Processing of LCO LIBs Leachates—Part I: Removal of Accompanying Metals and Monitoring Losses of Co and Li

Abstract

This study investigates the hydrometallurgical purification of the acidic leachate from spent LiCoO₂-based lithium batteries, focusing on the selective removal of Cu, Mn, and Ni while monitoring co-precipitation of Fe and Al and minimizing Co and Li losses. Thermodynamic modelling using HSC Chemistry 10 and Hydra/Medusa guided the design of precipitation conditions. The optimal Cu precipitation was achieved using Na₂S (Na₂S:Cu = 4:1, 20 °C, 5 min, 300 rpm), yielding > 99% removal. Mn was efficiently precipitated as MnO₂ using KMnO₄ (KMnO₄:Mn = 1:1, 20 °C, pH ≈ 2, 10–15 min, ≈97% efficiency). Ni was recovered as [Ni(DMG)₂] under DMG:Ni = 5:1, 80 °C, 15 min, pH ≈ 5, achieving ≈99% removal. Sequential 2 L experiments (precipitation order: Cu → Mn → Ni) validated the scalability of the process. Cu and Ni removal remained high (>95%), while Mn efficiency slightly decreased (≈91%) due to kinetic and redox inhomogeneity. No significant precipitation of Co and Li was observed, leaving them in solution and concentrating from 12.9 to 18.8 g·L⁻¹ and 2.71 to 3.50 g·L⁻¹, respectively, with total losses of <1%. The resulting CuS, MnO₂, and [Ni(DMG)₂] precipitates exhibited moderate purity (46–63%) but represented valuable secondary raw materials. Overall, sequential precipitation under optimized conditions demonstrates robust, selective removal of accompanying metals while concentrating Co and Li, providing an efficient and scalable route for LIBs leachate valorisation.

1. Introduction

The increasing deployment of lithium-ion batteries (LIBs) across electric vehicles, portable electronics, and stationary energy storage systems has resulted in a significant increase in end-of-life battery waste. LIBs are now the dominant electrochemical system due to their high energy density, long service life, and low weight, and they contain valuable and critical metals, particularly Li, Co, Ni, and Mn—whose primary extraction is energy-intensive, geopolitically sensitive, and environmentally burdensome, making recycling essential for sustainable access [1]. To support raw material autonomy, the EU has introduced legislation promoting circular economy and recycling, most recently Regulation (EU) 2023/1542, which replaced Directive 2006/66/EC and sets collection and recycling.

Targets (e.g., 95% for Co and Ni by 2031; 80% for Li), as well as minimum recycled content in new batteries while also addressing environmental and social aspects such as carbon footprint tracking and ethical sourcing [2].

Technologically, LIB recycling is primarily carried out via pyrometallurgical and hydrometallurgical methods, often in combination, with emerging approaches such as direct recycling and solvometallurgy gaining attention for their potential to improve efficiency and selectivity [3,4,5,6]. While pyrometallurgy enables rapid conversion of active materials into alloys and oxides at high temperatures, it often results in the loss of critical components, such as lithium, to the slag phase. Hydrometallurgy, in contrast, enables more selective and efficient recovery at lower temperatures and energy demand, making it favourable for the circular economy [7]. Typical hydrometallurgical procedures include battery discharging, mechanical pretreatment, leaching with acids and oxidizing/reducing agents, and separation/recovery of metals via solvent extraction (SX), precipitation, ion exchange, or electrowinning, with method choice depending on desired purity, cost, environmental impact, and target elements [7,8,9,10]. Current research focuses on improving efficiency, minimizing waste, and regenerating components such as PVDF and graphite [11].

Selective separation of metals is critical for recycling efficiency. SX exploits differences in metal affinities for the organic phase, allowing selective recovery of Co, Ni, and Li [12,13]. Precipitation recovers metals as sparingly soluble compounds, such as hydroxides or carbonates, with efficiency dependent on reagent, pH, and temperature, but can generate larger waste volumes [14].

Over the last decade, numerous studies have optimized metal separation from spent LIB leachates. Yang et al. [14] developed a four-step selective precipitation for Mn, Ni, Co, and Li, achieving efficiencies above 90%. Zhu et al. [15] selectively precipitated Co (94.7%) and Li (71%). Kang et al. [16] recovered Co using Cyanex 272 (95–98%) with minor losses, while Shuya et al. [17] applied two-stage SX with Versatic 10, achieving selective separation of Ni, Mn, Co, and Li₂CO₃ precipitation (99.61% purity). Sattar et al. [18] combined precipitation (using KMnO₄, dimethylglyoxime (DMG), and Na₂CO₃ as precipitating agents) and cobalt extraction using Cyanex 272, achieving efficiencies above 88%. Chen L. et al. [19] proposed selective Co recovery after Al removal, using P507 and ammonium oxalate precipitation (95% extraction, 99% Co precipitation). Chen X. et al. [20] combined precipitation and extraction for Ni (using DMG, 98.7% efficiency), Mn (using SX, 97.1% efficiency), and selective Li and Co precipitation. In another study, Chen X. et al. [21] applied multi-stage leachate processing, achieving extraction yields of 100% for Cu, 99.2% for Mn, 97.8% for Co, 95.8% for Li, and 99.1% for Ni. Li et al. [22] precipitated Ni (using DMG, 99.63% efficiency) and subsequently extracted Mn and Co (using P204, Cyanex 272). Talianova et al. [23] developed and experimentally verified a selective oxalic acid leaching process for spent LIBs black mass, achieving high lithium recovery (≈90%) with minimal cobalt dissolution, followed by spontaneous Co precipitation and production of Li₂CO₃ with 91% purity.

Based on this overview, most studies rely on a combination of precipitation and SX, mainly targeting Mn, Ni, and Cu with reagents such as Cyanex 272, P204, or D2EHPA. Solvent extraction, however, involves multiple steps, high costs, and toxic solvents, limiting practical and sustainable application. Efficient and selective separation of accompanying metals can also be achieved using optimized precipitation alone, though previous studies often focus only on selected metals rather than providing a comprehensive assessment of minor components such as Fe and Al.

This work provides a systematic and quantitative assessment of all metal components in spent LCO LIB leachates during selective precipitation, explicitly addressing:

• Detailed evaluation of precipitation conditions to select the most suitable reagents for accompanying metals (Cu, Mn, and Ni).
• Monitoring of precipitation efficiency and potential losses of other metals such as Fe and Al during Ni, Cu, and Mn removal.
• Time-dependent analysis of precipitation to determine optimal reaction times for selective separation.

Sequential precipitation experiments to assess stepwise efficiency, minimize losses of strategic elements, and quantify precipitate formation enable monitoring of removal efficiencies and provide insights into selectivity limits and co-precipitation phenomena.

The novelty of this work lies in the comprehensive and systematic assessment of accompanying metal components in leachates from spent LCO lithium-ion batteries, including minor elements such as Fe and Al, combined with time-resolved and sequential precipitation experiments to optimize selectivity and minimize losses, providing accurate quantitative data on the removal efficiency of individual accompanying metals. The refined leach solution containing cobalt and lithium will be further processed in a subsequent study on recovery and production of high-purity products.

2. Materials and Methods

All liquid samples from leaching and precipitation were analyzed for metal concentrations (Co, Li, Mn, Ni, Cu, Al, and Fe) using high-resolution continuum source atomic absorption spectrometry (AAS) on a contrAA 700 instrument (Analytik Jena GmbH, Jena, Germany). Values below the limit of detection (LOD) are reported as being below detection limit (BDL). The LOD represents the lowest reliably detectable concentration, typically ranging from 0.01 to 0.1 mg·L⁻¹ depending on the element and analytical conditions. Results were corrected for volume changes due to sampling and evaporation. Solid samples were analyzed in triplicate through AAS to determine metal content, ensuring reproducibility. The mineralogical composition of the solid phases was determined by X-ray diffraction (XRD) using a PANalytical X’Pert PRO MRD instrument (Malvern Panalytical, Almelo, Netherlands) with Co-Kα radiation. The morphology of selected precipitates was analyzed using a MIRA3 FE-SEM scanning electron microscope (TESCAN, Brno, Czech Republic), and local semi-quantitative elemental analysis was performed through energy-dispersive X-ray spectroscopy (EDX) on the same instrument, with a resolution of 1.2 nm at 30 kV and 2.3 nm at 3 kV.

2.1. Preparation of Leachate from LCO Active Mass for Precipitation

Spent LIBs from mobile phones, with a total mass of 13 kg, were used as the input material. Mechanical processing involved a two-stage crushing (a dual-rotor crusher followed by a hammer mill) and subsequent classification on a vibrating screen. The obtained fine fraction (<0.5 mm), referred to as the active mass, consisted of a mixture of cathode materials and graphite, representing 50.35% of the total input weight (6.625 kg). The active mass was subjected to chemical analysis. The average metal contents determined by atomic absorption spectrometry (AAS) are presented in

Table 1. Average metal content in the obtained active mass.

Metal	Co	Li	Mn	Ni	Cu	Al	Fe
[wt.%]	26.82	3.44	1.54	0.96	1.44	0.65	0.40

.

As presented in Table 1, Co and Li exhibited the highest concentrations, whereas other metals were present only in minor amounts. The presence of these impurities is linked to specific battery components: Cu originates from the anode current collector (foil), Al from the cathode current collector and casing, and Fe from the battery casing or structural elements. These residual fragments remain in the active mass because the complete separation of electrode foils and packaging materials is not achievable during sieving. Minor concentrations of Mn and Ni further reflect either cathode-level additives or impurities from the mixed-waste collection of spent LCO batteries.

The active mass was subjected to leaching using 2 M H₂SO₄ with the addition of 10 vol.% H₂O₂ (30%). Leaching was performed in a semi-pilot reactor at 60 °C for 45 min, with continuous stirring at 300 rpm under atmospheric pressure and a liquid-to-solid ratio (L:S) of 20:1. The leaching procedure produced approximately 40 L of leachate, and the average metal contents are summarized in

Table 2. Content of target metals in the obtained leachate determined by AAS.

Metal	Co	Li	Mn	Ni	Cu	Al	Fe
Average Content [mg·L−1]	12,895.00	3102.67	875.33	332.70	1141.50	434.53	165.43

.

The results indicate that the leaching process was non-selective, as nearly all metals present in the active mass were transferred into the solution. Consequently, the refinement of the leachate is required prior to the recovery of the main metals, cobalt and lithium. The obtained leachate composition was subsequently used as the input material for precipitation experiments.

2.2. Theoretical Study of Metal Precipitation

For the theoretical study of precipitation, various precipitating agents were selected for each of the target metals—Cu, Mn, and Ni—to identify the most suitable ones for selective precipitation. The theoretical study was conducted using the software HSC Chemistry 10 [24] and Hydra/Medusa (version 16, December 2010) [25]. HSC Chemistry 10 allowed the calculation of standard Gibbs energy changes (ΔG⁰), indicating the spontaneity of the reactions, and was also used to construct E–pH diagrams when comparison with speciation diagrams was required. Using the Hydra/Medusa programmes, speciation diagrams were constructed to show the dominant metal species as a function of pH, which assisted in identifying the most favourable pH conditions for precipitation. All fractional diagrams considered the actual concentration of the target metal in the leachate and were calculated assuming a 1:1 molar ratio of precipitating reagent to the metal being removed. Based on these diagrams, the pH intervals for maximum precipitation of each metal were determined.

2.2.1. Cu Precipitation

For Cu precipitation, the selected precipitating agents were Na₂S, H₂S, and NaOH. The ΔG⁰ calculations at 20 °C showed that all considered reactions are thermodynamically favourable, as summarized in

Table 3. Expected chemical reactions for Cu precipitation, ΔG⁰ values, and K_sp of the resulting precipitates.

Number	Chemical Reaction	T [°C]	ΔG0 [kJ]	Solubility Product (Ksp) [26,27]
(1)	CuSO4 + Na2S = CuS + Na2SO4	20	−49.466	CuS = 7.9 × 10−37
(2)	CuSO4 + H2S = CuS + H2SO4	20	−8.034	CuS = 7.9 × 10−37
(3)	CuSO4 + 2 NaOH = Cu(OH)2 + Na2SO4	20	−48.203	Cu(OH)2 = 1.6 × 10−19

. The resulting precipitates are sparingly soluble, as indicated by their low K_sp values.

All reactions considered show negative ΔG⁰ values for the proposed reagents at 20 °C, and the corresponding products are sparingly soluble, indicating that copper precipitation is thermodynamically spontaneous. Figure 1a shows the fractional diagram of Cu precipitation using H₂S and Na₂S, illustrating the possible formation of the present phases or compounds and their distribution in the leachate over the pH range of 0–14. Figure 1b presents the fractional diagram of Cu precipitation using NaOH. The coloured areas in the fractional diagrams illustrate the stability and occurrence of the investigated metal in individual precipitates or solid phases depending on the solution pH.

Fractional diagrams for sulphide reagents confirmed that CuS forms predominantly under strongly acidic conditions (pH < 2.5). The advantage of the sulphide precipitation method for Cu is the formation of insoluble CuS, which enables efficient Cu removal even at low pH values—thus, no pH adjustment is required for acidic leachates obtained from the leaching of active mass from spent LIBs. When NaOH is used, Cu precipitates as Cu(OH)₂ and CuO, with precipitation starting around pH 5 and complete Cu removal occurring at pH ≥ 6. A limitation of this method is its low selectivity, as co-precipitation of impurities may occur, reducing the purity of the final product.

2.2.2. Mn Precipitation

For the precipitation of Mn, Na₃PO₄, KMnO₄, and NaOH were chosen as reagents. As shown in

Table 4. Expected chemical reactions for Mn precipitation, ΔG⁰ values, and K_sp of the resulting precipitates.

Number	Chemical Reaction	T [°C]	ΔG0 [kJ]	Solubility Product (Ksp) [26,27]
(4)	3MnSO4 + 2Na3PO4 = Mn3(PO4)2 + 3Na2SO4	20	−40.921	Mn3(PO4)2 = 1.0 × 10−33
(5)	MnSO4 + 2NaOH = Na2SO4 + Mn(OH)2	20	−18.697	Mn(OH)2 = 4.6 × 10−14
(6)	2KMnO4 + 3MnSO4 + 2H2O = 5MnO2 + K2SO4 + 2H2SO4	20	−65.262	MnO2 = 1.5 × 10−18

, all investigated reactions have negative ΔG⁰ values at 20 °C, indicating that they are thermodynamically favourable. The formed precipitates are only slightly soluble due to their low K_sp values.

The fractional diagram indicated that the MnHPO₄ phase forms at very low pH when Na₃PO₄ is used and remains stable over a broad pH range (Figure 2a); based on this, only about 65% of Mn is expected to precipitate.

To determine the conditions for Mn precipitation using NaOH, a corresponding fractional diagram was constructed (Figure 2b).

As shown in Figure 2b, the use of NaOH for Mn precipitation requires a high pH—typically above 9—which can be technically challenging and less cost-effective for processing larger solution volumes. In addition, like Cu precipitation, this method often results in the co-precipitation of other metals present in the solution, reducing the purity of the final product.

Fractional diagrams for Mn in a KMnO₄ environment could not be constructed because the necessary thermodynamic data is not available. However, an E–pH diagram for the Mn–K–S system was constructed (Figure 3), which shows that MnO₂ can exist across the entire pH range within the region of water stability. Mn may also be present in solid form as MnO.OH, starting from around pH 4, and as Mn(OH)₂, from approximately pH 8. During the precipitation of Mn²⁺ using Mn⁷⁺ from KMnO₄, the oxidation of Mn²⁺ to Mn⁴⁺ can be expected, as shown in Reaction (6), with the formation of insoluble MnO₂. Significant pH adjustment is redundant, as precipitation is theoretically feasible under acidic conditions.

2.2.3. Ni Precipitation

The following reagents were selected for Ni precipitation: NaOH, Na₂C₂O₄, and DMG. The corresponding precipitation reactions and their thermodynamic parameters are summarized in

Table 5. Expected chemical reactions of Ni precipitation, ΔG⁰ values, and K_sp of the resulting precipitates.

Number	Chemical Reaction	T [°C]	ΔG0 [kJ]	Solubility Product (Ksp) [26,27]
(7)	NiSO4 + 2NaOH = Na2SO4 + Ni(OH)2	20	−18.958	Ni(OH)2 = 2.8 × 10−17
(8)	NiSO4 + Na2C2O4 = NiC2O4 + Na2SO4	20	−6.617	NiC2O4 = 4.0 × 10−10
(9)	NiSO4 + 2DMG = [Ni(DMG)2] + H2SO4	20	−75.100	[Ni(DMG)2] = 1.5 × 10−33

. The ΔG⁰ values at 20 °C are negative for all reactions, confirming their thermodynamic favourability, and the resulting compounds are characterized by low K_sp values, indicating their poor solubility.

Figure 4a shows the fractional diagram of Ni precipitation using NaOH and Figure 4b presents the fractional diagram of Ni precipitation using sodium oxalate.

According to the fractional diagram shown in Figure 4a, Ni begins to precipitate as Ni(OH)₂ at approximately pH 6. Above pH 7, nearly all nickel is present in a solid, insoluble form. One limitation of Ni precipitation with NaOH is that Cu also precipitates within a similar pH range, forming insoluble Cu(OH)₂ and CuO. Consequently, when both metals are present in the solution, they precipitate simultaneously, which complicates their selective separation.

The fractional diagram for Ni precipitation using sodium oxalate (Figure 4b) shows that Ni begins to precipitate as NiC₂O₄ at very low pH, continuing gradually up to pH 7, with a maximum precipitation of around 80%. Beyond pH 7, nickel starts to precipitate as Ni(OH)₂.

In the case of Ni precipitation using DMG, a highly selective and stable [Ni(DMG)₂] precipitate forms already at pH ≈ 5–6 [14,18,20,28,29]. The precipitation mechanism is governed by the principles of coordination chemistry, specifically the ligand field stabilization of the nickel complex. The [Ni(DMG)₂] complex is very stable, meaning there is a strong bond between the ligand and the central metal atom. A major advantage of this method is its high selectivity toward Ni. DMG does not significantly react with other metals commonly present in leachates, such as Cu²⁺, Mn²⁺, or Fe³⁺, and these reactions result in soluble or less stable complexes. This property makes DMG an ideal agent for the selective precipitation of nickel from polymetallic solutions [29,30,31].

Based on a theoretical study of Cu, Mn, and Ni precipitation, and utilizing fractional and, when necessary, E–pH diagrams, suitable precipitating agents were selected for the experimental phase for each metal. Na₂S was chosen for Cu, as it enables the formation of practically insoluble CuS, even in strongly acidic conditions (pH 0–2.5), thus eliminating the need for pH adjustment of the leachate. For Mn precipitation, Na₃PO₄ was selected, which facilitates the formation of MnHPO₄ precipitate over a wide pH range. According to the fractional diagram (Figure 2a), the maximum theoretical precipitation efficiency is approximately 65%. As an alternative, potassium permanganate was also selected to compare Mn precipitation efficiency, as it oxidizes Mn³⁺ in solution to MnO₂, with the formation of this compound theoretically possible from approximately pH 1. For Ni precipitation, DMG was selected based on literature evidence. This choice is justified because precipitation with sodium oxalate theoretically allows recovery of only about 70% of Ni, while precipitation with NaOH is not selective, as Cu and other metals also precipitate in a similar pH range, complicating separation.

This set of reagents is expected to provide efficient and selective recovery of the studied trace metals under acceptable pH conditions. An important next step is the theoretical investigation of the behaviour of the two main metals of interest—Co and Li—during the process.

2.2.4. The Effect of Minor Metal Precipitation on the Behaviour of Co and Li

This section focuses on evaluating the effect of precipitating Cu, Mn, and Ni using the selected reagents—Na₂S, Na₃PO₄, and KMnO₄ (DMG was excluded because thermodynamic data are not available)—on the behaviour of the main target elements, Co and Li, in the leachate. Fractional diagrams were used to analyze to what extent these reagents influence the stability of Co and Li in the leachate, while also identifying conditions under which minor metals can be effectively removed without undesirable losses of the main metals. Figure 5 present the fractional diagrams of Co and Li using Na₂S.

For cobalt, approximately 10% of CoS precipitates across the entire pH range in the presence of sulphide ions, while at higher pH values Co precipitates predominantly as Co(OH)₂ (Figure 5a). In contrast, Li remains dissolved across the entire pH range, demonstrating its stability and lack of co-precipitation under these conditions (Figure 5b).

The fractional diagrams for Co and Li during Mn precipitation with Na₃PO₄ (Figure 6) indicate that in the acidic pH range Co does not precipitate as a phosphate, and it begins to precipitate as Co(OH)₂ at approximately pH 6.2. Lithium remains fully dissolved across the entire pH range.

While the E–pH diagram for the Co–Na–P–S system at 20 °C (Figure 7a) confirms the formation of Co(OH)₂, starting from approximately pH 6.5, the E–pH diagram for the Li–Na–P–S system at the same temperature (Figure 7b), within the water stability region, indicates the formation of LiH₂PO₄ and Li₃PO₄ already from around pH 1. Although this does not fully correspond with the speciation diagram (Figure 6b), some co-precipitation of Li should still be expected, as lithium phosphate phases are not included in the Medusa database.

Even when using KMnO₄ for Mn precipitation, Co is expected to precipitate at pH > 6.5, whereas lithium remains stably dissolved (Figure 8a,b). The behaviour of both elements indicates that this method of Mn precipitation is potentially safe with respect to the loss of the main metals.

Regarding the use of DMG, according to the literature [29], it forms a highly selective and stable complex with nickel. When precipitating nickel using DMG, Co may start to form a complex already at approximately pH 6–7, which can lead to undesirable cobalt losses. In contrast, Li does not react with DMG and remains dissolved in the solution, allowing for its further processing without losses. Therefore, it is necessary to optimize precipitation conditions, such as pH, DMG concentration, and temperature, to minimize Co losses while effectively separating Ni from other metals [29,30,31].

From the theoretical study of the co-precipitation of the main metals, it follows that Co and Li losses during the precipitation of Cu, Mn, and Ni can be minimized if appropriate conditions are strictly maintained, particularly keeping the pH below 6. In all modelled cases, lithium remains stably dissolved except when using Na₃PO₄. Cobalt is more sensitive to increased pH and can partially convert into solid phases (e.g., sulphides or hydroxides), so its behaviour must be carefully monitored.

2.3. Precipitation Experiments

Precipitation experiments were conducted using standard apparatus equipped with a built-in thermostat and automatic stirring with adjustable rotation speed, which was maintained at 300 rpm for all experiments. The pH was measured at regular intervals using an Inolab pH 7310 m (WTW, Weilheim, Germany). The initial volume for the experiments was 300 mL, and the precipitation time was 30 min. All experimental procedures were conducted in triplicate to ensure reproducibility, and the data presented reflect the mean values of the three experiments.

After precipitation, the solids were filtered. Liquid samples were taken from the refined leachate to determine the content of the monitored metals using the AAS method. The obtained precipitates were filtered, thoroughly washed, and then dried at 105 °C to a constant weight before being subjected to a chemical composition analysis.

The efficiency of metal precipitation (η) was determined according to Equation (10):

$$\eta ={\displaystyle \frac{m_1}{m_0}}\times 100$$

(10)

where $m_1$ is the amount of metal in the leachate after precipitation and $m_0$ is the amount of metal in the leachate before precipitation. A detailed overview of the experimental conditions applied in the laboratory-scale precipitation tests is provided in

Table 6. Investigated conditions for the precipitation of accompanying metals.

Obtained Metal	Precipitating Agent	Molar Ratio	T [°C]	pH (Adjusted with NaOH)
Cu	Na2S	2, 3, 4, 5	20, 40, 60, 80	without adjustment (<1)
Mn	Na3PO4·12H2O	2, 3, 4, 5	20, 40, 60, 80	4
	KMnO4	0.5, 1, 1,5, 2	20, 40, 60, 80	2
Ni	DMG	2, 3, 4, 5	20, 40, 60, 80	5–6

.

Sequential Precipitation Procedure

To validate the applicability of the optimal precipitation parameters determined during laboratory-scale tests, a sequential precipitation experiment was conducted using the same leachate as in the previous experiments, with its composition given in Table 2. To ensure reproducibility, the entire procedure was repeated three times under identical conditions. While the optimization experiments were performed in 300 mL batches under control conditions, the sequential experiment began with 2 L of polymetallic leachate obtained from the sulfuric acid leaching of the active mass.

The entire solution was processed through a sequential precipitation scheme to remove copper, manganese, and nickel (Cu → Mn → Ni). Each step was carried out under the previously established optimal conditions:

• Cu precipitation: Na₂S as the precipitating agent, molar ratio Na₂S:Cu = 4:1, temperature = 20 °C, pH < 1 (without adjustment), reaction time = 5 min.
• Mn precipitation: KMnO₄ as the precipitating agent, molar ratio KMnO₄:Mn = 1:1, temperature = 20 °C, pH ≈ 2, reaction time = 15 min.
• Ni precipitation: DMG as the precipitating reagent, molar ratio DMG:Ni = 5:1, temperature = 80 °C, pH ≈ 5, reaction time = 15 min.

Between the individual steps, the leachate was filtered to remove the precipitate and ensure a homogeneous composition for the subsequent reaction. The process was performed with continuous stirring at 300 rpm and monitored through pH and temperature control. All liquid and solid samples collected after each step were analyzed through AAS to determine metal concentrations.

This approach facilitated the assessment of process reproducibility and stability during scale-up from laboratory to semi-pilot conditions.

3. Results and Discussion

3.1. Cu Precipitation

Figure 9a presents the precipitation efficiency of Cu with Na₂S at temperatures of 20–80 °C and molar ratios of Na₂S:Cu = 2:1, 3:1, 4:1, and 5:1, and Figure 9b presents the co-precipitation of Mn, Ni, Fe, and Al at 20 °C for all applied molar ratios.

The experimental data demonstrate that peak copper precipitation efficiency was achieved at 20 °C for molar ratios ranging from 3:1 to 5:1, with efficiencies between 93.13% and 99.02%. As the temperature increased, the efficiency of Cu precipitation decreased—the decline was slight at 40 °C but became significant at 60 °C and 80 °C, likely due to the increased solubility of the precipitate at higher temperatures. Conducting the precipitation at 20 °C is advantageous, as it obviates the need for external heating, thereby reducing operational energy costs. Based on the results, a molar ratio of Na₂S:Cu = 4:1 proved to be the most suitable, achieving an efficiency of up to 99%.

As illustrated in Figure 9a, the precipitation efficiency reaches its peak at this ratio and subsequently remains stagnant or exhibits a slight downward trend with further reagent addition. This behaviour suggests that the residual Cu concentration has reached its thermodynamic minimum for the given system. The minor decrease in efficiency observed at higher molar ratio could be attributed to the potential formation of soluble thiometallate or polysulfide complexes in the presence of excess sulphide ions [32]. This phenomenon, often referred to as over-sulphidization, may lead to the partial re-solubilization of the CuS precipitate, indicating that excessive reagent addition beyond the 4:1 ratio is counterproductive for maximizing copper recovery.

The analysis of the solution after 30 min (Figure 9b) showed a substantial co-precipitation of Al, Mn, and Ni, particularly at higher molar ratios. At this stage, the removal efficiency of these metals reached approximately 14–24 wt.%, whereas Fe removal remained low (2–5 wt.%). Cobalt and lithium were not removed from the solution under any of the tested conditions. These results suggest that the optimization of the precipitation time is necessary to minimize the loss of accompanying metals while achieving maximum Cu precipitation efficiency in the shortest possible time.

For the optimization of copper precipitation time, the best conditions for copper removal were selected (20 °C, molar ratio Na₂S:Cu = 4:1). An experiment was conducted to monitor the time dependence of precipitation over 60 min at a stirring speed of 300 rpm. Samples were taken at 2, 5, 10, 15, 20, 30, 45, and 60 min. The co-precipitation of cobalt, lithium, and other accompanying metals was also monitored. Figure 10 shows the efficiency of Cu precipitation and the simultaneous co-precipitation of other metals as a function of time under the specified conditions.

The results indicate that Cu precipitation occurs very rapidly, with near-maximum efficiency achieved within the first minutes of the process. This behaviour is closely related to the solubility of the formed sulphide. The precipitation of metal sulphides is governed by the solubility product (K_sp), where precipitation occurs if the ionic product [M²⁺]. [S²⁻] exceeds the K_sp of the corresponding metal sulphide. Under the same sulphide ion concentration, the metal with the lowest K_sp value precipitates first [33]. The solubility product of CuS (≈7.9 × 10⁻³⁷) [26] is among the lowest of common metal sulphides, which, together with the high affinity of Cu²⁺ for sulphur, explains its immediate and quantitative precipitation. For comparison, the K_sp of CoS is ≈4 × 10⁻²¹ and that of FeS is approximately 6 × 10⁻¹⁸ [26], reflecting significantly higher solubility for these compounds. The observed stability of CuS precipitation at 20 °C is consistent with these thermodynamic data. However, as shown in Figure 9a, the precipitation efficiency decreases at temperatures above 60 °C. This suggests that, while the K_sp remains low, the apparent solubility increases or competitive kinetic effects occur at higher temperatures. Therefore, maintaining a lower temperature is essential for maximizing the selectivity of Cu removal against Co and Ni, whose sulphides have higher K_sp and remain in the solution under the existing acidic conditions (pH < 1). The selectivity of this step is primarily governed by the solution pH. Under these conditions, the extremely low K_sp of CuS ensures its quantitative precipitation, while the higher solubility products of Co, Ni, Mn, and Fe sulphides prevent their formation, thus keeping them in the solution for subsequent recovery steps.

During the precipitation process, co-removal of other metals present in the leachate is also observed. Manganese achieves a removal efficiency of approximately 20 wt.% within the first 10 min, after which it remains essentially constant throughout the remainder of the process. Nickel exhibits similar behaviour, with precipitation observed from the 15th minute, also reaching around 20 wt.% efficiency. Among minor components, aluminum was detected in the precipitate, with a maximum efficiency of 18 wt.% from the 30th minute until the end of the process. The precipitation of MnS (K_sp ≈ 2.5 × 10⁻¹³) and NiS (K_sp ≈ 3 × 10⁻²⁰) [26] occurs only at higher concentrations of available sulphide ions. During the initial phase of the experiment, most S²⁻ is consumed by copper precipitation; only after its effective removal is sufficient free sulphide ion available to react with Mn²⁺ and Ni²⁺. Consequently, the precipitation of these metals is delayed, explaining their later appearance in the precipitate.

An important observation is that Co and Li, as the main metals of interest, remain in solution throughout the entire process, confirming the selectivity of the method. Although CoS formation could be expected based on K_sp values, its precipitation was not observed experimentally. This is attributable to the relatively higher K_sp of CoS compared to CuS, meaning CoS is more soluble and less likely to precipitate under the given conditions.

Based on the time-dependent precipitation efficiency, it can be concluded that copper sulphide precipitates very quickly and effectively, with the process practically complete within 2–5 min. Extending the reaction time beyond this period results in unwanted co-precipitation of manganese and nickel. Therefore, the optimal precipitation time can be considered 5 min, allowing selective removal of copper with minimal losses of other metals.

The optimal conditions for copper precipitation from acidic sulphate leachate (pH = 0–1) using Na₂S can be summarized as follows: molar ratio Na₂S:Cu = 4:1, temperature = 20 °C, reaction time = 5 min, and stirring speed = 300 rpm.

Analysis of the Obtained Cu Precipitate

The results of the chemical analysis of the precipitates obtained by copper precipitation using Na₂S under optimal conditions are shown in

Table 7. Average content of the monitored metals in the obtained Cu precipitates by precipitation with Na₂S:Cu = 4:1, T = 20 °C, t = 5 min, 300 rpm, (determined by AAS method).

Metal	Co	Li	Mn	Ni	Cu	Al	Fe
Average Content [wt.%]	2.7275	0.018	0.027	0.086	45.87	0.0095	0.039

.

Under the optimal conditions, a precipitate containing 45.87% Cu was obtained from the initial leachate. This corresponds to approximately 67 wt.% of CuS in the precipitate. The high copper content was further confirmed by SEM-EDX analysis, the spectrum of which is shown in Figure 11a. In addition to copper (68.2%) and sulphur (29.3%), cobalt was detected at a concentration of 2.5%. The crystalline structure was subsequently verified by XRD analysis (Figure 11b), where the diffraction peaks are consistent with the standard reference for covellite (CuS, JCPDS 06-0464). Phase identification was performed using the JCPDS database [34]. This phase identification confirms that the precipitate consists primarily of CuS, demonstrating the high selectivity of the precipitation process under the established acidic conditions.

Regarding the presence of impurities, although no decrease in cobalt concentration was observed in the leachates after copper precipitation, cobalt was incorporated into the precipitate at approximately 2.73% (AAS). This corresponds to a cobalt loss of about 0.6% during the Cu precipitation process, calculated based on the weight of the obtained precipitate. The presence of Co in the precipitate may result, for example, from its adsorption on the precipitate surface. Other monitored metals, such as Li, Ni, Mn, Al, and Fe, were present in the precipitate only at trace concentrations, with even lower losses than cobalt; for instance, the calculated lithium loss was approximately 0.0002%.

From the above, it follows that the main product of copper precipitation using Na₂S is a precipitate with a dominant copper content in the form of CuS, with cobalt as the primary impurity. This type of precipitate could be used in pyrometallurgical copper production, where accompanying elements such as Co and Ni would enter the crude alloy and could be recovered in subsequent refining steps. Conversely, elements such as Al and Fe would likely concentrate in the slag.

3.2. Mn Precipitation

The precipitation of Mn was carried out from a Cu-free leachate obtained under the previously established optimal conditions for Cu precipitation (Na₂S:Cu = 4:1, T = 20 °C, t = 5 min) in a large-scale experiment (V_input = 5000 mL), the composition of which is given in

Table 8. Average content of the monitored metals in the Cu-free leachate for Mn precipitation.

Metal	Co	Li	Mn	Ni	Cu	Al	Fe
Average Content [mg·L−1]	10,971.40	2289.30	764.35	257.59	0.00	385.91	53.21

. Two precipitating agents, Na₃PO₄·12H₂O and KMnO₄, were selected, and their effectiveness in removing manganese was verified in separate experiments.

3.2.1. Mn Precipitation Using Na₃PO₄

During the precipitation of Mn using Na₃PO₄·12H₂O, the following conditions were studied: Na₃PO₄·12H₂O:Mn molar ratios of 2:1, 3:1, 4:1, and 5:1; temperatures of 20, 40, 60, and 80 °C; precipitation time of 30 min; and stirring at 300 rpm. Preliminary experiments indicated that pH adjustment to approximately 4 was necessary to initiate precipitation.

The influence of the Na₃PO₄:Mn molar ratio and temperature was examined to determine the optimal conditions for Mn separation from the Cu-free leachate. Figure 12a illustrates the effect of temperature on the efficiency of Mn precipitation from the solution at different molar ratios.

For the study of the co-precipitation of metals (Co, Li, Mn, Al, and Fe), a temperature of 60 °C was selected, as it showed the highest efficiency in Mn precipitation. Figure 12b presents the co-precipitation of these metals under the applied conditions, depending on the Na₃PO₄:Mn molar ratio.

The obtained results indicate that the highest Mn precipitation efficiency was achieved at 60 °C and Na₃PO₄:Mn molar ratios of 4:1 and 5:1, reaching 64.5% and 59.5%, respectively. Precipitation efficiency increased with temperature, but a decrease was observed at 80 °C, likely due to partial redissolution of the precipitate. A higher molar ratio also enhanced Mn precipitation, particularly at elevated temperatures. These findings are consistent with the fraction diagram shown in Figure 2a, which also indicates a maximum Mn recovery of approximately 60% using Na₃PO₄.

Based on these results, a temperature of 60 °C was selected for the study of co-precipitation of metals (Co, Li, Mn, Al, and Fe) (Figure 12b), as it showed the highest efficiency in Mn precipitation. Significant co-precipitation of other metals was observed. Cobalt showed increasing co-precipitation with rising excess of the precipitating agent, reaching 19–49%. This reduces process selectivity toward manganese. Due to similar ionic radii and coordination behaviour, Co²⁺ and Mn²⁺ both form sparingly soluble phosphates—Co₃(PO₄)₂ (K_sp ≈ 2.05 × 10⁻³⁵) and Mn₃(PO₄)₂ (K_sp ≈ 1.0 × 10⁻³¹) [26]—with cobalt phosphate being less soluble. Thus, Co²⁺ tends to precipitate more readily under identical conditions. A higher phosphate excess increases PO₄³⁻ concentration, promoting precipitation of both metals and potentially causing non-selective co-precipitation. The pH ≈ 4 required for manganese precipitation also favours Co²⁺ removal, since phosphate species (HPO₄²⁻ and PO₄³⁻) readily react with divalent cations [35,36].

Lithium precipitation remained relatively stable (20–30%) across all molar ratios, reflecting its low sensitivity to reaction conditions. Due to the high solubility of Li₃PO₄ (K_sp ≈ 3.2 × 10⁻⁹) [26], lithium does not precipitate fully; observed losses likely result from Li adsorption onto phosphate solids.

Nickel co-precipitation was most pronounced at a low Na₃PO₄:Mn ratio (2:1), likely due to insufficient selectivity and limited PO₄³⁻ availability. At higher ratios, metals with lower phosphate solubilities (Mn, Fe, Al, and Co) precipitate preferentially, while Ni²⁺ largely remains in solution. This behaviour is favourable for maintaining Ni in the leachate for subsequent recovery.

Aluminum and iron co-precipitated almost completely (90–100%) under all tested conditions, as expected for Al due to its chemical behaviour. AlPO₄ has a very low solubility (K_sp ≈ 6.3 × 10⁻¹⁹) [26], and Al³⁺ easily hydrolyses at pH > 3, forming hydroxides or phosphates [37,38]. Fe²⁺ also forms highly insoluble Fe₃(PO₄)₂ (K_sp ≈ 10⁻³⁶–10⁻³¹) [26]. Consequently, both Al and Fe precipitate easily alongside Mn in phosphate media. While their removal can be beneficial for purification, it results in a mixed, compositionally complex precipitate.

Due to the low maximum precipitation efficiency of Mn (64.5%) and its significant non-selectivity and Li and Co co-precipitation, Na₃PO₄ was evaluated as unsuitable for manganese precipitation in the presence of Co, Li, and other metals. Therefore, subsequent experiments focused on Mn precipitation using KMnO₄.

3.2.2. Mn Precipitation Using KMnO₄

Figure 13a shows the effect of temperature on Mn precipitation efficiency at different KMnO₄:Mn molar ratios. The experiments were performed using a Cu-free leachate with the composition shown in Table 8. Figure 13b presents the co-precipitation of metals (Co, Li, Ni, Fe, and Al) during Mn precipitation at 20 °C, depending on the applied KMnO₄:Mn molar ratio.

The results indicate that the molar ratio of the oxidizing agent KMnO₄ to Mn is the key factor determining the efficiency of Mn precipitation, while temperature plays a secondary but still significant role. This aligns with thermodynamic predictions from the E–pH diagram (Figure 3), which indicate the formation of solid MnO₂ across the entire pH range, facilitated by the high oxidation potential of KMnO₄. The highest efficiency (97–100%) was achieved at molar ratios ranging from 1.5:1 to 2:1 at 20 °C. This excess, relative to the theoretical stoichiometry, was found necessary to ensure the quantitative oxidation of Mn²⁺ within the complex leachate matrix. Any residual KMnO₄ is effectively neutralized during the subsequent process stages, specifically during the pH adjustment and the addition of dimethylglyoxime for nickel recovery. This stepwise approach ensures that the oxidant does not interfere with the final product quality.

The lowest efficiency occurred at the sub-stoichiometric 0.5:1 ratio (≈30% at 20 °C, nearly zero at 80 °C) due to insufficient oxidizing capacity and competing reactions. The observed temperature effect likely results from KMnO₄ decomposition, side reactions, and reduced supersaturation for MnO₂ nucleation.

Co-precipitation behaviour under investigated conditions shows that Co, Li, and Ni did not co-precipitate at KMnO₄:Mn ratios of 0.5:1, 1:1, and 1.5:1, which is favourable for process selectivity. At the 2:1 ratio, Co and Li co-precipitation remained minimal (<1%). In contrast, Fe likely experienced significant co-precipitation (89–93%), which is consistent with thermodynamic evaluations reported in the literature [39]. These indicate that under oxidizing conditions, Fe²⁺ is readily converted to Fe³⁺, followed by the precipitation of Fe³⁺ oxyhydroxides such as goethite (FeO(OH)), whose extremely low solubility (K_sp = 1.1 × 10⁻⁴³ [26]) drives the extensive removal of Fe from solution even at low pH.

Aluminum co-precipitated in the range of 23–36% at all molar ratios. This can be attributed to the amphoteric nature of aluminum, which under slightly acidic conditions can form insoluble Al(OH)₃ [40]. Although Al generally dissolves in acidic media, the oxidation of Mn²⁺ by KMnO₄ can locally increase pH, promoting Al precipitation as hydroxide. Additionally, higher KMnO₄ excess can generate finely dispersed precipitates with high adsorption capacity, capturing Al³⁺ via sorption or co-precipitation mechanisms. These accompanying metals can be removed in subsequent processing steps. Based on these results, the optimal conditions for Mn precipitation from sulphate leachate are a KMnO₄:Mn ratio of 1:1–1.5, temperature of 20 °C, and slightly acidic pH (≈2). Under these conditions, Mn is efficiently precipitated, Co, Li, and Ni largely remain in solution, and Fe together with Al co-precipitates. Overall, KMnO₄ proves to be a highly selective and efficient precipitating agent compared to alternatives such as Na₃PO₄.

After determining the optimal temperature and molar ratio, the optimal reaction time was studied, as it affects both the energy demand and the technological efficiency of the process. A study was conducted on the effect of precipitation time (2–60 min) at 20 °C, with a stirring speed of 300 rpm and a KMnO₄:Mn molar ratio of 1, on the precipitation efficiency of Mn and the co-precipitating metals Fe and Al. Figure 14 shows the precipitation efficiency of Mn and the simultaneous co-precipitation of Fe and Al as a function of reaction time under these experimental conditions.

The results indicate that Mn precipitation is highly efficient within the first few minutes of the reaction—efficiency exceeds 98% and remains stable throughout the entire reaction time. This demonstrates the rapid oxidation of Mn²⁺ ions to insoluble MnO₂. Iron shows a similar trend, with precipitation ranging between 80 and 85% and remaining constant with increasing reaction time.

Aluminum co-precipitation gradually increases, reaching up to approximately 22%, likely due to local pH increases and adsorption/co-precipitation on MnO₂ surfaces. Based on these observations, the optimal reaction time was set at 15 min, which ensures effective Mn precipitation.

Analysis of the Obtained Mn Precipitate

The results of the precipitates obtained under conditions yielding the highest manganese removal efficiency (KMnO₄:Mn molar ratio = 1:1, T = 20 °C, t = 15 min, pH ≈ 2) are summarized in

Table 9. Average content of monitored metals in the obtained Mn precipitates by precipitation with KMnO₄: Mn = 1:1, T = 20 °C, t = 15 min, pH ≈ 2, 300 rpm, AAS method.

Metal	Co	Li	Mn	Ni	Cu	Al	Fe
Average Content [wt.%]	2.441	0.013	34.060	0.034	0.006	0.006	4.019

, showing their chemical composition determined through the AAS method.

Table 9 shows that Mn is the main component of the precipitate (34.06 wt.%). Co (2.441 wt.%) and Fe (4.019 wt.%) are also present, while Ni (0.034 wt.%), Li (0.013 wt.%), and Al (0.006 wt.%) are negligible, indicating minimal losses (e.g., Li loss ≈ 0.02 wt.%). Interestingly, Co appears in the precipitate despite no noticeable decrease in leachate concentration, likely due to sorption onto freshly formed MnO₂ via ion exchange, complexation, or adsorption [41]. This accounts for only ≈ 0.62 wt.% of the total cobalt in the leachate. The Fe content (4.019 wt.%) reflects an approximately 80% precipitation efficiency. Based on the measured manganese content (34.06 wt.%), the precipitate is estimated to contain approximately 53 wt.% MnO₂, its expected primary component.

The SEM-EDX analysis identified the presence of Mn and O, along with Fe and Co as the main impurities in the obtained precipitate. Additionally, Na from the reagent used for pH adjustment was detected, as shown in Figure 15a. The XRD analysis (Figure 15b) confirmed that the manganese precipitate is primarily composed of pyrolusite (MnO₂, JCPDS 24-0735 [34]), though phases of bixbyite (Mn₂O₃, JCPDS 41-1442 [34]) and hausmannite (Mn₃O₄, JCPDS 24-0734 [34]) were also detected. These findings indicate a partial reduction or structural transformation during the process. Additionally, the presence of potassium was confirmed in the form of K₂O (JCPDS 77-2176 [34]), which originates from the KMnO₄ used as the oxidizing and precipitating agent. No crystalline phases of Fe or Co were observed, likely due to their amorphous nature or concentrations below the XRD detection limit.

It can be concluded that the precipitate consists predominantly of manganese oxides with minor amounts of accompanying metals. From a selectivity and purity perspective, this product could be further processed as a raw material for manganese-based battery materials. The results confirm that KMnO₄ is a particularly suitable oxidizing agent for manganese removal.

The optimal conditions for Mn precipitation from acidic sulphate leachate using KMnO₄ are a KMnO₄:Mn molar ratio of 1:1, T = 20 °C, t = 10–15 min and pH ≈ 2. These conditions achieve up to 97% Mn precipitation efficiency with minimal precipitating agent consumption, reducing costs and improving process economics. Solution supersaturation is minimized, and Al co-precipitation remains acceptable (≈10%), while Fe co-precipitation remains significant (≈80%). Overall, these conditions provide an efficient process, producing a Mn-rich precipitate suitable for further processing and a Cu-Mn-free leachate for subsequent Ni, Co, and Li recovery.

3.3. Ni Precipitation

Nickel precipitation using DMG was carried out from the leachate after the removal of Cu and Mn under the defined optimal conditions (Step 1—Cu precipitation, Na₂S:Cu = 4:1, T = 20 °C, t = 5 min, without pH adjustment; Step 2—Mn precipitation, KMnO₄:Mn = 1:1, T = 20 °C, t = 15 min, pH ≈ 2). The content of the monitored components in the leachate used for the Ni precipitation experiments is presented in

Table 10. Average content of monitored metals in the Cu-Mn-free leachate for Ni precipitation.

Metal	Co	Li	Ni	Mn	Cu	Al	Fe
Average Content [mg·L−1]	12,410.00	2569.00	346.00	14.93	0.67	434.53	25.08

.

Figure 16a illustrates the effect of temperature on Ni precipitation efficiency at different DMG:Ni molar ratios (2–5). The experiments were carried out at pH ≈ 5 (adjusted with NaOH), with a precipitation time of 30 min and stirring at 300 rpm. Temperatures of 20, 40, 60, and 80 °C were studied to assess their influence on Ni recovery. Figure 16b shows the co-precipitation of other metals during Ni precipitation as a function of the DMG:Ni molar ratio at 80 °C.

Nickel precipitation using DMG proceeds efficiently due to the formation of the highly stable [Ni(DMG)₂] complex (log β = 13.38), which ensures effective removal of Ni from solution [42]. The efficiency of Ni precipitation increases with both temperature and the DMG:Ni molar ratio. At 20 °C, the efficiency ranged from approximately 50% at a 2:1 ratio to 57% at a 5:1 ratio. As the temperature increased to 80 °C, Ni precipitation efficiency rose substantially, reaching 80% at the 2:1 ratio and up to 99.8% at the 5:1 ratio. These results indicate that higher temperatures enhance the reaction kinetics and improve the effectiveness of the complexation reaction and that sufficient DMG is necessary to form the insoluble [Ni(DMG)₂] complex. This complex is highly stable and virtually insoluble in water, and therefore precipitates very effectively, especially when DMG is present in excess [28]. The marked increase in efficiency with temperature demonstrates that nickel precipitation using DMG is highly temperature-sensitive, making optimization of reaction conditions crucial. The highest efficiency (99.8%) was achieved with the combination of the highest tested temperature (80 °C) and the highest DMG:Ni molar ratio (5:1). In addition to nickel precipitation, the co-precipitation of other present metals—Co, Li, Fe, and Al—was also monitored. Figure 16b shows that Fe and Al co-precipitate significantly at 80 °C. Fe precipitation reached its maximum (≈70%) at lower DMG:Ni ratios (2:1–3:1) and slightly decreased at higher ratios, likely due to selective complexation of Ni²⁺ dominating over Fe²⁺ co-precipitation. Aluminum, in contrast, exhibited increasing precipitation efficiency with higher DMG excess, rising from 55% at a 2:1 ratio to 67% at a 5:1 ratio. This is probably caused by hydrolytic precipitation of Al(OH)₃ due to local pH changes and increased ionic strength rather than direct complexation with DMG [42]. Cobalt and lithium showed negligible co-precipitation under all tested conditions.

The reported results correspond to a precipitation time of 30 min. To determine the optimal precipitation time for Ni, additional experiments were conducted, and the time-dependent precipitation efficiency of Ni and other present metals is shown in Figure 17.

The results presented in Figure 17 indicate that Ni precipitation with DMG occurs rapidly within the first minutes, accompanied by significant co-precipitation of Fe and Al. After approximately 15 min, Ni precipitation stabilizes, suggesting that near equilibrium is reached. Al co-precipitation continues beyond 30 min, whereas Fe co-precipitation slightly decreases. Co co-precipitation appears at later times, likely due to its slower complexation with DMG [43], which is undesirable for selectivity. Lithium loss (≈10% after 20 min) likely occurs via physical mechanisms, such as inclusion in the [Ni(DMG)₂] precipitate or adsorption onto Fe and Al particles, rather than chemical complexation [31].

Based on these observations, the optimal precipitation time is 15 min, achieving efficient Ni removal together with significant Fe and Al co-precipitation while minimizing undesired Co and Li co-precipitation.

Analysis of the Obtained Ni Precipitate

The precipitates obtained from the experiments using DMG under conditions that yielded the highest Ni removal efficiency (DMG:Ni molar ratio = 5:1, T = 80 °C, t = 15 min, pH ≈ 5) were analyzed for their chemical composition using the AAS method (

Table 11. Content of monitored metals in the obtained Ni precipitates by precipitation with DMG:Ni = 5:1, T = 80 °C, t = 15 min, 300 rpm, pH ≈ 5, (determined by AAS method).

Metal	Co	Li	Mn	Ni	Cu	Al	Fe
Average Content [wt.%]	2.493	0.005	0.004	16.200	0.002	1.751	3.449

).

The average nickel content in the precipitates obtained under the established optimal conditions (DMG:Ni = 5:1, T = 80 °C, t = 15 min, 300 rpm, pH ≈ 5) was 16.2 wt.%, corresponding to the highest nickel precipitation efficiency of 98.9%. The precipitate thus contained approximately 56% [Ni(DMG)₂] by total mass, while the remaining ≈ 44% consisted of accompanying components (Co, Li, Fe, Al, Mn, and Cu), unreacted DMG, and bound water.

Among the impurities, cobalt, aluminum, and iron were present at significant levels, with average contents of 2.493 wt.% Co, 1.751 wt.% Al, and 3.449 wt.% Fe. Lithium, manganese, and copper were negligible, with average concentrations of 0.005 wt.%, 0.004 wt.%, and 0.002 wt.%, respectively.

Losses of the target metals (Co and Li) remained very low. Based on the leachate composition, Co loss was estimated at ≈1.9%, while Li losses did not exceed 0.5%. The trace presence of Li in the precipitate confirms that this is likely due to physical mechanisms, as previously indicated, such as inclusion in the [Ni(DMG)₂] precipitate or adsorption onto Fe and Al particles [31]. Similarly, Co is present only in trace amounts, most likely due to physical adsorption or mechanical entrapment in the [Ni(DMG)₂] matrix rather than the formation of distinct metal complexes. These findings are consistent with AAS analysis of the liquid phase after precipitation, which confirmed that nearly all Co and Li remained dissolved in the solution.

The SEM-EDX analysis (Figure 18a) revealed a high Ni content in the precipitate, along with the presence of Na, Al, and Fe, consistent with the chemical composition determined by AAS. Two phases were identified in the sample by XRD phase analysis, as shown in Figure 18b. The first phase corresponds to a coordinated low-molecular nickel complex with dimethylglyoxime, most likely the tetradimethylglyoximate complex [Ni(DMG)₂], with the molecular formula Ni₄N₁₆O₁₆C₃₂H₅₆ (JCPDS 17-0299 [34]). A second phase was also detected, corresponding to a related nickel complex structure (JCPDS 42-1981 [34]). The presence of these two related phases suggests a high degree of crystallinity and structural complexity in the final precipitate. No diffraction peaks for Fe or Co were observed, suggesting these impurities are either present in concentrations below the XRD detection limit or exist as amorphous phases.

Nickel precipitation using DMG proved to be highly effective, achieving nearly complete Ni removal from the leachate. However, significant co-precipitation of iron and aluminum also occurred, which reduced the purity of the obtained precipitate. At the same time, this co-precipitation allows for partial removal of unwanted accompanying metals from the leachate before further processing, thereby improving the overall process efficiency. The precipitate, containing Ni along with Fe and Al, can—after composition adjustment, such as dissolution followed by re-precipitation—serve as an intermediate product in nickel recycling to produce new cathode materials, catalysts, or electrical engineering materials.

3.4. Verification of Cu–Mn–Ni Precipitation and Co/Li Losses Using a Sequential Experiment

The sequential precipitation experiment was designed to verify the applicability of the optimal conditions determined in laboratory-scale tests to a larger and more representative leachate volume. While the initial optimization experiments were performed on 300 mL samples under controlled laboratory conditions, the sequential experiment was initiated with 2000 mL of leachate and continued until the entire batch volume was processed. Each precipitation step (Cu → Mn → Ni) was carried out consecutively under the previously established optimal parameters for temperature, pH, reagent type, and molar ratio. The order of metal removal was deliberately selected based on the required pH conditions: copper was precipitated first at the original leachate pH (without adjustment), followed by pH adjustment to 2 for manganese precipitation and to 5 for nickel precipitation. The comparison of leachate composition before and after sequential precipitation is shown in

Table 12. Comparison of average metal contents in the input leachate intended for sequential precipitation and in the output of Cu–Mn–Ni-free leachate, determined by AAS.

Leachate	Average Metals Content [mg·L−1]
	Co	Li	Mn	Ni	Cu	Al	Fe
Input Leachate, V = 2000 mL ± 0	12,895.0	2714.0	875.3	332.7	1141.5	413.0	165.4
Cu–Mn–Ni-Free Leachate, V = 1310 mL ± 27.5	18,805.0	3495.0	120.1	3.686	0.12	217.9	1.40

.

During sequential precipitation, the leachate volume decreased mainly due to partial retention of liquid in the precipitates, sampling losses, and minor evaporation. The concentrations of cobalt and lithium increased from 12.9 g·L⁻¹ and 2.71 g·L⁻¹ to 18.8 g·L⁻¹ and 3.50 g·L⁻¹, respectively, confirming that both elements remained in solution with minimal losses. This demonstrates the high selectivity of the process, as accompanying metals were efficiently removed, while Co and Li were retained and concentrated in the leachate. The mass balance and composition of the obtained precipitates are summarized in

Table 13. Average results of the sequential precipitation experiments—composition of the obtained precipitates, including quantification of the main metal losses, determined by AAS.

Step	Conditions	Metals Content [wt.%]	Losses Co/Li [%]
1.  Cu Precipitation	Na2S:Cu = 4:1, 20 °C, without pH adjustment, t = 5 min, ηCu = 99.98%	Cu 42.14; Co 4.05; Li 0.31; other < 0.12	Co 0.85; Li 2.70
2.  Mn Precipitation	KMnO4:Mn = 1:1, 20 °C, pH = 2, t = 15 min, ηMn = 90.9%	Mn 29.38; Fe 1.554; Al 1.55; Co 4.71; Li 0.60	Co 2.79; Li 2.32
3.  Ni Precipitation	DMG:Ni = 5:1, 80 °C, pH = 5, t = 30 min, ηNi = 98.94%	Ni 15.47; Fe 3.41; Al 4.29; Co 5.34; Li 0.21	Co 1.92; Li 0.48

.

3.4.1. Step 1—Cu Precipitation

The results of verification experiments show that during Step 1 (Cu precipitation), 5.42 g of precipitate containing 42.14 wt.% Cu was formed, with a precipitation efficiency of 99.98% and minimal Co and Li losses (0.85% and 2.7%, respectively). In the 300 mL experiments, Ni and Al co-precipitation began only after 15 min (≈20%) and 30 min (≈18%), respectively (Figure 10). In contrast, in the 2 L sequential experiment, partial co-precipitation was already detected after 5 min; (≈23% Ni and 21% Al), likely due to faster nucleation and growth of CuS particles, which provided a larger surface area and more adsorption sites [44]. Local enrichment of Ni²⁺ and Al³⁺ ions near growing CuS surfaces, as well as residual fine particles from previous steps, may also have promoted this effect. Such early co-precipitation and incorporation of Ni and Al during CuS formation are well documented in hydroxide and sulphide systems [45]. Despite this, the absolute amounts of Ni and Al in the precipitate remained negligible (<0.1 g each). The copper precipitation efficiency was nearly identical in both 300 mL and 2 L experiments, indicating that scale and sequential processing did not affect Cu removal.

3.4.2. Step 2—Mn Precipitation

In Step 2 (Mn precipitation), 19.14 g of precipitate containing 29.38 wt.% Mn was obtained, with an average precipitation efficiency of 90.9%. In the 300 mL experiments, about 80% Fe and 15% Al co-precipitated with Mn after 15 min (Figure 14), whereas in the 2 L sequential experiment, co-precipitation reached 93% Fe and 36% Al. The slightly lower Mn precipitation efficiency in the larger-scale test (≈90% vs. 97%) was likely due to enhanced nucleation and growth of MnO₂ particles with higher surface area, which promoted Fe³⁺ and Al³⁺ co-precipitation and reduced Mn²⁺ availability. Local enrichment of Fe³⁺ and Al³⁺ near MnO₂ surfaces and residual fine particles from the Cu precipitation step likely served as heterogeneous nucleation sites, altering local supersaturation and limiting Mn precipitation. These findings agree with literature reports showing that Fe and Al readily co-precipitate with Mn hydroxides and oxides under similar conditions, influenced by pH, mixing, and ion concentration [46,47].

Co and Ni remained mostly in solution during Mn precipitation, consistent with their low concentrations and higher pH thresholds for precipitation [48,49], explaining their negligible presence in the Mn precipitate and retention for subsequent selective Ni recovery. Overall, Mn and associated impurities were efficiently removed, while the main metals of interest remained in solution for the following Ni precipitation step.

3.4.3. Step 3—Ni Precipitation

In Step 3 (Ni precipitation), 10.72 g of precipitate containing 15.47 wt.% Ni was obtained, with an average Ni precipitation efficiency of 98.9%. Partial co-precipitation of Fe (94.2%) and Al (17.7%) occurred, while Co and Li losses remained minimal (1.9% and 0.5%). In the 300 mL tests, after 30 min, about 10% Li and 50% Fe and Al co-precipitated with Ni (Figure 17). In the 2 L sequential experiment, Li behaviour was similar (≈9%), whereas Fe (94%) and Al (30.5%) co-precipitation was more pronounced. The increased Fe and Al incorporation in the larger system likely resulted from enhanced nucleation and growth of [Ni(DMG)₂] particles and local microenvironments favouring adsorption or co-precipitation of these metals. Residual fine particles and reagents from previous steps probably acted as heterogeneous nucleation sites, promoting Fe and Al co-precipitation [50].

These observations align with literature reports describing Fe–Al hydroxide formation during Ni precipitation and the strong influence of pH, solution volume, and mixing on metal adsorption and co-precipitation [49]. Meanwhile, Co and Li remained mostly in solution, confirming the high selectivity of Ni removal under the applied conditions. Overall, the sequential process maintained excellent Ni removal efficiency while only slightly increasing Fe and Al co-precipitation.

The mass balance of the precipitates corresponded well with the expected metal contents, confirming the effectiveness of the selective separation procedure. The precipitates obtained during sequential Cu–Mn–Ni precipitation showed moderate purity (CuS ≈ 63%, MnO₂ ≈ 46%, [Ni(DMG)₂] ≈ 53%), primarily due to co-precipitation of accompanying metals and the presence of residual moisture and entrained mother liquor. Specifically, the main impurities in each precipitate were: Co and Li in CuS (4.05 wt.% Co, 0.31 wt.% Li); Co, Al, and Fe in MnO₂ (Co 4.7 wt.%, Al 1.55 wt.%, Fe 1.55 wt.%); and Co, Al, and Fe in [Ni(DMG)₂] (Co 5.34 wt.%, Al 4.29 wt.%, Fe 3.41 wt.%). These impurities reduced the overall product purity despite quantitative precipitation efficiencies. Such impurity levels are typical for single-stage precipitation from complex polymetallic leachates and could be further minimized by additional washing steps or recrystallization.

Although the relatively low purity limits their direct industrial use, the precipitates represent valuable secondary raw materials. They can be refined through dissolution and selective re-precipitation to yield higher-purity products. CuS may serve as feedstock in pyrometallurgical Cu production, while purified MnO₂ (≥90%) can be utilized for KMnO₄ production, water treatment, deoxidation in steelmaking, or ceramics [50]. The [Ni(DMG)₂] precipitate, after dissolution and purification, could be processed into NiO or Ni(OH)₂ precursors suitable for cathode materials in lithium-ion batteries and other nickel-based compounds, thus enabling efficient recovery of valuable metals from the leachate.

The mass balance of the precipitates corresponded well with the expected metal contents, confirming the effectiveness of the proposed selective separation procedure. The precipitates obtained during sequential Cu–Mn–Ni precipitation exhibited moderate purity (CuS ≈ 63%, MnO₂ ≈ 46%, [Ni(DMG)₂] ≈ 53%). The main impurities were Co and Li in CuS; Co (4.7 wt.%), Al, and Fe (1.5 wt.%) in MnO₂; and Co (5.3 wt.%), Al (4.3 wt.%), and Fe (3.4 wt.%) in [Ni(DMG)₂], which reduced the overall product purity despite nearly quantitative precipitation yields.

In addition to these elemental impurities, the reduced purity and increased mass of the precipitates were also influenced by the presence of crystallization-bound water and sorbed ionic species (mainly sulphates, alkali cations, and organic residues). This effect was particularly pronounced for MnO₂, where the experimentally obtained precipitate mass (19.14 g) exceeded the theoretically calculated amount (≈2.7 g) by more than sevenfold. Such a large discrepancy indicates substantial incorporation of hydration water, amorphous phases, and entrapped impurities within the oxide structure, which is typical of manganese oxides synthesized at low temperature under acidic conditions [51].

Despite their relatively low purity, the precipitates represent valuable secondary raw materials. Reduced purity is attributed to residual reagents, crystallization-bound water, and amorphous or volatile components, which can be partially removed via controlled thermal treatment or calcination. Further refinement through dissolution and selective re-precipitation can yield higher-purity products. CuS can serve as a feedstock for pyrometallurgical copper production, while purified MnO₂ (≥90%) is suitable for KMnO₄ synthesis, water treatment, steel deoxidation, or ceramics [52]. The [Ni(DMG)₂] precipitate, after dissolution and purification, can be converted into NiO or Ni(OH)₂ precursors for lithium-ion battery cathodes and other nickel-based compounds, enabling efficient recovery of valuable metals from the leachate.

The sequential precipitation process effectively concentrated Co and Li in the final leachate while removing most accompanying metals. As shown in the final analysis, the proposed purification sequence is highly effective, reducing the Fe concentration to a negligible level of 0.0014 g·L⁻¹ and Al to 0.218 g·L⁻¹. Mn was significantly reduced from 0.875 g·L⁻¹ to 0.120 g·L⁻¹ (Table 12). Although these residual amounts of Mn and Al indicate that oxidation and precipitation were not 100% complete under the applied conditions, they are sufficiently low not to interfere with the subsequent selective recovery of Co and Li. T The Co–Li-enriched leachate thus represents a concentrated, refined feed solution for subsequent selective recovery, while minor optimization of Mn and Al removal (e.g., optimization of the KMnO₄ dosage or pH) could further enhance the overall efficiency and product purity. Figure 19 shows a schematic of the proposed sequential precipitation process and the order of steps for removing accompanying metals.

4. Conclusions

The main outcomes of this study can be summarized as follows:

• Selective removal of accompanying metals: Cu was removed as CuS (>99%, pH < 1). Mn was oxidized and precipitated as MnO₂ (≈97% batch, ≈91% sequential at pH ≈ 2). Ni was recovered as [Ni(DMG)₂] (≈99%, pH ≈ 5, T = 80 °C). Fe removal exceeded 99%, while Al reached ≈ 47%.
• Sequential operation performance: The 2 L sequential test confirmed scalability and reproducibility. Mn removal efficiency decreased slightly (≈6%) due to kinetic and redox inhomogeneity.
• Residual components: Most accompanying metals were removed; Co and Li concentrated in the refined leachate. Residual Mn (≈0.12 g·L⁻¹) and Al (≈0.218 g·L⁻¹) remained, with minor impact on subsequent recovery. Additional Mn oxidation or pH-controlled Al removal could improve leachate quality.
• Co and Li behaviour: Both metals remained mostly in solution. The highest Li loss (≈10%) occurred during Ni precipitation, likely due to transient adsorption rather than true co-precipitation.
• Purity and utilization of precipitates: CuS, MnO₂, and [Ni(DMG)₂] showed moderate purity (≈46–63%) due to Co, Al, Fe, and Li impurities. After purification or thermal treatment, CuS can be used in copper production, MnO₂ in permanganates, catalysts, or ceramics, and [Ni(DMG)₂] as NiO/Ni(OH)₂ precursors for cathodes. Low-purity solids can still be valorised.
• The economic feasibility of the proposed recycling process is a key factor for its potential industrial application. The sequential precipitation route utilizes widely available and relatively inexpensive inorganic reagents, such as Na₂S and KMnO₄. The efficiency of these reagents at ambient temperatures (20 °C) significantly reduces energy-related operational costs. Furthermore, although DMG is a more specialized and costlier reagent, its high selectivity for nickel is economically justified. By preventing the co-precipitation of valuable Co and Li into the Ni fraction, the market value of the final Co-Li concentrated solution is preserved. The modular nature of the process also allows for the recovery of metals in separate, concentrated solid forms (CuS, MnO₂, and [Ni(DMG)₂]), which simplifies subsequent handling and potential secondary processing. This approach minimizes the generation of low-value bulk sludge, thereby reducing disposal costs and improving the overall economic balance of the leachate valorisation. Further research should focus on selective Co and Li recovery from the Cu–Mn–Ni-free leachate via multi-step precipitation by optimizing reagent type, dosage, and pH to maximize yield and purity while minimizing Li losses.