Influence of Ionomer Loading and Substrate Wettability on the Morphology of Ionomer Thin Films Using Coarse-Grained Solvent Evaporation Simulations

Hydrocarbon Ionomeric Binders for Fuel Cells and Electrolyzers

Ionomeric binders in catalyst layers, abbreviated as ionomers, play an essential role in the performance of polymer-electrolyte membrane fuel cells and electrolyzers. Due to environmental issues associated with perfluoroalkyl substances, alternative hydrocarbon ionomers have drawn substantial attention over the past few years. This review surveys literature to discuss ionomer requirements for the electrodes of fuel cells and electrolyzers, highlighting design principles of hydrocarbon ionomers to guide the development of advanced hydrocarbon ionomers.

Multiscale CO2 Electrocatalysis to C2+ Products: Reaction Mechanisms, Catalyst Design, and Device Fabrication

Electrosynthesis of value-added chemicals, directly from CO2, could foster achievement of carbon neutral through an alternative electrical approach to the energy-intensive thermochemical industry for carbon utilization. Progress in this area, based on electrogeneration of multicarbon products through CO2 electroreduction, however, lags far behind that for C1 products. Reaction routes are complicated and kinetics are slow with scale up to the high levels required for commercialization, posing significant problems. In this review, we identify and summarize state-of-art progress in multicarbon synthesis with a multiscale perspective and discuss current hurdles to be resolved for multicarbon generation from CO2 reduction including atomistic mechanisms, nanoscale electrocatalysts, microscale electrodes, and macroscale electrolyzers with guidelines for future research. The review ends with a cross-scale perspective that links discrepancies between different approaches with extensions to performance and stability issues that arise from extensions to an industrial environment.

Effect of Substrate Surface Charges on Proton Conduction of Ultrathin Nafion Films

A potential approach to enhance the suppressed proton conductivity of nanoscale ultrathin Nafion films is to adjust the ionomer structure via regulating the catalyst-ionomer interaction. To understand the interaction between substrate surface charges and Nafion molecules, self-assembled ultrathin films (∼20 nm) were prepared on the SiO₂ model substrates, which were modified with silane coupling agents to carry either negative (COO^-) or positive (NH₃⁺) charges. Specifically, the surface energy, phase separation, and proton conductivity were investigated by contact angle measurements, atomic force microscopy, and microelectrodes to illuminate the relationship between the substrate surface charge, thin-film nanostructure, and proton conduction. Compared to electrically neutral substrates, ultrathin films formed faster on the negatively charged substrate with an 83% increase in proton conductivity but formed more slowly on the positively charged substrate, with proton conductivity decreased by 35% at 50 °C. The surface charges interact with sulfonic acid groups of Nafion molecules to alter molecular orientation, resulting in different surface energies and phase separation, which are responsible for proton conductivity variation.

Deep Learning to Reveal the Distribution and Diffusion of Water Molecules in Fuel Cell Catalyst Layers

Water management in the catalyst layers (CLs) of proton-exchange membrane fuel cells is crucial for its commercialization and popularization. However, the high experimental or computational cost in obtaining water distribution and diffusion remains a bottleneck in the existing experimental methods and simulation algorithms, and further mechanistic exploration at the nanoscale is necessary. Herein, we integrate, for the first time, molecular dynamics simulation with our customized analysis framework based on a multiattribute point cloud dataset and an advanced deep learning network. This was achieved through our workflow that generates simulated transport data of water molecules in the CLs as the training and test dataset. Deep learning framework models the multibody solid-liquid system of CLs on a molecular scale and completes the mapping from the Pt/C substrate structure and Nafion aggregates to the density distribution and diffusion coefficient of water molecules. The prediction results are comprehensively analyzed and error evaluated, which reveals the highly anisotropic interaction landscape between 50,000 pairs of interacting nanoparticles and explains the structure and water transport property relationship in the hydrated Nafion film on the molecular scale. Compared to the conventional methods, the proposed deep learning framework shows computational cost efficiency, accuracy, and good visual display. Further, it has a generality potential to model macro- and microscopic mass transport in different components of fuel cells. Our framework is expected to make real-time predictions of the distribution and diffusion of water molecules in CLs as well as establish statistical significance in the structural optimization and design of CLs and other components of fuel cells.

Interfacial Distribution of Nafion Ionomer Thin Films on Nitrogen-Modified Carbon Surfaces

Chemically modified carbon supports for the cathode catalyst layers of polymer electrolyte fuel cells (PEFCs) show considerable promise for boosting the oxygen reduction reaction. This study evaluated the ionomer distribution of Nafion ionomer thin films on nitrogen (N)-modified carbon surfaces along their depth direction. Neutron reflectivity (NR) measurements performed using the double-contrast technique with H2O and D2O revealed that the introduction of N functional groups to carbon thin films promoted ionomer adsorption onto the surface under wet conditions (22 °C, 85% relative humidity). Molecular dynamics (MD) simulations conducted to verify the origin of the robust contact between the ionomer and N-modified carbon surface revealed an ionomer adsorption mechanism on the N-modified carbon surfaces, which involved Coulomb interactions between the positively charged carbon surface and the ionomer side chains with negatively charged sulfonic acid groups. The positive surface charge, which was determined using the contents of the N functional groups estimated by X-ray photoelectron spectroscopy, was found to be sufficient as an impetus for ionomer adsorption. This strategy involving NR measurements and MD simulations can provide insights into the solid-ionomer interfacial structures in a cathode catalyst layer and can therefore be extensively employed in studies on PEFCs.

The Martini Model in Materials Science

The Martini model, a coarse-grained force field initially developed with biomolecular simulations in mind, has found an increasing number of applications in the field of soft materials science. The model's underlying building block principle does not pose restrictions on its application beyond biomolecular systems. Here, the main applications to date of the Martini model in materials science are highlighted, and a perspective for the future developments in this field is given, particularly in light of recent developments such as the new version of the model, Martini 3.