Slug-flow-based continuous manufacturing of Fe-substituted Ni-rich NCM cathodes for lithium-ion batteries: synthesis and modeling

Arjun Patel^a, Michael L. Rasche^a, Sourav Mallick^a, Sunuk Kim^a, Mo Jiang^a, Mariappan Parans Paranthaman^b, Herman Lopez^c and Ram B. Gupta*^a
aDepartment of Chemical and Life Science Engineering, Virginia Commonwealth University, Richmond, VA 23219, USA. E-mail: rbgupta@vcu.edu
^bChemical Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
^cIonblox Inc., Fremont, CA 94538, USA

First published on 13th August 2025

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1. Introduction

Rechargeable lithium-ion batteries (LIB) are heavily used in portable electronic devices and electric vehicles (EVs) due to their higher volumetric and gravimetric energy densities compared to other battery technologies.^1–3 Current LIBs have come a long way since their first introduction in 1991 by Sony, with two to three-fold increase in the energy density at cell level (e.g., volumetric energy density increased from 220 to 700 Wh L⁻¹ and gravimetric energy density from 98 to 300 Wh kg⁻¹).⁴ Since the invention of LIBs, there has been extensive research on every component of the LIBs with a particular focus on the cathodes because of their high cost and bottleneck in achieving a high capacity compared to commonly used graphite anode which can deliver a specific capacity of 372 mAh g⁻¹.^5,6 Among all the available cathodes for lithium-ion batteries, LiTMO₂ (TM = Ni, Co, Mn or Al) (NCM or NCA) based layered oxide materials are potential candidates for high performance LIBs because of their high theoretical capacity, low cost and high operating voltage.⁷ In recent years, efforts are being made to reduce the cobalt content in the layered NCM materials due to high cost, toxic nature, environmental hazards, and human rights violations in Co mining.^8–11 Moreover, reducing cobalt and increasing Ni-content in the NCM cathode is helpful in lowering the overall cost of the cathode along with increasing the energy density.^11,12 Ni-rich Li[Ni_xCo_yMn_z]O₂ (x > 0.6; (x + y + z) = 1) (NCM) and Li[Ni_1−x−yCo_xAl_y]O₂ (NCA), are most studied cathode materials for lithium-ion due to their potential application in next generation energy storage systems.¹³ However, with increase in nickel content, these cathode materials suffer from issues such as capacity fading, poor rate capability, cyclic instability and thermal instability.^14–18 Several modification techniques such as doping, coating, morphological designs, and single crystal are employed to address the issues related to Ni-rich cathode materials to improve their electrochemical performance.^19–22 Among these mentioned modification strategies, doping or partial substitution, where a foreign metal is incorporated to stabilize the crystal lattice of Ni-rich cathodes, is now increasingly popular because of its effectiveness and simplicity.^23,24 It is well known that cobalt plays an important role in the crystal structure of NCM cathode material due to its electronic configuration. Cobalt can effectively reduce the Li⁺/Ni²⁺ mixing by screening the Ni⁺²–O₂–Ni⁺²/Mn⁺⁴ (180°) linear interlayer super exchange interaction due to the absence of unpaired electron in its electronic configuration Co⁺³.^25–27 However, the high cost, toxicity and socio-political issues limits the application of Co. Interestingly, Fe⁺³ has a similar electronic configuration as cobalt and can be used in NCM materials to reduce the Li⁺/Ni²⁺ mixing.^27–36

Furthermore, it is well known that the quality of precursors plays a significant role in the electrochemical performance of the cathode. Co-precipitation technique in combination of batch or semi-batch reactor is generally employed to produce the precursors for NCM cathode materials. However, the spatial inhomogeneities in batch and semi-batch reactors and variation from batch to batch hampers the quality of the product.^37,38 Therefore, continuous reactors are employed to improve the quality and increase the throughput of the product. Among continuous reactors, slug flow continuous reactors use tubes with the diameter of millimeter scale where flowing slugs of two or three different phases are used to carry out reactions. As the fluid flows in the tube maintained at the desired temperature, the reaction takes place. The homogeneity of each slug is maintained due to the intrinsic properties of slug flow which doesn’t require an external agitator such as mixing blades or stir bar. Furthermore, the small microliter volume of slugs along with internal circulation enhances heat and mass transfer within the microreactor.^39–43 Three phase systems are preferred over two-phase systems as the latter suffer from injection inaccuracies and fouling due to the affinity of products towards the tube walls. In three phase systems, a carrier liquid is used to isolate the chemical reagents from the tubing walls, thus preventing fouling.⁴⁴ Mineral oil is chosen as a continuous phase which separates the solid precipitate from a direct contact with the tubing, which can help avoid clogging of the reactor tubing. The surface tension for the nitrogen–mineral oil is much lower than that of the nitrogen–water system, so nitrogen–oil interfaces are energetically preferred in the case of water–oil–nitrogen three-phase flow i.e., less capillary pressure needs to be overcome. Also, the tubing material is hydrophobic. Therefore, for the water–oil–nitrogen system in this research, oil is the continuous phase, nitrogen and water are the dispersed phases.⁴⁵ The reagent addition is also improved in three phases due to a density difference between the reactants and the carrier liquid.⁴⁴

In this work a three-phase continuous slug flow reactor is used to synthesize high quality NCMFe battery cathode precursors using coprecipitation chemistry. The effect of reagent concentration and feeding sequence on the nature of the precursor particle are evaluated first. The experimental optimized parameters are further verified with the help of mathematical modelling. Here, the cobalt is partially substituted by iron to study the effect on the electrochemical performance of Li[Ni_0.85Co_(0.1−x)Mn_0.05Fe_x]O₂ (NCMFe)(where x = 0, 0.02, 0.04). The effect of varying amount of Fe on rate capability is examined at various C-rates.

2. Experimental section

2.1. Materials

Nickel(II) sulfate hexahydrate (≥98%), manganese(II) sulfate monohydrate (≥99%), cobalt(II) sulfate heptahydrate (≥99%), ammonium oxalate monohydrate (≥99%), ammonium hydroxide (28–30% NH₃ in H₂O by weight, purity ≥99.99%), iron sulfate, light mineral oil and lithium hydroxide (≥98%) were purchased from Sigma-Aldrich. All chemicals were used as received without further treatment. All the solutions were prepared with deionized water (DI).

2.2. Slug-flow synthesis of oxalate precursors

A schematic of three phase slug flow reactor used for this work is shown in Fig. 1. The experimental setup consists of a fluorinated ethylene propylene (FEP) tube (internal diameter 2.4 mm) as a tubular reactor, four syringe pumps (New era model #1000) to inject the reagents and oil into the reactor, a mass flow controller (Omega, model# FMA-2716A) to control the gas flowrate and heating incubator. A stable three phase slug flow is generated by pumping the three phases (oil, nitrogen and reagents) into the tube with precisely controlled flowrates.^46,47 To synthesize NCMFe with different composition, stoichiometric amount of NiSO₄·6H₂O, CoSO₄·7H₂O, MnSO₄·H₂O, and FeSO₄·7H₂O are dissolved in DI water to prepare a metal-ion solution with a 0.5 M concentration and filled into the syringe. At first T-junction, oil, nitrogen and metal salts are injected to form stable slug flow pattern. Once the flow is stabilized, NH₄OH is then injected to chelate the metals salts and increase the pH of the mixture to around 7.5. Lastly, ammonium oxalate is injected to trigger the nucleation. The slugs then pass through 50 feet of tube (equivalent to approximately 6 min of residence time) kept in a heading incubator maintained at 60 °C. As the slugs containing nuclei move downstream in the heated zone the growth of these particles takes place. The outlet of the tubular reactor, slug containing blue precipitates are collected into a 3-neck round bottom flask (with drain) containing DI water to quench and wash the solid precipitate.

2.3. Lithiation of the precursors

The solid products set at the bottom of the flask are collected, washed and filtered, followed by drying at 80 °C for 12 h to obtain the final precursor powder. The oil from the filtrate is separated and recycled. The oxalate precursor is then mixed thoroughly with LiOH·H₂O using a mortar and pestle in a molar ratio of 1:1.05 [(Ni + Co + Mn + Fe):Li]. This mixture is calcined in a tube furnace at 750 °C at a ramp rate of 0.4 °C min⁻¹ for 12 h in an oxygen environment. The samples are naturally cooled down to ambient before crushing them to obtain final Li[Ni_0.85Co_(0.1−x)Mn_0.05Fe_x]O₂ (where x = 0–0.04) cathode power material. The chemical reactions involved in the synthesis of the NCMFe materials are included in SI. The samples are labelled as NCMFe-(10,0), NCMFe-(8,2) and NCMFe-(6,4), based on the amount of Co and Fe in the samples.

2.4. Material characterization

The morphology and element distribution of the precursors and lithiated powders were analyzed with scanning electron microscopy (SEM, SU-700, Hitachi) equipped with energy dispersive spectroscopy (EDS) system. The crystallographic details were determined by X-ray powder diffraction (PANalytical, Empyrean X-ray diffractometer) using Cu Kα (λ = 1.5406 Å) radiation source with a step of 0.02° at 40 kV and 40 mA. Inductively coupled plasma-optical emission spectrometry (ICP-OES, Agilent Technologies, 5110-MS) was used to carry out compositional analysis of the material. X-ray photoelectron spectroscopy (XPS) of the lithiated material was performed using Phi VersaProbe III scanning XPS microprobe.

2.5. Electrochemical measurements

The electrochemical measurements were performed using CR2032 type coin cell provided by MTI. A slurry consisting of active material, conductive carbon (SuperP) and polyvinylidene difluoride (PVDF)(HSV900) in N-methyl pyrrolidone (NMP)(Sigma) [weight ratio of 8:1:1] is prepared by mixing these compounds at 2500 RPM for 12 min using Thinky mixture (AR-100). The resulting slurry was then coated on a battery grade aluminum foil using doctors’ blade technique. The coated electrodes are then dried at 110 °C for 12 h, calendered and punched into 14-mm diameter round disc. The coin cells were assembled in an argon-filled glove box (MBraun, O₂ < 0.05 ppm and H₂O < 0.05 ppm). Celgard 2340 tri-layer microporous membrane was used as a separator and 1.0 M LiPF₆ in ethylene carbonate/dimethyl carbonate (EC/DMC = 1:1) was used as the electrolyte. Lithium metal disk was used as an anode for half-cell configuration. The loading of the electrodes was maintained at 6–8 mg cm⁻² based on the total mass of the electrodes. The electrochemical performance of the cathode is evaluated through charge–discharge, rate capability and cycle life in MTI and ARBIN battery cycler considering 1C = 180 mA g⁻¹. The electrochemical impedance spectroscopy (EIS) was performed at various stages of cycling with an amplitude of 5 mV within a frequency range of 10⁵ Hz to 10⁻² Hz using a Gamry potentiostat Interface 5000E. All electrochemical tests were conducted at room temperature.

3. Results and discussion

3.1. Optimization of slug-flow reactor

Continuous precipitation of high-quality transition metal (TM) cathode precursor requires an optimized reactor setup. In order to find the best condition to precipitate the TM for cathode precursors, a series of controlled experiments were conducted in terms of feeding sequence, feeding location, flowrates and concentration of the reagents. In this section, effects of each of these conditions are studied to optimize the synthesis parameters for slug-flow reactor.

3.2. Mathematical modelling of co-precipitation in slug-flow reactor

Equilibrium modeling techniques developed for various formulations of NCM hydroxide and NCM oxalate are modified and applied to NCMF oxalate experiments to explore the effect of changing concentrations of inputs in the region about a central case (Table 1).⁴⁹ The solution equilibrium model finds the equilibrium concentrations and amounts of components in the NCMFe oxalate system co-precipitation reaction by solving a system of balances and chemical reaction equilibria. The overall mass balance within each slug, assuming the volumes are additive, is given as:

VT = V1 + V2 + V3	(1)

where V_T is the total volume and V₁, V₂ and V₃ correspond to the volume of metal sulfate, (NH₄)₂C₂O₄ and NH₄OH solutions. The mass balances for the total concentration of each of the three metal ions, oxalate ions and ammonia in solution are shown in eqn (2)–(4) respectively.

	(2)

	(3)

	(4)

where p_M is the molar ratio of transition metal (M), M refers to the individual transition metals, i.e. Ni, Co, Mn, and Fe. The input concentrations on the left-hand side of eqn (2)–(4) are also known. The remaining concentrations and amounts are determined by the equilibrium equations for metal oxalate, water, ammonium hydroxide, and metal-amine or metal-oxalate complexes. The details of equations and hypothesis used for theoretical modelling are included in SI (Tables S1–S4). The outcome of the modelling analysis is shown in Fig. 3 and Fig. S2.

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3.3. Characterization of NCMFe samples

Fig. 4a–c shows the SEM images of lithiated cathode materials at different magnifications. It is observed that a slow ramp rate during lithiation step (decomposition of oxalate to oxide) helps in retaining the spherical morphology of the final oxide materials with an average particle size of 2–5 μm and the Fe-content does not affect the particle size of the material. The EDAX maps of the three samples are shown in Fig. 4d, showing a homogeneous distribution of all the metals ions. The chemical composition of the three samples is confirmed using ICP-OES, shown in Fig. S3, indicating that the Fe is successfully incorporated into NCM materials.

The X-ray diffraction pattern for lithiated NCMFe-(10,0), (6,4) and 8,2) materials are shown in Fig. 5(a). The observed spectra for all three samples can be indexed to layered hexagonal α-NaFeO₂ structure with Rm space group. The magnified reflections (003) and (104) peaks are shown in Fig. 5(b) and (c) which shows the effect of incorporation of iron into the sample. It is observed that as the iron content increases from 0% to 4%, both the reflections shift towards lower 2θ values. This indicates an increase in interplanar distance in iron containing samples due to a larger ionic radius of Fe⁺³ (0.65 Å) compared to Co⁺³ (0.55 Å), which in turn is known to improve the Li⁺ ion diffusion in the layered structure leading to an enhanced rate capability of material.³⁴ Rietveld refinement is performed to further analyze the XRD data, Table 2 shows the calculated lattice parameters for three samples. The intensity ratio I₀₀₃/I₁₀₄ remains almost similar as the iron content is increased from 0% to 2% while decreasing the cobalt content from 10% to 8%, indicating a similar extent of Li⁺/Ni⁺ mixing in both the samples. On the contrary, a lower intensity ratio for NCMFe-(6,4) indicates a high degree of mixing. The c/a ration for all three materials is greater than 4.94 which indicates the formation of a well-defined hexagonal crystal structure. The splitting of (006)/(012) and (108)/(110) peaks confirm the formation of layered structure.⁵⁰ It is observed from the Rietveld refinement that there is an increase in the lattice volume with an increase in the iron content in the samples.

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XPS analysis is used to further understand the oxidation states of different elements in the oxide samples. The survey scan for NCMFe is included in SI (Fig. S4). The high-resolution Ni 2p_3/2 and Mn 2p_3/2 for all the three samples, such as NCMFe-(10,0), (8,2) and (6,4) are included in Fig. 6 to show the effect of Fe³⁺ doping. In all the cases, the Ni 2p_3/2 peaks are observed at 855.05 eV with a satellite peak at 861.25 eV. The 2p_3/2 can be deconvoluted in two peaks at 854 and 856 eV, corresponding to the Ni²⁺ and Ni³⁺, respectively. From Fig. 6a, c and e it is observed that the Ni³⁺ content is increasing with the increasing amount of Fe³⁺. The deconvoluted Mn 2p_3/2 spectra for all the three samples are shown in Fig. 6b, d and f. Mn 2p3/2 is observed at 642 eV and it is deconvoluted into two distinct peaks, indicating the presence of Mn³⁺ and Mn⁴⁺ states. In this case also, Mn⁴⁺ is found to be increased compared to Mn³⁺ with the increasing amount of Fe³⁺. For all the three cases, the high-resolution Co 2p_3/2 peak is observed at 779 eV, which is primarily composed of only +3 oxidation state (Fig. S5a–c). The Fe 2p_3/2 spectra for both the NCMFe-(8,2) and NCMFe-(6,4) primarily contains the +3 peak at 712 eV (Fig. S5d and e).

3.4. Electrochemical performance

The electrochemical studies were performed on three samples using CR2032 type coin cell with Li-foil (half-cell) as anode. All experiments were performed at room temperature and within a voltage window of 2.8–4.3 V vs. Li/Li⁺. The initial charge–discharge at 0.1C for all three materials is shown in Fig. 7a, the discharge capacity of NCMFe-(10,0), (8,2), and (6,4) are 200.6, 172.5 and 173.2 mAh g⁻¹, respectively. It is observed that the specific capacity decreases with an increase in iron content. To study the long-term performance, cycling stability test is conducted on three samples for 100 cycles at 0.5C within a voltage window of 2.8–4.3 V in half cell (Fig. 7b). The percentage of capacity retained by each sample after 100 cycles is 53%, 47% and 39% for NCMFe-(10,0),NCMFe-(8,2) and NCMFe-(6,4), respectively. The reason for low coulombic efficiency in the case of NCMFe-(6,4) can be attributed to the local distortion of the structure due to a phase change from hexagonal to cubic. It is observed that with the increase in the Fe-content in the NCM structure some of the Fe stabilizes in the lithium layer (3a) instead of TM-layer (3b), which hinders the lithium diffusion back into the cathode.^51,52 The cycling performance of both the iron containing sample is poorer than the undoped-NCM sample due to the local phase changes and distortion. The charge–discharge analysis for all the three materials is performed within a wide range of C-rates, ranging from 0.1C to 2C (Fig. S6). The rate capability plot for three samples at different C-rates is shown in Fig. 7c. It is observed that at low C-rates, up to 0.5C, the sample without iron performs better compared to samples with iron. However, when the C-rate is increased above 0.5C, it is seen that NCMFe-(8,2) shows a better charge storage performance compared to NCMFe-(10,0) and NCMFe-(6,4), with latter performing the worst at higher C-rates. Here, it is observed that the rate capability of NCMFe-(8,2) is better than the other two materials at 2C, retaining 70% of its capacity at 0.1C. Whereas NCMFe-(10,0) and NCMFe-(6,4) samples retained 34% and 24%, respectively. Furthermore, when the current rate was changed back to 0.1C, NCMFe-(8,2) regains 97% of its initial capacity (at 0.1C) while NCMFe-(10,0) regains 92% of its initial capacity. On the other hand, NCMF-(6,4) only regains 44% of its capacity at 0.1C, indicating severe degradation of materials due to higher charging and discharging currents. The poor rate capability of the NCMFe-(6,4) is attributed to the irreversible phase change from hexagonal to cubic structure due to the presence of Fe in the Li (3a) layer.^52–54

In order to understand the effect of Fe³⁺-content on the rate capability the deferential capacity (dQ/dV versus V) plots are derived at the beginning and end of the rate performance (Fig. 7d–f). It is observed that the original layered hexagonal structure (H1) of the Ni-rich cathodes are first transformed to monoclinic (M) phase followed by transformation to hexagonal 1 and 2 (H1 and H2) phases upon sweeping the voltage from 2.8 to 4.3 during charging due to delithiation and the reverse phase transition happens upon lithiation during discharging.⁵⁵ Although this phenomenon is common for all three as-synthesized material, the extent of polarization in terms of peak shift and intensity variation are significantly different at the beginning from that at the end of the rate-capability experiment. Among the three, the NCMFe-(8,2) shows the least peaks shift and intensity variation, signifying a better structural stability even at higher C-rates (Fig. 7e). Whereas, NCMFe-(10,0) shows a significant change in peak intensity at the high voltage region during lithiation process (Fig. 7d). The NCMFe-(6,4) shows a significant deviation in peak structure and position at the end of rate capability experiment, which further supports its worst rate performance (Fig. 7f). Hence, from this observation it can be inferred that an optimum amount of iron doping can efficiently mitigate the phase change related issue even at higher C-rate and assure a good rate performance. In order to get a better understanding on the effect of gradual replacement of Co³⁺ with Fe³⁺ on the redox process of the Ni-rich layered cathode, electrochemical impedance spectroscopy (EIS) was performed with each of the cathodes after 10 charge–discharge cycles. After analyzing the Nyquist plots (Fig. S7a) with the help of suitable equivalent circuit (Fig. S7b), it is observed that, the electrode–electrolyte interfacial resistance (R_f) decreases with increasing amount of Fe³⁺, signifying the improved surface conductivity. On the other hand, NCMFe-(8,2) shows the lowest charge transfer resistance (R_ct) compared to the other two cathodes. Furthermore, It is observed that the NCMFe-(8,2) achieves a higher Li⁺ diffusion co-efficient among the three, which further signifies that an optimum doping of Fe³⁺ facilitates the diffusion throughout the crystal structure of the Ni-rich layered cathode as shown in inset of Fig. S7. This clearly indicates that a facile charge-transfer is only possible with optimum amount of Fe³⁺ doping and higher amount of doping may worsen the scenario. Hence, from the study it is observed that Li[Ni_0.85Co_(0.1−x)Mn_0.05Fe_x]O₂ with 2% Fe³⁺ and 8% Co³⁺ shows a good rate performance with a fast charge-transfer kinetics.

4. Conclusion

In this study, a slug flow continuous reactor-based on co-precipitation reactor is used to synthesize Fe³⁺ substituted Ni-rich NCM precursor for lithium-ion battery precursors with varying Co and Fe contents. The optimized reagent concentration and feeding sequence results in a high-quality spherical precursor particle with a narrow particle size distribution. After a detailed study on the effect of feeding sequence on the quality of precursor particle, an optimum condition is established to produce the spherical NCMFe-oxalate precursor of particle size of 5–7 μm. The effect of the concentrations of metal salt, ammonium oxalate, and ammonium hydroxide solutions, used for the production of NCMFe-oxalate precursors are further verified with the help of equilibrium modelling. From the modelling analysis it is also supported that the reagent concentrations used for the manufacturing process offer the highest yield and the targeted composition of the precursors. Subsequently, all the three precursors are calcinated in pre-optimized condition to produce the final layered oxide and further characterized with various physical characterization techniques, including XRD, SEM, and XPS. A detailed electrochemical performance analysis was performed with all three materials to evaluate the effect of the Co³⁺-substitution with Fe³⁺ on the cathode performance. Here, it is observed that at low C-rates (<0.5C) the specific capacity of the Ni-rich cathode decreases with an increasing Fe³⁺-content. A very high Fe³⁺-doping (4%) results in severe degradation due to irreversible phase change. At the high C-rates of 1C and 2C, the material with 2% Fe³⁺ [NCMFe-(8,2)] shows a high specific capacity and better rate capability. Similarly, the charge transfer resistance and the polarization of electrode is the lowest for the [NCMFe-(8,2)] and offers a good rate performance.

Author contributions

Arjun Patel: material synthesis, electrochemical investigation, scientific conceptualization, Michael L. Rasche: theoretical modelling of the precursors, Sourav Mallick: electrochemistry analysis and mechanism, Sunuk Kim: slug-flow reactor discussions, Mariappan Parans Paranthaman: experimental design and revision, Herman Lopez: experimental design. Mo Jiang and Ram B. Gupta: conceptualization, supervision, and funding-acquisition. All authors contributed to and approved the final version of the manuscript.

Conflicts of interest

The authors declare no competing financial interest.

Data availability

The data supporting this article has been included as part of the SI. The supporting information include the copercipitation reactions, SEM images for different ammonium hydroxide concentration, equations and hypothesis for theoritical modelling, modelling data, ICP results, supplementary XPS data, electrochemical charge discharge and EIS plots. See DOI: https://doi.org/10.1039/d5ya00032g.

Acknowledgements

This material is based upon work supported by Virginia Commonwealth University, National Science Foundation (Grant No. CMMI-1940948) and U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Advanced Materials and Manufacturing Technologies Office (award DE-EE0009110). Research conducted at ORNL was supported by the U.S. Department of Energy, Office of Science, Basic Energy Sciences, Materials Sciences and Engineering Division. This manuscript has been authored by UTBattelle, LLC, under Contract No. DEAC05-00OR22725 with the U.S. Department of Energy. The U.S. Government retains and the publisher, by accepting the article for publication, acknowledges that the U.S. Government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for U.S. Government purposes. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (https://energy.gov/downloads/doe-public-access-plan). Mingyao Mou and Sophie Kothie are acknowledged for providing the slug flow co-precipitation technology developed in Mo Jiang Lab.

References

1. J. B. Goodenough and K.-S. Park, J. Am. Chem. Soc., 2013, 135, 1167–1176 CrossRef CAS PubMed .
2. K. Mizushima, P. C. Jones, P. J. Wiseman and J. B. Goodenough, Mater. Res. Bull., 1980, 15, 783–789 Search PubMed .
3. The Nobel Prize in Chemistry 2019. NobelPrize.org. Nobel Prize Outreach AB 2023. Tue. 6 Jun 2023. https://www.nobelprize.org/prizes/chemistry/2019/summary/.
4. M. Bianchini, M. Roca-Ayats, P. Hartmann, T. Brezesinski and J. Janek, Angew. Chem., Int. Ed., 2019, 58, 10434–10458 CrossRef CAS PubMed .
5. W. Yan, X. Jia, S. Yang, Y. Huang, Y. Yang and G. Yuan, J. Electrochem. Soc., 2020, 167, 120514 CrossRef CAS .
6. G. Bhutada, Breaking Down the Cost of an EV Battery Cell, https://www.visualcapitalist.com/breaking-down-the-cost-of-an-ev-battery-cell/, (accessed 6 February 2025).
7. S. Mallick, A. Patel, X. G. Sun, M. P. Paranthaman, M. Mou, J. H. Mugumya, M. Jiang, M. L. Rasche, H. Lopez and R. B. Gupta, J. Mater. Chem. A, 2023, 11, 3789–3821 RSC .
8. Y. Lv, S. Huang, Y. Zhao, S. Roy, X. Lu, Y. Hou and J. Zhang, Appl. Energy, 2022, 305, 117849 CrossRef CAS .
9. F. Schipper, E. M. Erickson, C. Erk, J.-Y. Shin, F. F. Chesneau and D. Aurbach, J. Electrochem. Soc., 2017, 164, A6220–A6228 CrossRef CAS .
10. N. Muralidharan, E. C. Self, M. Dixit, Z. Du, R. Essehli, R. Amin, J. Nanda and I. Belharouak, Adv. Energy Mater., 2022, 12, 2103050 CrossRef CAS .
11. S. Mallick, A. Patel, M. P. Paranthaman, J. H. Mugumya, S. Kim, M. L. Rasche, M. Jiang, H. Lopez and R. B. Gupta, Sustain. Energy Fuels, 2025, 9, 724–738 RSC .
12. H.-J. Noh, S. Youn, C. S. Yoon and Y.-K. Sun, J. Power Sources, 2013, 233, 121–130 CrossRef CAS .
13. A. Manthiram and J. B. Goodenough, Nat. Energy, 2021, 6, 323 CrossRef CAS .
14. H.-H. Ryu, K.-J. Park, C. S. Yoon and Y.-K. Sun, Chem. Mater., 2018, 30, 1155–1163 CrossRef CAS .
15. S. S. Zhang, Energy Storage Mater., 2020, 24, 247–254 Search PubMed .
16. G. L. Xu, X. Liu, A. Daali, R. Amine, Z. Chen and K. Amine, Adv. Funct. Mater., 2020, 30, 2004748 Search PubMed .
17. R. Pan, E. Jo, Z. Cui and A. Manthiram, Adv. Funct. Mater., 2023, 33, 2211461 CrossRef CAS .
18. Y. Gao, X. Wang, J. Geng, F. Liang, M. Chen and Z. Zou, J. Electron. Mater., 2023, 52, 72–95 Search PubMed .
19. H. H. Sun, U. H. Kim, J. H. Park, S. W. Park, D. H. Seo, A. Heller, C. B. Mullins, C. S. Yoon and Y. K. Sun, Nat. Commun., 2021, 12, 6552 CrossRef CAS PubMed .
20. J. Jeyakumar, Y. S. Wu, S. H. Wu, R. Jose and C. C. Yang, ACS Appl. Energy Mater., 2022, 5, 4796–4807 CrossRef CAS .
21. U. H. Kim, H. H. Ryu, J. H. Kim, R. Mücke, P. Kaghazchi, C. S. Yoon and Y. K. Sun, Adv. Energy Mater., 2019, 9, 1803902 CrossRef .
22. G. Ko, S. Jeong, S. Park, J. Lee, S. Kim, Y. Shin, W. Kim and K. Kwon, Energy Storage Mater., 2023, 60, 102840 CrossRef .
23. T. Weigel, F. Schipper, E. M. Erickson, F. A. Susai, B. Markovsky and D. Aurbach, ACS Energy Lett., 2019, 4, 508–516 CrossRef CAS .
24. A. Patel, S. Mallick, J. H. Mugumya, N. Lopez-Riveira, S. Kim, M. Jiang, M. P. Paranthaman, M. L. Rasche, H. Lopez and R. B. Gupta, Mater. Today Energy, 2024, 41, 101545 CrossRef CAS .
25. J. Zheng, Y. Ye, T. Liu, Y. Xiao, C. Wang, F. Wang and F. Pan, Acc. Chem. Res., 2019, 52, 2201–2209 CrossRef CAS PubMed .
26. J. Zheng, G. Teng, C. Xin, Z. Zhuo, J. Liu, Q. Li, Z. Hu, M. Xu, S. Yan, W. Yang and F. Pan, J. Phys. Chem. Lett., 2017, 8, 5537–5542 Search PubMed .
27. E. D. Orlova, A. A. Savina, S. A. Abakumov, A. V. Morozov and A. M. Abakumov, Symmetry, 2021, 13, 1628 CrossRef CAS .
28. Y. S. Meng, Y. W. Wu, B. J. Hwang, Y. Li and G. Ceder, J. Electrochem. Soc., 2004, 151, A1134 CrossRef CAS .
29. D. Liu, Z. Wang and L. Chen, Electrochim. Acta, 2006, 51, 4199–4203 CrossRef CAS .
30. T. Weigel, F. Schipper, E. M. Erickson, F. A. Susai, B. Markovsky and D. Aurbach, ACS Energy Lett., 2019, 4, 508–516 Search PubMed .
31. G. Zha, W. Hu, S. Agarwal, C. Ouyang, N. Hu and H. Hou, Chem. Eng. J., 2021, 409, 128343 CrossRef CAS .
32. C. Mi, E. Han, L. Li, L. Zhu, F. Cheng and X. Dai, Solid State Ionics, 2018, 325, 24–29 Search PubMed .
33. C. Kim, T. J. Park, S. G. Min, S. Bin Yang and J. T. Son, J. Korean Phys. Soc., 2014, 65, 243–247 Search PubMed .
34. F. Wu, G. T. Kim, M. Kuenzel, H. Zhang, J. Asenbauer, D. Geiger, U. Kaiser and S. Passerini, Adv. Energy Mater., 2019, 9, 1902445 CrossRef CAS .
35. G. Zha, N. Hu, Y. Luo, F. Wang, R. Wu, Y. Li, H. Fu and X. Fu, J. Taiwan Inst. Chem. Eng., 2023, 144, 104730 CrossRef CAS .
36. S. Park, C. Jo, H. J. Kim, S. Kim, S. T. Myung, H. K. Kang, H. Kim, J. Song, J. Yu and K. Kwon, J. Alloys Compd., 2020, 835, 155342 CrossRef CAS .
37. J. H. Mugumya, S. Mallick, A. Patel, M. L. Rasche, A. V. Sakpal, E. D. Huchler, S. Kim, R. B. Gupta and M. Jiang, J. Alloys Compd., 2024, 994, 174720 CrossRef CAS .
38. J. Jiang, H. Wu, L. Ni and M. Zou, Process Saf. Environ. Prot., 2018, 120, 87–96 CrossRef CAS .
39. M. Mou and M. Jiang, J. Pharm. Innov., 2020, 15, 281–294 CrossRef .
40. M. Jiang, Z. Zhu, E. Jimenez, C. D. Papageorgiou, J. Waetzig, A. Hardy, M. Langston and R. D. Braatz, Cryst. Growth Des., 2014, 14, 851–860 CrossRef CAS .
41. C. Yao, Y. Liu, S. Zhao, Z. Dong and G. Chen, AIChE J., 2017, 63, 1727–1739 CrossRef CAS .
42. M. T. Kreutzer, F. Kapteijn, J. A. Moulijn and J. J. Heiszwolf, Chem. Eng. Sci., 2005, 60, 5895–5916 CrossRef CAS .
43. M. L. Rasche, M. Jiang and R. D. Braatz, Comput. Chem. Eng., 2016, 95, 240–248 CrossRef CAS .
44. A. M. Nightingale, T. W. Phillips, J. H. Bannock and J. C. de Mello, Nat. Commun., 2014, 5, 3777 CrossRef CAS PubMed .
45. M. Mou, Dissertation, Virginia Commonwealth University, 2022 .
46. M. Mou, A. Patel, S. Mallick, K. Jayanthi, X.-G. Sun, M. P. Paranthaman, S. Kothe, E. Baral, S. Saleh, J. H. Mugumya, M. L. Rasche, R. B. Gupta, H. Lopez and M. Jiang, ACS Appl. Energy Mater., 2023, 6, 3213–3224 CrossRef CAS PubMed .
47. M. Mou, A. Patel, S. Mallick, B. P. Thapaliya, M. P. Paranthaman, J. H. Mugumya, M. L. Rasche, R. B. Gupta, S. Saleh, S. Kothe, E. Baral, G. P. Pandey, H. Lopez and M. Jiang, ACS Omega, 2022, 7, 42408–42417 CrossRef CAS PubMed .
48. M. Malik, K. H. Chan and G. Azimi, Mater. Today Energy, 2022, 28, 101066 CrossRef CAS .
49. J. H. Mugumya, M. L. Rasche, R. F. Rafferty, A. Patel, S. Mallick, M. Mou, J. A. Bobb, R. B. Gupta and M. Jiang, Energy Fuels, 2022, 36, 12261–12270 CrossRef CAS .
50. R. J. Gummow, M. M. Thackeray, W. I. F. David and S. Hull, Mater. Res. Bull., 1992, 27, 327–337 CrossRef CAS .
51. J. Reimers, Solid State Ionics, 1993, 61, 335–344 CrossRef CAS .
52. J. R. Mueller-Neuhaus, R. A. Dunlap and J. R. Dahn, J. Electrochem. Soc., 2000, 147, 3598 CrossRef CAS .
53. J. Wilcox, S. Patoux and M. Doeff, J. Electrochem. Soc., 2009, 156, A192 CrossRef CAS .
54. S. He, R. Zhang, X. Han, Y. Zhou, C. Zheng, C. Li, X. Xue, Y. Chen, Z. Wu, J. Gan, L. She, F. Qi, Y. Liu, M. Zhang, W. Du, Y. Jiang, M. Gao and H. Pan, Adv. Mater., 2025, 2413760 CrossRef PubMed .
55. W. Li, J. N. Reimers and J. R. Dahn, Solid State Ionics, 1993, 67, 123–130 CrossRef CAS .

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