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. 2026 Jan 24;16:6129. doi: 10.1038/s41598-026-36924-1

High purity lithium recovery from spent lithium-ion batteries using commercial nanofiltration membranes: a comparative performance assessment

Mamoona Alam 1,2,✉, Bart Van der Bruggen 2,3,4, Muhammad Ahsan Khan 2, Pengrui Jin 2, May Bin-Jumah 5, Mohammad Ibrahim 1,✉
PMCID: PMC12901316  PMID: 41580546

Abstract

The growing demand for lithium underscores the need to recover it efficiently from secondary resources such as spent lithium-ion batteries. This study investigates four commercial nanofiltration membranes (XN-45, NF-270, NF-90, and NFW) for lithium recovery from LIB synthetic leachate. These membranes, expected to have high permeability and moderate salt selectivity, were evaluated using single-ion and mixed-ion feed solutions containing Li⁺, Ni2⁺, Co2⁺, Mn2⁺, Al3⁺, and Fe3⁺. Lithium exhibited a low rejection by all membranes due to its monovalent nature, with XN-45 and NF-270 showing the rejection (18.5% and 19%), and the highest permeation indicating their potential for lithium recovery. Multivalent ions showed markedly higher rejections, particularly for the tighter NF-90 and NFW membranes, where multivalent ions exceeded 90% rejection. Mixed-ion conditions further enhanced rejection through competitive electrostatic interactions. The established order of performance based on rejection was NFW > NF-90 > NF-270 > XN-45 for multivalent ions, which displayed a clear basis for membrane selection. The findings demonstrate the applicability of commercial nanofiltration for lithium recovery and highlight its potential as an effective strategy in battery recycling and circular-economy processes and provides a clear framework for membrane selection in integrated lithium recovery and heavy-metal removal processes.

Keywords: Nanofiltration commercial membranes, Spent LIBs, Lithium recovery, Recycling methodologies

Subject terms: Chemistry, Materials science, Nanoscience and technology

Introduction

Lithium has high importance in the metal industry due to its wide range of attributes like high electro-chemical potential (3.045 V) and high energy density making it a suitable candidate for lithium-ion batteries (LIBs), ceramics, glass, and polymer industry, as well as in aluminum production1. At present more than 37% of the batteries market is worldwide based on LIBs. This is increasing with time due to the digitalization of many Equipments parts.2. The accelerating global transition towards the electric mobility is due to the upgradation of vehicles which results in an increasing number of spent batteries. Since, the cathode material of LIBs is composed of valuable metals, spent batteries to be considered a secondary source of these valuable metals3–5. The main source of lithium extraction are brine and minerals ores. Without considering other primary sources and keeping the increasing demand of lithium calls for the exploration and processing of all feasible resources particularly the secondary ones6,7. To ensure a resilient and sustainable supply chain attention is increasingly shift towards the recycling of LIBs. Recovering lithium from these secondary streams not only mitigates resource depletion and waste generation but also supports the circular economy principles by transforming waste into valuable materials8–10. Moreover, a proper treatment of spent LIBs is also needed to avoid substantial heavy metals contamination due to their release in the environment. In recent past, extensive work has been done in view of recycling of LIBs. A range of different industrial routes and procedures are focused on the recovery of valuable metals with a minimal focus on the recovery of lithium11–14. The widening gap between the global lithium production and the anticipated demand underscores the critical need for advance lithium and recycling technologies to ensure the long-term viability of the current lithium-based economy15.

Presently, most of the world’s lithium supply is obtained from the mining of rocks and brine salt lakes, both of which have significant economic and environmental challenges16,17. Ore mining is energy-intensive and generates substantial waste, while brine consumes a large amount of water and requires a long evaporation time16,18–20. Moreover, these conventional methods are geographically limited and vulnerable to geopolitical constrains20–23. In contrast, secondary sources such as spent lithium-ion batteries and industrial effluents remain underutilized, despite their high lithium content and recycling potential24–27. Therefore, developing clean, economical, and scalable technologies for the recovery of lithium from secondary resources has become the priority in research and technology development.

Among the conventional methods for recycling of LIBs hydrometallurgical methods are the most economical. In this approach, a leaching solution is produced. which usually contains both lithium and other valuable heavy metals28–30. The key challenge to handle the leachate from spent LIBs is its very low pH which requires neutralization for further processing and separations31–34. Sometimes the process of neutralization can lead to precipitation of supersaturated compounds, and this can constitute a key factor for the loss of precious metals as well as lithium35–37. To overcome these challenges, a membrane-based strategy for lithium recovery from synthetic leaching solution was developed, in which the synthetic leachate is treated via nano-filtration method. In this study advance lithium recovery was investigated by systematic comparison between the widely used commercial nano-filtration membranes under similar and representative lithium-ion battery leachate conditions. Lithium-ion separation is assessed through permeation and in the presence of other in competition multivalent ions rather than rejection trend alone. By linking the physiochemical properties of membranes with separation behaviour, the current study provides a good practical guidance for membrane selection in the recycling of LIBs.

In this paper, a representative spent LIBs synthetic leachate, featuring a low lithium concentration and a high salt concentration was selected as model system. The separation behavior of lithium from the leachate was subsequently examined using four commercial nano-filtration membranes.

Materials and methods

Chemicals and membranes

Synthetic solution of LIBs lixiviates were prepared. The chemical regents used were nickel (II) sulfate hexahydrate NiSO4.6H2O 99% from Thermo-scientific, cobalt (II) nitrate hexahydrate Co (NO3)2. 6H2O 99% from ACROS, manganese (II) sulfate tetrahydrate MnSO4. 4H2O 99% from Thermo-scientific, Iron (II) sulfate heptahydrate FeSO4.7H2O 99% from Sigma-Aldrich, aluminum chloride AlCl3 98% from Sigma Aldrich, lithium sulfate LiSO4 99% from Thermo-Scientific, fuming HCl 37% from Merck, polyethylene glycol PEG, 200 MW, 400 MW, 600 MW and 1000 MW from Sigma-Aldrich. Deionized water (DI) was consumed from Lab installed RO setup.

Commercial NF Membranes XN-45, NF-270, NF-90 and NFW were obtained from STERLI-TECH Corporations USA. Their physical features are summarized in Table 1.

Table 1.

Data provided by the manufacturer for the physical characteristics of the NF membranes.

XN45 NF270 NF90 NFW
Supplier TriSep Dow Filmtec Dow filmtec Synder
Chemical nature Polypiperazine-amide polyamide-TFC cellulose acetate Polyamide-TFC Polyamide-TFC Proprietary polyamide-TFC
Type Process softening chlorine resistant process High recovery process Mineral concentration high rejection low energy High flux, softening high rejection
Permeability 10 4 5 7
Molecular weight cut-off [Da] 150 Da ~ 500 Da  < 300 150 Da ~ 300 Da  ~ 600–800 Da
MgSO4 Rejection 90.0–99.0% 98.0% 98.0% 98.0%
Max. pressure [bar] 10 8 15 10
Temperature [°C] 42 41 40 40
pH range 2–11 2–11 0–9 3–10.5
Flux [(GFD)/psi] 20/110 22.9/70 10–19/225 65–70/110
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Experimental set-up

A lab-based bench-top crossflow set-up was used for the valorization of the process of recycling of spent LIBs. It is a one-cell customized set-up to investigate the performance of four NF commercial membranes. In step one, 4 L of synthetic LIBs lixiviate was placed in the feed tank and the working temperature was 25 °C was kept constant via thermostat. The set-up was equipped with a high pressure pump up to 10 bar. The feed was drawn via a tube to the membrane cell, which has a support and permeate collector. The retentate passing through the valve is helpful in maintaining the trans-membrane pressure, which is monitored via pressure transducers, one at the inlet point and the other at the outlet point of the membrane cell. In step two, the commercial NF membrane was cut into the desired shape according to the membrane cell module. The membrane was washed with DI water before being installed in the cell. The pure water permeability (PWP) test was conducted for 30 min at 10 bar pressure, after which the hydraulic permeability was calculated, and the flux of the membrane was checked.

Experimental design

The experimental study was based on synthetic LIBs lixiviate. The real leaching solution of LIBs is very complex to handle due to the black mass, therefore, a mimic solution of LIBs was designed as described by most LIBs used23. The synthetic solution was made of strategic elements which are present in the real spent LIBs. A typical leaching solution contains Co, Li, Ni, Al, Fe, and Mn. All these elements were used in the current investigation via four NF commercial membranes individually and in mixture as shown in Table 2.

Table 2.

Expected LIBs leaching lixiviate chemical composition of the self-made solution.

Metals Concentration in (g/L)
Li 0.8
Ni 1.50
Co 6.5
Mn 1.25
Fe 0.50
Al 0.8
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Separation performance test of NF membranes

The essential separation performance of the NF-membranes was evaluated via a bench-top crossflow setup with an efficient filtration area of 3 cm radius. Prior to the LIB permeate collection, all four membranes were tested for the trans-membrane pressure at 10 bar for 30 min to confirm reliable and stable figures. All the membranes were tested three times under 10 bar and 25 °C, the mean value was determined to limit the errors. The primary parameters were assessed for the (PWP) in L m−2 h−1 bar−1 using Eq. 1. Salt rejections were evaluated with single salt, the concentration was then demonstrated by measuring the conductivity. In this study, the concentration of both feed and permeate solutions was evaluated via a conductivity meter (model name from mobile picture) using Eq. 2.

graphic file with name d33e616.gif 1
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To examine the pore size distribution, the rejection of PEG with molecular weight of 200 g/mole, 400 g/mole, 600 g/mole, and 1000 g/mole were evaluated on the crossflow set-up.

Analytical technique

The metal concentration from different metals permeates and the LIB synthetic leachate mixture of metal ions permeate were analyzed via ICP-AES (Thermo Scientific iCAP 7400). The calibration curves were designed by using a standard solution of ICP composed of 27 elements, including those of LIB with the concentration of 100 µg/L in 2% HNO3 (0.5 M) in Milli Q water. Five standard solutions were made with different concentrations (4 ppm, 2 ppm, 1 ppm, 0.5 ppm, 0.2 ppm, and 0.1 ppm) for establishing a calibration curve. The detection limit for lithium in the detector of ICP is 4 ppm and for all other metals it was 100 ppm. The permeate samples from all four membranes were diluted up to 200 µL/9.8 mL in 2% HNO3 Milli Q water before analysis by ICP-AES. Each permeate was tested three times, and the results obtained were the average of these three measurements. The pH of the permeate and the feed was monitored with a pH meter (Orion VSTAR10).

Results and discussion

Structure of membranes

Chemical structure of membranes

The chemical structures of the four commercial nanofiltration membranes is illustrated in FTIR Spectra shown in Fig. 1. The peak at 1630 cm−1 is associated with the stretching of the amide group N–C=O, authenticating that the chemical composition of the membranes is polyamide.

Fig. 1.

Fig. 1

Fig. 1

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FTIR XN-45 (a), NF-270 (b), NF-90 (c) and NFW (d).

The four commercial NF membranes shows the distinct feature of O 1 s, N 1 s, and C 1 s distinguishing peaks in the XPS spectral survey, which aligns with the characteristic feature and structural attributes of polyamide as shown in Fig. 2.

Fig. 2.

Fig. 2

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XPS survey XN-45 (a), NF-270 (b), NF-90 (c) and NFW (d).

Morphology of membranes

SEM images and EDX results for the four commercial nanofiltration membranes were obtained at 10 kV and 3300 × magnification, providing detailed visualization of their surface and cross-sectional structures. XN-45, is piperazine-based (polypiperazine amide) membrane, shows a comparatively smooth surface with less pronounced nodular features than the PA-TFC membranes. This reduced nodularity indicates a lower surface roughness, which can potentially decrease fouling. Its cross-section reveals an asymmetric porous support with distinct finger-like voids. In comparison, (NF-270, NF-90, and NFW) as polyamide thin-film composite (PA-TFC) membranes, exhibits typical ridge valley nodular morphologies. NF-270 displays a cauliflower-like surface pattern and a cross-section with finger-like polysulfone support structures. NF-90 shows tightly packed ridges that give a grainy appearance, supported by a polysulfone layer with finger-like voids. NFW presents moderately rough but well-defined nodules, along with a clearly asymmetric support structure.

SEM images of used membranes further shows increased surface roughness and evident fouling on all membranes after exposure to high operating pressures in the crossflow system.

In conclusion, the SEM analysis highlights clear morphological distinctions among the membranes, with XN-45 exhibiting the smoothest surface and lowest nodularity, while the PA-TFC membranes demonstrate more complex ridge-valley structures as shown in Fig. 3.

Fig. 3.

Fig. 3

Fig. 3

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SEM of fresh and used/fouled XN-45 (a), NF-270 (b), NF-90 (c) and NFW (d).

Elemental composition of membranes

EDX (Energy Dispersive X-ray Spectroscopy) was employed for the four commercial NF membranes (XN-45, NF-270, NF-90 and NFW) for the chemical composition analysis as displayed in Figs. 4 and 5. The main findings are that the polyamide membranes exhibited dominant peaks of carbon, oxygen and nitrogen which are the key features of the presence of an active polyamide layer. Among the membranes under analysis NF-270 and NF-90 is showing a slightly higher oxygen content as compared to XN-45 representing a higher oxidation on the surface and hydrophilic functional groups. NFW is showing a comparatively lower nitrogen content reflecting a thinner layer of polyamide. A minor amount of Sulfur and chlorine were also detected in the analysis, likely present due to the presence of additives during membranes fabrication. The gold peak is due to the sputtering in view of the SEM images of the same samples.

Fig. 4.

Fig. 4

Fig. 4

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EDX of fresh membranes XN-45 (a), NF-270 (b), NF-90 (c) and NFW (d).

Fig. 5.

Fig. 5

Fig. 5

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EDX of used/fouled membranes XN-45, NF-270 (b), NF-90 (c) and NFW (d).

Physio-chemical surface properties of membranes

The four commercial NF membranes were analysed for their physio-chemical surface properties by measuring the water contact angle (WCA) as shown in graphs in Fig. 6. The WCA for XN-45 starts from 40 and drops slowly to 20°, in NF-270 the angle starts from 60° and drops towards 30°, in NF-90 the angle starts from 70 and gradually drops towards 40°, and in NFW the angle starts from 38 and drops to 20°.The water contact angles in all membranes, were reduced with time showing the strong spreading of water on the membranes surface, which represents the high wettability of membranes making them more hydrophilic.

Fig. 6.

Fig. 6

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Water contact angle (°) of XN-45 (a), NF-270 (b), NF-90 (c) and NFW (d).

The AFM results obtained according to ISO 25,178 for all four membranes before and after the experiments are shown in Fig. 7. The unused XN-45, NF-270, NF-290, and NFW membranes exhibited Sq values of approximately 10 nm, 1.94 nm, 20 nm, and 5.6 nm, respectively. Sq represents the root-mean-square surface roughness, where lower values indicate smoother and more uniform surfaces, consistent with the fresh, unfouled state of the membranes.

Fig. 7.

Fig. 7

Fig. 7

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AFM images of unused/fresh and used/fouled XN-45 (a), NF-270 (b), NF-90 (c) and NFW (d).

After the experiments, the Sq values increased to approximately 28.5 nm, 55.9 nm, 0.0717 µm, and 0.0864 µm for XN-45, NF-270, NF-290, and NFW, respectively. This increase reflects the development of surface irregularities due to foulant deposition and slight surface restructuring during filtration, resulting in a rougher topography. Despite this, the AFM profiles show no structural damage, indicating that the membranes remain suitable for additional filtration cycles.

Polyethylene glycol (PEG) rejection test

The separation performance of the four commercial nanofiltration membranes was evaluated using polyethylene glycol (PEG) solutions with molecular weights of 200, 400, 600 and 1000 Da. As shown in Fig. 8, all membranes exhibited an increasing rejection trend with increasing PEG molecular weight, confirming typical nanofiltration behaviour driven by steric hindrance. Among the tested membranes, NF-90 demonstrated the highest overall rejection, reaching ~ 92.1% for PEG 1000, followed by NF-270 and NFW, which showed comparable rejection profiles at higher molecular weights. In contrast, the XN-45 membrane displayed the most open structure, with low rejection at PEG 200 (57.7%) but a sharp increase to 89.6% at PEG 1000. The point of inflection for each curve provides insight into the molecular weight cut-off (MWCO) of the membranes: XN-45 showed a steep rise between PEG 400–600, whereas NF-270, NF-90 and NFW reached nearly 90% rejection at PEG 1000, indicating tighter pore structures. Overall, the PEG-based rejection profiles validate the suitability of PEG solute testing for characterizing MWCO in nanofiltration systems.

Fig. 8.

Fig. 8

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Rejection curve of PEG for MWCO of all membranes.

Rejection of salts

The rejection of salts is one of the most important features of commercial membranes. All NF membranes were investigated for salt rejection by using NaCl and MgSO4 as monovalent and divalent ions. The results are shown in Fig. 9. NF membranes strongly reject the divalent ions such as magnesium sulphate due to charge-based repulsion (Donnan exclusion), whereas the sodium chloride rejection is fairly low as monovalent ions easily pass through the NF membranes pore as charge repulsion is weak and not enough to block sodium ions.

Fig. 9.

Fig. 9

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Salt rejection of XN-45, NF-270, NF-90 and NFW.

Synthetic LIBs feed solution for recovery of lithium

The spent LIBs cathodes are composed of a mixture of other precious metals like nickel, aluminium, cobalt, manganese, iron along with lithium. The leaching solution contains all of these metal ions as per Table 2 g/L in concentration. Since the original leaching solution is difficult to handle due to the high viscosity of black mass from LIBs and its high pH, we synthesized the solution by using almost the same concentration of elements found in cathode material of LIBs. Each membrane was tested with each metal individually and as a mixture. The results rejection performance for XN-45, NF-270, NF-90 and NFW are shown in Fig. 10. The rejection percentage of all metal ions both individually and in a mixture of synthetic spent lithium-ion batteries leaching solution is due to Donnan effect and the steric hinderance effect, which is due to the physio-chemical surface properties of the NF membranes. Surface charge and membranes pore size also played a good part in the rejection percentage of bivalent and multivalent metal ions. As can be seen from the use of the mixture, the rejection of multivalent ions and monovalent ions increased due to positive charge on the surface of membranes.

Fig. 10.

Fig. 10

Fig. 10

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Rejection of metal ions and mixture of ions in all membranes.

Rejection difference between the membranes

As can been observed from the Fig. 10, the comparative analysis of lithium rejection across the four NF membranes shows a clear performance gradient. The rejection of lithium ions displayed very good results. Among the tested membranes XN-45 exhibits the highest lithium passage with only 18.5 of rejection, highlighting its suitability for lithium recovery. NF-270 showed a comparable behaviour with 19% rejection, confirming its relatively open pore structure that favouring monovalent ions transport. NF-90, with a denser active layer, restricted lithium permeation to a greater extent, resulting in 30% rejection. In contrast, the NFW membrane demonstrated the highest rejecting 44.5% of lithium ions and therefore allowing the least permeation. From the results it can concluded that the order of lithium ions recovery XN-45 > NF-270 > NF-90 > NFW. The order indicates the membrane with lower rejection values enable higher lithium passage due to weak steric and electrostatic hinderances experienced by monovalent ions.

Rejection difference between the ions in each membrane

The rejection behaviour of different metal ions of four NF membranes is displayed in Fig. 10. The rejection trend clearly demonstrated clear ion-independent selectivity governed by charge density and pore size of commercial membranes. For lithium, a monovalent ion, all membranes showed a low rejection, which increases progressively from XN-45 (18.5%) to NF-270 (19%), NF-90 (30%) and NFW (44.5%), reflecting their increasing structural tightness. In contras the other transition metal ions exhibits significantly higher rejection due to their multivalent nature. For XN-45, Ni2+, Co2+, Mn2+ and Fe3+ showed rejection values between 76 and 87%, while the mixed ion matrix reached 95.67%, indicating enhanced steric and electrostatic exclusion under competitive conditions. NF-270 presented similar trend with slightly higher rejection of Ni2+ (89.66%) and Co2+ (85.21%) whereas Al3+ and Mn2+ remained comparable to XN-45. NF-90 displayed stronger rejection toward Fe3+ (97.36%) and Al3+ (79.08%) but showed reduced rejection for Co2+ (69.33%) and Mn2+ (61.07%), suggesting ion-specific interactions with its dense polyamide layer. NFW, the tightest membrane, achieved consistently high rejection for multivalent ions including Co+2 (90.1%), Mn2+ (87.3%), and Fe3+ (97.55%) while still allowing moderate lithium ions permeation. Conclusively the rejection hierarchy for monovalent versus multivalent ions remained consistent across the membranes, with NFW offering the highest overall selectivity followed by NF-90, NF-270 and XN-45.

ICP analysis of NF permeates for lithium recovery

Permeates from the individual feed solution of each metal ions including lithium, nickel, aluminium, cobalt, manganese, iron, and a mixture of all these metal ions were collected and diluted carefully after each feed solution was passed through XN-45, NF-270, NF-90 and NFW nanofiltration membranes. The permeates were tested via ICP-AES for metal ions concentration in mg/L, as presented in Fig. 11. All membranes showed promising results for the recovery of lithium ions in permeates with an ideal low RSD (relative standard deviation) of 1.9% and the percentage recovery of the method with successful detection limit of 98%. NFW has the lowest recovered Li+ ions as shown in the graph as compared to other NF membranes. The maximum purity in leachate was achieved in XN-45 with the highest of 26.014% as depicted in Fig. 11. In Fig. 12 which is representing the mixture results are showing the recovery of Li+ ions up to 20.014% less as compared to individual Li+ ion solution due to steric hinderance and Donnan effect of other metal ions inside the solution. Figure 13 depicts the calibration curves of individual metal ions in permeate solutions.

Fig. 11.

Fig. 11

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Permeate of each metal ion solution from XN-45, NF-270, NF-90 and NFW.

Fig. 12.

Fig. 12

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Permeate of Mixture of metal ion from XN-45, NF-270, NF-90 and NFW.

Fig. 13.

Fig. 13

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Calibration curves conc. of permeate of each metal ion solutions.

Future prospects

The experimental results demonstrate that an optimal nanofiltration membrane holds several essential properties for the effective lithium recovery from the leaching solution of spent LIBs. One of the key considerations is the ability of the NF membrane used in the recovery of Li + ions to retain positive charge in acidic conditions. The primary factor for this repulsion force between the surface of the NF membrane and multivalent metal ions is the Donnan effect, due to which the NF membranes could pass Li+ ions with more efficiency by increasing the rejection percentage of other multivalent ions present in the leaching solution of the spent LIBs. The nanofiltration membranes employed showed excellent recovery for lithium ions separation, making them an effective choice for the recycling of LIBs. Other methods through which the selectivity of Li + ions can be improved are by adopting the inversion methods of surface charge to reinforce the positive charge across the surface of NF membranes33. There are many methods available in which the performance of NF membranes can be improved by grafting the surface of membranes with an additional layer of polymer for protection and for the long-term operational stability of the NF membranes.34. Other methods may include the addition of nanocomposites or nanoparticles for the structural stability of the surface of the NF membranes. Increasing the cross-linkage in the membrane configuration can also be helpful in the ion selectivity of the membranes35.

Conclusion

This study was conducted to demonstrates the recovery of lithium from the leachate of spent lithium-ion batteries, for which a synthetic leachate was used and deployed to the four commercial NF membranes. The performance of these nanofiltration membranes exhibit distinct ion-selectivity profiles governed by membrane structure, pore tightness, and ion valency of ions under investigation. The AFM, SEM, WCA, EDX of the deployed membranes provides the mechanistic behaviour especially the ion-membranes interactions and transport. Lithium, due to its monovalent charge and small hydrated radius, showed consistently a low rejection across all membranes, with XN-45 and NF-270 permitting the highest permeation and therefore offering the greatest potential for lithium recovery. In contrast, multivalent ions such as Ni2⁺, Co2⁺, Mn2⁺, Al3⁺, and Fe3⁺ were strongly rejected, particularly by the tighter NF-90 and NFW membranes, which achieved rejection levels exceeding 90% for several species. The enhanced rejection observed in mixed-ion systems (synthetic leachate) further highlights the influence of competitive transport and electrostatic interactions on the surface of membrane performance which is claimed by the manufacturers (STERLI-TECH). Overall, the rejection hierarchy—NFW > NF-90 > NF-270 > XN-45 for multivalent ions, and the inverse trend for lithium permeation—provides a clear framework for membrane selection. These findings underscore the feasibility of using lower-rejection membranes for efficient lithium recovery while reserving tighter membranes for applications requiring robust multivalent metal removal, thereby guiding the design of integrated separation strategies for the recovery of lithium from spent lithium-ion batteries and e-waste management. This work conclusively established that the nano-filtration membrane physico-chemical attributes including surface roughness, wettability, elemental composition, and morphological structures are the primary role player in ion-rejection behaviour and lithium ions selectivity. The present study thus provided a promising pathway for future innovative strategies aimed at the enhancing the recycling efficiency of the spent LIBs.

Acknowledgements

The authors acknowledge Princess Nourah bint Abdulrahman University Researchers Supporting Project number (PNURSP2026R737), Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia. The authors are also thankful to Maria lliopoulou and Despina Fragouli (smart Material group), Istituto Italiano di Technologia, via Morego 30, Genova, 16163 Italy for SEM and EDX testing facility.

Author contributions

**MA:** Methodology, Data curation, Investigation, Writing, original draft, Visualization, **BVB:** Supervision of the whole project and Conceptualization, **MAK:** Conceptualization, Validation of methodology, **PJ:** Validation of Results, Reviewing. **MI** : Supervision & reviewing, **MBJ:**

Data availability

All data generated or analyzed during this study are included in this published article.

Declarations

Competing interests

The authors declare no competing interests.

Footnotes

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Contributor Information

Mamoona Alam, Email: Mamoona.alam@sbbwu.edu.pk.

Mohammad Ibrahim, Email: dribrahim@awkum.edu.pk.

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