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Results for “fuel cell structure optimization”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

High spatial resolution temperature profile measurements of solid-oxide fuel cells

Temperature gradients resulting from local electrochemical reactions, current distribution and geometry of gas flow channels in solid oxide fuel cells (SOFCs) create thermal stresses, localized thermophysical property gradients and uneven property evolution, contributing to SOFC degradation. This paper presents a new method to perform temperature measurements (up to 800°C) at high spatial resolutions to monitor the operation of SOFCs. Using femtosecond laser irradiation, distributed fiber sensors were hardened for high temperature environment applications. Distributed fiber sensors were embedded in interconnected plates using an additive manufacturing method to perform temperature measurements with 4-mm spatial resolution during the operation of a planar fuel cell. The measurement revealed the impact of various H 2 fuel concentrations and current loads have on temperature profiles of the SOFC tested. Temperature variation on the anode side was found to be less than 5°C, and 3°C on the cathode side. The measurements were compared to results from a multiphysics fuel cell performance model simulating similar conditions. These simulations predicted similar temperature gradients, indicating the experimental data obtained is reasonable. The model also predicts that the effect of the embedded sensor has on the local temperature will be minimal and that the gradient of temperature in the gas channels will be captured despite the separation between the sensor and the gas flow. Finally, the high spatial resolution data harnessed by these distributed fiber sensors provides experimental support for model-based design and optimization to improve the operational efficiency and longevity of solid oxide fuel cells and fuel cell assemblies.

25 ENERGY STORAGE↗
DOE OSTI2025

PFSA-Ionomer Adsorption to C and Pt/C Particles in Fuel-Cell Inks

Catalyst inks used to make fuel-cell electrodes consist of Pt/C catalyst particles and a perfluorosulfonic acid (PFSA) ionomer dispersed in water/alcohol solvent mixtures. PFSA ionomer in the ink adsorbs to the surface of the catalyst particles, dictating the dispersion colloid properties. Following adsorption, the subsequent distribution of excess nonadsorbed ionomer in the ink then governs the final structure of the electrode. Here, we characterize the adsorption of the PFSA ionomer onto Pt/C catalyst particles. PFSA adsorption is largely irreversible. Adsorbed sulfonic-acid moieties impart a negative charge on the catalyst surface, causing electrostatic repulsion between the free ionomer in solution and the ionomer-covered Pt/C particle surface. The amount of adsorption is limited by the resulting electrostatic charge that grows as more ionomer adsorbs, and the catalyst surface becomes more negatively charged. Attenuating electrostatic repulsion by increasing the ink ionic strength promotes ionomer adsorption. Electrostatically limited adsorption is observed, irrespective of the solvent water/n-propanol ratio or the catalyst particle porosity and Pt loading. Experimentally measured ionomer adsorption isotherms are well predicted by a Smoluchowski-based kinetic adsorption model, in which the electrostatic energy barrier for adsorption is predicted from DLVO theory. These findings help to unravel the complex phenomena within these colloidal dispersions, allowing for subsequent tailoring of inks to optimize fuel-cell electrode structure and performance.

Adsorption↗
DOE OSTI2021

Tailoring catalyst layer structures for anion exchange membrane fuel cells by controlling the size of ionomer aggreates in dispersion

The development of anion exchange membranes and ionomers plays a critical role in performance of anion exchange membrane fuel cells. However, the optimal design of catalyst layer structures still remains unexplored despite its significance. Herein, the rational design guide is presented for cathode and anode catalyst layers using m-TPN1 ionomer by controlling the size of ionomer aggregates in dispersion and comparing various catalyst layer structures. The size of m-TPN1 aggregates decreases, creating a more uniform ionomer distribution and a larger triple-phase-boundary. As ionomer distribution of the cathode catalyst layer becomes more uniform, the power density of membrane-electrode-assembly is enhanced. Also, the power density at fully humidified condition strongly correlates with the porosity of anode catalyst layer due to the limitation of hydrogen transport at anode by water flooding.

42 ENGINEERING↗
DOE OSTI2020

New Approaches to Improved PEM Fuel Cell Catalyst Layers

Polymer-electrolyte membrane (PEM) fuel-cells are one of the most promising energy conversion technologies for renewable clean energy applications. A major challenge preventing their widespread commercialization is achieving high performance with lowloadings of platinum group metal (PGM) catalysts. One of the factors driving performance limitations in the cell is the mass transport losses within the cathode catalyst layers due to sluggish oxygen-reduction reactions occurring at the platinum-ionomer interface, which is believed to be linked to reduced transport of ions and oxygen. A viable solution to reduce the transport resistances in the catalyst layers is to create new ionomers that can provide good ion and oxygen transport needed to accomplish high-performing fuel cell catalysts. Characterization of transport properties of ionomers for various molecular architectures is the key step, in the effort to create and identify the optimized polymer structure with improved transport. Using this approach, Tetramer Technologies and LBNL propose improved fuel-cell catalyst ionomers based on Tetramers proprietary polymer chemistry, as highlighted under subtopic 17a Innovative Approaches Toward Discovery and Development of Improved Ionomers for Polymer Electrolyte Membrane Fuel Cell Catalyst Layer.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2020

Strain-Modulated Platinum–Palladium Nanowires for Oxygen Reduction Reaction

Electrocatalytic activity of alloy nanocatalytsts can be manipulated effectively by tuning their physical properties (ensemble, geometric, and ligand effects) to afford optimal surface structure and compositions for proton exchange membrane fuel cell (PEMFC) application. Herein, highly catalytic platinum-palladium nanowires (Pt n Pd 100-n NWs) with a subtle lattice strain and Boerdijk-Coxeter helix type morphology are synthesized through a surfactant-free, thermal single phase solvent method. X-ray diffraction results show that Pt n Pd 100-n NWs are exposed through the (111) facets and their shrinking or expanding lattice parameters can be modulated by the alloy compositions. Electrochemical results reveal that their high catalytic activity correlates with the lattice shrinking, facets, and bimetallic compositions, showing higher activity when the ratio of Pt and Pd is similar to ~78:22, which is further supported by DFT results. Compared to the nanoparticle type platinum-palladium alloyed catalysts with similar metal compositions (Pt n Pd 100-n NPs), the Pt n Pd 100-n NWs exhibit significantly improved electrocatalytic activity and stability for the oxygen reduction reaction. Our findings open new strategies to design the highly active and stable alloy nanocatalysts with controllable compositions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Uncovering Structure–Conductivity Relationships in Anion Exchange Membranes (AEMs) Using Interpretable Machine Learning

Anion exchange membranes (AEMs) play a vital role in the performance of water electrolyzers and fuel cells, yet their discovery and optimization remain challenging due to the complexity of structure–property relationships. In this study, we introduce a machine learning framework that leverages conditional graph neural networks (cGNNs) and descriptor-based models and a hybrid graph neural network (HGARE) to predict and interpret ionic conductivity. The descriptor-based pipeline employs principal component analysis (PCA), ablation, and SHAP analysis to identify factors governing anion conductivity, revealing electronic, topological, and compositional descriptors as key contributors. Beyond prediction, dimensionality reduction and clustering are performed by employing t-SNE and KMeans as well as SOM, which reveal distinct membranes clusters, some of which were enriched with high anion conductivity. Among graph-based approaches, the graph convolutional (GCN) achieved strong predictive performance, while the Hybrid Graph Autoencoder-Regressor Ensemble (HGARE) achieved the highest accuracy. Additionally, atom-level saliency maps from GCN provide spatial explanations for conductive behavior, revealing the importance of polarizable and flexible regions. This work contributes to the accelerated and data-driven design of high-performance AEMs.

Naghshnejad, Pegah [Department of Chemical Enginee↗
DOE OSTI2023

Grooved electrodes for high-power-density fuel cells

Proton exchange membrane fuel cells (PEMFCs) are leading candidates to decarbonize the transport sector, but widespread deployment will require improvements in lifetime, fuel economy and cost. Here we present the grooved electrode, an alternative electrode structure that enhances PEMFC performance and durability by coupling high ionomer (ion-conducting binder) content for improved H + transport with grooves for rapid O 2 transport. Grooved electrodes provide up to 50% higher performance than state-of-the-art conventional electrodes under standard operating conditions. Fuel cell diagnostics combined with multiphysics modelling demonstrate that grooved electrodes provide facile O 2 transport despite their high ionomer content, enabling improved reaction rate uniformity. Grooved electrodes also provide improved durability, with less performance loss after carbon corrosion compared with baseline electrodes. Machine learning analysis demonstrates the potential to further optimize grooved structures for next-generation PEMFCs with enhanced performance and durability, enabling smaller and cheaper fuel cell stacks with higher fuel efficiency.

25 ENERGY STORAGE↗
DOE OSTI2021

Exploring the structural uniformity and integrity of protonic ceramic thin film electrolyte using wet powder spraying

Thin protonic ceramic electrolyte contributes to lower ohmic resistance and enhances electrochemical performance of protonic ceramic electrochemical cells. However, manufacturing of large-scale thin electrolyte remains a challenge. Wet powder spraying is an attractive technique to deposit <10 µm thin electrolyte when advanced atomizing techniques and optimized spraying process are integrated. Here ultrasonic atomization is integrated in the wet powder spray technique to reduce the thickness of electrolyte. Moreover, a parametric study is conducted to optimize the wet powder spray process to deposit uniform and crack-free electrolyte film. It is illustrated that tuning of solid loading rates and spray passes can affect the morphology of the as-sprayed electrolyte film, enabling the structural compactness of the sintered electrolyte layer. To maintain chemical stability of the electrolyte layer during sintering, effect of sintering temperature is further investigated to produce a physically thin, structurally dense, and chemically homogeneous electrolyte layer. The protonic ceramic electrochemical cells fabricated with optimized spraying and sintering parameters demonstrate excellent performance under both fuel cell and electrolysis modes. In addition, the cells exhibit remarkable structural integrity during redox and long-term stability tests.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Development of Machine-Learned Interatomic Potentials to Predict Structure, Transport, and Reactivity in Platinum-Based Fuel Cells

Machine-learned interatomic potentials (MLIPs) have rapidly progressed in accuracy, speed, and data efficiency in recent years. However, training robust MLIPs in multicomponent systems remains a challenge. In this work, we train an MLIP to describe hydrated Nafion ionomers and platinum catalysts, which are important components of fuel cells, by constructing a diverse training set to describe the bulk polymer and interfacial catalyst–polymer interactions well. We use our trained MLIP to study the properties of the platinum–Nafion system, including polymer structure, proton mobility in a bulk Nafion polymer and near a platinum-Nafion interface, and reactions near and far from the interface, finding excellent results for structure and reactions contained within our training set. Transport seems to be well described, with both vehicular transport and Grotthuss hopping captured, although converged calculations of diffusivities were not computed because they require calculations of tens of nanoseconds that are challenging with current state-of-the-art MLIPs. The combined insights that this model provides can be leveraged to optimize fuel cell performance, and the approach can be applied to other chemical processes and devices where structure, transport, and reactivity all contribute to the overall observed performance.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Optimization of metal-supported solid oxide fuel cells with a focus on mass transport

Performance of symmetric-architecture metal-supported solid oxide fuel cells was improved significantly by optimizing the catalyst infiltration process and metal support structure. Optimization of component structure and processing parameters was performed during tape-casting and fabrication of button cells. Mass transport of oxygen in the metal support was identified as a major limitation. To overcome this limitation, pore former loading and thickness of the metal support (130–250 μm) were optimized. The catalyst infiltration process was also improved by studying the impact of firing temperature (400 °C–900 °C) and infiltration cycle numbers (1–15). The maximum power density of the optimized cell was 0.9 W cm –2 at 700°C using hydrogen as a fuel, a three-fold increase over the baseline cell performance. The degradation rate of optimized cells at 550 °C, 600 °C, and 700 °C was 2%, 4.5%, and 5.5% per 100 h, respectively. Here, the phenomena of mass transport, catalyst coarsening, and chromium poisoning on the catalyst were analyzed by electrochemical impedance spectroscopy and scanning electron microscopy.

13 HYDRO ENERGY↗
DOE OSTI2020

Electronic structure and oxophilicity optimization of mono-layer Pt for efficient electrocatalysis

The slow kinetics of the anodic hydrogen oxidation reaction (HOR) in alkaline medium is one of the limitations for anion exchange membrane fuel cells (AEMFCs). Hence, accurately regulate and understand catalytic interface structure are essential to solve this bottleneck and reveal the structure-activity relationship. In this work, a novel trimetal core-shell model with mono-layer Pt-shell is employed for hydrogen electrooxidation to avoid thermodynamic driven bulk/surface composition deviation. On account of the atomic radius discrepancies of 3d-transition metals M (M = Fe, Co and Cu), the electronic structure of mono-layer Pt is regulated by the strain-engineered Pd-M core and the electrocatalytic activity for HOR is tuned accordingly. Nevertheless, step-by-step electrochemical monitoring and surface-treatment experiments indicate that the oxophilicity optimization by low-valence M(OH) x species, rather than the hydrogen binding energy (HBE) optimization caused by strain engineering, influence the activity obviously. It is mainly derived from the enhanced adsorption of OH ad and accelerated desorption of the H ad . The trimetal core-shell model breathes new life into the low-Pt catalyst design for hydrogen electrooxidation reaction.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2022

Highly Durable Fluorinated High Oxygen Permeability Ionomers for Proton Exchange Membrane Fuel Cells

For proton exchange membrane fuel cells to be cost-competitive in light- and heavy-duty vehicle applications, their Pt content in the catalyst layers needs to be lowered. However, lowering the Pt content results in voltage losses due to high local oxygen transport resistances at the ionomer–Pt interface. It is therefore crucial to use ionomers that have higher oxygen permeability than Nafion. In this paper, novel high oxygen permeability ionomers (HOPIs) are presented, with up to five times higher oxygen permeability than Nafion, synthesized by copolymerization of perfluoro-2,2-dimethyl-1,3-dioxole (PDD) with perfluoro(4-methyl-3,6-dioxaoct-7-ene) sulfonyl fluoride (PFSVE). PDD is the source of higher permeability due to its open ring structure, while PFSVE provides ionic conductivity. Optimization of PDD content and equivalent weight enables increased fuel cell performance, mainly at high current densities, where HOPIs can achieve power densities >1.25 W cm -2 and exceed the 0.8 A cm -2 U.S. Department of Energy durability target by losing only 4.5 mV, which is over six times less than 30 mV. Finally, the interactions between HOPI and SO 3 - groups with a PtCo/C catalyst are also elucidated here at a fundamental level.

25 ENERGY STORAGE↗
DOE OSTI2022

Design of Graded Cathode Catalyst Layers with Various Ionomers for Fuel Cell Application

Proton exchange membrane fuel cells (PEMFCs) powered by green hydrogen (H2) have become a promising alternative to conventional hydrocarbon-fueled power generators. Despite technological advancements, further improvements in efficiency, durability, and low-cost production are required for the widespread adoption of PEMFCs. Though numerous approaches to improve PEMFC electrodes have been reported, most strategies utilize a single material set (e.g., one combination of catalyst and ionomer) to improve performance. Alternatively, anisotropic (graded) electrode structures with locally tunable properties may yield superior electrode performance due to improved ionic and gas phase transport. In this work, graded cathode catalyst layers (CCLs) incorporating different ionomers (Nafion D2020, Aquivion D79-25BS, and HOPI) were designed and prepared. Performance screening shows that some of these graded electrode structures have comparable performance to optimized single-ionomer electrode structures (D2020) suggesting some synergistic benefit. Additionally, we show that electrodes with lower equivalent weight (EW) D79 ionomer near the membrane and D2020 ionomer near the gas diffusion media outperformed electrodes with the inverted configuration. Finally, EIS analysis shows some graded ionomer structures (e.g. D79/D2020) have better than expected H+ conductivity, generally leading to better electrode performance. However, further optimization of ionomer content and catalyst ink formulations is needed to improve overall PEMFC performance.

DIRECT ENERGY CONVERSION↗
DOE OSTI2022

Active and Durable PGM-free Cathodic Electrocatalysts for Fuel Cell Application

Platinum Group Metal-free (PGM-free) Oxygen Reduction Reaction (ORR) electrocatalysts possess high intrinsic activity measured by a Rotating Disk Electrode (RDE) method. However, under fuel cell operating conditions, PGM-free ORR electrocatalysts have underperformed compared to platinum catalysts. PGM-free ORR electrocatalyst’s fuel cell performance can be improved by designing and optimizing the cathodic catalyst layer (CL) and Membrane Electrode Assembly (MEA) construction such that: 1) it efficiently provides oxygen access to ORR active sites (through catalyst morphology control); 2) it removes water from the CL (by tuning the hydrophobicity of the PGM-free catalysts and the catalyst layer structure); and 3) it increases proton conductivity (by homogeneous mixing of catalysts and ionomer). Studying the CL is complex due to the absence of well-established protocols of MEA activation, especially compared to platinum-containing catalysts. PGM-free fuel cell testing protocols would need to optimize potentiostatic vs galvanostatic measurements, scan rates, parameters of Electrochemical Impedance Spectroscopy (EIS) and Beginning of Experiment (BOE) criteria. To make the PGM-free catalyst’s fuel cell performance comparable to platinum, the synergistic effort of materials design, fine tuning of the catalyst layer and comprehensive electrochemical analysis is required.

08 HYDROGEN↗
DOE OSTI2023

Reactor physics characterization of triply periodic minimal surface-based nuclear fuel lattices

Triply periodic minimal surface (TPMS) lattices are receiving substantial attention in numerous engineering fields due to their impressive topology-driven physical characteristics. TPMS lattices are periodic structures of two distinct intertwined volume domains separated by an area-minimizing surface or wall. TPMS lattices have been observed in nature, such as biological membranes, skeletons, block copolymers, sea urchins, butterfly wings, and equipotential surfaces in crystals. Intriguingly, the topology of TPMS lattices can be easily parametrized via level-set equations and thus are heavily numerically and experimentally studied. Here, a significant research effort is currently applying TPMS lattices for heat exchangers and sinks. This paper extends TPMS lattice applications to nuclear reactor fuel designs, with a focus on identifying relevant TPMS geometric parameters controlling neutronics characteristics, such as reactivity, neutron spectrum, and heat removal properties. We found that fuel surface-area-to-volume ratios for TPMS lattices can be two orders of magnitude larger than current cylindrical fuel rods. Further, the selected TPMS lattice and its implicit equation, the unit cell pitch, wall thickness, and structure porosity are design parameters enabling neutronics optimization for both thermal and fast spectrum configurations, paving the way for exceptionally compact and dense nuclear core concepts.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

A Review on Bioinspired Proton Exchange Membrane Fuel Cell: Design and Materials

With the climate crisis gathering recognition, there has been significant interest in clean energy. As a reliable and clean energy solution, markets transitioning toward sustainable energy have identified polymer electrolyte membrane fuel cells (PEMFCs) as a critical technology. The increasing interest in PEMFCs is primarily due to their high energy density, high efficiency and zero greenhouse gas emission. However, additional development is required to overcome the current barriers associated with fuel cell component design, high manufacturing cost, and insufficient stability. Bioinspired designs have the potential to provide new and valuable insights using novel techniques for extracting design inspirations from biological structures. Applying these design concepts to develop materials and structures for various fuel cell components can be transformative. The well–adapted structures and functional features of biological systems have been proven to greatly enhance the performance of current designs through novel and optimized pathways. Bioinspired designs have indeed lived up to performance expectations and even exceed them. Herein, the potential and value of using these bioinspired designs are discussed. Recent studies and advancements based on nature–inspired structures for components of PEMFCs and how these design considerations substantiate their claim as an attractive alternative to conventional designs are discussed.

25 ENERGY STORAGE↗
DOE OSTI2020

Use of in Situ Synchrotron Techniques to Probe the Oxidized Surface of Molybdenum Nitride Oxygen Reduction Electrocatalysis

The development of active and stable earth-abundant catalysts for the oxygen reduction reaction (ORR) is needed for widespread, economic development of fuel cell technologies. Designing and optimizing these non-platinum group metals is challenging, however, because they are susceptible to composition and structure changes, including dissolution, oxidation, and corrosion, both in air and under reaction conditions. To identify the active surface, and thus understand the properties that affect activity, the catalyst surface must be characterized in situ. Herein, we utilize a grazing incidence electrochemical cell to investigate in situ composition and morphology changes of a molybdenum nitride (Mo-N) thin film catalyst using grazing incidence x-ray absorption spectroscopy (GI-XAS) and x-ray reflectivity (XRR). In rotating ring disk electrode measurements, we find that the activity, selectivity, stability, and capacitance of the Mo-N catalyst is dependent on the maximum potential to which it has been exposed. Specifically, the overpotential required to reach -2 mA cm-2geo decreases by over 90 mV when the maximum potential is increased from 0.3 to 0.8 V vs RHE (Figure 1). Because the Mo-N oxidizes rapidly in air, ex situ characterization methods including x-ray photoelectron spectroscopy and time-of-flight secondary ion mass spectrometry can provide only limited insight into these in situ catalyst changes. Using in situ GI-XAS measurements at applied potentials between 0.3 and 0.9 V vs RHE, however, we are able to determine that the surface of the film oxidizes and becomes more amorphous when exposed to increasingly higher potentials (Figure 1). Furthermore, the surface remains oxidized on the order of several hours when returned to "ORR relevant potentials" (< 0.6 V vs RHE), indicating that this surface-oxidized nitride is the active surface for ORR. Using in situ XRR measurements, we find that there is no change in surface roughness at potentials below 0.7 V vs RHE, but the film roughens significantly at 0.8 V vs RHE, correlating with ex situ measurements of Mo dissolution at this potential (Figure 1). We therefore conclude that the intrinsic activity of the Mo-N catalyst increases when exposed to potentials up to 0.7 V vs RHE, while above that potential activity enhancements are due to the exposure of more active sites through dissolution. The in situ electrochemical surface-sensitive x-ray characterization as used here is a promising methodology for understanding and leveraging surface dynamics to improve the performance of non-traditional catalysts.

Kreider, Melissa↗