(Invited) Unravelling Loss Mechanisms in PEM Water Electrolysis Cells Via Elaborated in Situ Techniques
Authors: Franzetti Irene , Dai Chenke , Hensle Niklas , Lickert Thomas , Smolinka Tom , Hanke-Rauschenbach Richard 
Published: December 2024

The urge for changes in our energy mix and in finding sustainable solutions for energy provision, pushes towards fast developments in the field of hydrogen technologies. Proton exchange membrane (PEM) water electrolysis is one of the most promising solutions for a green hydrogen production, but developments of this technology are necessary to make it cheap and feasible.
To achieve this, it is necessary to have well-established and advanced characterization methods. These methods can help us understand the limitations and identify areas for improvement in cheaper, performing, and alternative materials. They can also assist us in reducing the production and activation effort of its components. By identifying the specific mechanisms or factors that limit performance or stability under certain conditions, our advanced in situ characterization techniques can provide valuable insights on durability aspects.
Before utilizing advanced methods for evaluating PEM electrolysis cell, it is fundamental to accurately assess effects and changes during the tests. These changes must exceed the reproducibility error of our tests to be considered as performance variations only. To achieve this, a round robin test is conducted, which provides reproducibility error within our facility and across different institutes[
1,2
]. This study also offers a thorough overview of fundamental characterization, such as polarization curves and electrochemical impedance spectra (EIS).
When conducting EIS measurements, it is essential to ensure that external influences are not included in the evaluation and that the discussed mechanisms belong only to the electrolysis cell response[
3
]. Improving our cell structure and voltage sense connection allows to uncover previously hidden processes occurring in the high frequency region of the impedance spectrum. This helps to develop reliable equivalent circuit models (ECM) that accurately represent the electrochemical, transport and electrical mechanisms taking place within an electrolysis cell.
Impedance spectra serve as a valuable tool for assessing various processes occurring during electrolysis. When combined with a reference electrode, it is possible to evaluate the contribution of each electrode. It allows us to determine which electrode undergoes the most significant variations during cell activation or break-in. Additionally, EIS conducted with a reference electrode and distribution of relaxation times (DRT) can firstly provide evidence to the extent of contribution of each electrode to the overall spectra and can also specify the limiting processes associated with each electrode. The former evaluation is achieved via comparison of tests with variating operating condition in the very first hours of operation (activation or break-in). The latter study is approached via tests with different catalyst layer loadings and membrane thicknesses. These half-cell results can be used to drive developments in manufacturing of catalyst coated membrane (CCM) and fine-tuning the improvements of the electrode performance.
References:

Bender G, Carmo M, Smolinka T, et al. Initial approaches in benchmarking and round robin testing for proton exchange membrane water electrolyzers. International Journal of Hydrogen Energy. 2019;44(18):9174-9187. https://doi:10.1016/j.ijhydene.2019.02.074.

Lickert T, Fischer S, Young JL, et al. Advances in benchmarking and round robin testing for PEM water electrolysis: Reference protocol and hardware. Applied Energy. 2023;352:121898. https://doi:10.1016/j.apenergy.2023.121898.

Franzetti I, Pushkarev A, Chan A-L, Smolinka T. Parasitic Effects in Impedance Spectrum of PEM Water Electrolysis Cells: Case Study of High-Frequency Inductive Effects. Energy Technology. 2023;11(12):2300375. https://doi:10.1002/ente.202300375.

T.H. Wan, M. Saccoccio, C. Chen, F. Ciucci, Influence of the Discretization Methods on the Distribution of Relaxation Times Deconvolution: Implementing Radial Basis Functions with DRTtools, Electrochimica Acta, 184 (2015) 483-499.

A. Maradesa, B. Py, T.H. Wan, M.B. Effat, F. Ciucci, Selecting the Regularization Parameter in the Distribution of Relaxation Times, Journal of the Electrochemical Society, 170 (2023) 030502.

Figure 1