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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 469 records · Page 26

Toward Engineering of Solution Microenvironments for the CO 2 Reduction Reaction: Unraveling pH and Voltage Effects from a Combined Density-Functional–Continuum Theory

Engineering the electrolyte microenvironment represents an attractive route to tuning the selectivity of electrocatalytic reactions beyond catalyst composition and morphology. However, harnessing the full potential of this approach requires understanding the interplay between voltage, electrolyte composition, and adsorbate binding within the electrical double layer, which is absent from the usual theoretical approaches. In this study, we apply a recently developed density functional theory (DFT)–continuum approach based on the effective screening medium method and reference interaction site model (ESM–RISM) to explore electrolyte effects with an enhanced description of the electrochemical interface. Furthermore, applying this method to the binding of CO adsorbates in potassium-containing electrolytes on copper, a problem of direct relevance to CO 2 electroreduction to value-added products, we show that the interdependence of voltage and pH leads to an unexpected change in adsorption site preference on Cu(001) terraces. Our findings highlight the often-overlooked importance of the electrical double-layer structure for predicting catalyst operation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Corrosion rates measured under potentiostatic conditions to represent performance of a cermet nuclear waste form

Electrochemical tests were conducted to assess the corrosion performance of a developmental multiphase cermet nuclear waste form in different conditions. Corrosion currents were monitored as the surface equilibrated in an acidic brine solution during potentiostatic tests at different imposed potentials. Electrochemical impedance spectroscopy was used to quantify differences in the electrical properties of surfaces stabilised at different potentials. The passivating oxides that will stabilise the surface under disposal conditions are formed and maintained during testing. The measured corrosion currents were two orders of magnitude lower for passivated surfaces than for polished surfaces over a wide range of redox conditions. The electrochemical results were correlated with microscopic analyses of the corroded surfaces and physical models of the surface passivation and degradation processes are proposed. The measured corrosion rates are suitable for the long-term performance modeling of cermet nuclear waste forms.

Gattu, V. K.↗

Electrochemical Hydrogen Compression Cell Design (CRADA Final Report)

Electrochemical compression and purification is a high potential technology that is likely to outcompete mechanical compression for hydrogen end use applications. However, testing and understanding what is occurring within the cell is difficult as it is not readily accessible through experimentation. Thus, the main target is to increase performance and reduce cost of electrochemical hydrogen compression (EHC) and purification (EHP) cells and stacks using multiscale mathematical modeling informed by experiment. The models can provide physical insight into limiting processes and develop mitigation methods, which can be proven out through rapid sub-scale testing of the devices.

08 HYDROGEN↗

Insights into the Oxygen Evolution Reaction on Graphene-Based Single-Atom Catalysts from First-Principles-Informed Microkinetic Modeling

Single-atom transition metals embedded in nitrogen-doped graphene have emerged as promising electrocatalysts due to their high activity and low material cost. These materials have been shown to catalyze a variety of electrochemical reactions, but their active sites under reaction conditions remain poorly understood. Using first-principles density functional theory calculations, we develop a pH-dependent microkinetic model to evaluate the relative performance of transition metal catalysts embedded in fourfold N-substituted double carbon vacancies in graphene for the oxygen evolution reaction. We find that reaction pathways involving intermediates co-adsorbed on the metal site are preferred on all transition metals. These pathways lead to enhancements in catalytic activity and broaden the activity peak when compared with purely thermodynamics-based predictions. Furthermore, these findings demonstrate the importance of investigating reaction pathways on graphene-based catalysts and other two-dimensional (2D) materials that involve metal active centers decorated by spectator intermediate species.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Pit Stability Predictions of Additively Manufactured SS316 Surfaces Using Finite Element Analysis

Stainless steels are susceptible to localized forms of corrosion attack, such as pitting. The size and lifetime of a nucleated pit can vary, depending on a critical potential or current density criterion, which determines if the pit repassivates or continues growing. This work uses finite element method (FEM) modeling to compare the critical pit radii predicted by thermodynamic and kinetic repassivation criteria. Experimental electrochemical boundary conditions are used to capture the active pit kinetics. Geometric and environmental parameters, such as the pit shape and size (analogous to additively manufactured lack-of-fusion pores), solution concentration, and water layer thickness were considered to assess their impact on the pit repassivation criterion. The critical pit radius (the transition point from stable growth to repassivation) predicted for a hemispherical pit was larger when using the repassivation potential (E rp ) criteria, as opposed to the current density criteria (pit stability product). Including both the pit stability product and E rp into its calculations, the analytical maximum pit model predicted a critical radius two times more conservative than the FEA approach, under the conditions studied herein. The complex pits representing lack-of-fusion pores were shown to have minimal impact on the critical radius in atmospheric conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Electrolytic gold plating, stripping, and ion transport dynamics through a solid-state iodide perovskite

The pronounced electrochemical reactivity between halide perovskites and metal electrodes can introduce mobile extrinsic metal ions which can cause device instability or enable novel functionalities. Here we systematically investigate the kinetics of gold cation (Au + ) migration in indium tin oxide (ITO)/methylammonium lead triiodide (MAPbI 3 )/Au model devices under long-term potentiostatic biasing. Scanning electron microscopy (SEM), X-ray photoelectron spectroscopy (XPS), and density functional theory (DFT) analyses reveal that Au + ions, electrochemically generated at the Au anode, traverse the perovskite layer with diffusion coefficients on the order of 10 −11 to 10 −10 cm 2 s −1 and are subsequently reduced at the cathode as Au 0 clusters, resembling metal plating behavior in electrolytic cells and solid-state batteries during charging. Furthermore, reversing the applied bias strips the plated Au 0 , revealing reversibility suitable for bipolar resistive switching devices and providing direct evidence of the electrochemical and ionic nature of Au transport within the perovskite matrix. Quantitatively determining diffusion coefficients and ion concentrations provides foundational inputs for future drift-diffusion modelling opportunities and allows us to relate our findings to implications on long term operation of devices like photovoltaic modules. These results clearly demonstrate the solid-state electrochemical nature of perovskite devices, highlight methods to be more quantitative about ion transport properties, provide and emphasize the importance of disentangling electro-, photo-, photoelectrochemical processes for understanding device performance and unlocking new functionalities.

14 SOLAR ENERGY↗

Review of Ultrasonic Methods for Monitoring, Damage Detection, and Processing of Lithium-Ion Batteries Throughout Their Life Cycle

Lithium-ion batteries (LIBs) are the leading technology used in consumer electronics, electric vehicles, and grid-level electrochemical energy storage applications. The ever-increasing use of LIBs has highlighted a gap in understanding of their behavior throughout their life cycle. Current monitoring systems rely on electrical and sometimes temperature measurements to assess the internal state which limits information about complex electrochemical processes. In response, ultrasonic testing (UT) has shown promise for non-invasive assessment due to its ease of use and sensitivity to mechanical changes which are correlated with electrochemical changes within the battery. We summarize the research in UT methods applied to LIBs throughout their life cycle. We also discuss physics-based and data-driven modeling approaches used to interpret ultrasonic signals in the context of LIBs, with an emphasis on the existing challenge of establishing rigorous links between electrochemical behavior and elastic and poroelastic wave physics to gain insight regarding physical changes in the LIB that can be directly measured using UT. Finally, we discuss the challenges of implementing UT across the LIB life cycle and identify opportunities for further research. This review aims to provide helpful guidance to researchers and practitioners of UT in the growing field of UT for electrochemical battery systems.

25 ENERGY STORAGE↗

Multi-physics Preconditioning for Thermally Activated Batteries

Thermal batteries, also known as molten-salt batteries, are single-use reserve power systems activated by pyrotechnic heat generation, which transitions the solid electrolyte into a molten state. The simulation of these batteries relies on multiphysics modeling to evaluate performance and behavior under various conditions. This paper presents advancements in scalable preconditioning strategies for the Thermally Activated Battery Simulator (TABS) tool, enabling efficient solutions to the coupled electrochemical systems that dominate computational costs in thermal battery simulations. We propose a hierarchical block Gauss-Seidel preconditioner implemented through the Teko package in Trilinos, which effectively addresses the challenges posed by tightly coupled physics, including charge transport, porous flow, and species diffusion. The preconditioner leverages scalable subblock solvers, including smoothed aggregation algebraic multigrid (SA-AMG) methods and domain-decomposition techniques, to achieve robust convergence and parallel scalability. Strong and weak scaling studies demonstrate the solver’s ability to handle problem sizes up to 51.3 million degrees of freedom on 2048 processors, achieving near sub-second setup and solve times for the end-to-end electrochemical solve. These advancements significantly improve the computational efficiency and turnaround time of thermal battery simulations, paving the way for higher-resolution models and enabling the transition from 2D axisymmetric to full 3D simulations.

25 ENERGY STORAGE↗

Parametric analysis of anodic degradation mechanisms for fast charging lithium batteries with graphite anode

In this work, we report the impact of the temperature-driven synergistically-coupled anodic degradation mechanisms on the electrochemical performance of lithium batteries with graphite anode over multiple cycles. Temperature dependence of electrochemical reactions and damage mechanisms, such as solid electrolyte interface (SEI) growth, lithium plating/stripping, dead lithium storage/dissolution, and film cracking are incorporated into the degradation model. Results of a parametric analysis are presented, evaluating the effects of charging rates (1–6 C), operating temperatures (-15 – 45°C) and electrode design parameters, on the relative performance fade in the lithium-ion battery. Thermo-electrochemical process maps are developed to provide insights into the relationship between electrode performance and failure mechanisms. The simulation results predict a severe capacity loss due to lithium plating at low temperatures, which is further aggravated at high charging rates. A common strategy for mitigating lithium plating, through charging at high temperatures, also results in rapid capacity loss due to accelerated SEI formation. Simulation results are used to identify the combination of operating conditions and electrode design parameters that improve the electrochemical performance of the battery. These results demonstrate an opportunity to design safe and high-performance lithium-ion batteries, guided by anodic degradation models.

Battery design↗

CO2ROpt (Feedstock Allocation Optimization Model) [SWR-22-13]

Reducing greenhouse gas emissions remains a critical challenge for the transportation and chemical sectors. The electrochemical reduction of carbon dioxide is a potential pathway for production of fuels and chemicals that uses atmospheric carbon dioxide as a feedstock. Here we present an analysis of the potential for carbon dioxide captured from point sources and via direct air capture to be utilized in electrochemical reduction under different market scenarios. Using a numerical optimization framework and national data sets, scenarios for nationwide production of ethylene, formate, and carbon monoxide are evaluated at scales comparable to current production of these molecules in the United States. We show that developing a network for production of these products at scale requires capture and utilization of significant portions of the carbon dioxide that is currently emitted from large stationary point sources. Because carbon dioxide point sources are spatially and compositionally variable, their use for carbon dioxide reduction depends on electricity prices, capture cost, and location. If the power sector in the United States is decarbonized, carbon dioxide supply decreases significantly, increasing the importance of utilizing other carbon dioxide streams, and increasing the likelihood that direct air capture plays a role in supplying carbon dioxide feedstocks. These findings provide a first insight into the feedstock and energy constraints for carbon dioxide reduction.

Badgett, Alex↗

Unveiling the Mechanism of Mn Dissolution Through a Dynamic Cathode‐Electrolyte Interphase on LiMn2O4

Abstract Understanding the formation and evolution of the cathode‐electrolyte interphase (CEI), which forms at the interface between the cathode and electrolyte, is crucial for revealing degradation mechanisms in cathode materials, especially for developing strategies to stabilize the interphase in the strongly oxidizing conditions that evolve at high operating voltages in next‐generation Li‐ion batteries. However, The present understanding of the CEI is challenged by its complex and dynamic nature. In this work, near‐edge X‐ray absorption fine structure spectroscopy, electrochemical characterization, and reactive molecular dynamics simulations are combined to reveal a mechanism for CEI formation and evolution above model LiMn 2 O 4 (LMO) thin‐film electrodes in contact with conventional carbonate‐based electrolytes. It is found that Mn dissolution from LMO can be understood in terms of repetitive Mn 3 O 4 formation and dissolution behavior during cycling, which is closely connected to electrolyte decomposition and a key aspect of the CEI formation and growth. The behavior of the CEI in this model system offers detailed insight into the dynamic chemistry of the interphase, underscoring the important role of electrolyte composition and cathode surface structure in interphase degradation.

Ou, Wenhan↗

Improving the reliability of machine learned potentials for modeling inhomogeneous liquids

The atomic-scale response of inhomogeneous fluids at interfaces and surrounding solute particles plays a critical role in governing chemical, electrochemical, and biological processes. Classical molecular dynamics simulations have been applied extensively to simulate the response of fluids to inhomogeneities directly, but are limited by the accuracy of the underlying interatomic potentials. Here, we use neural network potentials (NNPs) trained to ab initio simulations to accurately predict the inhomogeneous responses of two distinct fluids: liquid water and molten NaCl. Although NNPs can be readily trained to model complex bulk systems across a range of state points, we show that to appropriately model a fluid's response at an interface, relevant inhomogeneous configurations must be included in the training data. In order to sufficiently sample appropriate configurations of such inhomogeneous fluids, we develop protocols based on molecular dynamics simulations in the presence of external potentials. We demonstrate that NNPs trained on inhomogeneous fluid configurations can more accurately predict several key properties of fluids—including the density response, surface tension and size-dependent cavitation free energies—for liquid water and molten NaCl, compared to both empirical interatomic potentials and NNPs that are not trained on such inhomogeneous configurations. This work therefore provides a first demonstration and framework to extract the response of inhomogeneous fluids from first principles for classical density-functional treatment of fluids free from empirical potentials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Model systems for screening and investigation of lithium metal electrode chemistry and dendrite formation

The use of lithium metal as an electrode for electrochemical energy storage will provide a significant impact on practical energy storage technology. Unfortunately, the use of lithium metal is plagued with challenging chemical problems. Specifically, the formation of a solid electrolyte interphase layer and the nucleation and growth of lithium dendrites: both must be addressed and controlled in order to achieve a practically useable pure lithium metal electrode. Currently sophisticated experimental techniques and computationally expensive simulations are being used to probe these problems but these methods are arduous and time consuming which delays timely evaluation and insight into the rapidly changing field of advanced energy storage. Here, we report the use of DFT simulations of lithium nanoclusters to investigate and explore lithium metal chemistry with inexpensive computational methods to gain greater insight into electrochemical reductions and the nucleation and growth of dendrites. DME, LiTFSI, and LiFSI reduction energetics and structures with electrode effects from lithium metal are reported providing better physical description of the absolute reduction potential characterization. The electronic structure of the lithium nanoclusters were used to investigate the nucleation and growth of lithium dendrites from an ab initio perspective. The results demonstrate that kinetic processes have more control over non uniform growth than thermodynamic processes. Based on this information, a non ab initio model was created in Matlab that shows the initial stages of dendrite nucleation considering approximately 2000 atoms.

25 ENERGY STORAGE↗

SOC Microstructural Property Estimator

This pre-trained ML model is a tool that uses basic compositional parameters for porous solid oxide cell (SOC) electrodes - the phase fractions and mean particle/pore diameters – as inputs and uses them to estimate additional electrochemical performance parameters: active (i.e., connected) TPB density, all tortuosity factors, and phase pair specific interfacial areas. The electrode is assumed to be composed of two solid phases and a pore phase. The property calculations are performed using neural network regression models trained on a large bank of synthetic electrode microstructural data that NETL has generated using the program DREAM3D (that bank is also hosted on EDX: https://edx.netl.doe.gov/dataset/soc-synthetic-microstructure-bank). This means the generated parameters are based on training from actual measured properties from 3D microstructures, not estimated from geometric simplifications. This tool was developed and is intended to replace percolation theory calculations in models that use hypothetical electrode properties. An example use case would be running SOC performance simulations across a parametric sweep of electrode designs (e.g., varying phase fractions and particle sizes) and assessing how it impacts the electrochemical performance of the SOC. Within the parameter space of the training data (statistics of that parameter space is provided in the readme file), this model achieves sub-5% mean absolute percent errors, an order of magnitude less error than percolation theory across the same parameter space. However, be aware that this tool was developed with parametric simulations in mind, and users are encouraged to assess accuracy for their own specific use case rather than taking accuracy metrics at face value. More info, including a usage guide, is in the included readme file. This tool should be cited with the DOI number provided.

Electrode Microstructure↗

Effect of Nanoscale Ce 0.8 Gd 0.2 O 2–δ Infiltrant and Steam Content on Ni–(Y 2 O 3 ) 0.08 (ZrO 2 ) 0.92 Fuel Electrode Degradation during High-Temperature Electrolysis

Studies of Ni–yttria-stabilized zirconia (YSZ) fuel electrode degradation mechanisms in solid oxide electrolysis cells (SOECs) are complicated by the different possible Ni–YSZ microstructures and compositions, and the variations in the H 2 /H 2 O ratio encountered in an electrolysis stack. Here, in this study, we describe a life testing scheme aimed at providing survey results on degradation as a function of the H 2 O–H 2 composition, with life tests carried out at five different steam contents from 90% to 10%. A Ni–YSZ-supported symmetric cell geometry is employed both with and without infiltrated nanoscale gadolinia-doped ceria (GDC). Impedance spectroscopy is utilized to observe changes in electrochemical characteristics during the life test, and a transmission-line-based equivalent circuit is used to model the data. Post-test electrode microstructures were observed. The results suggest that the GDC infiltrant reduces the electrode polarization resistance and provides more stable electrode polarization over a range of conditions.

08 HYDROGEN↗

First-principles modeling of chemistry in mixed solvents: Where to go from here?

Mixed solvents (i.e., binary or higher order mixtures of ionic or nonionic liquids) play crucial roles in chemical syntheses, separations, and electrochemical devices because they can be tuned for specific reactions and applications. Apart from fully explicit solvation treatments that can be difficult to parameterize or computationally expensive, there is currently no well-established first-principles regimen for reliably modeling atomic-scale chemistry in mixed solvent environments. We offer our perspective on how this process could be achieved in the near future as mixed solvent systems become more explored using theoretical and computational chemistry. We first outline what makes mixed solvent systems far more complex compared to single-component solvents. An overview of current and promising techniques for modeling mixed solvent environments is provided. We focus on so-called hybrid solvation treatments such as the conductor-like screening model for real solvents and the reference interaction site model, which are far less computationally demanding than explicit simulations. We also propose that cluster-continuum approaches rooted in physically rigorous quasi-chemical theory provide a robust, yet practical, route for studying chemical processes in mixed solvents.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Electrochemical Characterization of Degradation Modes of High-Voltage Li x Ni 0.33 Mn 0.33 Co 0.33 O 2 Electrodes

While deeply charged high-voltage cathodes can improve battery energy density, understanding and preventing any accelerated cell degradation is crucial to practical success. Here, to analyze the degradation of LiNi x Mn y Co 1–x–y O 2 (NMC) type material charged to 4.3 and 4.5 V, a physics-based model is applied to cycling data to obtain parameter estimates indicative of degradation modes, which are validated by simple electrochemical measurements and further interpreted by materials characterization. Growth rates of interfacial impedance and active material loss are greater at 4.5 V, as might be expected. However, when charged to 4.5 V, degradation rates are initially lower at a cycling C-rate of 1.0 C than at 0.5 C. Once degradation mode changes are quantified, simulations evaluate the contribution of individual degradation mode to performance losses and provide estimates of the energy-power correlation (Ragone plots) of cells after cycling.

25 ENERGY STORAGE↗

In Situ Synchrotron X-ray Scattering Investigation of Cathodic ZIF-8 Deposition on Graphite Using 3D-Printed Cells

Electrochemical approaches provide unique means to fabricate thin films of metal organic frameworks (MOFs). However, the kinetics of electrochemical MOF deposition has not been quantitatively investigated so far. In this study, we report the first in situ measurements of electrochemical MOF growth using transmission synchrotron X-ray scattering. Electrochemical cells based on poly(lactic acid) with two windows were fabricated using fused-deposition modelling. Here, the resulting 3D-printed cells, the surface of which was coated with paraffin wax to prevent solvent percolation through the polymer material, were used to monitor the cathodic growth of zeolitic imidazolate framework-8 (ZIF-8) on graphite in a methanol solution containing ZnCl 2 and 2-methylimidazole (Hmim) at different cathodic potentials. The resulting time-resolved X-ray diffraction data showed a gradual increase in crystal size with negligible changes in crystal orientation during the cathodic ZIF-8 deposition. More importantly, the time-resolved data provided a means to quantitatively assess the kinetics of the cathodic ZIF-8 growth using the Gualtieri model, revealing that the cathodic potential and Hmim concentration affected crystal growth kinetics, but not nucleation kinetics. These ZIF-8 samples exhibited changes in X-ray diffraction pattern after being washed with methanol and dried in air, indicating that in situ measurements are essential to investigate mechanisms behind MOF electrodeposition.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗