractions recovered from gravity separation, the heavy fraction obtained from the '250 µm – 500 µm' fraction. The objective was to remove base metals, by dissolving them, in the presence of H₂SO₄ and Fe(III). H₂O₂ was also used in order

<figure><img src="image_6.png" /><figcaption>**Fig. 2.** Schematic diagram of the different treatment steps applied to spent PLCC sample.</figcaption></figure>
to obtain an excess of Fe(III) during the whole experiment. The test was performed in duplicate to ensure the repeatability of the results. Results given in the study are a mean value of the duplicate, and the error bars represent the error obtained between the two tests.

### 2.3.1. Set up

The experiment was performed in laboratory-scale glass reactor with a working capacity of 2 L and jacketed for warm water circulation to maintain a constant operating temperature. The temperature of the circulating water was regulated by a cryothermostat and thermocouples placed in the reactor. The reactor was equipped with four baffles mounted 90° apart and extending down to the base of the vessel to optimise mixing of the pulp. The agitator was a dual impeller system (axial/radial) consisting of a standard 6-blade Rushton turbine in combination with a 3-blade 45° axial flow impeller. The gas supply system was designed to accommodate air which was injected beneath the turbine at the bottom of the reactor via a stainless steel pipe. The impellers and the gas injection pipe were positioned so as to keep to the standard dimensions and thus optimise gas mass transfer and mixing in the reactor. The top of the reactor was connected to a gas cooling system to prevent excessive evaporation.

### 2.3.2. Operating conditions and monitoring

Leaching experiment was carried out at a solid concentration of 5.0 % (w/v). The temperature was set to 35 °C. The air flow rate was maintained at 1330 NmL.min⁻¹ to avoid any oxygen limitation in the system, as oxidation is the main mechanism involved. At the beginning of each test, water was heated in the reactor and pH was adjusted to 2.0 with sulphuric acid (H₂SO₄ 96 %v/v). 100 g of Fe₂(SO₄)₃·xH₂O for analysis (from Carlo Erba) were added. pH was adjusted again to 1.25 with sulphuric acid. 95 g of heavy fraction from the '250 – 500 µm' fraction was then added. The stirring speed was maintained at 650 rpm, except during the first 30 min. During this period, stirring speed was increased up to 900 rpm as the solid was hydrophobic and was hardly suspended in the reactor.

Monitoring was performed every 15 min during the 2.5 first hours, and then twice a day. It included pH, redox potential and metal concentrations measurements. After measuring pH and redox potential, redox potential was manually adjusted to less than 670 mV vs SHE by the addition of H₂O₂ 30 %. pH was manually adjusted to 1.2 ± 0.1 with concentrated sulphuric acid when needed. Tests lasted 4 days. At the end of the experiment, the solid and the liquid phases of the pulp were separated by filtration on glass microfiber filters (from Ahlstrom, with pore size from 0.7 to 2.7 µm); the residue was rinsed with acidified water (pH 1.7, sulphuric acid). Complete characterization of the filtrate and the residue was performed to calculate mass balances. As they were consistent, metal dissolution yields were calculated as the ratio of the quantity of remaining metals in the residue versus the initial quantity of metals in the fraction that was leached.

## 2.4. Solid and liquids characterization

During leaching experiment, metal concentrations were measured with a 4210 MP-AES (microwave plasma atomic emission spectroscopy) from Agilent Technologies.

To determine metal concentrations in solid samples, a 5 g aliquot was leached at 200 °C for 2 h in a Kjeldatherm-Gerhardt digestion system with 45 mL of aqua regia prepared by mixing 11.2 mL of 67–69 % HNO₃ (trace metal grade, Fisher Chemical) and 33.6 mL of 32 % HCl (certified for analysis, Fisher Chemical). After filtration, the leachate was analysed using inductive coupled plasma-optical emission spectrometry (ICP-OES, Horiba Jobin Yvon Ultima 2) and inductive coupled plasma-mass spectrometry (ICP-MS) Thermo Scientific X Series for Ag, Al, Au, Co, Cr, Cu, Fe, Mn, Ni, Pb, Pd, Sb, Sn and Zn. The residue was rinsed with water and dried. The mass of the residue was determined in order to measure the quantity of materials that could not be dissolved with aqua regia.

The mass ratio of residue versus the initial mass was reported in this study as '%undissolved with aqua regia'. This ratio was often compared to the sum of all the metal contents (referred as '%metals') determined with ICP-OES and ICP-MS analysis after aqua regia digestion.

## 3. Results

Fourteen elements were analysed in this study. To clarify the reading, only the results concerning Cu, Au and Pd are reported in the following paragraphs as they are the most valuable metals present in the waste. Results for other metals are given in Supplementary Material and a brief interpretation is detailed in the last paragraph of this section.

### 3.1. Spent grinded PLCC characterization

Three samples of 5 g of grinded PLCC waste were analysed. Table 1 gives the mean metal content values obtained for other metals. The major element was Cu, with a content that reached 19.3 wt% (standard deviation of 0.7 wt%). Pd and Au contents reached 197 and 224 mg.kg⁻¹ respectively (standard deviation of 8 mg.kg⁻¹ for both).

The total proportion of metal (%metal) represented 21.4 wt% of the total weight of the waste, while the %undissolved with aqua regia (i.e. the mass of materials as plastics, carbon black and silica that were undissolved with aqua regia) reached 76.5 wt%. The difference between the total proportion of metal (21.4 wt%) and the proportion of digested material (23.5 wt%) may represent Si content, which was not quantified in our study. All these results are consistent with the generic data on PLCC composition reported in Fig. 1.

### 3.2. Size fractions characterization

During mineral processing steps, it is required to have samples with particles of similar size so as not to distort the separation results. Wet sieving was thus performed to produce different size fractions to be used during gravity separation. Fig. S1 in Supplementary material gives the particle size distribution. The d₈₀ (i.e. 80 wt% passing size) of the particle size distribution was around 900 µm.

Table 2 shows the concentration of Au, Cu and Pd, as well as the overall content in metals for each size fractions. The concentrations in the original sample were calculated according to the following equation:

$$x_{\text{sample}} = \sum_{i=1}^{5} w_{\text{fraction i}} \times x_{\text{fraction i}} \quad (6)$$

where $x_{\text{sample}}$, $w_{\text{fraction i}}$ and $x_{\text{fraction i}}$ denote the metal content in the original sample, the mass fraction of the size fraction i and the metal content in the size fraction i, respectively.

<table><caption>**Table 1**
Metal content (in mg.kg⁻¹) in the initial waste.</caption><thead><tr><th></th><th>Content</th></tr></thead><tbody><tr><td>Ag</td><td>265</td></tr><tr><td>Al</td><td>724</td></tr><tr><td>Au</td><td>224</td></tr><tr><td>Co</td><td>20.7</td></tr><tr><td>Cr</td><td>240</td></tr><tr><td>Cu</td><td>193 000</td></tr><tr><td>Fe</td><td>7 520</td></tr><tr><td>M</td><td>45.0</td></tr><tr><td>Ni</td><td>4 510</td></tr><tr><td>Pb</td><td>71.6</td></tr><tr><td>Pd</td><td>197</td></tr><tr><td>Sb</td><td>272</td></tr><tr><td>Sn</td><td>6 010</td></tr><tr><td>Zn</td><td>246</td></tr></tbody></table>
<table><caption>**Table 2**
Metal content (in mg.kg⁻¹ and wt%) in the different size fractions obtained from wet sieving.</caption><thead><tr><th></th><th>Unit</th><th>wt%</th><th>Au</th><th>Cu</th><th>Pd</th><th>Metal</th></tr><tr><th></th><th></th><th></th><th>mg.kg⁻¹</th><th>wt%</th><th>mg.kg⁻¹</th><th>wt%</th></tr></thead><tbody><tr><td rowspan="5">Size fractions</td><td>&gt; 800 µm</td><td>23.9</td><td>250</td><td>31.3</td><td>146</td><td>32.7</td></tr><tr><td>500–800 µm</td><td>23.7</td><td>254</td><td>30.8</td><td>219</td><td>33.0</td></tr><tr><td>250–500 µm</td><td>15.2</td><td>251</td><td>41.7</td><td>337</td><td>45.5</td></tr><tr><td>63–250 µm</td><td>12.7</td><td>299</td><td>7.87</td><td>100</td><td>9.2</td></tr><tr><td>&lt; 63 µm</td><td>24.6</td><td>187</td><td>3.73</td><td>122</td><td>6.2</td></tr><tr><td>Original sample</td><td></td><td>—</td><td>242</td><td>23.0</td><td>181</td><td>25.2</td></tr></tbody></table>

Analysed contents (reported in Section 3.1 in Table 1) and calculated contents (reported as ‘Original’ in Table 2) were compared. For Au and Pd, the difference was limited to less than 10 %. This indicates high accuracy of analysis for these metals. However, the difference was higher for Cu. This is probably related to the limited mass of sample that was analysed for each size fraction (5 g). This mass might be too low for particles as heterogeneous as e-waste, as previously demonstrated by Touzé et al. (2020).

Au was equally distributed in the coarsest size fractions, with a slightly higher content in the ‘63 – 250 µm’ fraction and a slightly lower content in the finest particles. Cu was mainly concentrated in the coarsest particles (> 500 µm), while Pd content was highest in the intermediate fraction (250 – 500 µm). For Au and Pd, the enrichment of one fraction versus the others (i.e. the ratio between the highest metal content and the lowest) was not pronounced (< 4). However, a ratio of approximately 10 was observed for Cu between the particles > 800 µm and the particles < 63 µm.

Finally, the total proportion of metals was high in the two coarsest fractions (around 33 wt%), reached its maximum in the intermediate fraction ‘250 – 500 µm’ (45.5 wt%) and was very low for finest fraction (6.2 wt%). This seems highly correlated with Cu content in the fraction. It was also consistent with the proportion of undissolved materials during aqua regia digestion (data not shown).

As Au, Cu and Pd were distributed over all the size fractions, it is required to consider all of them in subsequent unit operations in order to limit precious metal losses.

### 3.3. Production of a pre-concentrate with gravity separation

Gravity separation was performed with a shaking table on four

fractions (63–250 µm, 250–500 µm, 500–800 µm and > 800 µm) in order to concentrate Pd. The objective was to remove part of undesirable materials, in particular the plastics, carbon black and silica. The separation principle is based on interstitial percolation through a bed of particles. Two phenomena occur in parallel: the sedimentation of particles and the friction forces between the plate and the particles. The densest particles will migrate towards the surface of the plate while the lighter ones will remain in the upper layer of the water layer. The plate, with adjustable inclination, is subjected to asymmetrical longitudinal shocks that allow, on the one hand, stratification, and, on the other hand, the progression and evacuation of stratified particles between the riffles (plastic bars). The shaking table is not a suitable equipment for particle sizes below 63 µm. For this fraction, gravimetric separation is usually done using a centrifugal gravimetric separator (such as Falcon or Nelson) or a multi gravity separator (MGS). In this study, it was not possible to perform such tests.

The values obtained for Cu, Au and Pd for each size fraction are gathered in Table 3. As in the previous paragraph, the original sample refers to the concentrations in each mass fraction, calculated from the concentrations in each light and heavy fractions with Eq.(6). The data for other metals are given in Supplementary Material (Table S2).

Light fraction mass decreased (from 68 wt% to 36 wt%) with decreasing particle size (particles coarser than 800 µm to particles between 63 and 250 µm). Simultaneously, heavy fraction mass increased with decreasing particle size. It was previously shown that the quantity of metals is decreasing with decreasing particle size (Table 2). These two observations are contradictory, since the presence of a larger quantity of metals in the largest fraction should increase the heavy fraction mass in these fractions compared to the finest ones. This discrepancy may be explained by non-optimal operating conditions during the gravity separation of the finest fractions and/or a problem of wettability of the material. It could also be related to the presence of mixed particles in the coarsest fractions, i.e. particles in which metals are embedded in plastics or present on their surface. These mixed particles may exhibit the same behaviour than plastics, lowering the recovery of metals in the heavy fraction.

The quantity of metals analysed in each of the light fraction (% metal) decreased with decreasing particle size. On the contrary, heavy fractions are highly concentrated in metals. Total metal content increased when particle size decreased (the 250 – 500 µm fraction was even only composed with metals), except for the finest fraction. For this latter, the total metal content reached 43.5 wt%.

Regarding precious metals, the distribution of Au between light and heavy fractions was highly influenced by the particle size. In coarsest particles, Au was more concentrated in the light fraction compared to the heavy one. For the ‘500 – 800 µm’ fraction, opposite distribution is observed. When particle size further decreases, distribution of Au continues to increase in the heavy fraction.

<table><caption>**Table 3**
Mass fraction (in wt%), Au, Cu, Pd (in mg.kg⁻¹) and total metal contents (in wt%) in the different fractions obtained from gravity separation and associated recovery yields (in %).</caption><thead><tr><th rowspan="2"></th><th rowspan="2">Unit</th><th rowspan="2">wt%</th><th>Content</th><th rowspan="2">wt%</th><th rowspan="2">Pd</th><th rowspan="2">Metal</th><th colspan="3">Recovery Yield</th><th rowspan="2">Pd</th><th rowspan="2">Metal</th></tr><tr><th>Au</th><th>Cu</th><th>Au</th><th>Cu</th><th>Pd</th></tr></thead><tbody><tr><td rowspan="3">&gt; 800 µm</td><td>Light</td><td>68</td><td>249</td><td>7.78</td><td>70.6</td><td>8.20</td><td>75 %</td><td>20 %</td><td>34 %</td><td>20 %</td></tr><tr><td>Heavy</td><td>32</td><td>171</td><td>66.3</td><td>291</td><td>69.2</td><td>25 %</td><td>80 %</td><td>66 %</td><td>80 %</td></tr><tr><td>Original</td><td>—</td><td>224</td><td>26.7</td><td>142</td><td>27.9</td><td>—</td><td>—</td><td>—</td><td>—</td></tr><tr><td rowspan="3">500–800 µm</td><td>Light</td><td>73</td><td>249</td><td>7.20</td><td>55.0</td><td>7.64</td><td>69 %</td><td>18 %</td><td>20 %</td><td>18 %</td></tr><tr><td>Heavy</td><td>27</td><td>294</td><td>84.7</td><td>595</td><td>90.3</td><td>31 %</td><td>82 %</td><td>80 %</td><td>82 %</td></tr><tr><td>Original</td><td>—</td><td>261</td><td>28.3</td><td>202</td><td>30.2</td><td>—</td><td>—</td><td>—</td><td>—</td></tr><tr><td rowspan="3">250–500 µm</td><td>Light</td><td>49</td><td>162</td><td>3.52</td><td>35.4</td><td>3.86</td><td>29 %</td><td>4 %</td><td>4 %</td><td>4 %</td></tr><tr><td>Heavy</td><td>51</td><td>383</td><td>92.6</td><td>805</td><td>100</td><td>71 %</td><td>96 %</td><td>96 %</td><td>96 %</td></tr><tr><td>Original</td><td>—</td><td>275</td><td>49.1</td><td>429</td><td>53.3</td><td>—</td><td>—</td><td>—</td><td>—</td></tr><tr><td rowspan="3">63–250 µm</td><td>Light</td><td>36</td><td>200</td><td>1.50</td><td>43.0</td><td>2.13</td><td>14 %</td><td>2 %</td><td>6 %</td><td>3 %</td></tr><tr><td>Heavy</td><td>64</td><td>694</td><td>40.8</td><td>374</td><td>43.5</td><td>86 %</td><td>98 %</td><td>94 %</td><td>97 %</td></tr><tr><td>Original</td><td>—</td><td>518</td><td>26.8</td><td>257</td><td>28.8</td><td>—</td><td>—</td><td>—</td><td>—</td></tr></tbody></table>
In the light fractions, Pd content decreased when the particle size decreased, to reach a minimum value for the '250 – 500 µm' fraction. It slightly increased for smaller particle size. On the contrary, in the heavy fractions, Pd content increased when the particle size decreased, to reach the highest value for the '250 – 500 µm' fraction (805 mg.kg⁻¹). It decreased for smaller particle size. Whatever the particle size, Pd was highly concentrated in the heavy fractions.

Finally, Cu behaved similarly to the Pd, with a decreasing content with decreasing particle size in the light fractions, and an increasing content with decreasing particle size in the heavy fractions.

Analysed contents (reported in Table 2) and calculated contents (reported as 'Original' in Table 3) were compared. As in Section 3.2, the difference was mainly limited to less than 10 %, indicating high accuracy of analysis. However, for some values, as Au content in the '63 – 250 µm' fraction, higher difference was obtained (73 %), correlated to the intrinsic heterogeneity of the sample.

To conclude, the gravity separation demonstrated high efficiency for the size fractions, except for the ' > 800 µm' fraction. The majority of metals was recovered in the heavy fractions.

### 3.4. Production of a concentrate with leaching

In order to further concentrate the precious metals, a leaching step was performed to remove base metals. The proof of concept focused on the heavy fraction from the '250 – 500 µm' fraction, as it was the fraction with the highest Pd content (805 mg.kg⁻¹) and the highest metal content (around 96 wt% of metal).

The reagent was chosen in order to have significant selectivity between base metals and precious metals. There is plenty of literature on hydrometallurgical studies on e-waste (Kaya, 2016). Most of them (i) aims at recovering precious metals due to their economic value and (ii) focuses on PCBs waste. A high variety of leaching agent and conditions could be used to perform the leaching. However, lots of them are expensive, highly corrosive and not so selective. Sulphate- and Fe(III)-based processes proved to be industrially viable for the recovery of Cu from minerals (Dreisinger, 2006). It has the advantage to be performed in atmospheric conditions (low pressure and temperature). Yazici and Deveci (2014) studied the use of ferric sulphate leaching for Cu extraction from PCBs. They obtained high dissolution yields for Cu in some hours. However, they noticed the partial dissolution of precious metals (Pd and Ag). In their experiments, the acidity of the leaching solution was very high (pH < 0.5). The study from Istrate et al. (2018) also demonstrated that Pd and Ag were partially dissolved, but not Au. In order to limit undesirable precious metals dissolution, mild conditions were chosen: pH was set to 1.2 and temperature to 35 °C. In such conditions, Hubau et al. (2020) demonstrated that Eq.(1) was faster than Eq.(2) for base metals dissolution from PCBs. Ferric iron was regenerated through H₂O₂ addition to enhance Eq.(1). Even though the redox potential was not constant during the experiment, an excess of Fe(III) was obtained by manual addition of H₂O₂. Fig. S2 in Supplementary material introduces the Cu dissolution yield over time, as well as the Fe (III) concentration. It is not necessary to maintain the leaching step during 4 days, as the Cu dissolution and Fe(III) consumption did not change after 2 days.

As seen in Table 4, Cu dissolution yield reached 99.9 %, while Pd and Au dissolution yields were very limited, reaching less than 0.7 %: Pd and Au concentrations in the leachate were 0.2 mg.L⁻¹ and 0.4 µg.L⁻¹ respectively. The residual fraction, considered as the experimental concentrate, contains 4 890 mg.kg⁻¹ of Pd and 2 354 mg.kg⁻¹ of Au. The

<table><caption>**Table 4**
Dissolution yields and metal contents in the leaching residue.</caption><thead><tr><th></th><th>Au</th><th>Cu</th><th>Pd</th></tr></thead><tbody><tr><td>Dissolution yield</td><td>0.003 %</td><td>99.9 %</td><td>0.7 %</td></tr><tr><td>Metal content</td><td>2 354 mg.kg<sup>-1</sup></td><td>0.277 wt%</td><td>4 890 mg.kg<sup>-1</sup></td></tr></tbody></table>

%metal reached 37.7 wt%, with 30.4 wt% being Sn (as described in Supplementary material Table S2, Sn probably precipitated during the leaching) and only 0.28 wt% being Cu.

The leaching step was thus efficient to remove Cu, which initially represents 92.6 wt% of the fraction (Table 3). This enabled to subsequently increase precious metals content in the residue. To evaluate the efficiency of this flowsheet, the enrichment ratio which represents the ratio between the metal content in the concentrate and the metal content in the initial waste, was calculated. It reached 24.9 and 10.5 for Pd and Au respectively.

### Base metals behaviour

Fourteen elements were followed during the process. Metal contents are given in Supplementary Material Table S2. During sieving, three distinct metal behaviours were noticed. Pb was mainly concentrated in the coarsest particles (> 500 µm). Ag, Ni, Sn and Zn were particularly concentrated in the intermediate fraction (250 – 500 µm). Others base metals (Al, Co, Cr, Fe, Mn, Sb) were concentrated in the finest fraction (< 63 µm). Most metals were then recovered in the heavy fractions of the gravity process. Ag, Co, Fe, Mn, Ni, Pb, Sn and Zn were particularly distributed within the heavy fractions, with high enrichment ratios. As an example, enrichment reached more than 29 for Ni in the 250 – 500 µm fraction. This is consistent with the high density of metals compared to the other materials. Only Al and Sb were mainly distributed within the light fractions. Cr was equally distributed between light and heavy fractions. Finally, as for Cu, high dissolution yields (> 80 %) were obtained for most of the base metals (Al, Co, Fe, Mn, Pb, V and Zn) during the leaching step (see Fig. S3 in Supplementary material). Ni, Sn and W dissolution yields were lower (58 %, 9 % and 15 % respectively). Concerning precious metals, only 10 % of Pt was leached, but 99 % of Ag. Finally, the dissolution was limited (less than 2.0 %) for most of the rare earth elements (Ce, Dy, Er, Eu, Gd, Ho, La, Lu, Nd, Pr, Sm, Tb, Tm, Y and Yb). The ferric sulphate leaching proved its efficiency for base metals removal.

### 4. Discussion

In this study, a concentrate of precious metals was produced by grinding, sieving, gravity separation and leaching. The study demonstrated high efficiency of the gravity concentration of precious metals, together with high removal of base metals during ferric sulphate leaching. The enrichment ratio thus reached around 25 between Pd content in the concentrate and in the initial waste.

PLCC waste were, to our knowledge, not described in the literature. Their characterization and the comparison with the literature showed that their composition has some similarity with the one of spent PCBs. PCBs composition was thus used as a reference in our study in the absence of literature on PLCC waste. This work on PLCC gives insight into the possibility offered by physical processing to increase the content in precious metals in the waste before hydrometallurgical processing. Waste PLCCs were targeted in this study because they currently constitute an existing waste stream that is recovered at industrial level from manufacturer production scraps. Another source of spent PLCCs could, in the future, come from post-consumer waste: there are current research studies conducted on the desoldering of electronic components contained on spent printed circuit boards and their sorting by optical methods, in order to promote the massification of certain specific metals (Charpentier et al., 2023; van Beek et al., 2024; Monneron-Enaud et al., 2025). Thus, both flows (production scraps and post-consumer wastes) could provide PLCCs in the future.

The first unit operation that was performed consisted in grinding, to release the elements of interest. In the literature, there are, to our knowledge, no study regarding the recovery of Pd from electronic components as a function of the particle size. However, due to PLCC manufacturing, it seems impossible to grind enough to release pure particles of Pd, as they are used as very fine coatings of less than 1 µm
thickness. Furthermore, in the context of printed circuit boards (PCBs), it is often reported that the grinding step generates precious metals losses (Chancerel et al., 2009; Kaya, 2016). It is therefore necessary to find a compromise between limiting the grinding step and ensuring the accessibility of Pd (removal of the encapsulation). In our study, the grinding was limited, as the final $d_{80}$ was estimated around 900 µm in order to limit precious metals losses. However, 24 % of the particles were finer than 63 µm, even though the grinding was performed with a grid of 750 µm. This high quantity of fines particles was already observed during the shredding of other e-waste (such as PCBs, Hubau et al., 2019).

Grinding is a major step of the process, as it determines the recovery of metals in the different size fractions. As described by Abbadi et al. (2024), the difference of metal distribution within the waste, combined with different behaviour during shredding, may result in a preferential enrichment of one size fraction versus others. In this study, Au and Pd were mainly contained in intermediate fractions ('63–250 µm' and '250–500 µm' fractions respectively). However, the enrichment ratio versus other size fractions (i.e. ratio of metal content in enriched size fraction versus metal content in depleted size fraction) was limited (< 4), which does not enable to rely only on grinding to concentrate the metals. This is consistent with a previous study from Otsuki et al., 2020 that reported an Au enrichment ratio of 2.2 in the '250–500 µm' fraction in spent grinded PCBs. After grinding and sieving, Cu, as most of the base metals, was mainly distributed in coarse particles. This is consistent with previous studies that relate the difficulty of grinding Cu in e-waste, thus remaining in coarsest particles (Touzé et al., 2024; Otsuki et al., 2020). It thus seems that PLCC have similar grinding behaviour to PCBs. The % metal in the different fractions evolves significantly with the particle size: from 45.4 wt% in the '250–500 µm' fraction, to 9.2 % in the '63–250 µm' fraction and 6.2 % in the '< 63 µm' fraction. These fractions are therefore mainly composed of organic matter (plastics) and ceramics. Even if the last grinding step was performed with a 750 µm grid, the high proportion of these materials in the < 500 µm fractions demonstrates that they tend to be over-ground. It might be because of these materials that the proportion of '< 63 µm' fraction is so high (24 %).

The efficiency of gravity separation was previously reported as an efficient method for grinded PCBs using sink-float separation or wet jigging (Zhang and Forssberg, 1997; 1999); Sarvar et al. (2015)). Our study demonstrated similar results on PLCC waste, using shaking table. High metal enrichment was obtained in the heavy fractions. Shaking table is efficient and it is easy to perform the operation. Whatever the particle size, Pd was highly concentrated in the heavy fractions (Fig. 3).

When the size of the particle was reduced, the loss of metals within the light fraction was reduced. This was probably linked with a better liberation of metals in finer particles, the liberation being the release of metal from other materials. When metals are free, they are well

separated and recovered in the heavy fraction. When metals are still bonded, trapped or coated with other materials, they may follow the behaviour of these materials during gravity separation, thus being recovered in both heavy and light fractions. As an example, Au has a very high density (19.3 g.cm⁻³) compared to other materials (as Cu 8.9 g.cm⁻³, ceramics < 6.0 g.cm⁻³ and plastics < 2.0 g.cm⁻³) (Forsythe, 1954). Then, if Au is not recovered only in the heavy fraction, the metal is probably trapped, bonded or coated with other materials. Then, the liberation size can be deduced from Fig. 3: the liberation size of Pd and Cu was between 250 and 500 µm, as further decrease of particle size does not increase the recovery yield of these metals. By contrast, Au liberation size was < 63 µm, as its recovery yield still increased with decreasing particle size.

These observations are consistent with multiple studies that revealed that metal liberation is difficult to obtain for e-waste (in particular, spent PCBs, as detailed by Abbadi et al., 2024). The particle size required to reach a full metal liberation from e-waste is still discussed in the literature. The liberation size was estimated to 500 µm by Kaya (2016), to 75 µm by Ogunniyi et al. (2009) by scanning electron microscopy observation of multiple materials and to 150 µm by Vidyadhar and Das (2012) from the microscopic count of interlocked particles. In our study, the liberation of Pd and Cu was reached at particle size larger than the one of Au. The liberation size is different for each metal. It probably explains why there is still no consensus in the scientific literature around the liberation size for e-waste. This parameter is highly variable according to the metal that is targeted. In our study, the sample should be ground to 500 µm to obtain an optimal separation of Cu and Pd. Since grinding is a difficult operation that generates fine particles, it is necessary to find a compromise between separation efficiency and grinding implementation.

During leaching, high dissolution yields (> 80 %) were obtained for most of the base metals, while precious metals (except Ag) remained in the solid residue. The presence of a leaching step considerably decreased the base metals content in the concentrate, thus improving the enrichment ratio of Pd and Au. Thus, ferric sulphate leaching demonstrated high efficiency for the concentration of precious metals in the residue. Base metals could be further recovered from the leachate through different processes (electrowinning, precipitation, cementation, liquid-liquid extraction, etc) (Hubau et al., 2024). Similarly, Ag could be recovered from the liquid phase through precipitation as AgCl. The use of H₂O₂ to maintain oxidative conditions (ferrous iron oxidation into ferric iron) could be replaced by bio-oxidation. Acidophilic bioleaching, i.e. the use of an acidic leaching step catalyzed by microorganisms, may be an alternative to chemical leaching. Acidophilic bioleaching is currently used on an industrial scale for the production of Au from refractory ores. The concept is based on the dissolution of refractory minerals (pyrite and arsenopyrite) to concentrate Au in the residue. Acidophilic bioleaching was previously studied for e-waste such as spent Printed Circuit Boards (Hubau et al., 2020). It demonstrated that the presence of ferric iron and its regeneration by micro-organisms enabled a high dissolution of base metals without any dissolution of precious metals (Anaya-Garzon et al., 2021). Bioleaching has the advantages of having a low consumption of reagents (only N, P, K as nutrients, together with CO₂ as the source of carbon and O₂).

Experimentally, performing the whole process enabled to reach high Pd and Au enrichment ratios (25 and 11 respectively) on a specific fraction (the heavy fraction resulting for processing of the '250–500 µm' fraction). As individual unit operations demonstrate high recovery yields, it is expected that the treatment of all the size fractions could lead to a very high global recovery yield. A theoretical flowsheet, based on the extrapolation of results of all the unit operations to all the fractions, was thus proposed. The theoretical recovery yields and enrichment ratios were estimated. The scenario considered four hypothesis based on the experimental study:

<figure><img src="image_7.png" /><figcaption>**Fig. 3.** Recovery yield in the heavy fraction from the shaking table experiment, as a function of the particle size.</figcaption></figure>
1) A new shredding step would be included in order to have all the particles finer than 800 µm. For the calculations, the mass fraction of the ‘> 800 µm’ was set to 0. The distribution between the other size fractions was kept identical, as if the shredding of the ‘> 800 µm’ results in same distribution than the initial sample, with no modification of the size fractions composition. The mass balance was performed to ensure that this hypothesis was realistic.

2) The gravity separation would be applied to all the fractions, including the ‘< 63 µm’ fraction, in order to limit the loss of Pd that is contained in this fraction. Such separation might be performed with tools such as centrifuge gravimetric separators (Falcon, Knelson or MGS equipment) (Dinç et al., 2022). The metal recovery yields in the heavy and light fractions of the ‘<63 µm’ were estimated equal to the one of the ‘63 – 250 µm’ fraction as a first approach. The global distribution of the mass was estimated so that the %metal of the heavy fraction was similar to the one of the ‘63 – 250 µm’ fraction.

3) A second gravity separation step would be applied on the heavy fractions from the ‘<63 µm’ and ‘63—250 µm’ fractions, to increase their recovery yield and enrichment ratios. The separation is often twice performed in such processes to improve the performances. The yields and fractions contents from the second gravity separation were calculated with the same hypotheses as for hypothesis 2.

4) The leaching step would be applied to all the heavy fractions, to recover precious metals while removing base metals. The leaching step could be performed after the mixing of all the heavy fractions. For the calculations, metal contents in the leaching residues were estimated by hypothesizing that the leaching yields were similar whatever the particle size. It is well known that the particle size affects the leaching kinetics, but only the leaching yield was considered in this study. Estimated compositions of residues after leaching are given in Supplementary material (Table S3).

The concentrate would then result from the mixing of all the leached fractions. The resulting flowsheet, together with the estimated metal content and recovery yield of each fraction, is detailed in Fig. 4. In total, 87.5 % of Pd would be recovered by using this flowsheet. The resulting concentrate, with a Pd concentration of 4,600 mg·kg⁻¹, is significantly more concentrated than concentrates from primary production e.g., in the Bushveld complex, where Pd concentration rarely exceed 100 mg·kg⁻¹ (Gibson et al., 2023). Furthermore, this content is compatible with the production of new catalysts (> 1.5 g·kg⁻¹), as demonstrated by (Morales et al., 2023). The total mass would drastically be reduced during the process, as the mass of the concentrate represents only 3.7 % of the initial mass of the waste. The enrichment factor for Pd is estimated to be 23.4, close to that observed with the ‘250—500 µm’ fraction. Around 20 wt% of the concentrate is expected to be composed of metals. Sn should represent 70 % of the mass of these metals. In the context of the CAREME project, the need for a sufficient Pd concentration (ca. 1.5 g·kg⁻¹) in the waste can be easily reached using this flowsheet.

The batch of PLCC processed in this study has a low Au content compared to mean PLCC, and our results highlight the difficulty to recover quantitatively Au. The loss of metals from waste PCBs during physical processes was documented in the literature (as in Marra et al., 2019). This loss is mainly related to the difficulty of liberating the metal from other materials (here lighter materials such as plastics or ceramics) which prevents high efficiency from physical sorting processes. During primary processing of refractory Au ores, the economic cut-off for Au recovery during pre-concentration steps (mainly flotation) was estimated around 85 % (Fraser et al., 1991). In our study, Au recovery yield was only 59 % (enrichment factor 15.9), demonstrating the need to perform further studies dedicated to this metal.

The composition of the leachate was estimated in the case of a ratio solid-liquid of 1:10 (Fig. 4). Cu concentration reaches 78.6 g·L⁻¹. Various methods (precipitation, cementation, electrowinning, ...) could be used to recover Cu (Hubau et al., 2024). In industrial processes, solvent extraction followed by electrowinning are so far the most

common technologies for Cu processing from sulfuric acid matrices (Domic, 2007; Tunsu and Retegan, 2016). Solvent extraction concentrates Cu in the leachate up to 30–40 g·L⁻¹ Cu by SX. In our study, with such high concentration, direct electrowinning may be of interest to recover Cu. However, the presence of Fe could be detrimental to Cu recovery. Fe concentration in the leachate was estimated to 2.6 g·L⁻¹. Its removal (through precipitation with limestone or as jarosite), together with Al, is a prerequisite to any further metal recovery steps. The estimation of Fe concentration highlights that the Fe provided by the waste could be the only source of Fe in the leaching step, with no need of additional source, as already demonstrated in previous leaching study on e-waste (Hubau et al., 2020). Ag recovery could be performed priori to Cu recovery through NaCl addition to form AgCl, as proposed by Behnamfard et al. (2013) for the treatment of PCBs leachate. Finally, Ni recovery could be performed through solvent extraction, as often performed in Ni production industry (Sole et al., 2016).

Overall, this study opens new perspectives for the implementation of simple mechanical processes for the valorisation of e-waste containing mostly Pd as precious metals.

## 5. Conclusions

Due to the current demand in Pd, the development of new processes for its recovery from end-of-life wastes is of interest. Among them, waste from electronics industry are a potential resource due to their high Pd and Au content. In this study, a process based on the grinding, the gravity separation and acidic oxidative leaching of waste PLCC was established in order to concentrate the precious metals. It demonstrated that grinding was a major step of the process, as it determined the recovery of metals in the different size fractions. The difference of metal distribution within the waste, combined with different behaviour during shredding, resulted in a preferential enrichment of some size fractions. The combination of the sieving with the gravity separation enabled to determine the liberation size of metals. The liberation size of Au was < 63 µm, while the liberation size for Pd and Cu was around 500 µm. Shaking table was an efficient and easy to perform method. High metal enrichment was obtained in the heavy fractions, which were particularly concentrated in Pd. During leaching, high dissolution yields (> 80 %) were obtained for most of the base metals, while precious metals (except Ag) remained in the solid residue. The presence of a leaching step considerably decreased the base metals content in the concentrate, thus improving the enrichment ratio of Pd and Au. Performing the whole process enabled to reach high Pd and Au enrichment ratios (23.4 and 15.9 respectively). The anticipated recovery yields are 88 % and 59 % for Pd and Au respectively. Several options were identified to optimize the recovery yields. By improving the grinding in order to remove the ‘>800 µm’ fraction, combined with the gravity separation of the < 63 µm fraction, the repetition of gravity separation for the two finest fractions and the leaching of all the resulting heavy fractions. This opens new perspectives for the implementation of simple mechanical processes for the valorisation of e-waste.

## Funding Source

Authors want to thank Sovamep company (in particular Valentin Pierre) for providing the sample of PLCC waste. The study was funded by ANR agency (French Research Agency) under the grant agreement ANR-21-CE07-0057.

## CRediT authorship contribution statement

**Agathe Hubau:** Writing – original draft, Visualization, Validation, Methodology, Investigation.
**Anne-Gwénaëlle Guezennec:** Writing – review & editing, Conceptualization.
**Marion Erard:** Writing – review & editing, Investigation.
**Damien Bourgeois:** Writing – review & editing, Project administration, Funding acquisition, Conceptualization.
**Solène**
<figure><img src="image_8.png" /></figure>

<figure><img src="image_9.png" /><figcaption>Fig. 4. The theoretical flowsheet considered in this study, together with the estimated metal content (in wt% or mg.kg⁻¹) and recovery yields (%).</figcaption></figure>
**Touzé:** Writing – original draft, Visualization, Supervision, Project administration, Investigation, Funding acquisition, Conceptualization.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Appendix A. Supplementary data

Supplementary data to this article can be found online at https://doi.org/10.1016/j.wasman.2025.115198.

Data availability

Data will be made available on request.

References

Abbadi, A., Rácz, Á., Bokányi, L., 2024. Exploring the commutation process of waste printed circuit boards in recycling: a review. J. Mater. Cycles Waste Manage. 26, 1326-1348. https://doi.org/10.1007/s10163-024-01945-3.

Anaya-Garzon, J., Hubau, A., Guezennec, A.G., Joulian, C., 2021. Optimisation d'un réacteur de biolivixation de déchets de cartes électroniques. Rapport final. BRGM/ RP-70690-FR.

ANR, 2023. Project n°ANR-21-CE07-0057. https://anr.fr/Projet-ANR-21-CE07-0057 Accessed on 13 December 2023.

Behnamfard, A., Salarirad, M.M., Veglio, F., 2013. Process development for recovery of copper and precious metals from waste printed circuit boards with emphasis on palladium and gold leaching and precipitation. Waste Manag 33, 2354–2363. https://doi.org/10.1016/j.wasman.2013.07.017.

Birloaga, I., 2013. Recovery of base metals from waste CPU by hydrometallurgical processes. Metalurgia International, XVIII 2, 69.

Bourgeois, D., Lacanau, V., Mastretta, R., Contino-Pépin, C., Meyer, D., 2020. A simple process for the recovery of palladium from wastes of printed circuit boards. Hydrometall. 191. https://doi.org/10.1016/j.hydromet.2019.105241.

Chancерel, P., Meskers, C.EM., Hagelüken, C., Rotter, V.S., 2009. Assessment of precious Metal Flows during Preprocessing of Waste electrical and Electronic Equipment. J. Ind. Ecol. 13 (5), 791–810. https://doi.org/10.1111/j.1530-9290.2009.00171.x.

Charentier, N.M., Maurice, A.A., Xia, D., Li, W.J., Chua, C.-S., Brambilla, A., Gabriel, J.-C.P., 2023. Urban mining of unexploited spent critical metals from E-waste made possible using advanced sorting. Resour. Conserv. Recycl. 196. https://doi.org/10.1016/j.resconrec.2023.107033.

Chen, W., Li, M., Tang, J., 2013. Efficient Recovery of Cu from Wasted CPU Sockets by Slurry Electrolysis. Metals 13, 643. https://doi.org/10.3390/met13040643.

Cui, H., Anderson, C.G., 2016. Literature Review of Hydrometallurgical Recycling of Printed Circuit Boards (PCBs). J. Adv. Chem. Eng. 6 (1), 1000142. https://doi.org/10.4172/2090-4568.1000142.

Dinç, N.İ., Tosun, A.U., Baştırkıç, E., Özer, M., Burat, F., 2022. Recovery of valuable metals from WPCB fines by centrifugal gravity separation and froth flotation. J. Mater. Cycles Waste Manage. 24, 224–236. https://doi.org/10.1007/s10163-021-01310-8.

Domic, E.M., 2007. A Review of the Development and Current Status of Copper Bioleaching Operations in Chile: 25 Years of successful Commercial Implementation. In: Rawlings, D.E., Johnson, D.B. (Eds.), Biomining. Springer, Berlin, Heidelberg, pp. 81–95. https://doi.org/10.1007/978-3-540-34911-2_4.

Dreisinger, D., 2006. Copper leaching from primary sulfides: Options for biological and chemical extraction of copper. Hydrometall. 83 (1–4), 10–20. https://doi.org/10.1016/j.hydromet.2006.03.032.

Forsythe, W.E., 1954. Smithsonian Physical Tables. (9th Revised Edition).

Fraser, K.S., Walton, R.H., Wells, J.A., 1991. Processing of refractory gold ores. Miner. Eng. 4 (7-11), 1029-1041. https://doi.org/10.1016/0892-6875(91)90081-6.

Gibson, B.A.K.K., Nwaila, G., Manzi, M., Ghorbani, Y., Ndlovu, S., Petersen, J., 2023. The valorisation of platinum group metals from flotation tailings : a review of challenges and opportunities. Miner. Eng. 201. https://doi.org/10.1016/j.mineng.2023.108216.

Hubau, A., Anaya-Garzon, J., Guezennec, A.G., 2024. Devenir des métaux lors de la biolivixation de déchets de cartes électroniques : quelle influence sur les étapes aval de raffinage et de purification ?, Proceedings from the 19th congress of the French Process Engineering Society SFGP, October 2024, Beauville, France.

Hubau, A., Chagnes, A., Minier, M., Touzé, S., Chapron, S., Guezennec, A.G., 2019. Recycling-oriented methodology to sample and characterize the metal composition of waste Printed Circuit Boards. Waste Manag. 2019 (91), 62–71. https://doi.org/10.1016/j.wasman.2019.04.041.

Hubau, A., Minier, M., Chagnes, A., Joulian, C., Silvente, C., Guezennec, A.G., 2020. Recovery of metals in a double-stage continuous bioreactor for acidic bioleaching of printed circuit boards (PCBs). Sep. Purif. Technol. 238. https://doi.org/10.1016/j.seppur.2019.116481.

Istrate, E., Petrescu, M.I., Iacob, G., Buzatu, T., Ghica, V.G., Buzatu, M., Niculescu, F., 2018. Extraction and separation of nonferrous and precious metals from waste of electrical and electronic equipment through ferric sulfate leaching and electrolysis. J. Chem. Technol. Biotechnol. 93, 2878-2886. https://doi.org/10.1002/jctb.5641.

Johnson Matthey, 2025. PGM market report.

Kaksonen, A.H., Morris, C., Rea, S., Li, J., Usher, K.M., McDonald, R.G., Hilario, F., Hosken, T., Jackson, M., du Plessis, C.A., 2014. Biohydrometallurgical iron oxidation and precipitation: Part II — Jarosite precipitate characterization and acid recovery by conversion to hematite. Hydrometall. 147–148, 264–272. https://doi.org/10.1016/j.hydromet.2014.04.015.

Kaya, M., 2016. Recovery of metals and nonmetals from electronic waste by physical and chemical recycling processes. Waste Manag. 57, 64–90. https://doi.org/10.1016/j.wasman.2016.08.004.

Labbé, J.F., 2014. Panorama mondial 2012 du marché des platinoïdes. Rapport Public. BRGM/RP-63169-FR, 215p.

Lee, C.Y., Yang, S.P., Yang, C.H., Lu, M.K., Kuo, T.T., Ho, C.E., 2020. Influence of Pd(P) thickness on the Pd-free solder rection between eutectic Sn-Ag alloy and Au/Pd(P)/ Ni(P)/Cu multilayer. Surf. Coat. Technol. 395. https://doi.org/10.1016/j.surcoat.2020.125879.

Lu, Y., Yang, B., Gao, Y., Xu, Z., 2022. An automatic sorting system for electronic components detached from waste printed circuit boards. Waste Manag. 137, 1–8. https://doi.org/10.1016/j.wasman.2021.10.016.

Mäkinen, J., Bachér, J., Kaartinen, T., Wahlström, M., Salminen, J., 2015. The effect of flotation and parameters for bioleaching of printed circuit boards. Miner. Eng. 75, 26–31. https://doi.org/10.1016/j.mineng.2015.01.009.

Marra, A., Cesaro, A., Belgiorio, V., 2019. Separation efficiency of valuable and critical metals in WEEE mechanical treatments. J. Clean. Prod. 186, 490–498. https://doi.org/10.1016/j.jclepro.2018.03.112.

Monneron-Enaud, B., Bravo-Méndez, A.H., Wiche, O., Schlömann, M., 2025. Rate-limiting factors for indirect two-step biodismantling for printed circuit board recycling. Resour. Conserv. Recycl. 218. https://doi.org/10.1016/j.resconrec.2025.108253.

Mouser electronics website, 2014. Cypress Semiconductor Corporation product information notification. Accessed on 24 July 2024. https://www.mouser.com/PCN/Cypress_Semiconductor_145304.pdf.

Nextpcb website, https://www.nextpcb.com. Accessed on 24 July 2024.

Ogunninyi, I.O., Vermaak, M.K.G., Groot, D.R., 2009. Chemical composition and liberation characterization of printed circuit board commutation fines for beneficiation investigations. Waste Management 29, 2140–2146. https://doi.org/10.1016/j.wasman.2009.03.004.

Otsuki, A., De La Mensbruge, L., King, A., Serranti, S., Fiore, L., Bonifazi, G., 2020. Non-destructive characterization of mechanically processed waste printed circuit boards - particle liberation analysis. Waste Management 102, 510–519. https://doi.org/10.1016/j.wasman.2019.11.006.

Sarvar, M., Salarirad, M.M., Shabani, M.A., 2015. Characterization of mechanical separation of metals from computer printed circuit boards (PCBs) based on mineral processing methods. Waste Management 45, 246–257. https://doi.org/10.1016/j.wasman.2015.06.020.

Shinko Electric Industries Co. Ltd. Website, https://www.shinko.co.jp/english/product/package/leadframe/qfn.php. Accessed on 24 July 2024.

Silvas, F.P.C., Jiménez Correa, M.M., Caldas, M.P.K., de Moraes, V.T., Espinosa, D.C.R., Tenório, J.A.S., 2016. Printed circuit board recycling: Physical processing and copper extraction by selective leaching. Waste Management 46, 503–510. https://doi.org/10.1016/j.wasman.2015.08.030.

Touzé, S., Guignot, S., Hubau, A., Devau, N., Chapron, S., 2020. Sampling waste printed circuit boards: Achieving the right combination between particle size and sample mass to measure metal content. Waste Management 118, 380–390. https://doi.org/10.1016/j.wasman.2020.08.054.

Touzé, S., Hubau, A., Ghestem, J.P., Moreau, P., Lafaurie, N., Noireaux, J., 2024. Estimation of the uncertainty of metal content in a batch of Waste Printed Circuit Boards from computer motherboards. Waste Management 189, 325–333. https://doi.org/10.1016/j.wasman.2024.08.010.

Vidyadhar, A., Das, A., 2012. Kinetics and efficacy of froth flotation for the recovery of metal values from pulverized printed circuit boards, XXVI International Mineral Processing Congress (IMPC). New Delhi 236–243.

Romo Y Morales, M.M., Brunet-Manquat, A., Dib, H., Roussel, J.L., Morfin, F., Burel, L., Bourgeois, D., Kaper, H., 2023. Direct valorization of recycled palladium as heterogeneous catalysts for total oxidation of methane. ChemCatChem,15, e202300354. doi: 10.1002/cctc.202300354.

Sole, K.C., Mooiman, M., Hardwick, E., 2016. Present and future applications of ion exchange in hydrometallurgy: an overview. Proceedings of IEx 2016 – Hydrometallurgy Session.

Tunsu, C., Retegan, T., 2016. Chapter 6 - Hydrometallurgical Processes for the Recovery of Metals from WEEE, in: Chagnes, A., Cote, G., Ekberg, C., Nilsson, M., Retegan, T. (Eds.), WEEE Recycling. Elsevier, pp. 139–175. doi: 10.1016/B978-0-12-803363-0.00006-7.

van Beek, M.C., Wu, Y., Rem, P.C., 2024. Mechanically sorting Electronic Components from Discarded Printed Circuit Boards to Enable Recycling of critical Raw Materials, Electronics goes Green 2024+ (EGG). Berlin, Germany 1–6. https://doi.org/10.23919/EGG62010.2024.10631232.

Yamane, L.H., Tavares de Moraes, V., Espinosa, D.C.R., Tenório, J.A.S., 2011. Recycling of WEEE: Characterization of spent printed circuit boards from mobile phones and computers. Waste Management 31, 2553–2558. https://doi.org/10.1016/j.wasman.2011.07.006.
Yazici, E.Y., Deveci, H., 2014. Ferric sulphate leaching of metals from waste printed circuit boards. International Journal of Mineral Processing 133, 39–45. https://doi.org/10.1016/j.minpro.2014.09.015.

Zhang, S., Forssberg, E., 1997. Mechanical separation-oriented characterization of electronic scrap. Resources, Conservation and Recycling 21, 247–269. https://doi.org/10.1016/S0921-3449(97)00039-6.

Zhang, S., Forssberg, E., 1999. Intelligent liberation and classification of electronic scrap. Powder Technology, 105, 295-301. doi: 10.1016/S0032-5910(99)00151-5.