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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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Control-Oriented Modeling of Lithium-Ion Batteries

Battery management systems (BMSs), which monitor and optimize performance while ensuring safety, require control-oriented models, i.e., models tailored to the design and implementation of estimation and control algorithms. Physics-based electrochemical models describe detailed battery phenomena, but are too computationally intensive for use in estimation and control applications. Single particle models (SPMs), which retain some of the physics of electrochemical models, are often used for control-oriented battery modeling since they are computationally efficient; however, they are only valid over very low frequency ranges and C-rates. Empirical equivalent circuit models (ECMs) are also used for control-oriented battery modeling since they are computationally efficient and can describe battery behavior over wide frequency ranges; however, they provide no physical understanding of the battery and, therefore, have limited applicability. Further, fractional order terms (e.g., Warburg impedances) are often employed, making the models unwieldy for use in the time domain. This work provides a control-oriented battery model that combines the benefits of SPM and ECM models, while overcoming their limitations. The proposed model incorporates some of the battery physics found in electrochemical models, can easily be used in both the time and frequency domains, and describes battery behavior over its entire frequency range. A linearized single particle model, which incorporates key electrochemical parameters, is used for modeling battery physics at very low frequencies. For low frequencies, integer-order linear systems are used to approximate diffusion physics described by Warburg impedances, and high frequency behavior is modeled by the double layer capacitance effect. The proposed battery model is more computationally efficient than full electrochemical models since it does not require the solution of PDEs, is accurate for a wider frequency range than the SPM considered in this paper, and does not suffer from the unwieldiness and limited applicability of empirical ECMs. Finally, the model is validated in the time and frequency domains via a comparison to pseudo-two-dimensional (P2D) model simulations and experimental data.

25 ENERGY STORAGE↗
DOE OSTI2020

Surrogate Model Development of Spent Fuel Degradation for Repository Performance Assessment

In model simulations of deep geologic repositories, UO 2 fuel matrix degradation typically begins as soon as the waste package breaches and groundwater contacts the fuel surface. The initial degradation rate depends on the timing of these events, burnup of the fuel, temperature, and concentrations of dissolved reactants. Estimating the initial rate of degradation is fairly straightforward, but as UO 2 corrosion products precipitate on the fuel surface and the movement of dissolved species between the fuel surface and environment is impeded by the precipitated solids, the rate is more difficult to quantify. At that point, calculating the degradation rate becomes a reactive-transport problem in which a large number of equations must be solved by iteration for a large number of grid cells at each time step. The consequence is that repository simulations, which are already expensive, become much more expensive, especially when hundreds or thousands of waste packages breach. The Fuel Matrix Degradation (FMD) model is the process model of the Spent Fuel and Waste Science and Technology (SFWST) campaign of the US Department of Energy (DOE). It calculates spent fuel degradation rates as a function of radiolysis, redox reactions, electrochemical reactions, alteration layer growth, and diffusion of reactants through the alteration layer. Like other similar fuel degradation process models, it is a complicated model requiring a large number of calculations and iterations at each time step.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Comparative Analysis via CFD Simulation on the Impact of Graphite Anode Morphologies on the Discharge of a Lithium-Ion Battery

The morphology of electrode materials plays a crucial role in determining the performance of lithium-ion batteries. Traditional computational models often simplify graphite flakes as uniformly sized spheres, which limits their predictive accuracy. In this study, we present a computational workflow that overcomes these limitations by incorporating a more realistic representation of graphite morphologies. This workflow is designed to be flexible and reproducible, enabling efficient evaluation of electrochemical performance across diverse material structures. By exploring different graphite morphologies, our approach accelerates the optimization of material preparation techniques and processing conditions. Our findings reveal that incorporating greater morphological complexity leads to significant deviations from classical model predictions. Instead, our refined model offers a more accurate representation of battery discharge behavior, closely aligning with experimental data. This improvement underscores the importance of detailed morphological descriptions in advancing battery design and performance assessments. To promote accessibility and reproducibility, we provide the developed code for seamless integration with the COMSOL API, allowing researchers to implement and adapt it easily. This computational framework serves as a valuable tool for investigating the impact of graphite morphology on battery performance, bridging the gap between theoretical modeling and experimental validation to enhance lithium-ion battery technology.

25 ENERGY STORAGE↗
DOE OSTI2022

Digitalization of an experimental electrochemical reactor via the smart manufacturing innovation platform

The exponential increase in data produced over the last two decades has revolutionized the way we collect, store, process, analyze, model, and interpret information to improve profitability. Manufacturing is no exception. How- ever, Smart Manufacturing, the digital practice, organization, workforce, and infrastructure transformation for collection and deployment of data and models at scale and at all levels of manufacturing, is a complex, costly, and labor-intensive journey that is still seeing slow adoption. The Clean Energy Smart Manufacturing Innovation Institute (CESMII), a national Manufacturing USA public-private partnership sponsored by the Department of Energy, is addressing this scaled use of data and modeling in manufacturing. CESMII has focused on how to col- lect and use operating data for numerous applications that improve productivity, precision, and performance of manufacturing operations from factory floor to supply chain using process simulation, predictive analytics, mon- itoring and control, and real-time optimization. Because contextualized data are key, CESMII has developed the Smart Manufacturing Innovation Platform (SMIP) to lower the barriers to the data that are needed to accelerate data-based model building, improve data visualization, and more quickly gain insights. Reusable, standards-based ways of doing data collection, ingestion, and contextualization are particularly important for scaling access and use of data. The SMIP uses a standards-based definition and construct for reusable information models called an SM Profile. When an SM Profile is used in conjunction with the SMIP, the SMIP ensures the availability of contextualized, operational data for model building. The present work demonstrates Smart Manufacturing and the application of the SMIP for building several data-centered models for the operation and control of an ex- perimental electrochemical reactor that reduces carbon dioxide (CO 2 ) gas to valuable liquid and gas chemicals, such as alcohols, olefins, and syngas. We describe how the SMIP plays a central role in more effective model building and we demonstrate how the electochemical reactor can be controlled and optimized for the desired products. Use of the SMIP involves the transmission of real-time sensor measurements to a cloud resource so that the operating data are available to all model building experts. The data collection and transmission process is fully automated to greatly reduce the need for manual manipulation of the data. Data-driven machine learning models are used for advanced real-time state estimation, real-time optimization, and model-based feedback control for the reactor. The application models are implemented as a system to monitor the data flow and control the electrochemical reactor with a single visualization interface. SM Profiles are used to demonstrate reusability of the information models for the reactor and the instrumentation. The application packages, algorithms, and user interfaces developed are cast as Docker images in a library to facilitate reusability of the application models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Multi-fidelity electrochemical modeling of thermally activated battery cells

Thermally activated batteries undergo a series of coupled physical changes during activation that influence battery performance. These processes include energetic material burning, heat transfer, electrolyte phase change, capillary-driven two-phase porous flow, ion transport, electrochemical reactions, and electrical transport. Several of these processes are strongly coupled and have a significant effect on battery performance, but others have minimal impact or may be suitably represented by reduced-order models. Additionally, assessing the relative importance of these phenomena must be based on comparisons to a high-fidelity model including all known processes. In this work, we first present and demonstrate a high-fidelity, multi-physics model of electrochemical performance. This novel multi-physics model enables predictions of how competing physical processes affect battery performance and provides unique insights into the difficult-to-measure processes that happen during battery activation. We introduce four categories of model fidelity that include different physical simplifications, assumptions, and reduced-order models to decouple or remove costly elements of the simulation. Using this approach, we show an order-of-magnitude reduction in computational cost while preserving all design-relevant quantities of interest within 5 percent. The validity of this approach and these model reductions is demonstrated by comparison between results from the full fidelity model and the different reduced models.

25 ENERGY STORAGE↗
DOE OSTI2025

Finite element modeling of electropolishing of radio frequency dipole Nb crab cavity in hydrofluoric-sulfuric acid electrolyte

The superior performance of niobium superconducting radio frequency (SRF) cavities is achieved through meticulous surface treatment, notably via chemical electropolishing, ensuring exceptionally smooth surfaces. While this technique has been extensively employed for cylindrically symmetric structures, addressing more intricate geometries poses significant challenges in achieving uniform polishing and controlled material removal, especially when moving away from retractable cathodes. This presents a multifaceted electrochemical, thermal, and fluid dynamics conundrum. A prime example is the 197 MHz radio frequency dipole (RFD) crabbing cavity proposed for the Electron Ion Collider (EIC) project, exemplifying such complex structures. Our groundbreaking work integrates the localized oxide thickness variation, considering its impact on current distribution and Joule heating, within the framework of multi-physics modeling using the COMSOL® simulation suite. This approach was applied to a comprehensive model of the RFD cavity, allowing us to investigate optimal external cooling water flow conditions necessary for achieving desirable outcomes. In conclusion, this illustrates the increasing utility of such multi-physics codes to greatly aid in designing solutions to challenging processing requirements for increasingly complex accelerator cavities.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Selective and Stable Ethanol Synthesis via Electrochemical CO 2 Reduction in a Solid Electrolyte Reactor

Electrochemical CO 2 reduction to ethanol faces challenges such as low selectivity, a product mixture with liquid electrolyte, and poor catalyst/reactor stability. Here, we developed a grain-rich zinc-doped Cu 2 O precatalyst that presented a high ethanol Faradaic efficiency of over 40% under a current density of 350 mA·cm –2 . Our density functional theory (DFT) simulation suggested that Zn atoms inside the structure have a greater carbophilicity than the Cu atoms to help facilitate *CHCHO formation, a key reaction intermediate toward ethanol instead of other C 2 products. Here, a high Faradaic efficiency ratio between ethanol and ethylene (FE EtOH /FE C2H4 ) reached 2.34 in the zinc-doped Cu 2 O precatalyst, representing an over 4-fold improvement compared to bare Cu 2 O precatalyst. By integrating this Cu-based catalyst into a porous solid electrolyte (PSE) reactor with a salt-managing design, we achieved stable ethanol production for over 180 h under a current density of 250 mA·cm –2 while maintaining ethanol selectivity at ~30%.

09 BIOMASS FUELS↗
DOE OSTI2026

Electrostatic Gating of Ionic Conductance through Heterogeneous van der Waals Nanopores

Nanofluidic ionic transistors typically require gate voltages above 1 V and operate only at submillimolar ionic strengths, limiting their biocompatible applications. We demonstrate ionic transistors consisting of single sub-10 nm nanopores drilled in van der Waals (vdW) heterostructures with internal gate electrodes made of few-layer graphene. These devices deliver up to 10-fold current modulation at gate voltages as low as 0.3 V in 10 mM KCl, and ∼2-fold modulation at near-physiological 100 mM KCl. Baseline conductance with no gate shows surface-charge-dominated transport below 100 mM KCl, consistent with negatively charged hBN walls and ∼5 nm opening of the pores. The surface charge and the electrochemical asymmetry introduced by the three-electrode configuration govern the device’s behavior: negative gate voltage (V G ) enriches ionic concentrations and enhances current, whereas positive V G induces a local depletion zone that suppresses transport. The current modulation by V G is dependent on the polarity of the transmembrane potential and leads to ion current rectification. Molecular dynamics simulations of a nanopore in a hBN–graphene–hBN stack reveal confinement and surface charge-dependent suppression of the relative permittivity of interfacial water. Continuum modeling with radially varying interfacial water permittivity reproduces the asymmetric I–V characteristics and explains how the embedded gate sculpts local potential and ion concentrations. By enabling sub-0.5 V control of ionic transport at up to 100 mM salt concentrations, these devices address a key need in nanofluidics to create low-power ionic circuits and biosensing.

Materials science↗
DOE OSTI2021

Highly Concentrated Electrolytes: Electrochemical and Physicochemical Characteristics of LiPF 6 in Propylene Carbonate Solutions

Highly concentrated electrolytes (HCEs) based on LiPF 6 in propylene carbonate (PC) have been examined as lithium-ion battery electrolytes. These HCEs have lower ionic conductivities and higher viscosities than ethylene carbonate (EC) electrolytes with 1.2 M LiPF 6 , but they have higher Li + ion transference numbers. Electrochemical cycling behaviour of LiNi 0.8 Co 0.015 Al 0.05 O 2 //graphite cells with 3.2 M LiPF 6 in PC resembles that of cells with EC-based electrolytes; the HCE cells have higher impedance, which can be lowered by increasing test temperature. By employing Raman and infrared spectroscopy, combined with density functional theory and ab initio molecular dynamics simulations, we reveal that the Li + solvation structure and speciation are key factors that determine cell performance. Two distinct regimes are observed as a function of salt concentration—in the conventional regime, the solvation number (SN) is mostly constant, while in the HCE regime it decreases linearly. Graphite exfoliation is suppressed only at very high salt concentrations ( > 2.4 M), where [ PC ] free /[Li + ] < 1 and P F 6 − f r e e > P C f r e e . Results from the Advanced Electrolyte Model indicate that Li + desolvation improves at higher LiPF 6 concentrations, thereby mitigating PC co-intercalation into the graphite. However, Li + ion transport is hindered in the HCEs, which increases impedance at both the oxide-positive and graphite-negative electrodes.

25 ENERGY STORAGE↗
DOE OSTI2023

Computationally Guided Design of Multiple Impurities Tolerant Electrode (Final Report)

The current project was based on a combined experimental and computational approach, which can help recommend better cathode materials under multiple impurities conditions. The PI will mainly take in charge of experimental and computational thermodynamics of the selected cathode materials for the SOFC applications under multiple impurities. While the co-PI will run the electrochemical tests of the cathodes recommended and eventually the long-term degradation tests. At the end of the project, a multiple tolerant cathode material based on the combined experimental and computational approach will be recommended and the reliability of the commonly used accelerated testing will be evaluated. It will address multiple impurities poisoning effect of SO2, CO2, Cr and H2O on the LSM, LSCF and LNO cathodes by identifying the formation of the detrimental secondary phases by XRD, SEM and TEM techniques. And further recommended cathode material will be subjected to electrochemical testing and the most promising ones will be applied to long-term tests. The hybrid approach the PI proposed will not only be applied to the design of multiple impurities tolerant cathodes but will also be considered in the future oxygen electrode applications in SOECs or reversible SOCs. This hybrid computational and experimental approach includes four sections: 1) Investigation of single impurity poisoning on LSM, LSCF and LNO cathodes in the presence of SO2, CO2, Cr. In this section, LSM, LSCF cathodes from FuelCellMaterials and LNO cathodes from Sol-Gel synthesis will be heat-treated in the above single impurity. And the formation of the secondary phases as well as the corresponding simulations will be cross compared, which shows good agreement between each other. Meanwhile, the accelerated testing approach will be evaluated in these systems compared with the previous published work to understand the reliability of the approach. 2) Investigation of multiple impurities poisoning on LSM, LSCF and LNO cathodes in the presence of Cr+H2O, SO2+Cr and SO2+Cr+H2O conditions. We have also applied these 3 candidate cathodes under these multiple impurities’ conditions and the long-term degradation mechanism of the multiple impurities will be understood with the help of the combined experimental and computational approach. Meanwhile, the synergistic effect of those impurities will be compared with the individual ones in the same cathode system to further reveal the actual operating conditions. 3) Electrochemical testing and polarization of the recommended cathode. We have demonstrated very low polarization resistance in LSCF (core)-LSM (shell) electrodes using MSD process and analyzed impedance spectra using DRT analysis and confirming that the low polarization resistance in LSM infiltrated MSD cells is due to reduction in polarization resistance associated with O2-adsorption process. 4). Long-term degradation testing. We have developed a versatile MSD-based process to deposit various continuous coatings onto porous scaffolds and established baseline for longer term Cr-impurity testing in future projects.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Understanding and Manipulating Counterion Condensation within Charged Polymer Electrolytes for Selective and Low Resistant Membrane Separations

Polymeric ion-exchange membranes are found at the heart of numerous electrochemical systems spanning separations (electrodialysis and membrane capacitive deionization) and energy conversion and storage (flow batteries, fuel cells, and electrolyzers). The ion-exchange membrane separators need to be ion conducting but electron insulating, and in many scenarios selective for a particular ion to conduct. Because of their polymeric nature, the molecular architectures of ion-exchange membranes lack the molecular precision found in many inorganic materials. Plus, they contain numerous structural defects that impede ionic transport. As a result of their poor structure, it has been difficult to carefully probe the underlying physics that governs ion transport in ion-exchange membranes. We investigated counterion condensation phenomena in ion-exchange membranes and correlated it to bulk ionic charge transport and selectivity in precisely defined and long-range ordered materials afforded through the principles of directed self-assembly. A multi-faceted approach spanning i.) advanced metrology, two-dimensional atomic force microscopy, x-ray scattering, and ion-exchange equilibria, and ii.) molecular simulations (classical molecular dynamics and ab-inito molecular dynamics) that bridge multiple time and length scales, were employed to correlate the extent of counterion condensation to ionic conductivity and selectivity. After uncovering the extent of the condensation phenomena in this project, new macromolecular chemistries were employed to manipulate the ion pairing interactions of the condensed counterions to tethered ions on the polymer backbone so more facile and selective conduction rates can be attained. The research has aided in the rational design of polymeric ion-exchange membrane separators with high current density for electrochemical systems and subsequently better energy efficiency.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Transport phenomena in electrolyte solutions: Nonequilibrium thermodynamics and statistical mechanics

The theory of transport phenomena in multicomponent electrolyte solutions is presented here through the integration of continuum mechanics, electromagnetism, and nonequilibrium thermodynamics. The governing equations of irreversible thermodynamics, including balance laws, Maxwell's equations, internal entropy production, and linear laws relating the thermodynamic forces and fluxes, are derived. Green–Kubo relations for the transport coefficients connecting electrochemical potential gradients and diffusive fluxes are obtained in terms of the flux–flux time correlations. Furthermore, the relationship between the derived transport coefficients and those of the Stefan–Maxwell and infinitely dilute frameworks are presented, and the connection between the transport matrix and experimentally measurable quantities is described. To exemplify the application of the derived Green–Kubo relations in molecular simulations, the matrix of transport coefficients for lithium and chloride ions in dimethyl sulfoxide is computed using classical molecular dynamics and compared with experimental measurements.

42 ENGINEERING↗
DOE OSTI2021

Computational design of microarchitected porous electrodes for redox flow batteries

Porous electrodes are used as the core reactive component across electrochemical technologies. In flowing systems, controlling the fluid distribution, species transport, and reactive environment is critical to attaining high performance. However, conventional electrode materials like felts and papers provide few opportunities for precise engineering of the electrode and its microstructure. To address these limitations, architected electrodes composed of unit cells with spatially varying geometry determined via computational optimization are proposed. Resolved simulation is employed to develop a homogenized description of the constituent unit cells. These effective properties serve as inputs to a continuum model for the electrode when used in the negative half-cell of a vanadium redox flow battery. Porosity distributions minimizing power loss are then determined via computational design optimization to generate architected porosity electrodes. The architected electrodes are compared to bulk, uniform porosity electrodes and found to lead to increased power efficiency across operating flow rates and currents. The design methodology is further used to generate a scaled-up electrode with comparable power efficiency to the bench-scale systems. Finally, the variable porosity architecture and computational design methodology presented here thus offers a novel pathway for automatically generating spatially engineered electrode structures with improved power performance.

25 ENERGY STORAGE↗
DOE OSTI2026

pH-Driven Restructuring of Hydration Layers and Cation Adsorption at the Alumina–Water Interface

Oxide−water interfaces underpin ion separations, catalysis, and electrochemical energy technologies, where the electrical double layer (EDL) controls adsorption, transport, and reactivity. However, the molecular-scale links between pHdependent surface protonation, hydration-layer structure, and counterion adsorption remain poorly defined. Here, we combine in situ crystal truncation rod (CTR) and resonant anomalous X-ray reflectivity (RAXR) with streaming potential measurements and ab initio molecular dynamics (AIMD) simulations to resolve the chemical and structural evolution of the EDL at the single-crystal alumina (012)−water interface in 10 mM Rb + over pH 3−12. CTR measurements reveal two distinct adsorbed water layers at ∼2.2 and ∼3.5 Å above the surface. Each water layer shifts toward the substrate at transition pHs near 6.5 and 10.6, respectively, reflecting changes in primary hydration layer structure in response to the deprotonation of bridging and terminal aluminol groups. RAXR shows a 10-fold increase in Rb + coverage and a decrease in mean adsorption height from ∼3.5 to ∼2.7 Å with increasing pH, indicating enhanced counterion binding accompanied by Stern layer contraction. Streaming potential measurements demonstrate that the zeta potential, i.e., the potential at the hydrodynamic shear plane, is positive at pH 3 and becomes negative at pH ≥ 3.5. The negative charge magnitude increases with increasing pH, consistent with progressive surface deprotonation at higher pH. AIMD identifies inner- and outer-sphere Rb+ complexes whose adsorption heights and coordination geometries depend sensitively on the protonation state of surface oxygens, providing atomistic support for the experimentally inferred trends. These measurements establish two discrete, site-specific pH transitions in hydration-layer structure that track aluminol (de)protonation and quantitatively link them to a pH-driven contraction of the Stern layer (increasing Rb + coverage and decreasing adsorption height). This provides a direct structural basis for connecting surface acid−base chemistry to ion binding distances at an oxide−water interface.

Adsorption↗
DOE OSTI2025

Dusty Gas Model for Solid Oxide Fuel Cell Fuel Electrode

This model applies the Dusty Gas Model simulate multi-component species transport in SOFC (solid oxide fuel cell) anodes which considers the pressure gradient across the fuel electrode. This studyhas been verified with the analytical solution for different fuel electrode thicknesses and with literature values. The model was developed using the VoronoiFVM platform in Julia which is a built in implicit and semi implicit solver that integrates electrochemical behavior, microstructural effects, and transient analysis for accurate prediction of species transport under varying conditions.

dusty gas model (DGM)↗
DOE OSTI2020

Behind the Meter Storage for Electric Vehicle Charging, Electrochemical and Thermal Energy Storage, and Solar Photovoltaic

In response to the potentially large and irregular demand from EVs, along with changing load profiles from buildings with on-site generation, utilities are evaluating multiple options for managing dynamic loads, including time-of-use pricing, demand charges, battery storage, and curtailment of variable generation. Buildings, as well as commercial, public, and workplace EV charging operations, can use a combination of electrochemical battery storage and thermal energy storage coupled with on-site generation to manage energy costs as well as provide resiliency and reliability for EV charging and building energy loads. We are completing a behind the meter storage analysis that focuses on determining the optimal system designs and energy flows for thermal and electrochemical behind the meter storage with on-site solar photovoltaic (PV) generation enabling electric vehicle charging in various climates, building types, and utility rate structures. In completing this analysis, we have developed a tool that combines existing battery models via the System Advisor Model (SAM) and building modeling software via EnergyPlus into a single interface. This tool allows us to simulate a building with a detailed battery model to properly size the battery, thermal energy storage, and solar PV systems to maximize profit for the system owner. This also allows us to assess how the battery degrades under various supervisory control dispatch algorithms to control charging/discharging; we can also see how thermal energy storage is created and used to complement the battery to reduce thermal loads in the building. With this project, we can analyze new batteries that are designed specifically for energy storage, rather than designed to be extremely energy dense for electric vehicle applications, using battery lifetime models from other national labs and the existing SAM battery model, which has detailed lifetime and degradation parameters. We can also assess novel thermal storage technologies by integrating them into the whole building energy simulation program EnergyPlus. Because the model calls both SAM and EnergyPlus, required inputs need to be compatible for both models. These inputs include, on a high-level, the following: weather files, building and electric vehicle load profiles, electricity rate tariff information, and system cost information for the stationary battery, solar PV, and thermal storage system. The various buildings we are studying for this analysis are retail big-box grocery store, commercial office building, fleet vehicle depot and operations facility, multi-family residential, and electric vehicle charging station. For these different applications, the battery and thermal storage will be dispatched differently, and the various technologies are sized differently to optimize cost.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2023

Modeling Nanoscale Ohmics in Carbon Supports of Fuel Cell Cathodes

Here, reducing platinum (Pt) loading in polymer electrolyte fuel cells (PEFCs) while meeting performace requirements is critical to their widespread deployment. However, significant polarization losses manifest at higher current densities in cathodes with lower Pt content. The morphology of the carbon supports in PEFC cathodes affects the location of Pt deposition into the micropits or onto the surface of the carbon support, translating into different kinetic and transport resistances. In this work, we derive an agglomerate scale model that differentiates the sink terms for Pt on the surface and in the pits of carbon supports. We develop an approach to assess the impact of nanoscale ohmic resistance to Pt in the micropits arising from weakly ionic solution in the carbon support on PEFC performance. Effectiveness factors relating the actual reaction rate to the maximum reaction rate (had all the Pt been exposed) are derived and embedded into a one-dimensional catalyst layer model. Parameters in the catalyst layer model are tuned based on experimental local oxygen transport resistances. Subsequently, we estimate bounds for the micropore resistances based on geometric and physical arguments. Lastly, polarization curves are simulated to assess the effect of the micropore resistance in fully-humidified and oxygen-rich environments.

25 ENERGY STORAGE↗
DOE OSTI2026

Correlating surface adsorbate configuration and electrochemical performance of IrO 2 during seawater-relevant electrolysis

Seawater electrolysis alleviates freshwater demand to produce clean hydrogen while eliminating the need for water purification steps. The anodic process, seawater oxidation, typically requires high overpotentials and yields low selectivity to oxygen via the oxygen evolution reaction (OER), primarily due to the competing chlorine evolution reaction (CER) and hypochlorite evolution reaction (HCER) in pH-neutral conditions. Here, combining in situ surface-enhanced Raman characterization, grand canonical density functional theory-based calculations, and kinetic Monte Carlo simulations, we report the evolution of surface adsorbate configurations driven by applied potential and pH during seawater-relevant OER over IrO 2 , a highly OER-active and chloride-corrosion-resistant catalyst. As a result, the chemical properties of active sites, and thereby the kinetics of OER and CER/HCER, are effectively tuned. However, it is revealed that there is no optimal combination of potential and pH to achieve both high activity and high selectivity for seawater-relevant OER. To address this limitation, we establish a correlation between activity/selectivity and surface adsorbate configurations, enabling the optimization of highly active and OER-selective IrO 2 -based catalysts in seawater-relevant oxidation by modulating the local adsorbate environment of active sites.

08 HYDROGEN↗