Development of a predictive model for performance analysis of anion exchange membrane electrolysers

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Authors: Riccardo Venturino, Alessio D’Alessandro, Laura Traversone, Fiammetta Rita Bianchi, Bárbara Bosio
Cited by: 2
References: 40

Abstract

Anion Exchange Membrane (AEM) water electrolysis is a promising solution for hydrogen production that consists of low-cost metals as the electrocatalyst and low-concentration alkaline solutions as the electrolyte, overcoming common issues of other low-temperature cells. This technology is investigated by developing an in-home-built Python model able to predict AEM electrolyser electrochemical performance under a dry cathode configuration as a function of applied working conditions and microstructural parameters. Polarisation losses derive from electrochemistry principles and consider effects due to the presence of bubbles that form on the electrode surface and evolve within the electrolyte. It is noteworthy that the asymmetric behaviour of AEM cells requires specific assumptions and equations for each side in view of different anodic and cathodic environments. Following the model is preliminarily validated through an ad hoc testing campaign on a lab-scale cell. Simulation results allow for identifying the limiting factors (i.e., current and solution molarity), distinguishing different polarisation losses (activation and ohmic loss as the predominant factor in high and low concentrated alkaline solutions, respectively), and quantifying losses due to bubbles (around 8% of total polarisation in the worst case). In detail, the bubbles generate turbulence within the liquid, favouring the reactant diffusion mechanisms, but decrease the effective active area and the electrolyte conductivity, resulting in the predominant effect.

Fields of Study & Subjects

Membrane-based Ion Separation Techniques Fuel Cells and Related Materials Advanced battery technologies research

Publication details

Journal / source
Electrochimica Acta
Publisher
Elsevier BV
Volume
565
Pages
148753–148753
Publication date
27 March 2026
Language
EN