Objective Driven by China's "dual carbon" goals, the alkaline electrolyzer has garnered significant attention due to its technological maturity and large-scale capacity. This review aims to provide technical support for enhancing the hydrogen production efficiency of alkaline electrolyzers and promoting their application in renewable energy systems.
Method This paper summarizes the mechanisms and recent progress concerning the influence of key components—such as electrolyzer structure, diaphragm, and catalysts—on hydrogen production efficiency. Based on this analysis, strategies for improving efficiency are proposed.
Result The review finds that: (1) Circular electrolyzers offer superior pressure resistance, while square electrolyzers provide more uniform current and temperature distribution; (2) Advanced diaphragms, including polymer-based, solvated-ion, and anion exchange membranes (AEMs), are being optimized towards high mechanical strength, low ionic resistance, and high gas barrier properties; (3) Current research focuses on non-precious metal catalysts, such as multi-component Fe-Ni-based and Mo-based composites and alloys, with strategies like nano-structuring and novel support design to enhance activity and cost-effectiveness; (4) KOH remains the preferred electrolyte due to its high ionic conductivity and ability to minimize overpotential and electrode corrosion; (5) Both narrow-gap and zero-gap electrode configurations are mainstream approaches to reduce ohmic losses; (6) High-pressure operation can further decrease overpotential and overall energy consumption.
Conclusion The hydrogen production efficiency can be enhanced through innovations like square-cell designs, advanced diaphragms (e.g., porous polymer, solvated-ion, AEMs), and multi-component/alloy catalysts. When coupling alkaline electrolyzers with variable renewable energy sources like wind and solar, dynamic efficiency can be improved by implementing strategies such as automated electrolyte replenishment and preheating. Furthermore, integrating artificial intelligence for the synergistic control of multiple parameters—including electrolyte flow rate, temperature, and pressure—is a key pathway to optimizing performance under dynamic operating conditions.