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Toward Energy-Efficient Alkaline Water Electrolysis: Advances in Mass Transport Optimization and Electrolyzer Design

  • Qian Zhang
  • , Yawen Hao
  • , Hongjun Chen
  • , Jialu Li
  • , Yifan Zeng
  • , Jinqi Xiong
  • , Yaoti Cheng
  • , Adnan Ozden
  • , Antonio Tricoli
  • , Fengwang Li
    • University of Sydney

    Research output: Contribution to journalReview articlepeer-review

    39 Scopus citations

    Abstract

    Alkaline water electrolysis (AWE) offers a promising route for scalable renewable hydrogen production but is constrained by significant multiscale mass-transport challenges that limit its efficiency and durability. Recent advances in hierarchical membrane structures, gradient porous electrodes, and optimized flow-field designs have enhanced ionic conductivity, gas separation, and electrolyte distribution. Concurrently, innovative bubble-management strategies, including surface modifications and external-field assistance, effectively mitigate gas-induced transport bottlenecks. Looking forward, emerging intelligent interface platforms that integrate adaptive materials, embedded sensors, and AI-driven digital twins promise real-time mass transport control and predictive system optimization. This review synthesizes critical progress and outlines future pathways, emphasizing that integrated materials-to-system approaches are essential for advancing robust, efficient, and economically viable hydrogen production.

    Original languageBritish English
    Article numbere04039
    JournalAdvanced Energy Materials
    Volume16
    Issue number1
    DOIs
    StatePublished - 7 Jan 2026

    UN SDGs

    This output contributes to the following UN Sustainable Development Goals (SDGs)

    1. SDG 7 - Affordable and Clean Energy
      SDG 7 Affordable and Clean Energy

    Keywords

    • AI-enabled control systems
    • alkaline water electrolysis
    • bubble dynamics
    • hydrogen production
    • mass transport optimization
    • membrane engineering

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