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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Correlating Solvation Free Energy to Electrolyte Properties for Lithium Metal Batteries

The electrolyte plays a critical role in lithium metal batteries. In particular, ion solvation profoundly impacts key electrolyte properties and battery performance. Here, in this study, we systematically investigate solvation-property relationships in a series of electrolytes with different solvent-diluent ratios. Through potentiometric techniques that measure the relative solvation free energies of electrolytes, we find that weaker solvation correlates with larger ion clusters, lower ionic conductivity and diffusion coefficient, and superior electrochemical stability. Weaker solvation leads to the formation of a small number of Li clusters with large hydrodynamic radii, which lowers the Li + diffusivity and ionic conductivity of the electrolyte. Concurrently, weaker solvation leads to improved electrochemical stability at both the cathode and anode interfaces. Understanding these solvation-property relationships and trade-offs is important to designing electrolytes for optimized lithium metal battery performance.

25 ENERGY STORAGE↗
NASA NTRS1984

The dayside Venus ionosphere. II - Combined numerical model of ion and neutral composition above 120 km

The median vertical profile of ion densities for the dayside Venusian ionosphere obtained by the orbiter retarding potential analyzer (ORPA) is simulated by one-dimensional model calculations. The model includes both neutral and ionic chemistry, eddy and molecular diffusion for neutral constituents, and ion-plasma diffusion for ionic constituents. The electron and ion temperatures measured by the ORPA are used to calculate the plasma diffusion coefficients and scale heights for ions. The predicted O2(+) densities below about 200 km agree particularly well with observations by the ORPA, but the model values are significantly less than those measured by the orbiter ion mass spectrometer. The observed ion composition is interpreted in terms of densities of the neutral atmosphere and its composition.

Shimazaki, T.↗
DOE OSTI2023

Machine learning predictions of diffusion in bulk and confined ionic liquids using simple descriptors

Ionic liquids have many intriguing properties and widespread applications such as separations and energy storage. However, ionic liquids are complex fluids and predicting their behavior is difficult, particularly in confined environments. We introduce fast and computationally efficient machine learning (ML) models that can predict diffusion coefficients and ionic conductivity of bulk and nanoconfined ionic liquids over a wide temperature range (350–500 K). The ML models are trained on molecular dynamics simulation data for 29 unique ionic liquids as bulk fluids and confined in graphite slit pores. This model is based on simple physical descriptors of the cations and anions such as molecular weight and surface area. Here, we also demonstrate that accurate results can be obtained using only descriptors derived from SMILES (simplified molecular-input line-entry system) codes for the ions with minimal computational effort. This offers a fast and efficient method for estimating diffusion and conductivity of nanoconfined ionic liquids at various temperatures without the need for expensive molecular dynamics simulations.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2020

Quantifying Single-Ion Transport in Percolated Ionic Aggregates of Polymer Melts

Single-ion conducting polymers such as ionomers are promising battery electrolyte materials, but it is critical to understand how rates and mechanisms of free cation transport depend on the nanoscale aggregation of cations and polymer-bound anions. We perform coarse-grained molecular dynamics simulations of ionomer melts to understand cation mobility as a function of polymer architecture, background relative permittivity, and corresponding ionic aggregate morphology. In systems exhibiting percolated ionic aggregates, cations diffuse via stepping motions along the ionic aggregates. These diffusivities can be quantitatively predicted by calculating the lifetimes of continuous association between oppositely charged ions, which equal the time scales of the stepping (diffusive) motions. In contrast, predicting cation diffusivity for systems with isolated ionic aggregates requires another time scale. Finally, our results suggest that to improve conductivity the Coulombic interaction strength should be strong enough to favor percolated aggregates but weak enough to facilitate ion dissociation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Machine-learning-assisted deciphering of microstructural effects on ionic transport in composite materials: A case study of Li 7 La 3 Zr 2 O 12 -LiCoO 2

The effective diffusivity of ionic species in multiphase materials is critical for the design and function of composite materials for electrochemical energy storage. In practice, effective diffusivity depends sensitively not only on the intrinsic diffusivities of constituting materials but also on their topological arrangement; nevertheless, these coupled contributions are oversimplified in most analytical models. Here, we combine atomistically informed mesoscale modeling and machine learning (ML) analysis to unravel how such features affect effective diffusivity in two-phase composites. Using the Li 7 La 3 Zr 2 O 12 -LiCoO 2 composite solid-state battery cathode as a model system, we compute effective diffusivity for 600 distinct dense polycrystalline microstructures with different topological configurations of grains, grain boundaries, and heterointerfaces. We verify that in addition to atomic-scale variabilities, microstructural feature diversity can significantly impact effective transport properties. Across the ensemble of test microstructures, this often results in bimodal distributions of effective diffusivity that encompass two qualitatively distinct operating mechanisms, which we identify via flux analysis. An ML approach reveals that the most critical determining factors for effective diffusivity are the connectivity of bulk phases and their heterointerfaces. The role of ionic mobility at the heterointerfaces is also discussed. These insights highlight the combined importance of microstructure and interface engineering in tuning the transport properties of ionic species in composite materials. In conclusion, our framework can also be extended for understanding generic microstructure-property relationships in other complex multiphase materials.

25 ENERGY STORAGE↗
DOE OSTI2020

Diffusivity and Structure of Room Temperature Ionic Liquid in Various Organic Solvents

Room-temperature ionic liquids (RTILs) hold promise for applications in electric double layer capacitors (EDLCs), owing to a much wider potential window, lower vapor pressure, and better thermal and chemical stabilities compared to conventional aqueous and organic electrolytes. However, because the low diffusivity of ions in neat RTILs negates the EDLCs’ advantage of high power density, the ionic liquids are often used in mixture with organic solvents. In this study, we measured the diffusivity of cations and anions in RTIL, 1-butyl-3-methylimidazolium bis(trifluoromethylsulfonyl) ([BMIM + ][TFSI – ]), mixed with 10 organic solvents, by using the pulsed-field gradient NMR method. The ion diffusivity was found to follow that of neat solvents and in most studied solvents showed an excellent agreement with the predicted values reported in the recent molecular dynamics (MD) study [Thompson, M. W.; J. Phys. Chem. B 2019, 123, 1340-1347]. In two solvents consisting of long-chain molecules, however, the MD simulations predictions slightly underestimated the ionic diffusivities. The degree of ion dissociation was also estimated for each solvent by comparing the ionic conductivity with the molar conductivity derived from the diffusion measurements. The degree of ion dissociation and the hydrodynamic radius of ions suggest that the ions are coordinated by ~1 solvent molecule. Finally, the scarcity of solvent–ion interactions explains the fact that the diffusivity of ions in the mixture significantly depends on the viscosity of the solvent.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Ion diffusion coefficients in poly(3-alkylthiophenes) for energy conversion and biosensing: role of side-chain length and microstructure

Conductive polymers are promising materials as active elements for energy storage and conversion devices due to mixed ion–electron conduction. The ion diffusion coefficient is a relative measure of the efficacy of ion transport, allowing for comparison between materials and electrochemical conditions. In this work, diffusion coefficients of hexafluorophosphate (PF6–) counterions in poly(3-alkylthiophene) (P3AT) materials are measured as a function of both side-chain length and microstructure using electrochemical impedance spectroscopy (EIS). For semi-crystalline films, the diffusion coefficient is found to be anomalous and nearly independent of applied electrochemical potential. Here, the anomalous behavior of diffusion indicates that spin casting yields compact films with an enthalpic barrier to ion transport, attributed to ionic trapping. Diffusion coefficient values ~10 –11 cm 2 s –1 were measured for all films, indicating interchain spacing, in the absence of strong intermolecular interactions with the electrolyte, is not a viable design strategy to control ion transport. For the prototypical system of poly(3-hexylthiophene), we observe almost no potential dependence in ion transport for regioregular and regiorandom films of comparable molecular weight, with both exhibiting anomalous diffusion. Alternatively, changing the microstructure of poly(3-hexylthiophene) to a mostly amorphous, ion-imprinted structure yields ~500× increase in the diffusion coefficient to ~2 × 10 –8 cm 2 s –1 at 0.8 V vs. Ag/Ag + with behavior closer to ordinary diffusion. Collectively, these results indicate new insight into ion transport in conductive polymers, where ionic trapping effects can be mitigated through electrodeposition protocols over post-synthesis processing (i.e. spin coating).

14 SOLAR ENERGY↗
DOE OSTI2020

Diffusion coefficients in the envelopes of white dwarfs

The diffusion of elements is a key process in understanding the unusual surface composition of white dwarfs and their spectral evolution. The diffusion coefficients of Paquette et al. have been widely used to model diffusion in white dwarfs. In this work, we perform new calculations of the coefficients of interdiffusion and ionic thermal diffusion with (1) a more advanced model that uses a recent modification of the calculation of the collision integrals that is more suitable for the partially ionized, partially degenerate, and moderately coupled plasma and (2) classical molecular dynamics. The coefficients are evaluated for silicon and calcium in white dwarf envelopes of hydrogen and helium. A comparison of our results with Paquette et al. shows that the latter systematically underestimates the coefficient of interdiffusion yet provides reliable estimates for the relatively weakly coupled plasmas found in nearly all types of stars, as well as in white dwarfs with hydrogen envelopes. In white dwarfs with cool helium envelopes (${T}_{\mathrm{eff}}$ < 15,000 K), the difference grows to more than a factor of two. We also explored the effect of the ionization model used to determine the charges of the ions and found that it can be a substantial source of discrepancy between different calculations. Finally, we consider the relative diffusion timescales of Si and Ca in the context of the pollution of white dwarf photospheres by accreted planetesimals and find factor of ≳3 differences between calculations based on Paquette et al. and our model.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Bulk and Short-Circuit Anion Diffusion in Epitaxial Fe 2 O 3 Films Quantified Using Buried Isotopic Tracer Layers

Self-diffusion is a fundamental physical process that, in solid materials, is intimately correlated with both microstructure and functional properties. In this work, a universal approach is presented to precisely characterize self-diffusion in ionic solids by isotopically enriching anions and/or cations at specific locations within an epitaxial film stack, and characterize their redistribution at high spatial resolution with atom probe tomography. Nanoscale anion diffusivity is quantified in epitaxial α-Fe 2 O 3 thin films deposited by molecular beam epitaxy with a thin (10 nm) buried layer highly enriched in 18 O. The isotopic sensitivity of the atom probe allows precise measurement of 18 O distribution across the sharp interfaces between this layer and the surrounding Fe 2 O 3 after annealing. Short-circuit anion diffusion through 1D and 2D structural defects in Fe 2 O 3 are also directly visualized in 3D. This versatile approach to study precisely tailored thin film samples at high spatial and mass fidelity will facilitate a deeper understanding of atomic-scale diffusion phenomena.

36 MATERIALS SCIENCE↗
NASA NTRS2018

Molecular Dynamics Simulations of Liquid and Polymer Electrolytes for Energy Storage Devices

Advancing beyond current lithium-ion technology is necessary in order to enable energy storage devices for electric airplanes. Electrolyte stability is a key limiting factor, yet the design of improved electrolytes remains a formidable challenge. Molecular dynamics (MD) simulations are a powerful tool for studying electrolytes, since they can be used to evaluate structural, thermodynamic, and transport properties, and can provide molecular-level detail often inaccessible to experimental techniques. Our computational materials groups at the NASA Ames Research Center has developed models and methods to accurately simulate both liquid and polymer electrolytes.We report the results from atomistic MD simulations of several electrolyte materials, with lithium salts dissolved in ionic liquids, dimethoxyethane (DME), and polyethylene oxide (PEO). For improved accuracy, we employ polarizable models, where each atom is given an environment-dependent atomic dipole. The simulations accurately predict bulk transport properties, including viscosity, diffusion, and ionic conductivity, in quantitative agreement with available experimental data. Moreover, the simulations provide important insights into the solvation structure of the lithium ions.We also report the results from coarse-grained MD simulations of polyanion electrolytes. In order to more efficiently capture the longer length- and time-scales of these systems, we employ a generic bead-spring model. These simulations provide important insight into how the polymer chain architecture and ionic interaction strengths affect the ionic aggregation behavior and cation dynamics. Despite the simplicity of the model, the simulations yield qualitative agreement with experimental data for similar systems.

Abbott, Lauren J.↗
DOE OSTI2023

Pore connectivity influences mass transport in natural rocks: Pore structure, gas diffusion and batch sorption studies

For this work, six rocks (one granodiorite, one limestone, two chalks, one mudstone, and one dolostone) with different extents of heterogeneity at six different particle sizes (from 75 to 8000 μm) were studied to describe the effects of pore connectivity on mass transport. The methods applied were (i) porosity measurement of granular rocks, (ii) analyses of gas-phase diffusive transport in a bed of packed particles, along with a solid quartz method at these six particle sizes being developed to identify the contribution of intraparticle diffusion, and (iii) batch sorption tests of multiple ions (anions and cations) with subsequent analyses of inductively coupled plasma-mass spectrometry. Granular porosity measurement results reveal that with decreasing particle sizes, the effective porosities for the “heterogenous” group of rocks (Grimsel granodiorite and Edwards limestone) increase, whereas the porosities of another “homogeneous” group (two Israel chalk samples, Japan mudstone, and Wyoming dolostone) remain constant. Gas diffusion results show that the intraparticle gas diffusion coefficient among these two sample groups, varying in the magnitude of 10 -8 to 10 -6 m 2 /s, are not directly correlated to the porosity differences. Moreover, the batch sorption work displays a different affinity of rocks for various tracers. For Grimsel granodiorite, Japan mudstone, and Wyoming dolostone, the adsorption capacity of Sm 3+ and Eu 3+ increases as the particle size decreases. In general, this integrated research of grain size distribution, granular rock porosity, intraparticle diffusivity, and ionic sorption capacity gives insights into the pore connectivity effect on both physical and chemical transport behaviors for different lithologies and/or different particle sizes.

58 GEOSCIENCES↗
DOE OSTI2020

Mixtures of octanol and an ionic liquid: Structure and transport

Ionic liquids (ILs) with long alkyl substituents are amphiphilic, which leads to a bicontinuous liquid structure. The strongly interacting anionic and cationic head groups form a long range charge network, with the hydrocarbon tails forming a nonpolar domain. Such nonpolar domains have been shown to dissolve a variety of neutral organic solvents. In mixtures of ILs with solvents the neutral organic molecules residing in the nonpolar domains experience different environments and friction from the charged cations and anions. Thus, the neutral molecules diffuse much faster than predicted by hydrodynamic scaling using the average viscosity of the mixture. Here, we report studies on the structure and transport properties of mixtures of 1-octanol with the IL trihexyltetradecylphosphonium bis(trifluoromethylsulfonyl)imide (P 6,6,6,14 + /NTf 2 – ). The majority of the atom fraction in the P 6,6,6,14 + cation comprises four hydrocarbon substituents. The unique amphiphilic nature of ILs with the P 6,6,6,14 + cation makes 1-octanol fully miscible with the IL at ambient temperatures. X-ray scattering experiments show that the IL structure persists in the mixtures for 1-octanol mole fractions as large as x oct = 0.90. The self-diffusion coefficients of the three molecular species in the mixtures were measured by NMR experiments. The self-diffusion of the P 6,6,6,14 + cation is well described by the Stokes–Einstein equation, while the diffusivity of the NTf 2 – anion is slightly lower than the hydrodynamic prediction. The measured diffusivities of octanol in these mixtures are 1.3–4 times higher than the hydrodynamic predictions.

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

Crowded electrolytes containing redoxmers in different states of charge: Solution structure, properties, and fundamental limits on energy density

Nonaqueous redox flow batteries use liquid electrolytes containing redox-active organic molecules (redoxmers) as their energy storage medium. To maximize energy density, the redoxmer concentration needs to be maximized while maintaining low viscosity and high ionic conductivity. During charge, a redoxmer molecule pairs with an ion in the electrolyte while another ion migrates across the membrane to maintain electric neutrality. In a crowded electrolyte, this reconstitution changes physical and chemical properties of the solution. To explore these behaviors, a phenothiazine redoxmer fully miscible with acetonitrile was used, and electrochemical charge was mimicked by chemical oxidation. The solutions were examined using small-angle X-ray scattering, nuclear magnetic resonance, and conductometry and modeled using classical molecular dynamics. Overall, our study indicates that physical and structural properties of redoxmer solutions in both states of charge make it exceedingly difficult to increase the redoxmer concentrations over 2 M at any temperature without compromising dynamic properties of such solutions. The cause for this limitation is proximity to a gel-like regime in which fluidity, diffusivity, and ionic conductivity exponentially decrease with increasing concentration. This tendency is compounded by non-Arrhenius behavior of the electrolyte: a small increase in the concentration outruns gains in fluidity and conductivity at a higher temperature. Thus the properties of crowded electrolytes generally make it impossible to operate when gel-like behavior sets in. Pushing the redoxmer concentration to 2.5-3 M might be possible for small redoxmer molecules, but it would require the use of ionic liquid electrolytes at 340-360 K. (C) 2021 Elsevier B.V. All rights reserved.

25 ENERGY STORAGE↗
DOE OSTI2022

A pseudo-two-dimensional (P2D) model for FeS 2 conversion cathode batteries

Conversion cathode materials are gaining interest for secondary batteries due to their high theoretical energy and power density. However, practical application as a secondary battery material is currently limited by practical issues such as poor cyclability. To better understand these materials, we have, for this study, developed a pseudo-two-dimensional model for conversion cathodes. We apply this model to FeS 2 – a material that undergoes intercalation followed by conversion during discharge. The model is derived from the half-cell Doyle–Fuller–Newman model with additional loss terms added to reflect the converted shell resistance as the reaction progresses. We also account for polydisperse active material particles by incorporating a variable active surface area and effective particle radius. Using the model, we show that the leading loss mechanisms for FeS 2 are associated with solid-state diffusion and electrical transport limitations through the converted shell material. The polydisperse simulations are also compared to a monodisperse system, and we show that polydispersity has very little effect on the intercalation behavior yet leads to capacity loss during the conversion reaction. Finally, we provide the code as an open-source Python Battery Mathematical Modeling (PyBaMM) model that can be used to identify performance limitations for other conversion cathode materials.

25 ENERGY STORAGE↗
NASA NTRS2021

On the Oxidation of the Silicon Bond Coat in Environmental Barrier Coatings

Deal and Grove’s formulation is applied to model the oxidation of the silicon bond coat in environmental barrier coatings. The approach is similar to the author’s previous study, except now the oxidant is assumed to flow through the coating as oxygen ions via vacancies on the oxygen sublattice. The use of an “effective permeability” of the oxidant in the coating is required under the vacancy diffusion assumption. It is found that the linear-parabolic growth equation from Deal and Grove, , is still applicable for the oxidation of the silicon bond coat, but the equation for the parameter A must be modified to account for the coating. The expression for B is the same as that obtained by Deal and Grove and thus is unaffected by the presence of a coating. The modified expression for A is a linear function of the coating thickness and includes the ratio of the oxidant permeability in the oxide to its effective permeability in the coating.

silicon oxidation, ionic diffusion, permeation, li↗
DOE OSTI2023

An Interface–Type Memristive Device for Artificial Synapse and Neuromorphic Computing

Interface-type (IT) metal/oxide Schottky memristive devices have attracted considerable attention over filament-type (FT) devices for neuromorphic computing because of their uniform, filament-free, and analog resistive switching (RS) characteristics. The most recent IT devices are based on oxygen ions and vacancies movement to alter interfacial Schottky barrier parameters and thereby control RS properties. However, the reliability and stability of these devices have been significantly affected by the undesired diffusion of ionic species. Herein, a reliable interface-dominated memristive device is demonstrated using a simple Au/Nb-doped SrTiO 3 (Nb:STO) Schottky structure. The Au/Nb:STO Schottky barrier modulation by charge trapping and detrapping is responsible for the analog resistive switching characteristics. Because of its interface-controlled RS, the proposed device shows low device-to-device, cell-to-cell, and cycle-to-cycle variability while maintaining high repeatability and stability during endurance and retention tests. Furthermore, the Au/Nb:STO IT memristive device exhibits versatile synaptic functions with an excellent uniformity, programmability, and reliability. A simulated artificial neural network with Au/Nb:STO synapses achieves a high recognition accuracy of 94.72% for large digit recognition from MNIST database. These results suggest that IT resistive switching can be potentially used for artificial synapses to build next-generation neuromorphic computing.

36 MATERIALS SCIENCE↗