Skip to main content
SpringerLink
Log in

Understanding wetting behavior in electrode–electrolyte interface formation and its sensitivity to electrode-current collector interaction: a lattice Boltzmann method approach

  • Published:
Journal of Thermal Analysis and Calorimetry Aims and scope Submit manuscript

Abstract

The formation of the electrolyte–electrode interface is essential for the performance of Li-ion batteries. This study aims to explore the wetting characteristics of an electrolyte within a porous electrode positioned between a current collector and a separator. By utilizing the Shan-Chen-based lattice Boltzmann method, an in-house code has been developed and thoroughly validated. This code integrates actual contact angles at the interfaces between the electrolyte and battery components. Furthermore, code acceleration through GPU-based parallel programming facilitates adequate meshing, underscoring the novelty and originality of our approach. The results of this study provide insights into the overall saturation curves and imbibition rates and clarify the primary mechanisms of electrolyte wetting within the porous matrix via local wetting rates. The electrode-current collector interface emerged as a critical factor influencing the imbibition rate and gas entrapment tendencies. Pore types at the interface have been categorized, focusing on how the material contact angle variations between the current collector and electrolyte influence wetting dynamics. Notably, it is observed that higher contact angles (90°) between the electrolyte and current collector increase the risk of trapping gas. Conversely, lower angles (15° and 35°) improve overall saturation; however, the enhancement of the wetting rate is particularly noticeable when interconnected pores are present at the interfaces of the electrode and battery components. This study underscores the combined influence of the separator and current collector in comprehending electrolyte wetting behavior, thus contributing to the advancement of battery technology.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11

Similar content being viewed by others

Abbreviations

\({F}_{\upsigma } \) :

External force for component \(\sigma \)

\({e}_{\text{i}}\) :

Particle lattice velocity in the \(ith\) direction

\({FF}_{\upsigma } \) :

Fluid–fluid force for component \(\sigma \)

\({f}_{\text{i}}^{\sigma }\) :

Particle distribution function for component \(\sigma \)

\({G}_{\text{ff}}\) :

Fluid–fluid force parameter

\({f}_{\text{i}}^{\upsigma ,\text{eq}}\) :

Equilibrium distribution function for component \(\sigma \)

\({G}_{\text{sf}}\) :

Solid–fluid force parameter

\(\tau \) :

Single-relaxation time

\( \mathop u\limits^{ \vee } \) :

Common velocity of two components

\({u}_{\upsigma } ^{\text{eq}}\) :

Macroscopic velocity

\({\alpha }_{\text{i}}\) :

Weighting factor

\( \upsilon \) :

Kinematic viscosity

\({c}_{\text{s}}\) :

Speed of sound

\(lu\) :

Lattice units

R:

Final radius of the droplet

\(\Delta P\) :

Laplace pressure

CC- θ°:

Contact angle between electrolyte and current collector, θ = 15°, 35°, or 90°

\(CMn\) :

Marker for specific imbibition rates (\(n = 1, 2\))

PIRn:

Marker for poor imbibition rate

\(\sigma \) :

Component indicator

\(\gamma \) :

Surface tension

\(i\) :

Discrete direction index

References

  1. An SJ, Li J, Daniel C, Mohanty D, Nagpure S, Wood DL III. The state of understanding of the lithium-ion-battery graphite solid electrolyte interphase (SEI) and its relationship to formation cycling. Carbon N Y. 2016;105:52–76.

    Article  CAS  Google Scholar 

  2. Wang A, Kadam S, Li H, Shi S, Qi Y. Review on modeling of the anode solid electrolyte interphase (SEI) for lithium-ion batteries. npj Comput Mater. 2018;4(1):1–26.

    Article  Google Scholar 

  3. Sun YY, Hsieh TY, Duh YS, Kao CS. Thermal behaviors of electrolytes in lithium-ion batteries determined by differential scanning calorimeter. J Therm Anal Calorim. 2014;116(3):1175–9. https://doi.org/10.1007/s10973-014-3683-9.

    Article  CAS  Google Scholar 

  4. Duh YS, Tsai MT, Kao CS. Characterization on the thermal runaway of commercial 18650 lithium-ion batteries used in electric vehicle. J Therm Anal Calorim. 2017;127(1):983–93. https://doi.org/10.1007/s10973-016-5767-1.

    Article  CAS  Google Scholar 

  5. Reddy TB. Linden’s handbook of batteries. New York: McGraw-Hill Education; 2011.

    Google Scholar 

  6. Knoche T, Reinhart G. Electrolyte filling of large-scale lithium-ion batteries: challenges for production technology and possible approaches. Appl Mech Mater. 2015;794:11–8.

    Article  Google Scholar 

  7. Armand M, Tarascon J-M. Building better batteries. Nature. 2008;451(7179):652–7.

    Article  CAS  PubMed  Google Scholar 

  8. Sakti A, Michalek JJ, Fuchs ERH, Whitacre JF. A techno-economic analysis and optimization of Li-ion batteries for light-duty passenger vehicle electrification. J Power Sources. 2015;273:966–80.

    Article  CAS  Google Scholar 

  9. Wood DL III, Li J, Daniel C. Prospects for reducing the processing cost of lithium ion batteries. J Power Sources. 2015;275:234–42.

    Article  CAS  Google Scholar 

  10. Wood DL III, Li J, An SJ. Formation challenges of lithium-ion battery manufacturing. Joule. 2019;3(12):2884–8.

    Article  Google Scholar 

  11. Wang C, Lin Y, Chiu K, Leu H, Ko T. Advanced carbon cloth as current collector for enhanced electrochemical performance of lithium-rich layered oxide cathodes. ChemistrySelect. 2017;2(16):4419–27.

    Article  CAS  Google Scholar 

  12. Lee H, Yanilmaz M, Toprakci O, Fu K, Zhang X. A review of recent developments in membrane separators for rechargeable lithium-ion batteries. Energy Environ Sci. 2014;7(12):3857–86.

    Article  CAS  Google Scholar 

  13. Arora P, Zhang Z. Battery separators. Chem Rev. 2004;104(10):4419–62.

    Article  CAS  PubMed  Google Scholar 

  14. Wanner J, Birke KP. Investigation of the influence of electrode surface structures on wettability after electrolyte filling based on experiments and a lattice Boltzmann simulation. Energies. 2023;16(15):5640.

    Article  CAS  Google Scholar 

  15. Wanner J, Birke KP. Comparison of an experimental electrolyte wetting of a lithium-ion battery anode and separator by a lattice Boltzmann simulation. Batteries. 2022;8(12):277.

    Article  CAS  Google Scholar 

  16. Jeon DH, Song J-H, Yun J, Lee J-W. Mechanistic insight into wettability enhancement of lithium-ion batteries using a ceramic-coated layer. ACS Nano. 2022;17(2):1305–14.

    Article  Google Scholar 

  17. Kühnel R-S, Obeidi S, Lübke M, Lex-Balducci A, Balducci A. Evaluation of the wetting time of porous electrodes in electrolytic solutions containing ionic liquid. J Appl Electrochem. 2013;43(7):697–704.

    Article  Google Scholar 

  18. Wu MS, Liao TL, Wang YY, Wan CC. Assessment of the wettability of porous electrodes for lithium-ion batteries. J Appl Electrochem. 2004;34(8):797–805. https://doi.org/10.1023/B:JACH.0000035599.56679.15.

    Article  CAS  Google Scholar 

  19. Pfleging W, Pröll J. A new approach for rapid electrolyte wetting in tape cast electrodes for lithium-ion batteries. J Mater Chem A. 2014;2(36):14918–26.

    Article  CAS  Google Scholar 

  20. Sheng Y, Fell CR, Son YK, Metz BM, Jiang J, Church BC. Effect of calendering on electrode wettability in lithium-ion batteries. Front Energy Res. 2014;2:56.

    Article  Google Scholar 

  21. Schilling A, et al. Influence of separator material on infiltration rate and wetting behavior of lithium-ion batteries. Energy Technol. 2020;8(2):1900078.

    Article  CAS  Google Scholar 

  22. Walji N, MacDonald BD. Influence of geometry and surrounding conditions on fluid flow in paper-based devices. Micromachines. 2016;7(5):73.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Chang S, Seo J, Hong S, Lee D-G, Kim W. Dynamics of liquid imbibition through paper with intra-fibre pores. J Fluid Mech. 2018;845:36–50.

    Article  CAS  Google Scholar 

  24. Knoche T, Zinth V, Schulz M, Schnell J, Gilles R, Reinhart G. In situ visualization of the electrolyte solvent filling process by neutron radiography. J Power Sources. 2016;331:267–76.

    Article  CAS  Google Scholar 

  25. Weydanz WJ, et al. Visualization of electrolyte filling process and influence of vacuum during filling for hard case prismatic lithium ion cells by neutron imaging to optimize the production process. J Power Sources. 2018;380:126–34.

    Article  CAS  Google Scholar 

  26. Schilling A, Gümbel P, Möller M, Kalkan F, Dietrich F, Dröder K. X-ray based visualization of the electrolyte filling process of lithium ion batteries. J Electrochem Soc. 2018;166(3):A5163.

    Article  Google Scholar 

  27. Lanz M, Lehmann E, Imhof R, Exnar I, Novák P. In situ neutron radiography of lithium-ion batteries during charge/discharge cycling. J Power Sources. 2001;101(2):177–81.

    Article  CAS  Google Scholar 

  28. Chen H-S, et al. Quantificational 4D visualization and mechanism analysis of inhomogeneous electrolyte wetting. eTransportation. 2023;16:100232.

    Article  Google Scholar 

  29. Davoodabadi A, Li J, Zhou H, Wood DL, Singler TJ, Jin C. Effect of calendering and temperature on electrolyte wetting in lithium-ion battery electrodes. J Energy Storage. 2019;26:1010354. https://doi.org/10.1016/j.est.2019.101034.

    Article  Google Scholar 

  30. Kaden Nicolaj, Schlimbach Ricarda, García Álvaro Rohde, Dröder Klaus. A systematic literature analysis on electrolyte filling and wetting in lithium-ion battery production. Batteries. 2023;9(3):164. https://doi.org/10.3390/batteries9030164.

    Article  CAS  Google Scholar 

  31. Quadrio M, et al. Review of computational fluid dynamics in the assessment of nasal air flow and analysis of its limitations. Eur Arch oto-rhino-laryngology. 2014;271(9):2349–54.

    Article  Google Scholar 

  32. Chen L, Kang Q, Mu Y, He Y-L, Tao W-Q. A critical review of the pseudopotential multiphase lattice Boltzmann model: Methods and applications. Int J Heat Mass Transf. 2014;76:210–36.

    Article  CAS  Google Scholar 

  33. Lee SG, Jeon DH. Effect of electrode compression on the wettability of lithium-ion batteries. J Power Sources. 2014;265:363–9. https://doi.org/10.1016/j.jpowsour.2014.04.127.

    Article  CAS  Google Scholar 

  34. Shodiev A, Zanotto FM, Yu J, Chouchane M, Li J, Franco AA. Designing electrode architectures to facilitate electrolyte infiltration for lithium-ion batteries. Energy Storage Mater. 2022;49:268–77. https://doi.org/10.1016/j.ensm.2022.03.049.

    Article  Google Scholar 

  35. Jeon DH. Wettability in electrodes and its impact on the performance of lithium-ion batteries. Energy Storage Mater. 2019;18:139–47. https://doi.org/10.1016/j.ensm.2019.01.002.

    Article  Google Scholar 

  36. Doolen G. Lattice gas methods for partial differential equations. CRC Press; 2019.

    Book  Google Scholar 

  37. Chen S, Wang Z, Shan X, Doolen GD. Lattice Boltzmann computational fluid dynamics in three dimensions. J Stat Phys. 1992;68:379–400.

    Article  Google Scholar 

  38. Swift MR, Orlandini E, Osborn WR, Yeomans JM. Lattice Boltzmann simulations of liquid-gas and binary fluid systems. Phys Rev E. 1996;54(5):5041–52. https://doi.org/10.1103/PhysRevE.54.5041.

    Article  CAS  Google Scholar 

  39. Shan X, Chen H. Lattice Boltzmann model for simulating flows with multiple phases and components. Phys Rev E. 1993. https://doi.org/10.1103/PhysRevE.47.1815.

    Article  Google Scholar 

  40. Shan X, Doolen G. Multicomponent lattice-Boltzmann model with interparticle interaction. J Stat Phys. 1995. https://doi.org/10.1007/BF02179985.

    Article  Google Scholar 

  41. Timm K, Kusumaatmaja H, Kuzmin A, Shardt O, Silva G, Viggen E. The lattice Boltzmann method: principles and practice. AG Cham: Switz. Springer Int. Publ; 2016.

    Google Scholar 

  42. Lee SG, Jeon DH, Kim BM, Kang JH, Kim C-J. Lattice boltzmann simulation for electrolyte transport in porous electrode of lithium ion batteries. J Electrochem Soc. 2013;160(4):H258–65. https://doi.org/10.1149/2.017306jes.

    Article  CAS  Google Scholar 

  43. Jeon DH. Enhancing electrode wettability in lithium-ion battery via particle-size ratio control. Appl Mater Today. 2021;22:100976. https://doi.org/10.1016/j.apmt.2021.100976.

    Article  Google Scholar 

  44. Shodiev A, et al. Insight on electrolyte infiltration of lithium ion battery electrodes by means of a new three-dimensional-resolved lattice Boltzmann model. Energy Storage Mater. 2021;38:80–92. https://doi.org/10.1016/j.ensm.2021.02.029.

    Article  Google Scholar 

  45. Lautenschlaeger MP, et al. Understanding electrolyte filling of lithium-ion battery electrodes on the pore scale using the lattice boltzmann method. Batter Supercaps. 2022;5:202200090. https://doi.org/10.1002/batt.202200090.

    Article  CAS  Google Scholar 

  46. Hagemeister J, Günter FJ, Rinner T, Zhu F, Papst A, Daub R. Numerical models of the electrolyte filling process of lithium-ion batteries to accelerate and improve the process and cell design. Batteries. 2022;8(10):159.

    Article  CAS  Google Scholar 

  47. El Malki A, Asch M, Arcelus O, Shodiev A, Yu J, Franco AA. Machine learning for optimal electrode wettability in lithium ion batteries. J Power Sources Adv. 2023;20:100114.

    Article  Google Scholar 

  48. Shodiev A, Duquesnoy M, Arcelus O, Chouchane M, Li J, Franco AA. Machine learning 3D-resolved prediction of electrolyte infiltration in battery porous electrodes. J Power Sources. 2021;511:230384.

    Article  CAS  Google Scholar 

  49. Taner T. The novel and innovative design with using h2 fuel of pem fuel cell: Efficiency of thermodynamic analyze. Fuel. 2021;302:121109. https://doi.org/10.1016/j.fuel.2021.121109.

    Article  CAS  Google Scholar 

  50. Taner T. The micro-scale modeling by experimental study in PEM fuel cell. J Therm Eng. 2017;3(6):1515–26. https://doi.org/10.18186/journal-of-thermal-engineering.331755.

    Article  CAS  Google Scholar 

  51. Taner T, Naqvi SAH, Ozkaymak M. Techno-economic analysis of a more efficient hydrogen generation system prototype: a case study of PEM electrolyzer with Cr-C coated SS304 bipolar plates. Fuel Cells. 2019;19(1):19–26. https://doi.org/10.1002/fuce.201700225.

    Article  CAS  Google Scholar 

  52. Taner T, Kürşat Demirci O. Energy and economic analysis of the wind turbine plant’s draft for the Aksaray city. Appl Ecol Environ Sci. 2014;2(3):82–5. https://doi.org/10.12691/aees-2-3-2.

    Article  Google Scholar 

  53. Taner T. Energy and exergy analyze of PEM fuel cell: a case study of modeling and simulations. Energy. 2018;143:284–94. https://doi.org/10.1016/j.energy.2017.10.102.

    Article  Google Scholar 

  54. Taner T. Economic analysis of a wind power plant: a case study for the cappadocia region. J Mech Sci Technol. 2018;32(3):1379–89. https://doi.org/10.1007/s12206-018-0241-6.

    Article  Google Scholar 

  55. Kuzmin A, Januszewski M, Eskin D, Mostowfi F, Derksen JJ. Simulations of gravity-driven flow of binary liquids in microchannels. Chem Eng J. 2011;171(2):646–54.

    Article  CAS  Google Scholar 

  56. Kuzmin A, Januszewski M, Eskin D, Mostowfi F, Derksen JJ. Three-dimensional binary-liquid lattice Boltzmann simulation of microchannels with rectangular cross sections. Chem Eng J. 2011;178:306–16.

    Article  CAS  Google Scholar 

  57. Montellà EP, Chareyre B, Salager S, Gens A. Benchmark cases for a multi-component Lattice-Boltzmann method in hydrostatic conditions. MethodsX. 2020;7:101090.

    Article  PubMed  PubMed Central  Google Scholar 

  58. Zakirov T, Galeev A. Absolute permeability calculations in micro-computed tomography models of sandstones by Navier-Stokes and lattice Boltzmann equations. Int J Heat Mass Transf. 2019;129:415–26.

    Article  Google Scholar 

  59. Beuse T, Fingerle M, Wagner C, Winter M, Börner M. Comprehensive insights into the porosity of lithium-ion battery electrodes: A comparative study on positive electrodes based on lini0.6mn0.2co0.2o2 (nmc622). Batteries. 2021;7(4):622. https://doi.org/10.3390/batteries7040070.

    Article  CAS  Google Scholar 

  60. Liu H, Valocchi AJ, Werth C, Kang Q, Oostrom M. Pore-scale simulation of liquid CO2 displacement of water using a two-phase lattice Boltzmann model. Adv Water Resour. 2014;73:144–58.

    Article  CAS  Google Scholar 

  61. Xu A, Shi L, Zhao TS. Accelerated lattice Boltzmann simulation using GPU and OpenACC with data management. Int J Heat Mass Transf. 2017;109:577–88.

    Article  Google Scholar 

  62. Adeeb E, Ha H. Computational analysis of naturally oscillating tandem square and circular bluff bodies: a GPU based immersed boundary–lattice Boltzmann approach. Eng Appl Comput Fluid Mech. 2022;16(1):995–1017. https://doi.org/10.1080/19942060.2022.2060309.

    Article  Google Scholar 

  63. Davoodabadi A, Jin C, Wood DL, Singler TJ, Li J. On electrolyte wetting through lithium-ion battery separators. Extrem Mech Lett. 2020;40:100960. https://doi.org/10.1016/j.eml.2020.100960.

    Article  Google Scholar 

  64. Davoodabadi A, Li J, Liang Y, Wood DL, Singler TJ, Jin C. Analysis of electrolyte imbibition through lithium-ion battery electrodes. J Power Sources. 2019;424(3):193–203. https://doi.org/10.1016/j.jpowsour.2019.03.115.

    Article  CAS  Google Scholar 

  65. Sauter C, Zahn R, Wood V. Understanding electrolyte infilling of lithium ion batteries. J Electrochem Soc. 2020;167(10):100546. https://doi.org/10.1149/1945-7111/ab9bfd.

    Article  CAS  Google Scholar 

  66. Abubaker M, Sohn CH, Ali HM. Wetting characteristics of Li-ion battery electrodes: Impact of calendaring and current collector contact angle-a lattice boltzmann method investigation. Energy Rep. 2024;11:2333–45.

    Article  Google Scholar 

  67. Bhatnagar PL, Gross EP, Krook M. A model for collision processes in gases. I. Small amplitude processes in charged and neutral one-component systems. Phys Rev. 1954;94(3):511.

    Article  CAS  Google Scholar 

  68. Landau LD, Lifshitz EM. Fluid mechanics: landau and lifshitz: course of theoretical physics. NJ: Elsevier; 2013. p. 6.

    Google Scholar 

  69. Montellà EP et al (2022) Benchmark cases for a multi-component Lattice–Boltzmann method in hydrostatic conditions to cite this version : HAL Id : hal-03493291 Benchmark cases for a multi-component Lattice-Boltzmann method in hydrostatic conditions. pp 0–20

  70. Gennes P-G, Brochard-Wyart F, Quéré D. Capillarity and wetting phenomena: drops, bubbles, pearls, waves. New York: Springer; 2004. p. 21–65.

    Book  Google Scholar 

  71. Rowlinson JS and Widom B (2013) Molecular theory of capillarity. Courier Corporation

  72. Huang H, Thorne DT, Schaap MG, Sukop MC. Proposed approximation for contact angles in Shan-and-Chen-type multicomponent multiphase lattice Boltzmann models. Physical Review E. 2007. https://doi.org/10.1103/PhysRevE.76.066701.

    Article  Google Scholar 

  73. Schmieschek S, Harting J. Contact angle determination in multicomponent lattice Boltzmann simulations. Commun Comput Phys. 2011;9(5):1165–78.

    Article  Google Scholar 

  74. Yamada M, Watanabe T, Gunji T, Wu J, Matsumoto F. Review of the design of current collectors for improving the battery performance in lithium-ion and post-lithium-ion batteries. Electrochem. 2020;1(2):124–59.

    Article  Google Scholar 

  75. Günter FJ, Rössler S, Schulz M, Braunwarth W, Gilles R, Reinhart G. Influence of the cell format on the electrolyte filling process of lithium-ion cells. Energy Technol. 2020;8(2):1801108.

    Article  Google Scholar 

  76. Jiang M, et al. Full-cell cycling of a self-supporting aluminum foil anode with a phosphate conversion coating. ACS Appl Mater Interfaces. 2019;11(17):15656–61. https://doi.org/10.1021/acsami.9b02813.

    Article  CAS  PubMed  Google Scholar 

  77. “Particle size ratio control, DH Jeon, 2021.” .

  78. Zakirov TR, Khramchenkov MG. Wettability effect on the invasion patterns during immiscible displacement in heterogeneous porous media under dynamic conditions: a numerical study. J Pet Sci Eng. 2021;206:109049. https://doi.org/10.1016/j.petrol.2021.109049.

    Article  CAS  Google Scholar 

  79. Jung M, Brinkmann M, Seemann R, Hiller T, de La Lama MS, Herminghaus S. Wettability controls slow immiscible displacement through local interfacial instabilities. Phys Rev Fluids. 2016;1(7):74202.

    Article  Google Scholar 

  80. Singh K, Jung M, Brinkmann M, Seemann R. Capillary-dominated fluid displacement in porous media. Annu Rev Fluid Mech. 2019;51:429–49.

    Article  Google Scholar 

  81. Holtzman R, Segre E. Wettability stabilizes fluid invasion into porous media via nonlocal, cooperative pore filling. Phys Rev Lett. 2015;115(16):164501.

    Article  PubMed  Google Scholar 

  82. Sangrós Giménez C, Finke B, Schilde C, Froböse L, Kwade A. Numerical simulation of the behavior of lithium-ion battery electrodes during the calendaring process via the discrete element method. Powder Technol. 2019;349:1–11. https://doi.org/10.1016/j.powtec.2019.03.020.

    Article  Google Scholar 

Download references

Acknowledgements

This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. 2022R1F1A1061903).

Author information

Authors and Affiliations

  1. Department of Mechanical Engineering, Kyungpook National University, Daegu, 41566, South Korea

    Muhammad Abubaker & Chang-Hyun Sohn

  2. Department of Mechanical Engineering, COMSATS University Islamabad, Sahiwal, 57000, Pakistan

    Muhammad Abubaker

  3. Mechanical Engineering Department, King Fahd University of Petroleum and Minerals, Dhahran, 31261, Saudi Arabia

    Hafiz Muhammad Ali

  4. Interdisciplinary Research Center for Sustainable Energy Systems (IRC-SES), King Fahd University of Petroleum and Minerals, Dhahran, 31261, Saudi Arabia

    Hafiz Muhammad Ali

Authors
  1. Muhammad Abubaker
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Chang-Hyun Sohn
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Hafiz Muhammad Ali
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Chang-Hyun Sohn.

Additional information

Publisher's Note

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

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Abubaker, M., Sohn, CH. & Ali, H.M. Understanding wetting behavior in electrode–electrolyte interface formation and its sensitivity to electrode-current collector interaction: a lattice Boltzmann method approach. J Therm Anal Calorim (2024). https://doi.org/10.1007/s10973-024-13140-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s10973-024-13140-5

Keywords

Search

Navigation