Multi-scale modeling of the multi-phase flow in water electrolyzers for green hydrogen production

Abstract

Water electrolyzers play a crucial role in green hydrogen production. However, their efficiency and scalability are often compromised by bubble dynamics across various scales, from nanoscale to macroscale components. This review explores multi-scale modeling as a tool to visualize multi-phase flow and improve mass transport in water electrolyzers. At the nanoscale, molecular dynamics (MD) simulations reveal how electrode surface features and wettability influence nanobubble nucleation and stability. Moving to the mesoscale, models such as volume of fluid (VOF) and lattice Boltzmann method (LBM) shed light on bubble transport in porous transport layers (PTLs). These insights inform innovative designs, including gradient porosity and hydrophilic-hydrophobic patterning, aimed at minimizing gas saturation. At the macroscale, VOF simulations elucidate two-phase flow regimes within channels, showing how flow field geometry and wettability affect bubble discharging. Moreover, artificial intelligence (AI)-driven surrogate models expedite the optimization process, allowing for rapid exploration of structural parameters in channel-rib flow fields and porous flow field designs. By integrating these approaches, we can bridge theoretical insights with experimental validation, ultimately enhancing water electrolyzer performance, reducing costs, and advancing affordable, high-efficiency hydrogen production.