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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Anodic Activity of Hydrated and Anhydrous Iron (II) Oxalate in Li-Ion Batteries

We discuss the applicability of the naturally occurring compound Ferrous Oxalate Dihydrate (FOD) (FeC2O4·2H2O) as an anode material in Li-ion batteries. Using first-principles modeling, we evaluate the electrochemical activity of FOD and demonstrate how its structural water content affects the intercalation reaction and contributes to its performance. We show that both Li0 and Li+ intercalation in FOD yields similar results. Our analysis indicates that fully dehydrated ferrous oxalate is a more promising anodic material with higher electrochemical stability: it carries 20% higher theoretical Li storage capacity and a lower voltage (0.68 V at the PBE/cc-pVDZ level), compared to its hydrated (2.29 V) or partially hydrated (1.43 V) counterparts.

Keshavarz, Fatemeh↗
DOE OSTI2023

Learning heterogeneous reaction kinetics from X-ray movies pixel-by-pixel

Reaction rates at spatially heterogeneous, unstable interfaces are notoriously difficult to quantify, yet are essential in engineering many chemical systems, such as batteries 1 and electrocatalysts 2. Experimental characterizations of such materials by operando microscopy produce rich image datasets 3–6, but data-driven methods to learn physics from these images are still lacking because of the complex coupling of reaction kinetics, surface chemistry and phase separation 7. Here we show that heterogeneous reaction kinetics can be learned from in situ scanning transmission X-ray microscopy (STXM) images of carbon-coated lithium iron phosphate (LFP) nanoparticles. Combining a large dataset of STXM images with a thermodynamically consistent electrochemical phase-field model, partial differential equation (PDE)-constrained optimization and uncertainty quantification, we extract the free-energy landscape and reaction kinetics and verify their consistency with theoretical models. We also simultaneously learn the spatial heterogeneity of the reaction rate, which closely matches the carbon-coating thickness profiles obtained through Auger electron microscopy (AEM). Across 180,000 image pixels, the mean discrepancy with the learned model is remarkably small (<7%) and comparable with experimental noise. Our results open the possibility of learning nonequilibrium material properties beyond the reach of traditional experimental methods and offer a new non-destructive technique for characterizing and optimizing heterogeneous reactive surfaces.

Chueh, William↗
DOE OSTI2021

Modeling dissociation of ionic liquids with electrolyte NRTL model

Dissociation of ionic liquids (ILs) is critical to electrochemical process performance by affecting ionic conductivity. Prior studies of thermodynamic modeling either assumed no dissociation or complete dissociation that were not consistent with experimental observations. This work presented an eNRTL model for three aqueous imidazolium-based IL systems: [Emim][EtSO 4 ], [Emim][TFA], and [Emim][TfO]. The model accurately correlates the IL dissociation and VLE data in the entire concentration range from pure IL to infinite dilution aqueous solution. The system non-ideality is dominated by the dissociation chemistry. Dissociation behavior is driven by strong short-range interaction of the molecular IL-water pair relative to the dissociated IL-water pair, consistent with prior studies indicating that molecular IL and water can form an energetically favorable complex. The interaction energy parameters calculated in this work qualitatively agrees with the hydrogen bonding ability of the anions previously reported. This research not only provides a model that well describes the IL dissociation but also demonstrates the physical significance of eNRTL model.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Modeling atomically mixed graded density impactors

Graded density impactors (GDIs) are multi-material composite impactors used in gas gun experiments to tailor the drive conditions imparted to a sample test material. Previous graded density impactors generally rely on thin, but discrete, layers of different materials. The thinner and the greater number of layers will result in smoother compression. Taken to the limit of very thin layers would be pure material 1 at one surface, such as the front surface of an impactor, smoothly transitioning at the atomic scale to pure material 2 on the back surface. Such an impactor can initially shock, then smoothly compresses a material during a dynamic experiment. This type of experiment can serve to explore a larger region of thermodynamic space than a single or even multi-shock experiments. An overview of how graded density impactors are made is reviewed and sample results are given. Additionally, a strategy for modeling these kinds of impactors is presented. The length scales of constituent mixing are given from the experimental build through electrochemical-deposition. Equation of state models for pure constituents and their subsequent mixtures are presented. It is demonstrated that the time scales for pressure and temperature equilibration, for atomically mixed GDIs, are short enough to be a justifiable closure for the resulting multiphase flow. Furthermore, we present simulation results of dynamic shock followed by a ramp compression, utilizing a silver/gold graded density impactor, onto a tantalum sample.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

P-Type Electrochemical Doping Can Occur by Cation Expulsion in a High Performing Polymer for Organic Electrochemical Transistors

We investigate the mechanism of ion-dependent charge compensation during electrochemical oxidation (doping) of the model mixed ionic/electronic transporting polythiophene derivative poly(3-{[2-(2-methoxyethoxy)ethoxy]methyl}thiophene-2,5-diyl) (P3MEEMT). Using a combination of electrochemical quartz microbalance gravimetry and glow discharge optical emission spectroscopy, we show that charge compensation during polymer redox processes proceeds via a cation-dependent mechanism. For p-type polymer oxidation in certain electrolytes, charge compensation is achieved by both eventual injection of anions into the film, as well as initial expulsion of cations from the film. We compare doping mechanisms for a variety of electrolyte salts including potassium chloride, tetrabutylammonium chloride, potassium hexafluorophosphate (KPF6), and tetrabutylammonium hexafluorophosphate. For the electrolyte KPF6, both the cations and anions coexist in the water-swelled polymer even prior to application of electrical bias. Our data indicate that electrochemical doping (hole injection into the polymer and ionic charge compensation) proceeds via the following mechanism: (1) hydration of the neutral film by electrolyte (water, cations, anions), (2) cation (K+) expulsion from the film upon initial application of an oxidative bias, and (3) anion injection into the film at higher oxidation/doping levels (>~2 × 1020/cm3). Understanding the mechanism of charge compensation during the doping process should allow for the design of improved mixed ionic/electronic conductors for use in applications ranging from organic supercapacitors and redox flow batteries to bioelectronic sensors, thermoelectrics, and devices for neuromorphic computing.

Flagg, Lucas Q.↗
DOE OSTI2026

Correlating binding energies of adsorbed CO and H on model surfaces with CO/H 2 selectivity from co-electrolysis of CO 2 and H 2 O over copper–palladium bimetallic catalysts

Binding energies of adsorbed CO and H are key descriptors governing the activity and selectivity of the co-electrolysis of CO 2 and H 2 O to produce syngas with desired CO/H 2 ratios. Palladium hydride (PdH), which forms in situ at negative overpotentials, has been identified as the active Pd phase for CO 2 reduction to syngas. Herein, binding energies of CO and H are determined using temperature programmed desorption (TPD) of CO and H 2 from Pd(111), PdH/Pd(111), and Cu/PdH/Pd(111) under ultra-high vacuum (UHV) conditions. TPD results reveal that desorption of H 2 from subsurface PdH occurs at 460 K, while desorption from surface PdH is more facile at 320 K. CO desorption temperatures shift 20 K lower on PdH/Pd(111) compared to on Pd(111). The presence of 0.7 ML Cu further increases the desorption temperature of H 2 by 30 K while simultaneously reducing CO desorption temperatures by 70 K. Density functional theory (DFT) calculations show that CO adsorption onto Pd sites is hindered on the 0.7 ML Cu/PdH/Pd(111) surface while the kinetic barrier for H 2 desorption is increased. The trends in the binding energies of CO and H on model surfaces are consistent with electrochemical measurements of CuPd powder catalysts in a membrane electrode assembly (MEA), where H 2 evolution is reduced while CO production is enhanced compared to unmodified Pd catalysts. Overall, the results from model surface studies (TPD and DFT) provide a prediction and explanation for the activity and CO/H 2 ratios observed in electrochemical experiments. This study also demonstrates that CuPd is a promising catalyst with reduced Pd-loading to produce CO-rich syngas.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Physical model and experimental validation of a high temperature proton exchange membrane electrochemical hydrogen pump cell for efficient single-stage extraction of low concentration hydrogen gas

There is interest in valorization of existing natural gas infrastructure to facilitate the co-transportation of hydrogen via blending of hydrogen gas initially at limited concentrations of 1–20 vol% H2 and to subsequently extract hydrogen at fuel cell quality standards (SAE J2719/ISO14687-2). High temperature proton exchange membrane electrochemical hydrogen pump (HT-PEM EHP) based on phosphoric acid doped polybenzimidazole (PA-PBI) exhibits good performance at elevated temperatures (>120 °C), which provides desirable tolerance to non-methane natural gas constituents that are problematic for lower temperature based EHP. To better understand the suitability of the HT-PEM EHP for such gas separation processes, a two-dimensional model of EHP based on PA-PBI was developed. The model is validated for several relevant operating conditions and across cells with differing amounts of phosphoric acid content in the electrodes. Operando micro x-ray computed tomography (CT) imaging of an HT-PEM EHP was used to further validate physical parameters and assumptions of the model. The impacts of pressure, relative humidity of the anode feed, and concentration of feed gases on separation performance are investigated. This study shows that a specific energy of separation of 5.1 kWh/kg H2 at a hydrogen recovery factor (HRF) of 50 vol% can be achieved in a single stage with the EHP, producing fuel cell quality hydrogen purity of 99.99 vol% H2 from a 2 vol% H2/CH4 feed blend, while pressurizing the product H2 at a pressure ratio of 1.3 relative to feed pressure.

Stansberry, John M↗
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 OSTI2020

Mechanistic Models as Framework for Understanding Biomarker Disposition: Prediction of Creatinine‐Drug Interactions

Creatinine is widely used as a biomarker of glomerular filtration, and, hence, renal function. However, transporter‐mediated secretion also contributes to its renal clearance, albeit to a lesser degree. Inhibition of these transporters causes transient serum creatinine elevation, which can be mistaken as impaired renal function. The current study developed mechanistic models of creatinine kinetics within physiologically based framework accounting for multiple transporters involved in creatinine renal elimination, assuming either unidirectional or bidirectional‐OCT2 transport (driven by electrochemical gradient). Robustness of creatinine models was assessed by predicting creatinine‐drug interactions with 10 perpetrators; performance evaluation accounted for 5% intra‐individual variability in serum creatinine. Models showed comparable predictive performances of the maximum steady‐state effect regardless of OCT2 directionality assumptions. However, only the bidirectional‐OCT2 model successfully predicted the minimal effect of ranitidine. The dynamic nature of models provides clear advantage to static approaches and most advanced framework for evaluating interplay between multiple processes in creatinine renal disposition.

Scotcher, Daniel↗
DOE OSTI2020

Toward quantifying capacity losses due to solid electrolyte interphase evolution in silicon thin film batteries

To understand the origins of failure and limited cycle life in lithium-ion batteries (LIBs), it is imperative to quantitatively link capacity-fading mechanisms to electrochemical and chemical processes. This is extremely challenging in real systems where capacity is lost during each cycle to both active material loss and solid electrolyte interphase (SEI) evolution, two indistinguishable contributions in traditional electrochemical measurements. Here, we have used a model system in combination with (1) precision measurements of the overall Coulombic efficiency via electrochemical experiments and (2) x-ray reflectivity measurements of the active material losses. The model system consisted of a 515 Å thick amorphous silicon (a-Si) thin film on silicon carbide in half-cell geometry using a carbonate electrolyte with LiPF6 salt. This approach allowed us to quantify the capacity lost during each cycle due to SEI evolution. Combined with electrochemical analysis, we identify SEI growth as the major contribution to capacity fading. Specifically, the continued SEI growth results in increasing overpotentials due to increased SEI resistance, and this leads to lower extent of lithiation when the cutoff voltage is reached during lithiation. Our results suggest that SEI grows more with increased time spent at low voltages where electrolyte decomposition is favored. Finally, we extracted a proportionality constant for SEI growth following a parabolic growth law. Our methodology allows for the quantitative determination of lithium-ion loss mechanisms in LIBs by separately tracking lithium ions within the active materials and the SEI and offers a powerful method of quantitatively understanding LIB loss mechanisms.

25 ENERGY STORAGE↗
NASA NTRSDate not supplied

Practical Battery Thermal Modeling Techniques

Lithium-ion batteries are thermo-electrochemical devices, whereby nearly every facet of their functionality and performance are thermally driven. As a result, it is important to have thermal modeling techniques that effectively capture the intricacies of both the electrochemical nature of the battery and also the complex thermal network that typically results from the design of the battery thermal management system. Here we present a thermal modeling workflow and a set of general assumptions for how to construct a thermal model of a Li-ion battery pack. We use a 14-cell bank of 18650-format Li-ion cells, loosely based on a proposed alternative battery design for Orion, as the example. Although the workflow is performed with Thermal Desktop and related utilities, the focus of this presentation is less about software specific techniques, but rather is focused on the assumptions and conditions that should be used in a model (regardless of the tool used to build the model). Example cases and results will be presented for charge, discharge, and thermal runaway.

lithium-ion battery↗
DOE OSTI2020

Impact Modeling and Testing of Pouch and Prismatic Cells

Understanding battery response under impact is critical to improve the safety of electrified vehicles. Nevertheless, predicting the impact behaviors of batteries is not straightforward since a battery cell usually contains hundreds of thin layers with dramatically different material properties and multiple physical processes occur simultaneously during cell deformation. Here we utilized both empirical tests and numerical models to capture the failure process of pouch and prismatic cells in various impact scenarios. In each test, a cell was hit once by an indenter dropped from a certain height. During which the cell penetration, loading force, voltage and temperature were monitored to characterize the cell’s response. Meanwhile, numerical models were developed to capture the coupled mechanical, electrical, electrochemical and thermal responses of batteries. In these models, the cell bulk was treated as a homogeneous part to achieve computational efficiency required by large-scale simulations, and it was represented by the geologic cap model that allows both shear and compaction deformation. Simulation results showed agreement with experimental data in essential features of cell behaviors during impact. Details of the test setup, model development and cell failure behaviors are presented in this paper. Additionally, capabilities, limitations and future improvement of the battery safety modeling are discussed.

25 ENERGY STORAGE↗
DOE OSTI2025

A Full-Cell Model for Direct Toluene Electro-Hydrogenation Electrolysis

Liquid organic hydrogen carriers (LOHCs) are organic molecules that undergo a hydrogenation/dehydrogenation cycle to enable storage and transportation of hydrogen fuel under ambient conditions. One promising LOHC candidate is toluene, which can be converted to methylcyclohexane (MCH) electrochemically, enabling a decarbonized process when green electricity is used. In this study, we developed a full-cell model for the direct electro-hydrogenation of toluene to MCH, utilizing a zero-gap membrane electrode assembly architecture. The model incorporates electrochemical kinetics, ionic transport, water transport across the membrane, and mass transport effects. Electrochemical kinetics are characterized using Tafel analysis on Pt/Ru catalyst. The model is validated against experimental data, including polarization curves, Faradaic efficiencies, and water crossover. A voltage breakdown analysis shows that the performance is dominated by kinetic losses, and the model is used to carry out a comparison of different toluene electro-hydrogenation reaction catalysts. Finally, a sensitivity analysis is conducted on key design parameters illustrating which can be modified to maximize electrolyzer performance. The cathode specific surface area and cathode porous transport layer thickness (PTL) have the largest impact on the current density, while the PTL thickness and Pt loading in the PTL have the largest impact on Faradaic efficiency.

Ehlinger, Victoria M. [Lawrence Livermore National↗
DOE OSTI2023

Quantifying neptunium oxidation states in nitric acid through spectroelectrochemistry and chemometrics

Controlled-potential in situ thin-layer spectropotentiometry was leveraged to generate visible/near-infrared (VIS/NIR) absorption spectral data sets for the development of chemometric models to quantify Np(III/IV/V/VI) oxidation states in HNO 3 . This technology would be valuable in laboratory studies and when monitoring process solutions to guide feed adjustments for radiochemical separations—the performance of which depends on oxidation state. This approach successfully isolated and stabilized Np species in pure (~99%) oxidation states without compromising solution optical properties. Multivariate curve resolution–alternating least squares models were evaluated to resolve spectral and component concentrations from a scan that sequentially produced Np(VI), Np(V), Np(IV), and Np(III) spectra with mixtures of two valences at a time. Although it provided a useful approximation, the method was not able to quantitively resolve each component likely because of rotational ambiguity. Additionally, partial least squares regression models were built from artificial and electrochemically generated VIS/NIR spectral training sets to study the effect of interionic interactions on spectral characteristics. Models built with true Bi-chemical mixtures of coexisting Np oxidation states and spectra generated from additive combinations of pure end points had similar prediction performance. This methodology can be used to directly quantify Np concentration and the ratio of Np oxidation states and other actinides in remote settings such as hot cells.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2026

Pore-Scale Transport Effects in Electrochemical CO 2 Reduction on Gold via Coupled Microkinetic-Transport Modeling

A pore-resolved modeling framework is developed to quantify how pore-scale transport affects the intrinsic microkinetics of CO 2 -to-CO on Au. A DFT-informed microkinetic model is coupled self-consistently to a Generalized-Modified Poisson–Nernst–Planck (GMPNP) transport description in a single, electrolyte-filled cylindrical pore, allowing local concentrations and potential to feed back into site-specific reaction rates. FIB-SEM is used to determine pore sizes within realistic electrode materials. Across pore diameters, d p = 10–6000 nm, the surface-averaged CO 2 reduction rate is systematically reduced relative to the ideal microkinetic baseline where mass transport is not accounted for; the effectiveness factor 𝜂 𝑠,CO 2 , which quantifies this ratio, decreases rapidly at more negative potentials and is about 1% near −1.0 V vs SHE due to reactant depletion. Spatial maps reveal pore-bulk alkalization that emerges at higher cathodic bias, with a small, near-wall pH dip due to electrostatic repulsion of hydroxide at the cathode interface. For a fixed aspect ratio L p /d p , narrower pores exhibit larger 𝜂 𝑠,CO 2 by shortening diffusion paths, whereas variations in the aspect ratio L p /d p play a secondary role. A dimensionless analysis (surface/bulk Damköhler numbers) delineates operating regimes. In conclusion, this work offers a concept for incorporating microkinetic models into homogenized porous-electrode models through effectiveness factors and pore-size distribution.

Au-catalyst↗