Gas-Induced Structural Damages in Forward-Bias Bipolar Membrane CO2 Electrolysis Studied by Fast X-ray Tomography.

Forward-bias bipolar membrane (BPM) CO2 coelectrolysis (CO2ELY) aims at overcoming the issues of salt precipitation and CO2 crossover in anion exchange membrane CO2ELY. Increasing the stability of BPM-CO2ELY is crucial for widespread application of the technique. In this study, we employ time-resolved X-ray tomographic microscopy to elucidate the structural dynamics that occur within the electrochemical cell during operation under various conditions. Using advanced image processing methods, including custom 4D machine learning segmentation, we can visualize and quantify damages in the membrane and anode catalyst layer (CL). We compare our results to a CO2 transport model and hypothesize gaseous CO2 as the cause of the observed damages. At any operation condition, CO2 is formed at the junction in the center of the BPM by recombination of carbonate ions. CO2 migrates to the anode by diffusion and goes into the gas phase at the interface of the membrane and anode CL. After sufficient CO2 accumulation and pressure buildup after only tens of minutes, small irreversible holes break into the CL distributed over the entire active area. Additionally, at higher current densities, the CO2 accumulation leads to membrane delamination at the BPM junction. Despite the clear degradation processes, we do not observe an obvious direct effect on the electrochemical performance. The poor stability of BPM-CO2ELY remains an open question.

Operando Scanning Small-/Wide-Angle X-ray Scattering for Polymer Electrolyte Fuel Cells: Investigation of Catalyst Layer Saturation and Membrane Hydration- Capabilities and Challenges.

Polymer electrolyte fuel cells are an essential technology for future local emission-free mobility. One of the critical challenges for thriving commercialization is water management in the cells. We propose small- and wide-angle X-ray scattering as a suitable diagnostic tool to quantify the liquid saturation in the catalyst layer and determine the hydration of the ion-conducting membrane in real operating conditions. The challenges that may occur in operando data collection are described in detail─separation of the anode and cathode, cell alignment to the beam, X-ray radiation damage, and the possibility of membrane swelling. A synergistic development of experimental setup, data acquisition, and data interpretation circumvents the major challenges and leads to practical and reliable insights.

On the water transport mechanism through the microporous layers of operando polymer electrolyte fuel cells probed directly by X-ray tomographic microscopy.

Product water transport via the microporous layer (MPL) and gas diffusion layer (GDL) substrate during polymer electrolyte fuel cell (PEFC) operation was directly and quantitatively observed by X-ray tomographic microscopy (XTM). The liquid water distribution in two types of MPLs with different pore size distributions (PSDs) was characterized as a function of the inlet gas relative humidity (RH) and current density under humid operating conditions at 45 °C. During the first minute of PEFC operation, liquid water mainly accumulated at the catalyst layer (CL)/MPL interface and in the GDL substrate close to the flow fields. Furthermore, under all tested conditions, saturation in the MPL was low (<25%), whereas under the rib, the saturation in the GDL was up to ca. 70%. Based on these XTM results, it is confirmed that in the high porosity MPLs, vapor transport was non-negligible even at high humidity conditions. Therefore, on top of the widely discussed MPL pore size and its distribution, it is proposed that the lower thermal conductivity from the high porosity of MPLs can also be a main cause of promoted vapor transport, reducing water saturation near the CL.

How the Porous Transport Layer Interface Affects Catalyst Utilization and Performance in Polymer Electrolyte Water Electrolysis.

Cost reduction and fast scale-up of electrolyzer technologies are essential for decarbonizing several crucial branches of industry. For polymer electrolyte water electrolysis, this requires a dramatic reduction of the expensive and scarce iridium-based catalyst, making its efficient utilization a key factor. The interfacial properties between the porous transport layer (PTL) and the catalyst layer (CL) are crucial for optimal catalyst utilization. Therefore, it is essential to understand the relationship between this interface and electrochemical performance. In this study, we fabricated a matrix of two-dimensional interface layers with a well-known model structure, integrating them as an additional layer between the PTL and the CL. By characterizing the performance and conducting an in-depth analysis of the overpotentials, we were able to estimate the catalyst utilization at different current densities, correlating them to the geometric properties of the model PTLs. We found that large areas of the CL become inactive at increasing current density either due to dry-out, oxygen saturation (under the PTL), or the high resistance of the CL away from the pore edges. We experimentally estimated the water penetration in the CL under the PTL to be ≈20 µm. Experimental results were corroborated using a 3D-multiphysics model to calculate the current distribution in the CL and estimate the impact of membrane dry-out. Finally, we observed a strong pressure dependency on performance and high-frequency resistance, which indicates that with the employed model PTLs, a significant gas phase accumulates in the CL under the lands, hindering the distribution of liquid water. The findings of this work can be extrapolated to improve and engineer PTLs with advanced interface properties, helping to reach the required target goals in cost and iridium loadings.

Quantification of PEFC Catalyst Layer Saturation via In Silico, Ex Situ, and In Situ Small-Angle X-ray Scattering.

The complex nature of liquid water saturation of polymer electrolyte fuel cell (PEFC) catalyst layers (CLs) greatly affects the device performance. To investigate this problem, we present a method to quantify the presence of liquid water in a PEFC CL using small-angle X-ray scattering (SAXS). This method leverages the differences in electron densities between the solid catalyst matrix and the liquid water filled pores of the CL under both dry and wet conditions. This approach is validated using ex situ wetting experiments, which aid the study of the transient saturation of a CL in a flow cell configuration in situ. The azimuthally integrated scattering data are fitted using 3D morphology models of the CL under dry conditions. Different wetting scenarios are realized in silico, and the corresponding SAXS data are numerically simulated by a direct 3D Fourier transformation. The simulated SAXS profiles of the different wetting scenarios are used to interpret the measured SAXS data which allows the derivation of the most probable wetting mechanism within a flow cell electrode.

Understanding the microstructure of a core-shell anode catalyst layer for polymer electrolyte water electrolysis.

Reducing precious metal loading in the anodic catalyst layer (CL) is indispensable for lowering capital costs and enabling the widespread adoption of polymer electrolyte water electrolysis. This work presents the first three-dimensional reconstruction of a TiO2-supported IrO2 based core shell CL (3 mgIrO2/cm2), using high-resolution X-ray ptychographic tomography at cryogenic temperature of 90 K. The high data quality and phase sensitivity of the technique have allowed the reconstruction of all four phases namely pore space, IrO2, TiO2 support matrix and the ionomer network, the latter of which has proven to be a challenge in the past. Results show that the IrO2 forms thin nanoporous shells around the TiO2 particles and that the ionomer has a non-uniform thickness and partially covers the catalyst. The TiO2 particles do not form a percolating network while all other phases have high connectivity. The analysis of the CL ionic and electronic conductivity shows that for a dry CL, the ionic conductivity is orders of magnitudes lower than the electronic conductivity. Varying the electronic conductivity of the support phase by simulations, reveals that the conductivity of the support does not have a considerable impact on the overall CL electrical conductivity.

On the role of pore constrictions in gas diffusion electrodes.

Water management by gas diffusion electrodes is a fundamental aspect of the performance of electrochemical cells. Herein, we introduce the characteristic constrictions size as a descriptor for microporous layers (MPL). This parameter is calculated by volumetric analysis of focused ion beam nanotomography and compared to mercury intrusion porosimetry measurements.

Deep learning based classification of dynamic processes in time-resolved X-ray tomographic microscopy.

Time-resolved X-ray tomographic microscopy is an invaluable technique to investigate dynamic processes in 3D for extended time periods. Because of the limited signal-to-noise ratio caused by the short exposure times and sparse angular sampling frequency, obtaining quantitative information through post-processing remains challenging and requires intensive manual labor. This severely limits the accessible experimental parameter space and so, prevents fully exploiting the capabilities of the dedicated time-resolved X-ray tomographic stations. Though automatic approaches, often exploiting iterative reconstruction methods, are currently being developed, the required computational costs typically remain high. Here, we propose a highly efficient reconstruction and classification pipeline (SIRT-FBP-MS-D-DIFF) that combines an algebraic filter approximation and machine learning to significantly reduce the computational time. The dynamic features are reconstructed by standard filtered back-projection with an algebraic filter to approximate iterative reconstruction quality in a computationally efficient manner. The raw reconstructions are post-processed with a trained convolutional neural network to extract the dynamic features from the low signal-to-noise ratio reconstructions in a fully automatic manner. The capabilities of the proposed pipeline are demonstrated on three different dynamic fuel cell datasets, one exploited for training and two for testing without network retraining. The proposed approach enables automatic processing of several hundreds of datasets in a single day on a single GPU node readily available at most institutions, so extending the possibilities in future dynamic X-ray tomographic investigations.

Operando Liquid Pressure Determination in Polymer Electrolyte Fuel Cells.

Extending the operating range of fuel cells to higher current densities is limited by the ability of the cell to remove the water produced by the electrochemical reaction, avoiding flooding of the gas diffusion layers. It is therefore of great interest to understand the complex and dynamic mechanisms of water cluster formation in an operando fuel cell setting as this can elucidate necessary changes to the gas diffusion layer properties with the goal of minimizing the number, size, and instability of the water clusters formed. In this study, we investigate the cluster formation process using X-ray tomographic microscopy at 1 Hz frequency combined with interfacial curvature analysis and volume-of-fluid simulations to assess the pressure evolution in the water phase. This made it possible to observe the increase in capillary pressure when the advancing water front had to overcome a throat between two neighboring pores and the nuanced interactions of volume and pressure evolution during the droplet formation and its feeding path instability. A 2 kPa higher breakthrough pressure compared to static ex situ capillary pressure versus saturation evaluations was observed, which suggests a rethinking of the dynamic liquid water invasion process in polymer electrolyte fuel cell gas diffusion layers.

A Method for Spatial Quantification of Water in Microporous Layers of Polymer Electrolyte Fuel Cells by X-ray Tomographic Microscopy.

A microporous layer (MPL) is typically added to the gas diffusion layer of polymer electrolyte fuel cells (PEFCs) to promote cell performance and water management. The transport mechanism of the water through the MPL is, however, not well understood due to its small pores (20-500 nm). Here, we demonstrate that polychromatic X-ray tomographic microscopy (XTM) can be used to determine the porosity and the spatial distribution of water in nanoporous materials and can quantitatively map the liquid water saturation of MPLs. The presented technique requires no a priori knowledge of the composition of the MPL and has a field of view on the millimeter scale, which is orders of magnitude larger than conventional electron microscopy techniques for nanoscale materials. The available field of view is compatible with existing operando cells for X-ray tomography, paving the way for the analysis of water transport in MPLs during operation.

Gas Diffusion Layers with Deterministic Structure for High Performance Polymer Electrolyte Fuel Cells.

Hydrogen-fed polymer electrolyte fuel cells (PEFCs) are promising electrochemical energy converters and a key technology for sustainable mobility and coupling energy sectors. Under operating conditions, water is produced by the oxygen reduction reaction. The gas diffusion layer (GDL) materials, interfacing the reaction sites and gas feed channels, play a key role in the water management. When water condenses in the GDL pore structure, the gas transport to the cathode catalyst layer is deteriorated, thus limiting the cell performance. State-of-the-art GDL materials are stochastic, porous media based on carbon fibers, where water and gas are transported on random, tortuous paths through the pore network. In this work, a novel approach based on a material with a deterministic structure, with a two-layered fabric, is presented. This material, with just one pore throat in the transport path, facilitates water transport and increases the effective diffusivity for gas transport through its open structure. Furthermore, the regular pattern opens up a wide range of tuning opportunities. The presented results demonstrate the improved water management, on the basis of X-ray tomographic image data, and superior cell performance of this novel class of materials, able to be adapted to the local channel geometry.

Polymer electrolyte fuel cell performance degradation at different synchrotron beam intensities.

The degradation of cell performance of polymer electrolyte fuel cells under monochromatic X-ray irradiation at 13.5 keV was studied in galvanostatic and potentiostatic operation modes in a through-plane imaging direction over a range of two orders of magnitude beam intensity at the TOMCAT beamline of the Swiss Light Source. The performance degradation was found to be a function of X-ray dose and independent of beam intensity, whereas the degradation rate correlates with beam intensity. The cell performance was more sensitive to X-ray irradiation at higher temperature and gas feed humidity. High-frequency resistance measurements and the analysis of product water allow conclusions to be drawn on the dominating degradation processes, namely change of hydrophobicity of the electrode and sulfate contamination of the electrocatalyst.