Dispersion of Nafion Ionomer Aggregates in 1-Propanol/Water Solutions: Effects of Ionomer Concentration, Alcohol Content, and Salt Addition

Self-Assembly of Lamellae-in-Lamellae by Double-Tail Cationic Surfactants

The molecular structures of surfactants play a pivotal role in influencing their self-assembly behaviors. In this work, using simulations and experiments, an unconventional hierarchically layered structure in the didodecyldimethylammonium bromide (DDAB)/water binary system: lamellae-in-lamellae is revealed, a new self-assembly structure in surfactant system. This self-assembly structure refers to a lamellar structure with a shorter periodic length (inner lamellae) embedded in a lamellar phase with a longer periodic length (outer lamellae). The normal vectors of these two lamellar regions orient perpendicularly. In addition, it is observed that this lamellar-in-lamellar phase disappears when the two tails of the cationic surfactants become longer. The formation of the lamellar-in-lamellar architecture arises from multiple interacting factors. The key element is that the short tails of the DDAB surfactants enhance hydrophilicity and rigidity, which facilitates the formation of the inner lamellae. Moreover, the lateral monolayer of the inner lamellae provides shielding from the water and prompts the formation of the outer lamellae. These findings indicate that molecular structures and flexibility can profoundly redirect the hierarchical self-assembly behaviors in amphiphilic systems. More broadly, this work presents a new strategy to deliberately program hierarchical nanomaterials by designing specific surfactant molecules to act as tunable scaffolds, reactors, and carriers.

Predicting Diffusion Coefficients in Nafion Membranes during the Soaking Process Using a Machine Learning Approach

Nafion, a versatile polymer used in electrochemistry and membrane technologies, exhibits complex behaviors in saline environments. This study explores Nafion membrane's IR spectra during soaking and subsequent drying processes in salt solutions at various concentrations. Utilizing the principles of Fick's second law, diffusion coefficients for these processes are derived via exponential approximation. By harnessing machine learning (ML) techniques, including the optimization of neural network hyperparameters via a genetic algorithm (GA) and leveraging various regressors, we effectively pinpointed the optimal model for predicting diffusion coefficients. Notably, for the prediction of soaking coefficients, our model is composed of layers with 64, 64, 32, and 16 neurons, employing ReLU, ELU, sigmoid, and ELU activation functions, respectively. Conversely, for drying coefficients, our model features two hidden layers with 16 and 12 neurons, utilizing sigmoid and ELU activation functions, respectively.

Colloidal Stability of PFSA-Ionomer Dispersions. Part I. Single-Ion Electrostatic Interaction Potential Energies

Charged colloidal particles neutralized by a single counterion are increasingly important for many emerging technologies. Attention here is paid specifically to hydrogen fuel cells and water electrolyzers whose catalyst layers are manufactured from a perfluorinated sulfonic acid polymer (PFSA) suspended in aqueous/alcohol solutions. Partially dissolved PFSA aggregates, known collectively as ionomers, are stabilized by the electrostatic repulsion of overlapping diffuse double layers consisting of only protons dissociated from the suspended polymer. We denote such double layers containing no added electrolyte as "single ion". Size-distribution predictions build upon interparticle interaction potential energies from the Derjaguin-Landau-Verwey-Overbeek (DLVO) formalism. However, when only a single counterion is present in solution, classical DLVO electrostatic potential energies no longer apply. Accordingly, here a new formulation is proposed to describe how single-counterion diffuse double layers interact in colloidal suspensions. Part II (Srivastav, H.; Weber, A. Z.; Radke, C. J. Langmuir 2024 DOI: 10.1021/acs.langmuir.3c03904) of this contribution uses the new single-ion interaction energies to predict aggregated size distributions and the resulting solution pH of PFSA in mixtures of n-propanol and water. A single-counterion diffuse layer cannot reach an electrically neutral concentration far from a charged particle. Consequently, nowhere in the dispersion is the solvent neutral, and the diffuse layer emanating from one particle always experiences the presence of other particles (or walls). Thus, in addition to an intervening interparticle repulsive force, a backside osmotic force is always present. With this new construction, we establish that single-ion repulsive pair interaction energies are much larger than those of classical DLVO electrostatic potentials. The proposed single-ion electrostatic pair potential governs dramatic new dispersion behavior, including dispersions that are stable at a low volume fraction but unstable at a high volume fraction and finite volume-fraction dispersions that are unstable with fine particles but stable with coarse particles. The proposed single-counterion electrostatic pair potential provides a general expression for predicting colloidal behavior for any charged particle dispersion in ionizing solvents with no added electrolyte.

Customizing Catalyst/Ionomer Interface for High-Durability Electrode of Proton Exchange Membrane Fuel Cells

Commercialization applications of proton exchange membrane fuel cells (PEMFCs) are throttled by the durability issues of the electrodes prepared by using catalyst inks. Probing into a desirable catalyst/ionomer interface by adjusting the catalyst inks is an effective way for obtaining high-durability electrodes. The present study investigated quantitatively the catalyst/ionomer interfaces based on the viscosity (η) property of the isopropyl alcohol (IPA) and dipropylene glycol (DPG) nonaqueous mixture solvent for the first time. Accelerated stress test (AST) showed that η as one of the characteristic parameters of the solvent had a threshold effect on the durability of electrodes. The electrodes in the half-cell and single cell all exhibited the highest durability using IPA:DPG = 2:6 (η = 27.00 cP) as the dispersion solvent in this work, embodied by its ECSA loss rate, and the cell potential loss was minimum after AST. The ECSA loss mechanism showed that a fine catalyst/ionomer interface structure was created for the highest durability electrode by regulating the η values of the solvent, and the carbon corrosion loss (le) and Pt particle dissolution loss (ld) were weakened. Based on the molecular dynamics (MD) simulation and 19F NMR spectra results, the solvent ratio (various η and similar ε and δ) affected the dispersion states of the ionomer. For the catalyst inks with the highest durability (IPA:DPG = 2:6), the Nafion backbone and side chain presented a higher mobility behavior in the solvent and tended to show the structure of extension separation and the respective aggregation of hydrophilic/hydrophobic phases. Meanwhile, Pt slab models suggested that the side chain of Nafion more easily adhered to the Pt interface zone, while the backbone was pushed toward the carbon support interface zone as more DPG molecules distributed on the Pt surface, which reduced the dissolution of Pt particles and the corrosion of the carbon support. These catalyst/ionomer interface structures tailored by regulating the solvent η values provide insights into improving the electrode durability.

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.

Micromodification of the Catalyst Layer by CO to Increase Pt Utilization for Proton-Exchange Membrane Fuel Cells

Improving the utilization of platinum in proton-exchange membrane (PEM) fuel cells is critical to reducing their cost. In the past decade, numerous Pt-based oxygen reduction reaction catalysts with high specific and mass activities have been developed. However, the high activities are mostly achieved in rotating disk electrode (RDE) measurement and have rarely been accomplished at the membrane electrode assembly (MEA) level. The failure of these direct translations from RDE to MEA has been well documented with several key reasons having been previously identified. One of them is the resistance caused by complex mass transport pathways in the MEA. Herein, we improve the proton and oxygen transportations in the MEA by building a thin and uniform distribution of ionomer on the catalyst surface. As a result, a PEM fuel cell design is capable of showing a current density improvement of 38% at the same voltage (0.6 V) under the H₂/air operation.

The polarized Raman spectra of N-methylpyrrolidone-an effective method for determination of intermolecular interaction and H-bond formation

The isotropic and anisotropic component Raman spectra and H NMR of N-methylpyrrolidone (NMP)/carbon tetrachloride and NMP/methanol binary mixture at different volume fractions have been collected. The polarization Raman frequencies and frequency differences of CO stretching vibration for NMP/methanol mixture show unique concentration-dependence and abrupt jump feature. It is found that the H-bond between solute and solvent does not destroy the noncoincidence (NCE) phenomenon, but has a significant synergistic effect on the NCE. Two distinctive clusters constrained by H-bond and intermolecular interactions were easily determined by means of linear extension method from abrupt jump curve. The experimental phenomena can be well explained by aggregation-induced splitting theory with the proposed dimer structure and H-bond cluster model. Applying the same methodology the conformation of NMP in water has been determined successfully. The establishment of this method will play an important role in the determination of biomolecule aggregation behavior and supramolecular self-assembly structure.

Effect of Catalyst Ink and Formation Process on the Multiscale Structure of Catalyst Layers in PEM Fuel Cells

The structure of a catalyst layer (CL) significantly impacts the performance, durability, and cost of proton exchange membrane (PEM) fuel cells and is influenced by the catalyst ink and the CL formation process. However, the relationship between the composition, formulation, and preparation of catalyst ink and the CL formation process and the CL structure is still not completely understood. This review, therefore, focuses on the effect of the composition, formulation, and preparation of catalyst ink and the CL formation process on the CL structure. The CL structure depends on the microstructure and macroscopic properties of catalyst ink, which are decided by catalyst, ionomer, or solvent(s) and their ratios, addition order, and dispersion. To form a well-defined CL, the catalyst ink, substrate, coating process, and drying process need to be well understood and optimized and match each other. To understand this relationship, promote the continuous and scalable production of membrane electrode assemblies, and guarantee the consistency of the CLs produced, further efforts need to be devoted to investigating the microstructure of catalyst ink (especially the catalyst ink with high solid content), the reversibility of the aged ink, and the drying process. Furthermore, except for the certain variables studied, the other manufacturing processes and conditions also require attention to avoid inconsistent conclusions.

Longitudinal strand ordering leads to shear thinning in Nafion

Proton-exchange membrane fuel cells (PEMFC) offer a promising energy generation alternative for a wide range of technologies thanks to their ecological friendliness and unparalleled efficiency. At the heart of these electrochemical cells lies the membrane electrode assembly with its most important energy conversion components, the Proton Exchange Membrane. This component is created through the use of printing techniques and Nafion inks. The physicochemical properties of the ink, such as its viscosity under shear, are critical for the finished product. In this work we present non-equilibrium Molecular Dynamics simulations using a MARTINI based coarse-grained model for Nafion to understand the mechanism governing the shear viscosity of Nafion solutions. By simulating a Couette flow and calculating density maps of the Nafion chains in these simulations we shed light on the process that leads to the experimentally observed shear thinning effects of Nafion solutions under flow. We observe rod-shaped Nafion microstructures, 3 nm in size on average, when shear flow is absent or low. Higher shear rates instead break these structures and align Nafion strands along the direction of the flow, resulting in lower shear viscosities. Our work paves the way for a deeper understanding of the dynamic and mechanical properties of Nafion including studies of more complex CL and PEM inks.

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.

Solvent-Dependent Adsorption of Perfluorosulfonated Ionomers on a Pt(111) Surface Using Atomic Force Microscopy

The adsorption behavior of perfluorosulfonated ionomers (PFSIs) on a Pt(111) surface in various solvents is investigated by in situ atomic force microscopy (AFM) and discussed on the basis of aggregation of PFSIs in the liquid phase. The AFM images show that, in an aqueous solution of PFSI (0.1 wt % Nafion + 99.9 wt % water), PFSI aggregates with a lateral size of 20-200 nm adsorb on the Pt(111) surface. In a PFSI solution containing a small amount of 1-propanol (0.1 wt % Nafion + 99.5 wt % water + 0.4 wt % 1-propanol), however, slightly smaller aggregates adsorb on the Pt(111) surface. Such solvent-dependent sizes of adsorbed aggregates are in reasonable agreement with apparent hydrodynamic radii of PFSIs in the corresponding solutions determined by dynamic light scattering (DLS) while assuming the formation of spherical aggregation. Interestingly, a step-terrace structure characteristic to a clean Pt(111) surface is observed in a propanol-rich PFSI solution (0.1 wt % Nafion + 44.45 wt % water + 55.45 wt % 1-propanol) but X-ray photoelectron spectroscopy clearly indicates the existence of fluorocarbon species at the Pt(111) surface, suggesting the formation of a smooth adsorbed layer of PFSIs in a lying down configuration. Absence of any features assignable to aggregates in DLS data suggests well-dispersion of PFSIs in such propanol-rich solution without aggregations. Thus, the adsorbed structure of PFSIs at Pt surfaces can be controlled by tuning the composition of mixed solvent, which affects the aggregation of PFSI in the liquid phase.