Time-Dependent Behavior of Waste Lithium-Ion Batteries in Secondary Copper Smelting

: As the electriﬁcation sector expands rapidly, the demand for metals used in batteries is increasing signiﬁcantly. New approaches for lithium-ion battery (LIB) recycling have to be investigated and new technologies developed in order to secure the future supply of battery metals (i.e., lithium, cobalt, nickel). In this work, the possibility of integrating LIB recycling with secondary copper smelting was further investigated. The time-dependent behavior of battery metals (Li, Co, Ni, Mn) in simulated secondary copper smelting conditions was investigated for the ﬁrst time. In the study, copper alloy was used as a medium for collecting valuable metals and the distribution coefﬁcients of these metals between copper alloy and slag were used for evaluating the recycling efﬁciencies. The determined distribution coefﬁcients follow the order Ni >> Co >> Mn > Li throughout the time range investigated. In our study, the evolution of phases and their chemical composition were investigated in laboratory-scale experiments under reducing conditions of oxygen partial pressure p(O 2 ) = 10 − 10 atm, at 1300 ◦ C. The results showed that already after 1 h holding time, the major elements were in equilibrium. However, based on the microstructural observations and trace elements distributions, the required full equilibration time for the system was determined to be 16 h.


Introduction
It is evident that the demand for lithium-ion batteries (LIBs) is significantly increasing as the electrification sector expands. According to the International Energy Agency (IEA), roughly 15-25 million electric vehicles will be sold annually by 2025 and 25-40 million by 2030 [1]. As the production of rechargeable batteries increases, the demand for battery raw materials rises as well. The energy transformation is the main factor influencing the global demand for lithium, cobalt and nickel [2]. As most of the battery metals are produced only in a few countries, supply risks, as well as environmental and ethical issues, may occur [3].
One of the important strategies for circulating the critical battery materials in the supply chain is finding the most efficient ways for recovering the materials from waste LIBs [4]. In recent years, great effort has been made globally to develop efficient recycling technologies for lithium-ion batteries, and these technologies have been described in several review papers [4][5][6][7][8][9].
Currently, pyrometallurgical processes are widely used in industry as a route for recycling various metal-rich waste streams, including batteries. The advantages and disadvantages of high-temperature processes in recycling were described in the work of Chen et al. [10]. The authors highlighted that the pyrometallurgical treatment process is simple and mature, and does not require physical pretreatment (e.g sorting or size reduction) [10]. Moreover, pyrometallurgical processes have the advantage of high-rate chemical reactions, which lead to high treatment capacities [7]. Pyrometallurgical methods for battery recycling include thermal pretreatment, roasting/calcination and smelting. In every experiment, the starting mass of the battery scrap was approximately 4 wt% of the mass of the copper alloy. The amount of battery scrap was chosen so that the initial concentration of Co in the sample was 1 wt% of the mass of copper alloy, as in our previous equilibrium study [11].

Experimental Methods
The applied experimental method was based on heating the sample charge at a controlled temperature and gas atmosphere followed by rapid quenching into the ice-water mixture. Experiments were conducted under simulated black copper smelting conditions at 1300 • C at reducing conditions of oxygen partial pressure pO 2 = 10 −10 atm. The laboratory vertical furnace (Nabertherm, Lilienthal, Germany, RHTV 120-150/18) with MoSi 2 heating elements and an alumina reaction tube (Frialit AL 23; Friatec AG, Mannheim, Germany; 45 mm OD and 38 mm ID). A calibrated S-type Pt/Pt10Rh thermocouple (Johnson-Matthey, London, UK) with an uncertainty of ±3 • C was used to control the experimental temperature. The furnace setup was presented in detail in a previous study of Klemettinen et al. [22].
The prepared mixture containing slag, copper alloy and battery scrap was placed in an alumina crucible held by a Pt-wire basket. The first 0.2 g of the metal alloy was weighed into the crucible, then approximately 0.008 g of battery scrap was added on top of the metal alloy, followed by adding 0.2 g of slag on top of the mixture. The weight ratio between metal alloy, slag and battery scrap was 1:1:0.04. The crucible was hooked with a platinumrhodium wire and pulled up to the hot zone of the furnace. More details regarding the procedure of introducing the sample into the furnace were described in a previous study of Dańczak et al. [28]. The samples were kept in the hot zone for different times, from 1.5 min to 48 h. Holding times of less than 1.5 min were tested but omitted since the samples did not melt completely. The gas atmosphere was obtained by mixing CO and CO 2 with flow rates of 174.5 mL/min and 125.6 mL/min, respectively. The gas flow rates were calculated using MTDATA software and the SGTE pure substances database [33]. During experiments, the gas flow gates were controlled using mass flow controllers (DFC 26, Aalborg, Orangeburg, NY, USA). After appropriate contact times, the samples were rapidly quenched in an ice-Batteries 2022, 8, 190 4 of 13 water mixture without compromising the gas atmosphere. The quenched samples were cut in half, mounted in epoxy resin, ground, polished and carbon coated (Figure 1). samples did not melt completely. The gas atmosphere was obtained by mixing CO and CO2 with flow rates of 174.5 mL/min and 125.6 mL/min, respectively. The gas flow rates were calculated using MTDATA software and the SGTE pure substances database [33]. During experiments, the gas flow gates were controlled using mass flow controllers (DFC 26, Aalborg, Orangeburg, NY, USA). After appropriate contact times, the samples were rapidly quenched in an ice-water mixture without compromising the gas atmosphere. The quenched samples were cut in half, mounted in epoxy resin, ground, polished and carbon coated ( Figure 1).

Figure 1.
Photograph of a typical sample cross-section in epoxy after analyses. The violet color of the copper alloy is a result of carbon coating. The small holes on the slag and copper alloy are laser pits produced by LA-ICP-MS. Photo: Aalto University, Eren Ö ztekin.

Sample Analysis
The sample microstructures were analyzed with SEM (Scanning Electron Microscope; Mira3, Tescan, Czech Republic) and the composition of phases was preliminarily investigated with EDS (Energy Dispersive Spectrometer, Thermo Fisher Scientific, Waltham, MA, USA). For more accurate phase composition analyses regarding major and trace elements, EPMA and LA-ICP-MS were used, respectively.
The EPMA analyses were obtained with CAMECA SX100 electron microprobe at the Geological Survey of Finland (GTK) using WDS (wavelength-dispersive spectrometry) technique. The accelerating voltage and beam current were 20 kV and 60 nA, respectively. A focused beam was used for the spinel phase, while a defocused beam was used for slag (20 µ m) and the metal phase (50 µ m). Analytical results were corrected using the PAP online correction program [34]. Natural minerals and synthetic metals were used as standards as follows: obsidian for O (Kα), quartz for Si (Kα), almandine for Al (Kα), diopside for Mg (Lβ), hematite for Fe (Mα), rhodonite for Mn (Kα), cobaltite for Co (Kα), copper for Cu (Lα), tin for Sn (Lα) and nickel for Ni (Kα).
The concentrations of several elements fell under the detection limits of EPMA, so their concentrations were quantified using LA-ICP-MS at GTK. The details of the equipment used have been presented previously [11]. The metal alloy was analyzed using a 50 µ m diameter laser spot size, 10 Hz pulse frequency and 3.2 J/cm 2 power. External calibration was conducted using UQAC FeS-1 pressed sulfide pellet [35] and USGS MASS1 [36] was used as a monitor. 60 Ni isotope was used as the internal standard. The slag was also

Sample Analysis
The sample microstructures were analyzed with SEM (Scanning Electron Microscope; Mira3, Tescan, Czech Republic) and the composition of phases was preliminarily investigated with EDS (Energy Dispersive Spectrometer, Thermo Fisher Scientific, Waltham, MA, USA). For more accurate phase composition analyses regarding major and trace elements, EPMA and LA-ICP-MS were used, respectively.
The EPMA analyses were obtained with CAMECA SX100 electron microprobe at the Geological Survey of Finland (GTK) using WDS (wavelength-dispersive spectrometry) technique. The accelerating voltage and beam current were 20 kV and 60 nA, respectively. A focused beam was used for the spinel phase, while a defocused beam was used for slag (20 µm) and the metal phase (50 µm). Analytical results were corrected using the PAP on-line correction program [34]. Natural minerals and synthetic metals were used as standards as follows: obsidian for O (Kα), quartz for Si (Kα), almandine for Al (Kα), diopside for Mg (Lβ), hematite for Fe (Mα), rhodonite for Mn (Kα), cobaltite for Co (Kα), copper for Cu (Lα), tin for Sn (Lα) and nickel for Ni (Kα).
The concentrations of several elements fell under the detection limits of EPMA, so their concentrations were quantified using LA-ICP-MS at GTK. The details of the equipment used have been presented previously [11]. The metal alloy was analyzed using a 50 µm diameter laser spot size, 10 Hz pulse frequency and 3.2 J/cm 2 power. External calibration was conducted using UQAC FeS-1 pressed sulfide pellet [35] and USGS MASS1 [36] was used as a monitor. 60 Ni isotope was used as the internal standard. The slag was also analyzed using 50 µm diameter spots, but with 5 Hz pulse frequency and 2.17 J/cm 2 power. NIST 610 and 612 [37] were used for calibration and as a monitor, respectively. The internal standard was the 29 Si isotope.
The analysis protocol followed a 2-s pause, 5 pre-ablation shots, 20-s flushing, 20-s background analysis and either 300 (metal, 10 Hz) or 200 (slag, 5 Hz) laser shots. The mass signal intensities were converted to elemental concentrations using Glitter software [38]. The detection limits obtained using EPMA and LA-ICP-MS are shown in Table S1 in Supplementary Materials. Figure 2 shows the general microstructure of a sample after a short (10 min), and long (48 h) holding time. Every sample consisted of a glassy slag phase, metal alloy, alumina crucible and primary spinel phase. In every sample, the spinel grains, so-called discrete spinels, were found within the slag. Additionally, in all samples, a spinel layer was formed between the slag and alumina crucible. However, the thickness and uniformity of this layer increased significantly as the holding time increased. The holding time did not seem to influence the microstructure of the metal alloy, as a large alloy droplet was observed in every sample, even after 1.5 min time. No quantifiable differences were found between the visual appearance of metal alloys in samples after different holding times. analyzed using 50 µ m diameter spots, but with 5 Hz pulse frequency and 2.17 J/cm 2 power. NIST 610 and 612 [37] were used for calibration and as a monitor, respectively. The internal standard was the 29 Si isotope. The analysis protocol followed a 2-s pause, 5 pre-ablation shots, 20-s flushing, 20-s background analysis and either 300 (metal, 10 Hz) or 200 (slag, 5 Hz) laser shots. The mass signal intensities were converted to elemental concentrations using Glitter software [38]. The detection limits obtained using EPMA and LA-ICP-MS are shown in Table S1 in Supplementary Materials. Figure 2 shows the general microstructure of a sample after a short (10 min), and long (48 h) holding time. Every sample consisted of a glassy slag phase, metal alloy, alumina crucible and primary spinel phase. In every sample, the spinel grains, so-called discrete spinels, were found within the slag. Additionally, in all samples, a spinel layer was formed between the slag and alumina crucible. However, the thickness and uniformity of this layer increased significantly as the holding time increased. The holding time did not seem to influence the microstructure of the metal alloy, as a large alloy droplet was observed in every sample, even after 1.5 min time. No quantifiable differences were found between the visual appearance of metal alloys in samples after different holding times.  The visual evolution of discrete spinels as a function of increasing holding time is presented in Figure 3. In the samples after short holding times (1.5-5 min), the discrete spinel grains were smaller than 10 microns and seemed to be 'dispersed' within the whole slag phase. Moreover, these spinels did not have a well-defined shape or size. With longer holding times, the individual spinel grains seemed to accumulate and increase in size, which can be seen in the microstructure image of the sample after 10 min holding time. However, these grains were still not big enough to be properly analyzed with the EPMA technique, without obtaining a signal from the surrounding slag phase. The size of the spinel grains was enough for the compositional analysis with EPMA after 30 min holding time. As the holding time increased further, the spinel grains grew in size and had more defined shapes. The color of the spinel in the SEM-backscattered electron images also became darker, corresponding to the change in composition from iron-oxide-rich to alumina-rich [24]. There were no visible differences in the sample microstructures after 16 h contact time.

Time-Dependent Evolution of Sample Microstructure
The visual evolution of discrete spinels as a function of increasing holding time is presented in Figure 3. In the samples after short holding times (1.5-5 min), the discrete spinel grains were smaller than 10 microns and seemed to be 'dispersed' within the whole slag phase. Moreover, these spinels did not have a well-defined shape or size. With longer holding times, the individual spinel grains seemed to accumulate and increase in size, which can be seen in the microstructure image of the sample after 10 min holding time. However, these grains were still not big enough to be properly analyzed with the EPMA technique, without obtaining a signal from the surrounding slag phase. The size of the spinel grains was enough for the compositional analysis with EPMA after 30 min holding time. As the holding time increased further, the spinel grains grew in size and had more defined shapes. The color of the spinel in the SEM-backscattered electron images also became darker, corresponding to the change in composition from iron-oxide-rich to alumina-rich [24]. There were no visible differences in the sample microstructures after 16 h contact time.

Concentration of Major Elements in Slag and Spinel
The concentrations of major elements (Fe, Al, O, Mg and Si) were analyzed with the EPMA technique. Figure 4 shows these concentrations in slag and spinel as a function of

Concentration of Major Elements in Slag and Spinel
The concentrations of major elements (Fe, Al, O, Mg and Si) were analyzed with the EPMA technique. Figure 4 shows these concentrations in slag and spinel as a function of time. The biggest changes in the concentrations of major elements in slag occurred within the first 5 min.
The concentration of Fe in slag first decreased from 36.5 wt% at 1.5 min holding time to 34.4 wt% after 2.5 min holding time, and as the time increased to 20 min, the concentration increased to 38.4 wt%. After 48 h, the Fe concentration was 35.4 wt%. Oxygen concentration in slag firstly also decreased slightly, and the final value after 48 h was 38.9 wt%. The concentration of Al in the slag increased from 6.4 wt% after 1.5 min to 7.9 wt% after 48 h, whereas the concentration of Mg decreased slightly from 3.4 wt% to 3.1 wt% within the same time. The concentration of Si in the slag remained relatively constant throughout the time series, with the final value being 15.5 wt% after 48 h.

Composition of Metal Alloy
The concentrations of Cu, Co, Ni, O and Sn in the metal alloy, analyzed with EPMA, are presented in Figure 5. The metal alloy was formed already after 1.5 min holding time

Composition of Metal Alloy
The concentrations of Cu, Co, Ni, O and Sn in the metal alloy, analyzed with EPMA, are presented in Figure 5. The metal alloy was formed already after 1.5 min holding time and the Cu concentration at that time was 94.3 wt%. With the increasing holding time, Cu concentration varied between 93 and 96 wt%, with the final value being 94.1 wt% after 48 h. The concentration of Sn in the metal alloy reached 3.5 wt% after the shortest time of 1.5 min. With longer holding times, its concentration varied significantly between 1.7 and 4.2 wt%. However, the concentration of Sn after the longest holding time of 48 h was 3.4 wt%; similar as after 1.5 min. The large variation in Sn concentration can be attributed to the stripe-like structure of the metal alloy shown in Figure 2, bottom right corner. Some Sn evaporation may also have taken place [23], contributing to the large concentration variations between samples as well as within one sample. h. The concentration of Sn in the metal alloy reached 3.5 wt% after the shortest time of 1.5 min. With longer holding times, its concentration varied significantly between 1.7 and 4.2 wt%. However, the concentration of Sn after the longest holding time of 48 h was 3.4 wt%; similar as after 1.5 min. The large variation in Sn concentration can be attributed to the stripe-like structure of the metal alloy shown in Figure 2, bottom right corner. Some Sn evaporation may also have taken place [23], contributing to the large concentration variations between samples as well as within one sample. The concentration of iron in the metal alloy increased from 0.1 wt% after 1.5 min to 1 wt% after 8 h holding time. After this time, its concentration decreased slightly to 0.8 wt%.
The concentration values of nickel were found to be scattered between 0.5 and 1.4 wt% at different holding times, which can also be attributed to the stripe-like structure of the alloy, i.e., the brighter stripes ( Figure 2) contain higher concentrations of nickel and tin than the matrix. Generally, when tin and nickel concentrations in the alloy decreased, copper concentration increased. The cobalt and oxygen concentrations in the alloy remained quite stable as a function of time, approximately 0.5 wt% and 0.2 wt%, respectively. It should be highlighted that after 1 h holding time, the concentrations of Co, Cu, Ni, Fe and O reached the same values as after 48 h.

Discussion
In a multi-element system, the change in concentration of elements in the slag or metal alloy may not always represent the actual change in the recovery of these metals to the metal phase. In our study, the industrial battery scrap used in the experiments was a heterogenous mixture of chemical compounds. Therefore, the starting concentrations of metals in the system may slightly vary in each experiment. When evaluating the recovery of different (trace) metals to the alloy phase, the distribution coefficients of these metals between alloy and slag provide information independent of the slight variations in the starting concentration between different samples. The concentration of iron in the metal alloy increased from 0.1 wt% after 1.5 min to 1 wt% after 8 h holding time. After this time, its concentration decreased slightly to 0.8 wt%.
The concentration values of nickel were found to be scattered between 0.5 and 1.4 wt% at different holding times, which can also be attributed to the stripe-like structure of the alloy, i.e., the brighter stripes ( Figure 2) contain higher concentrations of nickel and tin than the matrix. Generally, when tin and nickel concentrations in the alloy decreased, copper concentration increased. The cobalt and oxygen concentrations in the alloy remained quite stable as a function of time, approximately 0.5 wt% and 0.2 wt%, respectively. It should be highlighted that after 1 h holding time, the concentrations of Co, Cu, Ni, Fe and O reached the same values as after 48 h.

Discussion
In a multi-element system, the change in concentration of elements in the slag or metal alloy may not always represent the actual change in the recovery of these metals to the metal phase. In our study, the industrial battery scrap used in the experiments was a heterogenous mixture of chemical compounds. Therefore, the starting concentrations of metals in the system may slightly vary in each experiment. When evaluating the recovery of different (trace) metals to the alloy phase, the distribution coefficients of these metals between alloy and slag provide information independent of the slight variations in the starting concentration between different samples.
In metal-slag equilibriums at a high temperature, the oxidic dissolution reaction of a minor element X with a valence of 2v in the slag can be expressed by Equation (1).
The equilibrium constant K for the above reaction can be described by the activities of X in metal and XO v in slag, according to Equation (2) where a i is the activity of a chemical species and p O 2 is oxygen partial pressure. As described in the work of Takeda and Yazawa [39,40], the distribution ratio of an element X between molten metal and the slag is expressed in Equation (3): where the [ ] and ( ) brackets represent the copper alloy and slag phases, respectively. In the above equation, L Cu/s (X) is the distribution coefficient of element X between copper alloy and slag; n T is the total moles of constituents in 100 g of each phase and γ is the activity coefficient.
The distribution coefficient described with Equation (3) is often used while studying the behavior of trace metals in different systems in metallurgical processes. In this study, copper alloy is used as a medium for collecting the trace metals and the distribution coefficients between copper alloy and slag are essential parameters utilized for evaluating the recycling efficiencies of different metals in copper smelting. If the distribution coefficient of a metal is below 1 (or 0 in logarithmic scale), most of this metal distributes into the slag phase, where its recovery is difficult.
The distribution coefficients of metals are typically determined at equilibrium conditions and presented as a function of oxygen partial pressure or temperature, or of concentration of additives (e.g., CaO, MgO, K 2 O). In this study, the experiments were conducted at a constant temperature and oxygen partial pressure. In all experiments, the starting composition of the mixture was also constant, neglecting the possible variations in battery scrap composition mentioned earlier. The only controlled variable was the high-temperature holding time. Therefore, in this study, the distribution coefficients of different metals were presented as a function of contact time (t). The distribution coefficient values of metals determined at selected times (t) can be described by Equation (4) [14].
(4) Figure 6 shows the logarithms of distribution coefficients of Li, Mn, Ni, Sn, Co, Pb, Fe and Cu between copper alloy and the slag as a function of holding time. Comparisons with our previous equilibrium studies [11,28] are also presented. The calculated values of distribution coefficients and their uncertainties are presented in Table S6 in Supplementary Materials. For copper and iron, the most significant changes in the calculated distribution coefficients occurred before 2.5 min of holding. During that time, the logarithmic distribution coefficient of copper decreased from 3.0 at 1.5 min to 2.2 at 2.5 min and the logarithmic distribution coefficient of iron increased from −2.5 to −2.0. After 2.5 min holding time, the distribution coefficient of copper remained stable, at approximately 2.2 in log scale, all the way up to the longest time. In comparison, the logarithmic distribution coefficient of iron increased further up to −1.6 during the first 60 min. After that, its value remained stable. The low value of iron distribution coefficient indicates that most of the iron remained in the slag phase as iron oxides.
Similar to copper and iron, the distribution coefficient of cobalt decreased the most significantly before 2.5 min holding time, from 1.0 to 0.0 in a log scale. After that time, it increased slightly to 0.1. This is in agreement with the results of our previous equilibrium study [11]. The logarithmic distribution coefficient value close to 0 indicates that cobalt is basically evenly distributed between copper alloy and the slag at pO 2 = 10 −10 atm.
In the case of lead, its calculated logarithmic distribution coefficient changed between 1.0 and 1.5 at different contact times without a visible trend. The concentration of lead in the slag decreased close to or even below the LA-ICP-MS detection limits at 8 h and longer holding times, which contributes to the uncertainty of the true distribution coefficient values after long holding times. For copper and iron, the most significant changes in the calculated distribution ficients occurred before 2.5 min of holding. During that time, the logarithmic distrib coefficient of copper decreased from 3.0 at 1.5 min to 2.2 at 2.5 min and the logari distribution coefficient of iron increased from −2.5 to −2.0. After 2.5 min holding tim distribution coefficient of copper remained stable, at approximately 2.2 in log scale, a way up to the longest time. In comparison, the logarithmic distribution coefficient o increased further up to −1.6 during the first 60 min. After that, its value remained s The low value of iron distribution coefficient indicates that most of the iron remain the slag phase as iron oxides.
Similar to copper and iron, the distribution coefficient of cobalt decreased the significantly before 2.5 min holding time, from 1.0 to 0.0 in a log scale. After that ti increased slightly to 0.1. This is in agreement with the results of our previous equilib study [11]. The logarithmic distribution coefficient value close to 0 indicates that co basically evenly distributed between copper alloy and the slag at pO2 = 10 −10 atm.
In the case of lead, its calculated logarithmic distribution coefficient changed bet 1.0 and 1.5 at different contact times without a visible trend. The concentration of le the slag decreased close to or even below the LA-ICP-MS detection limits at 8 h and l The logarithmic distribution coefficients of lithium and manganese have very negative values and are much lower in comparison to the other trace elements in this study, which shows that lithium and manganese deport strongly into the slag phase rather than into copper alloy under the investigated conditions. Their distribution coefficient values seem to be fluctuating without clear trends, which can be explained by their extremely low concentrations in the copper alloy. However, the values are in fair agreement with our previous equilibrium study [11].
The calculated distribution coefficients L Cu/s (X) t of battery metals (Li, Co, Ni, Mn) followed the order of Ni >> Co >> Mn > Li at both the shortest (1.5 min) and the longest (48 h) holding time. This order corresponds to the Ellingham diagram showing the stabilities of battery metal oxides [11].

Conclusions
As battery metals such as lithium, cobalt and nickel, are characterized by high demand and/or supply risks, new ways for securing their availability in the future have to be developed. Recycling lithium-ion batteries through high-temperature processes is a viable option for recovering some of the valuable metals within. Integration of battery recycling with already existing pyrometallurgical operations helps decrease investment costs compared to building greenfield facilities. However, changing the feeds of existing smelters introduces many new elements into the system, and therefore influences the process chemistry and recovery of valuables.
In this study, the possibility of integrating LIB recycling with secondary copper smelting was further investigated. The behavior of battery metals in simulated reducing conditions of secondary copper smelting was investigated as a function of time for the first time. The evolution of phases in the system and the required equilibration time were investigated as well.
The visual observations regarding sample microstructure are important for determining the equilibration time. One important criterion for the achievement of equilibrium is that the phases present do not change as a function of equilibration time [23]. In our study, already after 1.5 min holding time all equilibrium phases, i.e., slag, metal alloy and spinel were present and remained in the samples with the longer holding times. Other important criteria are that all phases are homogeneous, and the microstructure does not change as a function of time [13,23]. In this study, the most significant change in sample microstructure was connected to the spinel layer and spinel grains. The spinel layer between the slag and crucible became much thicker and more uniform as a function of time, and the size of the discrete spinels increased as well. These changes were observed until 16 h holding time. After 16 h, the phases were homogeneous and the microstructures of samples did not change anymore.
In this study, the chemical compositions were analyzed using the state-of-the-art direct phase analysis methods EPMA and LA-ICP-MS. The concentrations of major elements in the slag remained surprisingly constant throughout the investigated time series, apart from iron, which also stabilized at approximately 30 min holding time. In spinel, the concentrations of major elements changed until 1 h holding time, after which they remained basically stable over the remaining time. The concentrations of major elements in the metal alloy after 1 h holding time reached very similar values as after 48 h contact time.
The results indicated that already after 1 h holding time, the major elements are in equilibrium. However, the observations regarding sample microstructure as well as trace element distribution coefficients suggest that a 16 h holding time is required to obtain steady-state microstructure and homogeneous phases. Therefore, the equilibration time cannot be verified only based on the concentrations of major elements. The distribution of trace elements between metal alloy and slag, as well as microstructural observations, must be taken into consideration. Based on the data presented in Figure 6 as well as the microstructural observations, it can be concluded that 16 h is sufficient for equilibrating the samples of this study, which also verifies that the equilibration times chosen in our previous studies have been sufficient [11,20,22,24,28]. The distribution coefficients of Pb, Li and Mn were somewhat fluctuating even after 16 h due to analysis difficulties associated with extremely low concentrations in slag (Pb) or alloy phase (Li, Mn).
The distribution coefficients of battery metals (Li, Co, Ni, Mn) between metal alloy and slag were investigated as a function of time and their values followed the order of Ni >> Co >> Mn > Li at both the shortest (1.5 min) and the longest (48 h) holding time.
The logarithmic values of the distribution coefficients suggest that most of the Ni can be recovered to the metal phase. In the case of cobalt, half of it can be recovered in the metal alloy and the other half is deported to the slag under the experimental conditions applied in this study. Lithium and manganese heavily deport to the slag phase and are basically lost in current copper smelting operations.

Supplementary Materials:
The following supporting information can be downloaded at: https: //www.mdpi.com/article/10.3390/batteries8100190/s1. Table S1: EPMA and LA-ICP-MS detection limits (in ppm). Table S2: Average concentrations and standard deviations of aluminum, iron, magnesium, oxygen, silicon and copper in metal alloy, slag and spinel. All results from EPMA. Table S3: Average concentrations and standard deviations of cobalt, nickel and tin in metal alloy, slag and spinel. All results from EPMA. Table S4: Average concentrations and standard deviations of Li, Co, Mn, and Ni in metal and slag phases, based on LA-ICP-MS analyses. Table S5: Average concentrations and standard deviations of Cu, Pb and Sn in metal and slag phases, based on LA-ICP-MS analyses. Table S6: Distribution coefficients of Cu, Sn, Ni, Pb, Co, Fe, Mn and Li between metal alloy and slag and their uncertainties.