Ultrasound-assisted water electrolysis: evidence-tiered net-benefit assessment and scale-up constraints

Ultrasound-assisted water electrolysis (sono-electrolysis) is increasingly proposed as a process-intensification strategy to mitigate gas-management losses, yet its practical value remains difficult to assess because boundaries, acoustic metrology, and control modes are often reported inconsistently. This review presents an assessment-oriented evidence synthesis of low-temperature electrolysers, including alkaline electrolyser (AEL), proton exchange membrane electrolyser (PEMEL), and anion exchange membrane electrolyser (AEMEL), using a PRISMA-lite workflow, a minimum reporting set, and evidence tiering based on boundary completeness. Quantitative net-benefit inference is restricted to deployability-grade studies that report matched baselines, operating-point comparability, usable-hydrogen verification, temperature history/control, and an acoustic delivery descriptor beyond nameplate power. Across benchmarkable cases, the most consistent positive pathway is bubble management: ultrasound can reduce bubble coverage and bubble-associated resistance, yielding measurable voltage or current gains at defined operating points. However, three recurrent patterns limit generality: temperature contraction, efficiency reversals under indirect coupling, and durability-constraining cases in which short-term performance gains are offset by material penalties. A system-level framework based on total specific energy consumption, SECtotal=(Pelec+Pus+Paux)/mH2 , is then used to translate apparent electrochemical gains into net-benefit interpretation. The available evidence shows that signed net benefit is scarce, highly coupling-dependent, and frequently negated by auxiliary energy demand or durability losses. Ultrasound is therefore best interpreted not as a generic efficiency upgrade, but as a conditional bubble-management actuator whose practical value must be demonstrated under measured acoustic delivery, explicit system boundaries, and stability screening. The review concludes with evidence-weighted net-benefit windows, deployability gates, and a measurement-first roadmap for future scale-up-relevant studies.