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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Coordination changes in liquid tin under shock compression determined using in situ femtosecond x-ray diffraction

Little is known regarding the liquid structure of materials compressed to extreme conditions, and even less is known about liquid structures undergoing rapid compression on nanosecond timescales. Here, we report on liquid structure factor and radial distribution function measurements of tin shock compressed to 84(19) GPa. High-quality, femtosecond x-ray diffraction measurements at the Linac Coherent Light Source were used to extract the liquid diffuse scattering signal. From the radial distribution function, we find that the structural evolution of the liquid with increasing pressure mimics the evolution of the solid phase. With increasing pressure, we find that the liquid structure evolves from a complex structure, with a low coordination number, to a simple liquid structure with a coordination number of ~12. We provide a pathway for future experiments to study liquids at elevated pressures using high-energy lasers to shock compress materials beyond the reach of static diamond anvil cell techniques.

X-ray diffraction↗
DOE OSTI2022

Complex pH-Dependent Interactions between Weak Polyelectrolyte Block Copolymer Micelles and Molecular Fluorophores

Amphiphilic block copolymers with weak polyelectrolyte blocks can assemble stimulus-responsive nanostructures and interfaces. Applications of these materials in drug delivery, biomimetics, and sensing largely rely on the well-understood swelling of polyelectrolyte chains upon deprotonation, often induced by changes in pH or ionic strength. This deprotonation can also tune interfacial interactions between the polyelectrolyte blocks and surrounding solution, an effect which is less studied than morphological swelling of polyelectrolytes but can be just as critical for intended function. Here, we investigate whether the pH-driven morphological response of polyelectrolyte-bearing nanostructures also affects the interactions of these nanostructures with molecules in solution, using micelles of a short-chain polybutadiene-block-poly(acrylic acid) (pBd–pAA) as a model system. Here we introduce a Förster resonance energy transfer (FRET) approach to probe interactions between micelles and fluorescent molecular solutes as a function of solution pH. As expected, the pAA corona of these pBd–pAA micelles increases in thickness monotonically as a function of pH. However, FRET efficiency, which provides a metric of the spatial proximity of fluorescently labeled micelles and freely diffusing fluorophores, exhibits complex nonmonotonic behavior as a function of pH, indicating that the average separation of micelles and acceptor fluorophores is not strictly correlated with micelle swelling. Dialysis experiments quantify the affinity of fluorophores for micelles as a function of pH, confirming that changes in FRET are driven almost entirely by the pH-dependent affinity of the pAA block for the investigated molecular fluorophores, not simply by a shape change of the pAA corona. This study provides key insights into the interfacial interactions between weak-polyelectrolyte-bearing nanostructures and molecular solutes, of importance for the development of their stimulus-responsive applications.

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

Multiscale, mechanistic calculation of the effective silver diffusion coefficient in polycrystalline silicon carbide: application to silver release in AGR-1 TRISO particles

The silicon carbide (SiC) layer in tristructural isotropic (TRISO) fuel particles serves as a barrier to prevent the escape of fission from the fuel kernel. The release of silver (Ag) is a concern due to the long half-life of the 110mAg isotope. In this study, the effective diffusion coefficient of the fission product Ag through the grain boundary (GB) network is calculated using a combination of atomistic and phase-field methods. Atomistic calculations of Ag diffusivity in SiC bulk and GBs are leveraged to develop a mesoscale effective Ag diffusion coefficient (Deff) in SiC. Since GBs serve as pathways for Ag diffusion, Deff is defined as a function of temperature, microstructure variables, and fluence. Deff is implemented in the fuel performance code Bison to predict Ag release from AGR-1 TRISO fuel particles. We hereby quantify the impact of SiC grain size and irradiation on Ag release and improve Bison's predictions.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Numerical fluid dynamics for FRG flow equations: Zero-dimensional QFTs as numerical test cases. II. Entropy production and irreversibility of RG flows

Herein we demonstrate that the reformulation of renormalization group (RG) flow equations as nonlinear heat equations has severe implications on the understanding of RG flows in general. We demonstrate by explicitly constructing an entropy function for a zero-dimensional Z 2 -symmetric model that the dissipative character of generic nonlinear diffusion equations is also hard-coded in the functional RG equation. This renders RG flows manifestly irreversible, revealing the semigroup property of RG transformations on the level of the flow equation itself. Additionally, we argue that the dissipative character of RG flows, its irreversibility and the entropy production during the RG flow may be linked to the existence of a so-called C– / A-function. In total, this introduces an asymmetry in the so-called RG time—in complete analogy to the thermodynamic arrow of time—and allows for an interpretation of infrared actions as equilibrium solutions of dissipative RG flows equations. The impossibility of resolving microphysics from macrophysics is evident in this framework. Furthermore, we directly link the irreversibility and the entropy production in RG flows to an explicit numerical entropy production, which is manifest in diffusive and non-linear partial differential equations (PDEs) and a standard mathematical tool for the analysis of PDEs. Using exactly solvable zero-dimensional Z 2 -symmetric models, we explicitly compute the (numerical) entropy production related to the total variation nonincreasing property of the PDE during RG flows toward the infrared limit. Finally, we discuss generalizations of our findings and relations to the C– / A-theorem as well as how our work may help to construct truncations of RG flow equations in the future, including numerically stable schemes for solving the corresponding PDEs.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Quantum Ornstein-Zernike theory for two-temperature two-component plasmas

Laboratory plasma production almost always preferentially heats either the ions or electrons, leading to a two-temperature state. In this state, density functional theory molecular dynamic simulation is the state of the art for modeling bulk material properties. We construct a statistical mechanics model for the two temperature limit that is theoretically consistent with the molecular dynamics method. We proceed to derive the electron-ion multi-temperature quantum Ornstein-Zernike equations for the first time. This allows the construction of a two-temperature two-component plasma model using the average atom from which we can compute bulk material properties at a fraction of the computation time of the two-temperature density functional theory simulation. The accuracy of the model is benchmarked against ion pair correlation and self-diffusion results from ab initio simulation. Here, we proceed to compute the viscosity and ion thermal conductivity as a function of both ion and electron temperature.

Ab initio molecular dynamics↗
DOE OSTI2022

NMR and Theoretical Study of In-Pore Diffusivity of Ionic Liquid–Solvent Mixtures

We report despite having a lower energy density than common batteries, electric double-layer capacitors (EDLCs) offer several advantages for high-power applications, including high power density, quick charge and discharge time, and long cycle life. Room-temperature ionic liquids (RTILs) have been intensely studied as promising electrolytes for applications in ELDCs because of their wide potential window, low volatility, as well as thermal and chemical stability. The main deficiency of neat RTILs in such applications is the sluggish diffusivity, which restricts the EDLCs’ power density. To alleviate the slow diffusivity, RTILs can be used in a mixture with organic solvents. In this study, we applied two-dimensional exchange nuclear magnetic resonance spectroscopy (2D EXSY NMR) and molecular dynamics (MD) simulations to investigate the diffusivity of anions of an RTIL, namely, 1-butyl-3-methyl-imidazolium bis(trifluoromethylsulfonyl)imide (BMIM + –TFSI – ), dissolved in five different organic solvents, in the micropores of activated carbon. We determined that the relative concentrations of ions in solutions in the micropores were higher than those in the bulk solutions and were also solvent-dependent. The ion diffusivities in the pores were found to be almost 2 orders of magnitude slower than in the bulk solutions, with methanol showing the largest relative disparity. These results suggested that the interactions of solvents with the activated carbon are critical not only to the power density of EDLCs but also to the energy density. The comparisons of ion diffusivities between the experiments and the MD simulations suggest the need to consider also the surface functionalities of activated carbon for the simulation of ion diffusion in the micropores of activated carbon.

electric double layer capacitors↗
DOE OSTI2020

Evaluation of Amorphous Oxide Coatings for High-Voltage Li-Ion Battery Applications Using a First-Principles Framework

Cathode surface coatings are widely used industrially as a means to suppress degradation and improve electrochemical performance of lithium-ion batteries. However, developing an optimal coating is challenging, as different coating materials may enhance one aspect of performance while hindering another. Furthermore, to elucidate the fundamental thermodynamic and transport properties of amorphous cathode coating materials, here, we present a framework for calculating and analyzing the Li + and O 2- transport and the stability against delithiation in such materials. Our framework includes systematic workflows of ab-initio molecular dynamics calculations to obtain amorphous structures and diffusion trajectories coupled with an analysis of critical changes of the active-ion local environment during diffusion. Based on these data, we provide an estimate of room-temperature diffusivities, including statistical error bars, and the evaluation of the coating suitability in terms of its ability to facilitate Li + transport while blocking O 2- transport. Finally, we add the thermodynamic stability analysis of the coating chemistry within the operating voltage of common Li-ion cathodes. We apply this framework to two commonly used amorphous coating materials, Al 2 O 3 and ZnO. We find that (1) in general, a higher Li + content increases both Li + and O 2- diffusivities in both Al 2 O 3 and ZnO. Also, Li + and O 2- diffuse much faster in ZnO than in Al 2 O 3 . (2) However, neither Al 2 O 3 nor ZnO is expected to retain a significant concentration of Li + at high charge. (3) ZnO performs much more poorly in terms of O 2- blocking, and hence, Al 2 O 3 is preferred for high-voltage cathode applications. These results will help to quantitatively evaluate amorphous materials, such as metal oxides and fluorides, for different performance metrics and facilitate the development of optimal cathode coatings.

25 ENERGY STORAGE↗
DOE OSTI2021

Charge balance functions for heavy-ion collisions at energies available at the CERN Large Hadron Collider

Heavy-ion collisions at the Large Hadron Collider provide the conditions to investigate regions of quark-gluon plasma that reach higher temperatures and that persist for longer periods of time compared with collisions at the Relativistic Heavy Ion Collider. This extended duration allows correlations from charge conservation to better separate during the quark-gluon plasma phase, and thus be better distinguished from correlations that develop during the hadron phase or during hadronization. Here, charge balance functions binned by relative rapidity and azimuthal angle and indexed by species are considered. A detailed theoretical model that evolves charge correlations throughout the entirety of an event is compared with preliminary results from the ALICE Collaboration. The comparison with experiment provides insight into the evolution of the chemistry and diffusivity during the collision. A ratio of balance functions is proposed to better isolate the effects of diffusion and thus better constrain the diffusivity.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

A Phase-Field Model for In-Space Manufacturing of Binary Alloys

The integrity of the final printed components is mostly dictated by the adhesion between the particles and phases that form upon solidification, which is a major problem in printing metallic parts using available In-Space Manufacturing (ISM) technologies based on the Fused Deposition Modeling (FDM) methodology. Understanding the melting/solidification process helps increase particle adherence and allows to produce components with greater mechanical integrity. We developed a phase-field model of solidification for binary alloys. The phase-field approach is unique in capturing the microstructure with computationally tractable costs. The developed phase-field model of solidification of binary alloys satisfies the stability conditions at all temperatures. The suggested model is tuned for Ni-Cu alloy feedstocks. We derived the Ginzburg-Landau equations governing the phase transformation kinetics and solved them analytically for the dilute solution. We calculated the concentration profile as a function of interface velocity for a one-dimensional steady-state diffuse interface neglecting elasticity and obtained the partition coefficient, k, as a function of interface velocity. Numerical simulations for the diluted solution are used to study the interface velocity as a function of undercooling for the classic sharp interface model, partitionless solidification, and thin interface.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Enhanced Nanostructure Dynamics on Au(111) with Adsorbed Sulfur due to Au–S Complex Formation

Chemisorbed species can enhance the fluxional dynamics of nanostructured metal surfaces which has implications for applications such as catalysis. Scanning tunneling microscopy studies at room temperature reveal that the presence of adsorbed sulfur (S) greatly enhances the decay rate of 2D Au islands in the vicinity of extended step edges on Au(111). This enhancement is already significant at S coverages, θS, of a few hundredths of a monolayer (ML), and is most pronounced for 0.1–0.3 ML where the decay rate is increased by a factor of around 30. For θ S close to saturation at about 0.6 ML, sulfur induces pitting and reconstruction of the entire surface, and Au islands are stabilized. Enhanced coarsening at lower θS is attributed to the formation and diffusion across terraces of Au–S complexes, particularly AuS 2 and Au4S 4 , with some lesser contribution from Au3S4. This picture is supported by density functional theory analysis of complex formation energies and diffusion barriers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
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 OSTI2023

Atomistic models of In and Ga diffusion in Cu(In,Ga)Se 2

To improve the performance of Cu(In,Ga)Se 2 thin-film photovoltaic devices, a robust understanding of the dominant diffusion pathways of the alloy species In and Ga is needed. Here, the most probable defect complexes and mechanisms for In and Ga diffusion are identified with the aid of density functional theory. The binding energies and migration barriers for these complexes are calculated in bulk CuInSe 2 and CuGaSe 2 . Analytic models and kinetic lattice Monte Carlo simulations are employed to predict the diffusivity of In and Ga under variations in composition and temperature. Here, we find that a model based on coulombic interactions between group III antisites and vacancies on the Cu-sublattice produces results that match well with experiment.

14 SOLAR ENERGY↗
DOE OSTI2020

Molecular Origins of the Barriers to Proton Transport in Acidic Aqueous Solutions

The self-consistent iterative multistate empirical valence bond (SCI-MS-EVB) method is used to analyze the structure, thermodynamics, and dynamics of hydrochloric acid solutions. The reorientation timescales of irreversible proton transport are elucidated by simulating 0.43 M, 0.85 M, 1.68 M, and 3.26 M HCl solutions at 270 K, 285 K, 300 K, 315 K, and 330 K. The results indicate increased counter-ion pairing with increasing concentration, which manifests itself via a reduced hydronium oxygen–chloride (O*-Cl) structuring in the radial distribution functions. Increasing ionic concentration also reduces the diffusion of the hydrated excess protons, principally by reducing the contribution of the Grotthuss proton hopping (shuttling) mechanism to the overall diffusion process. In agreement with prior experimental findings, a decrease in the activation energy of reorientation timescales was also observed, which is explicitly explained using activated rate theory and an energy-entropy decomposition of the state-averaged radial distribution functions. Furthermore, these results provide atomistic verification of suggestions from recent two-dimensional infrared spectroscopy experiments that chloride anions (as opposed to hydrated excess protons) create entropic barriers to proton transport.

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

Universal dynamics of coarsening during polymer-polymer thin-film spinodal dewetting kinetics

The dewetting dynamics of a supported bilayer polymer thin film on a solid substrate is investigated using grazing incidence x-ray photon correlation spectroscopy. We find that the top layer dewets via the spinodal mechanism. The kinetics of the dewetting is studied by monitoring the time evolution of the surface diffuse x-ray scattering intensity. We study the time evolution of fluctuations about the average surface structure by measuring the two-time x-ray intensity fluctuation correlation functions. Using these two-time correlation functions we quantify the crossover from early-time diffusive dynamics to hydrodynamics. The early diffusive regime satisfies dynamic universality. The two-time correlation functions also quantify the onset of hydrodynamic effects. The hydrodynamic regime is observed during the spinodal dewetting process as these interactions are not screened.

36 MATERIALS SCIENCE↗
DOE OSTI2022

($\mathrm{INVITED}$)Counter-ion effect on the diffusion behavior of $\mathrm{Y}$b, $\mathrm{L}$u, and $\mathrm{N}$d ions in $\mathrm{YAG}$ transparent ceramics

The ability to fabricate additively manufactured laser waveguides with sharp dopant concentration interfaces is limited by diffusion of the dopants at the temperatures required to fully densify the material. Compositional analysis of bilayer samples, where each layer was either undoped YAG or YAG doped with Yb, Lu, or Nd, were fabricated such that all combinations were available for testing. Samples were fabricated at both 1750°C and 1850°C to determine the diffusion behavior of each dopant alone and also in the presence of a second dopant. It was found that the experimental concentration profiles exhibited both intragranular (bulk) and grain boundary contributions, and thus fitting to a complementary error function equation required the use of two diffusion coefficients. Nd always diffused further along grain boundaries than the other dopants, due in part to its small segregation coefficient in YAG. It is shown that the presence of Nd as a counter dopant inhibits intragranular diffusion of other dopants while enhancing their grain boundary diffusion. All the observed trends were attributed to a combination of intragranular lattice strain due to: dopant ions replacing yttrium substitutionally, the relative driving forces for the segregation of dopant ions to grain boundaries, and the ability of one dopant to affect the diffusion of a different dopant in the other direction to maintain charge neutrality.

36 MATERIALS SCIENCE↗
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

Atomic scale understanding of organic anion separations using ion-exchange resins

A combination of ab initio and classical molecular dynamic simulations was used to explore the adsorption/desorption and diffusion characteristics of ion-exchange resins for extraction of organic anions in electrically-driven separation processes. We considered two classes of carboxylate mixtures that are commonly encountered in bioprocessing separations: a short chain fatty acid mixture (acetate/butyrate) and an aromatic mixture (ferulate/coumarate). The suitability of several resin materials including PFC100E, IRC86, PFA444 and IRA67 was interrogated. The decomposition of the interaction energies by the symmetry-adapted perturbation theory and the classical molecular dynamic simulations of organic diffusion together reveal that the geometries of the organic anions and the functional groups of the resins, as well as their Columbic interactions, are the controlling factors in the diffusion process of the organic compounds in these resins. Additionally, classical simulations also show that modifying the functionality of resin beads, the magnitude of electric fields, and the ratio of organic mixtures may provide an effective way to control the diffusion rate and obtain selective separation of these organic mixtures. Finally, a general suggestion for favorable separation conditions is summarized.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Discrete generative diffusion models without stochastic differential equations: A tensor network approach

Diffusion models (DMs) are a class of generative machine learning methods that sample a target distribution by transforming samples of a trivial (often Gaussian) distribution using a learned stochastic differential equation. In standard DMs, this is done by learning a “score function” that reverses the effect of adding diffusive noise to the distribution of interest. Here we consider the generalisation of DMs to lattice systems with discrete degrees of freedom, and where noise is added via Markov chain jump dynamics. We show how to use tensor networks (TNs) to efficiently define and sample such “discrete diffusion models” (DDMs) without explicitly having to solve a stochastic differential equation. We show the following: (i) by parametrising the data and evolution operators as TNs, the denoising dynamics can be represented exactly; (ii) the auto-regressive nature of TNs allows to generate samples efficiently and without bias; (iii) for sampling Boltzmann-like distributions, TNs allow to construct an efficient learning scheme that integrates well with Monte Carlo. We illustrate this approach to study the equilibrium of two models with non-trivial thermodynamics, the d = 1 constrained Fredkin chain and the d = 2 Ising model. Published by the American Physical Society 2025

Causer, Luke (ORCID:0000000194243473)↗