MXene-based interface-engineering electrocatalysts and artificial intelligence-driven strategies for advanced anion exchange membrane water and seawater electrolysis

Abstract

Green hydrogen production through water electrolysis is a promising pathway for renewable-energy integration and low-carbon development. Among electrolysis technologies, Anion Exchange Membrane Water Electrolysis (AEMWE) is attracting increasing attention because it enables alkaline operation, uses earth-abundant catalysts, and can use lower-cost system components. However, translating high electrocatalytic activity from three-electrode testing to membrane electrode assembly (MEA) operation remains challenging due to interfacial resistance, catalyst-ionomer incompatibility, mass-transport limitations, membrane degradation, and long-term durability issues. In this context, two-dimensional MXene-based materials have emerged as promising platforms for AEM water and seawater electrolysis owing to their high electrical conductivity, tunable surface terminations, hydrophilicity, structural flexibility, and strong interfacial coupling with catalytic phases. This review critically discusses recent progress in MXene-based catalysts and membrane-related systems, focusing on heterostructure engineering, multicomponent nanocomposites, defect modulation, and surface/interface regulation. The roles of MXenes as conductive scaffolds, charge-transfer mediators, adsorption-energy regulators, catalyst-dispersion supports, and mass-transport promoters are examined in relation to the kinetics and stability of HER/OER. Special attention is given to seawater electrolysis, where chloride-induced corrosion, competing chlorine evolution, salt precipitation, and catalyst/membrane instability remain major barriers. Recent advances in MXene-containing anion-exchange membranes are also discussed in terms of structure-property relationships involving surface terminations, polymer-MXene compatibility, microphase separation, swelling control, mechanical reinforcement, and gas-crossover suppression. Finally, artificial intelligence, machine learning, and digital-twin frameworks are presented as complementary tools for descriptor identification, catalyst and membrane screening, and MEA-level performance prediction. Overall, this review provides a critical overview of MXene-enabled interface engineering for durable and practically relevant AEM water and seawater electrolysis systems.