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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Precise Linker Length and Dynamic Bond Exchange Control Penetrant Diffusion in Dense Vitrimers

Polymer networks with dynamic covalent bonds have been investigated for their self-healing ability, recyclability, and potential as more sustainable materials. Recent results have indicated that in some cases, bond exchange can enhance the transport of penetrants in dense networks, pointing to their potential for separations of membranes. Here, imine dynamic bonds in ethylene oxide (EO) networks with precise linker lengths were synthesized to investigate the transport of N,N′-bis(2,5-di-tert-butylphenyl)-3,4,9,10-perylenedicarboximide (BTBP), a large, anisotropic dye molecule. Networks with mesh sizes smaller than, comparable to, and greater than the size of the penetrant axes were investigated to probe the effects of bond exchange and network confinement on transport. Mesh sizes, which ranged from 0.5 to 1.62 nm, were determined from shear rheology, glass transitions by calorimetry, and probe diffusion coefficients by fluorescence recovery after photobleaching. Permanent networks with identical EO chain lengths were prepared as control samples, and up to a 3 orders of magnitude increase in diffusion coefficient is observed in the dynamic systems for short linkers containing 13 backbone atoms. The longest linkers with 71 backbone atoms show no difference between the permanent and dynamic networks. Linkers shorter than 11 backbone atoms, corresponding to a mesh size smaller than the penetrant small axis, diffusion is no longer observable on the experimental time scale, indicating a sharp cutoff attributed to the precise linkers and narrow mesh size distribution. The dynamic imine exchange time scales were compared to the diffusive hopping times of penetrants and indicate that exchange can occur during a diffusive displacement. Furthermore, these findings provide insights into the factors affecting penetrant transport in dense polymers and inspire the development of next-generation selective polymer membranes.

Diffusion↗
DOE OSTI2024

Multi-Tiered Estimation for Correlation Spectroscopy in 3D (MTECS3D) v0.1

This innovative software estimates rotational diffusion coefficients of particles from X-ray photon correlation spectroscopy (XPCS) data of monodispersed particle systems. It is the first method capable of extracting rotational diffusion information from three-dimensional particle systems using XPCS. Using the angular-temporal cross-correlation of the XPCS images, this software is able to estimate the rotational diffusion coefficients with only a few percent relative errors while requiring minimal prior knowledge of particle structures. This software enhances XPCS analysis capabilities, allowing researchers to study translational and rotational Brownian dynamics of particles in suspension across various temporal and spatial scales.

Hu, Zixi↗
DOE OSTI2020

Polysulfide entrapment and retardation in gel electrolyte Li–S batteries: experiments and modeling

Gelling the electrolyte in lithium–sulfur (Li–S) batteries provides advantages in terms of safety and mitigating polysulfide shuttling leading to reduced side reactions and dendrite growth on the anode side. In the current study, organic and ceramic crosslinkers have been used to improve the entrapment of polysulfides and prevent them from shuttling to the anode side. However, the performance of gel electrolytes is still far from being on par with liquid electrolytes in terms of raw capacity. The discharge curves exhibit an extended first plateau for gel electrolyte batteries compared to liquid electrolytes, showing that polysulfides are better trapped in the gel system. Yet, in the conversion of soluble polysulfides into insoluble polysulfides, the second plateau was delayed. Qualitative and quantitative analysis of the polysulfide diffusion in the liquid electrolyte and gel electrolyte systems were also conducted to predict the relative diffusivity ratio between the liquid electrolyte and gel electrolyte for simulation. To probe what happens at the end of the discharge, where the mass transport in the gel electrolyte appears to be slow, a modified discharge procedure was used where the cell is first paused after discharge and then discharged a second time before recharging normally. Coin cell tests for two gel electrolytes in addition to liquid electrolyte show up to 7% capacity recovery after the pause, which indicates that the diffusion of species during the pause is responsible for the failure recovery. Additionally, the recovery is higher for gel electrolytes compared to liquid, for higher C-rates, and for longer pause times. To better understand this behavior, a Li–S numerical model with mass transport limited reactions was used to examine the polysulfide diffusion coefficients expected in different electrolyte systems. The model is able to reproduce the trends seen in experiments and yields a higher recovery for smaller Li 2 S 4 diffusion coefficients, suggesting that insufficient Li 2 S 4 mass transport is responsible for failure at the end of discharge. By identifying the effect that gel electrolytes have on the state of the battery during discharge using both experimental and simulation methods, this work is a step towards leveraging the advantages of gel electrolytes and mitigating their weaknesses.

25 ENERGY STORAGE↗
DOE OSTI2022

Dynamics of Bottlebrush Polymers in Solution by Neutron Spin Echo Spectroscopy

In this work, we present dynamical and morphological studies on poly(dimethylsiloxane) (PDMS)-based bottlebrush polymers in solution. A combination of small-angle neutron scattering (SANS), pulsed field gradient nuclear magnetic resonance (PFG NMR), and neutron spin echo (NSE) spectroscopy was used to identify structural changes inherent in changing the side-chain length while keeping the backbone constant. These morphological changes are mirrored in the diffusion coefficient determined by PFG NMR, resulting in two coefficients for the elongated and one for the more spherical sample. Faster motions are tracked by NSE using the advantage of time- and length-scale resolutions with the diffusion coefficient predetermined by PFG NMR. Hereby, the sample with short side chains relaxes like wormlike micelles considering the longitudinal direction, whereas the dynamics along the radial extension shows a much stronger Q-dependence as known from any theory. The dynamical behavior within the blob region, covered with the more spherical sample, follows the predictions of Zimm as well as of Zilman and Granek (ZG).

36 MATERIALS SCIENCE↗
DOE OSTI2023

Heavy Quark Diffusion from 2+1 Flavor Lattice QCD with 320 MeV Pion Mass

We present the first calculations of the heavy flavor diffusion coefficient using lattice QCD with light dynamical quarks corresponding to a pion mass of around 320 MeV. For temperatures 195 MeV< 𝑇 <352 MeV, the heavy quark spatial diffusion coefficient is found to be significantly smaller than previous quenched lattice QCD and recent phenomenological estimates. The result implies very fast hydrodynamization of heavy quarks in the quark-gluon plasma created during ultrarelativistic heavy-ion collision experiments.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Diffusion of Atoms in Glassy Mixtures of Deuterium and Lithium

The diffusion coefficients of D and Li were calculated in amorphous, glassy Li+D mixtures for various concentrations of D in lithium over the temperature range 100–1000 K. The densities of the mixtures as a function of temperature were also determined. The diffusion coefficients were obtained by the analysis of the mean-squared displacement using molecular dynamics with ReaxFF, a reactive force field. In conclusion, the diffusion and density data obtained for Li+D mixtures were compared with the available experimental and calculated data reported in the literature.

Diffusion↗
DOE OSTI2020

Mean force kinetic theory applied to self-diffusion in supercritical Lennard-Jones fluids

A new kinetic-theory-based calculation of the self-diffusion coefficient for dense supercritical Lennard-Jones fluids is presented. The mean force kinetic theory, which was recently developed for transport in dense plasmas, is applied for the calculation of diffusion in dense neutral fluids. The calculation only requires the pair distribution function, a quantity that is readily calculable from equilibrium statistical mechanics for many systems, including the Lennard-Jones fluid. The self-diffusion coefficients are compared with calculations from molecular dynamics simulations, and good agreement at high density is demonstrated, even in the vicinity of the solid–fluid coexistence line. A comparison of different kinetic models with molecular dynamics simulations demonstrates that the transport coefficients have important contributions due to particle interaction via a potential of mean force and local correlations, which increase the collision rate. The new calculations compare well to those from free-volume theory and overcome a limitation of this theory that prevents its use in systems that interact via long range monotonic potentials. It is expected that this approach will also apply to other systems, including neutral-plasma and neutral-electrolyte mixtures.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Compression Acceleration of Protons and Heavier Ions at the Heliospheric Current Sheet

Abstract Recent observations by the Parker Solar Probe (PSP) suggest that protons and heavier ions are accelerated to high energies by magnetic reconnection at the heliospheric current sheet (HCS). By solving the energetic particle transport equation in large-scale MHD simulations, we study the compression acceleration of protons and heavier ions in the reconnecting HCS. We find that the acceleration of multispecies ions results in nonthermal power-law distributions with a spectral index consistent with the PSP observations. Our study shows that the high-energy cutoff of protons can reach E max ∼ 0.1 –1 MeV depending on the particle diffusion coefficients. We also study how the high-energy cutoff of different ion species scales with the charge-to-mass ratio E max ∝ ( Q / M ) α . When determining the diffusion coefficients from the quasi-linear theory with a Kolmogorov magnetic power spectrum, we find that α ∼ 0.4, which is somewhat smaller than α ∼ 0.7 observed by PSP.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Evaluating diffusion and the thermodynamic factor for binary ionic mixtures

Molecular dynamics (MD) simulations are a powerful tool for the calculation of transport properties in mixtures. Not only are MD simulations capable of treating multicomponent systems, they are also applicable over a wide range of temperatures and densities. In plasma physics, this is particularly important for applications such as inertial confinement fusion. While many studies have focused on the effect of plasma coupling on transport properties, here we focus on the effects of mixing. We compute the thermodynamic factor, a measure of ideal/non-ideal mixing, for three binary ionic mixtures. Here, we consider mixtures of hydrogen and carbon, hydrogen and argon, and argon and carbon, each at 500 randomly generated state points in the warm dense matter and plasma regimes. The calculated thermodynamic factors indicate different mixing behavior across phase space, which can significantly affect the corresponding mutual diffusion coefficients. As MD simulations are still computationally expensive, we apply modern data science tools to predict the thermodynamic factor over a large phase space. Further, we propose a more accurate approximation to the mutual diffusion coefficient than the commonly applied Darken relation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Enhanced Diffusive Transport in Fluctuating Porous Media

Mass transport within porous structures is a ubiquitous process in biological, geological, and technological systems. Despite the importance of these phenomena, there is no comprehensive theory that describes the complex and diverse transport behavior within porous environments. While the porous matrix itself is generally considered a static and passive participant, many porous environments are in fact dynamic, with fluctuating walls, pores that open and close, and dynamically changing cross-links. While diffusion has been measured in fluctuating structures, notably in model biological systems, it is rarely possible to isolate the effect of fluctuations because of the absence of control experiments involving an identical static counterpart, and it is generally impossible to observe the dynamics of the structure. In this paper, we present a direct comparison of the diffusion of nanoparticles of various sizes within a trackable, fluctuating porous matrix and a geometrically equivalent static matrix, in conditions spanning a range of regimes from obstructed to highly confined. The experimental system comprised a close-packed layer of colloidal spheres that were either immobilized to a planar surface or allowed to fluctuate locally, within the space defined by their nearest neighbors. Interestingly, the effective long-time diffusion coefficient was approximately 35–65% greater in the fluctuating porous matrix than in the static one (depending on the size of the nanoparticle probes), regardless of the geometric regime. This was explained by considering the enhancing effects of matrix fluctuations on the short-time diffusion coefficient and cooperative “gate-opening” motions of matrix particles and nanoparticle probes.

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

Physics-Informed Deep Neural Networks for Learning Parameters and Constitutive Relationships in Subsurface Flow Problems

In this paper, we present a physics informed deep neural network (DNN) method for estimating parameters and unknown physics (constitutive relationships) in partial differential equation (PDE) models. We use PDEs in addition to measurements to train DNNs to approximate unknown parameters and constitutive relationships as well as states. The proposed approach increases the accuracy of DNN approximations of partially known functions when a limited number of measurements is available and allows for training DNNs when no direct measurements of the functions of interest are available. We employ physics informed DNNs to estimate the unknown space-dependent diffusion coefficient in a linear diffusion equation and an unknown constitutive relationship in a non-linear diffusion equation. For the parameter estimation problem, we assume that partial measurements of the coefficient and states are available and demonstrate that under these conditions, the proposed method is more accurate than state-of-the-art methods. For the non-linear diffusion PDE model with a fully unknown constitutive relationship (i.e., no measurements of constitutive relationship are available), the physics informed DNN method can accurately estimate the non-linear constitutive relationship based on state measurements only. Finally, we demonstrate that the proposed method remains accurate in the presence of measurement noise.

42 ENGINEERING↗
DOE OSTI2024

Electrochemical Study of OH - in Molten MgCl 2 -NaCl-KCl Salts

Here the present study determines the equilibrium concentration of OH- in molten MgCl 2 -NaCl-KCl salts and measures the kinetic properties data of OH- (diffusion coefficient, exchange current density, charge transfer coefficient, limiting current density, and standard rate constant) accordingly at different temperatures. The equilibrium concentration of OH- descends as the temperature increases, which ranges from 4.11 to 2.84 × 10 -6 mol cm -3 in the temperature range of 600 °C–800 °C. The diffusion coefficient follows Arrhenius law with a value between 2.46 and 4.48 × 10 -4 cm 2 s -1 . The exchange and limit current densities, and standard rate constant increase with temperature. The calculated standard rate constant κ 0 follows Arrhenius law, which is in the range from 1.23 to 2.50 × 10 -4 cm s -1 . The measured charge transfer coefficient is independent of temperature, which validates the present measurements.

14 SOLAR ENERGY↗
DOE OSTI2021

The mobility of small, over-pressurized helium bubbles in tungsten at 2000 K

Fusion reactor environments inevitably lead to the formation of high-pressure helium bubbles whose nucleation, growth, and diffusion strongly impact the performance of plasma-facing components. Here this research describes a diffusion mechanism of over-pressurized bubbles via a sequence of Frenkel pair nucleation, self-interstitial migration, and Frenkel pair annihilation. Molecular dynamics was used to simulate the diffusion of small bubbles in tungsten at 2000 K with helium-per-vacancy ratios in the range of 4.5 to 7. The diffusion coefficients are calculated and their dependence on helium content, number of vacancies, and number of attached self-interstitials is characterized. It is found that bubbles are most mobile when the nucleation/annihilation rates of Frenkel pairs are nearly equal and when the bubbles nucleate and annihilate a single self-interstitial. All bubbles experience a peak diffusivity, which can be as high as 10 -11 m 2 /s decreasing with bubble size. The calculated diffusion coefficients provide valuable insight into the mobility of small, high-pressure bubbles, and can be used as input parameters in mesoscale models to improve predictions of plasma-surface interactions. (LA-UR-21-21881)

36 MATERIALS SCIENCE↗
DOE OSTI2022

Conversion Kinetics and Ionic Conductivity in Na-β”-Alumina + YSZ (Naβ”AY) Sodium Solid Electrolyte via Vapor Phase Conversion Process

Sodium ion batteries have been receiving increasing attention and may see potential revival in the near future, particularly in large-scale grid energy storage coupling with wind and solar power generation, due to the abundant sodium resources, low cost, and sufficiently high energy density. Among the known sodium ion conductors, the Na-β”-alumina electrolyte remains highly attractive because of its high ionic conductivity. This study focuses on the vapor phase synthesis of a Na-β”-Alumina + YSZ (Naβ”AY) composite sodium electrolyte, which has higher mechanical strength and stability than conventional single phase β”-Alumina. The objectives are the measurement of conversion kinetics through a newly developed weight-gain based model and the determination of sodium ionic conductivity in the composite electrolyte. Starting samples contained ~70 vol% α-Alumina and ~30 vol% YSZ (3 mol% Y 2 O 3 stabilized Zirconia) with and without a thin alumina surface layer made by sintering in air at 1600 °C. The sintered samples were placed in a powder of Na-β”-alumina and heat-treated at 1250 °C for various periods. Sample dimensions and weight were measured as a function of heat treatment time. The conversion of α-Alumina in the α-Alumina + YSZ composite into Naβ”AY occurred by coupled diffusion of sodium ions through Na-β”-alumina and of oxygen ions through YSZ, effectively diffusing Na2O. From the analysis of the time dependence of sample mass and dimensions, the effective diffusion coefficient of Na 2 O through the sample, D eff , was estimated to be 1.74 x 10 -7 cm2 s -1 , and the effective interface transfer parameter, k eff , was estimated as 2.33 x 10 -6 cm s -1 . By depositing a thin alumina coating layer on top of the bulk composite, the chemical diffusion coefficient of oxygen through single phase Na-β”-alumina was estimated as 4.35 x 10 -10 cm 2 s -1 . An AC impedance measurement was performed on a fully converted Naβ”AY composite, and the conductivity of the composite electrolyte was 1.3 x 10 -1 S cm -1 at 300 °C and 1.6 x 10 -3 S cm -1 at 25 °C, indicating promising applications in solid state or molten salt batteries at low to intermediate temperatures.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Beyond fragmented dopant dynamics in quantum spin lattices: Robust localization and non-Gaussian diffusion

The motion of dopants in magnetic spin lattices has received tremendous attention for at least four decades due to its connection to high-temperature superconductivity. Despite these efforts, we lack a complete understanding of their behavior, especially out of the equilibrium and at nonzero temperatures. In this paper, we take a significant step towards a much deeper understanding based on state-of-the-art matrix-product-state calculations. In particular, we investigate the nonequilibrium dynamics of a dopant in two-leg 𝑡−𝐽 ladders with antiferromagnetic XXZ spin interactions. In the Ising limit, we find that the dopant is localized for all investigated nonzero temperatures due to an emergent disordered potential, with a localization length controlled by the underlying correlation length of the spin lattice, which increases exponentially with decreasing temperature. The dopant, hereby, only delocalizes asymptotically in the zero temperature limit. This greatly generalizes the localization effect discovered recently in Hilbert space fragmented models [Phys. Rev. Res. 6, 023325 (2024), SciPost Phys. Core 7, 054 (2024)]. In the presence of spin-exchange processes at rate 𝛼, the dopant diffuses with a diffusion coefficient, 𝐷 ℎ , depending nonmonotonically on 𝛼. It initially increases linearly as 𝐷 ℎ ∝ 𝛼 for 𝛼 ≪ 1 before dropping off as 𝛼 −1 for 𝛼 > 1. Moreover, we show that the underlying spin dynamics at infinite temperature behaves qualitatively the same, albeit with important quantitative differences. We substantiate these findings by showing that the dynamics features self-similar scaling behavior, which strongly deviates from the Gaussian behavior of regular diffusion, especially for weak spin exchange. Finally, we show that the diffusion coefficient 𝐷 ℎ follows an Arrhenius relation at high temperatures, whereby it is exponentially suppressed upon cooling.

Anomalous diffusion↗
DOE OSTI2023

Determination of the Interfacial Energy between Graphene Nanoplatelets and Deuterated or Hydrogenated Polystyrene

The tracer diffusion coefficients of various graphene nanoplatelet-polystyrene (GNP-PS) systems were determined by using dynamic secondary ion mass spectrometry, which provided insights into the interactions within the polymer nanocomposite system. Bilayer films, where one contained trace amounts of deuterated polystyrene (dPS), were produced, and the interdiffusion was measured by detecting the position of the dPS interface. GNPs were placed in both or only one of the two layers. The diffusion coefficient was decreased when GNPs were present in both layers as compared to the samples without GNP, indicating an attractive interaction between GNP and polystyrene. Surprisingly, the coefficient increased relative to the control when GNPs were present only in the PS containing layer, whereas it decreased most strongly when GNP and dPS were present only in the same layer, indicating that an additional preference existed for GNPs and dPS. A significant difference in interfacial energies was measured using contact angle goniometry of PS or dPS droplets on flat GNP layers, confirming the preferential interaction. DFT calculations were used to calculate the interfacial interaction between GNP and dPS or PS, and they showed an attractive potential which was maximal when the PS rings were conformal with the GNP structure. Furthermore, the differential energy between PS and dPS at the GNP interface was in excellent agreement with the measured value. In contrast, contact angle goniometry indicated that the interaction between GNP and poly(methyl methacrylate) (PMMA) was unfavorable, and no difference in interfacial energy between dPMMA and PMMA was observed. Therefore, these techniques can provide a means for determining the relative affinity between GNP and different polymer hosts, which can be an important consideration in the mechanics and adhesion properties of the compounds.

36 MATERIALS SCIENCE↗