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At least 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Cluster spin glass correlations and dynamics in Zn 0.5⁢ Mn 0.5⁢ Te

Here, we present a combined magnetometry, muon spin-relaxation (𝜇⁢SR), and neutron-scattering study of the insulating spin glass Zn 0.5 ⁢Mn 0.5 ⁢Te, for which magnetic Mn 2+ and nonmagnetic Zn 2+ ions are randomly distributed on a face-centered cubic lattice. The magnetometry and 𝜇⁢SR results confirm a spin freezing transition around 𝑇 𝑓 ≈ 23 K, with the spin-fluctuation rate decreasing gradually and somewhat inhomogeneously through the sample volume as the temperature decreases toward 𝑇 𝑓 . Characteristic spin-correlation times well above 𝑇 𝑓 are on the order of 10 −10 s, much slower than typically observed in canonical spin glasses but in line with expectations for a cluster spin glass. Using magnetic pair distribution function (mPDF) analysis and reverse Monte Carlo (RMC) modeling of the magnetic diffuse neutron-scattering data, we show that the spin-glass ground state consists of clusters of spins exhibiting short-range-ordered type-III antiferromagnetic correlations with a locally ordered moment of 3.1⁢(1)⁢𝜇 B between nearest-neighbor spins. The type-III correlations decay exponentially as a function of spin separation distance with a correlation length of approximately 5 Å. The diffuse magnetic scattering and corresponding mPDF show no significant changes across 𝑇 𝑓 , indicating that the dynamically fluctuating short-range spin correlations in the paramagnetic state retain the same basic type-III configuration that characterizes the spin-glass state; the only change apparent from the neutron-scattering data is a gradual reduction of the correlation length and locally ordered moment with increasing temperature. Taken together, these results paint a unique and detailed picture of the local magnetic structure and dynamics in Zn 0.5 ⁢Mn 0.5⁢ Te and provide strong evidence that this material is best described as a cluster spin glass. In addition, this work showcases a statistical method for extracting diffuse scattering signals from neutron powder diffraction data, which we developed to facilitate the mPDF and RMC analysis of the neutron data. This method has the potential to be broadly useful for neutron powder diffraction experiments on a variety of materials with short-range atomic or magnetic order.

magnetism↗
DOE OSTI2022

Temperature-Dependent Constrained Diffusion of Micro-Confined Alkylimidazolium Chloride Ionic Liquids

Alkylimidazolium chloride ionic liquids (ILs) have many uses in a variety of separation systems, including micro-confined separation systems. To understand the separation mechanism in these systems, the diffusion properties of analytes in ILs under relevant operating conditions, including micro-confinement dimension and temperature, should be known. For example, separation efficiencies for various IL-based microextraction techniques are dependent on the sample volume and temperature. Temperature-dependent (20–100 °C) fluorescence recovery after photobleaching (FRAP) was utilized to determine the diffusion properties of a zwitterionic, hydrophilic dye, ATTO 647, in alkylimidazolium chloride ILs in micro-confined geometries. These micro-confined geometries were generated by sandwiching the IL between glass substrates that were separated by ~1 to 100 μm. From the measured temperature-dependent FRAP data, we note alkyl chain length-, thickness-, and temperature-dependent diffusion coefficients, with values ranging from 0.021 to 46 μm 2 /s. Deviations from Brownian diffusion are observed at lower temperatures and increasingly less so at elevated temperatures; the differences are attributed to alterations in intermolecular interactions that reduce temperature-dependent nanoscale structural heterogeneities. Furthermore, the temperature- and thickness-dependent data provide a useful foundation for efficient design of micro-confined IL separation systems.

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

Reaction-diffusive dynamics of number-conserving dissipative quantum state preparation

The use of dissipation for the controlled creation of nontrivial quantum many-body correlated states is of much fundamental and practical interest. What is the result of imposing number conservation, which, in closed system, gives rise to diffusive spreading? For this work, we investigate this question for a paradigmatic model of a two-band system, with dissipative dynamics aiming to empty one band and to populate the other, which had been introduced before for the dissipative stabilization of topological states. Going beyond the mean-field treatment of the dissipative dynamics, we demonstrate the emergence of a diffusive regime for the particle and hole density modes at intermediate length- and timescales, which, interestingly, can only be excited in nonlinear response to external fields. We also identify processes that limit the diffusive behavior of this mode at the longest length- and timescales. Strikingly, we find that these processes lead to a reaction-diffusion dynamics governed by the Fisher-Kolmogorov-Petrovsky-Piskunov equation, making the designed dark state unstable towards a state with a finite particle and hole density.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Bulk and surface diffusion of neodymium in alpha-uranium: Ab initio calculations and kinetic Monte Carlo simulations

A fundamental understanding of lanthanide transport in metallic fuels is critical for high fidelity modeling of the fuel-cladding chemical interaction (FCCI) phenomenon, which can lead to the formation of brittle intermetallic compounds and premature failure of the cladding. Here we report a combined ab initio density functional theory (DFT) and kinetic Monte Carlo (KMC) study of the bulk diffusivity of Nd in α-U, fully taking into account the effect of radiation enhanced diffusion. In this work, the vacancy mechanism is considered to be the dominant mechanism for the bulk diffusion of Nd since a Nd interstitial is found to be intrinsically unstable in α-U. The surface diffusivity of a Nd adatom on α-U (001) surface has been further predicted using KMC simulations parameterized by DFT calculations. The present study suggests that Nd transport via the surface diffusion mechanism can be many orders of magnitude faster than bulk diffusion. Furthermore, the results from the present lower length scale study can be used to inform mesoscale phase-field simulations to determine the effective diffusion coefficient of Nd through α-U with a porous microstructure.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Proton Diffusion in Liquid 1,2,3-Triazole Studied by Incoherent Quasi-Elastic Neutron Scattering

Improving the proton transport in polymer electrolytes impacts the performance of next-generation solid-state batteries. However, little is known about proton conductivity in nonaqueous systems due to the lack of an appropriate level of fundamental understanding. Here, we studied the proton transport in small molecules with dynamic hydrogen bonding, 1,2,3-triazole, as a model system of proton hopping in a nonaqueous environment using incoherent quasi-elastic neutron scattering. By using the jump-diffusion model, we identified the elementary jump-diffusion motion of protons at a much shorter length scale than those by nuclear magnetic resonance and impedance spectroscopy for the estimated long-range diffusion. In addition, a spatially restricted diffusive motion was observed, indicating that proton motion in 1,2,3-triazole is complex with various local correlated dynamics. In conclusion, these correlated dynamics will be important in elucidating the nature of the proton dynamics in nonaqueous systems.

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

Towards inverse microstructure-centered materials design using generative phase-field modeling and deep variational autoencoders

The field of Integrated Computational Materials Engineering (ICME) combines a broad range of methods to study materials’ responses over a spectrum of length scales. A relatively unexplored aspect of microstructure-sensitive materials design is uncertainty propagation and quantification (UP/UQ) of materials’ microstructure, as well as establishing process-structure–property (PSP) relationships for inverse material design. In this study, an efficient UP technique built on the idea of changing probability measures and a deep generative unsupervised representative machine learning method for microstructure-based design of thermal conductivity of materials is proposed. Probability measures are used to represent microstructure space, and Wasserstein metrics are used to test the efficiency of the UP method. By using deep Variational AutoEncoder (VAE), we identify the correlations between the material/process parameters and the thermal conductivity of heterogeneous dual-phase microstructures. Through high-throughput screening, UP, and the deep-generative VAE method, PSP relationships that are too complex can be revealed by exploiting the materials’ design space with an emphasis on microstructures. As a last point, we demonstrate generative machine learning serves as a useful tool for inverse microstructure-centered materials design, and we demonstrate this by examining the inverse design of thermal conductivity in nano-structured materials. Here, the results reveal the effects of morphology, volume fraction, characteristic length scale, and the individual thermal diffusivity of phases on the thermal conductivity of dual-phase alloys. Our findings emphasize the advantages of high-throughput phase-field modeling and generative deep learning for linking PSP and inverse microstructure-centered materials design.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Molecular dynamics simulations of radiation response of $\mathrm{LiAlO_2}$ and $\mathrm{LiAl_5O_8}$

Here, we report the findings of a computational investigation of defect production and migration in two lithium aluminate ceramics: LiAlO 2 and LiAl 5 O 8 . Although the first ceramic, LiAlO 2 has been widely investigated computationally, especially via molecular dynamics (MD), there have been no MD studies done on LiAl 5 O 8 up to date, due to the lack of interatomic potentials for this system. This work implemented an existing set of Li-Al-O coulombic and Buckingham potential parameters for the LiAl 5 O 8 system from the literature, followed by validating it based on experimental values of density, crystallinity, bond lengths and melting point. The Li + diffusion in the two ceramics was examined and was found to be one order of magnitude slower in LiAl 5 O 8 (D 0 = 3.17 x 10 -11 m 2 /s) as compared to that in LiAlO 2 (D 0 = 4.02 x 10 -10 m 2 /s) at 600 K. The lithium vacancy migration barrier of 4.15 eV in LiAl 5 O 8 was more than three times that in LiAlO 2 (1.31 eV) possibly due to stronger ordering in the Li-O 6 octahedra of LiAl 5 O 8 than in Li-O 4 tetrahedra of LiAlO 2 . The Li displacement threshold energy (E d ) in LiAl 5 O 8 was found to have a median value of 68 eV which is much higher than that in LiAlO 2 (40 eV). The greater E d for Li signifies a lower likelihood for defect formation and clustering and thus lower tendency for amorphization in LiAl 5 O 8 . The presented results show the difference in defect dynamics in the two ceramics that may help us understand the susceptibility of the two ceramics to amorphization caused by irradiation.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Ion correlations explain kinetic selectivity in diffusion-limited solid-state synthesis reactions

Establishing viable solid-state synthesis pathways for novel inorganic materials remains a major challenge in materials science. Previous pathway design methods using pairwise reaction approaches have navigated the thermodynamic landscape with first-principles data but lack kinetic information, limiting their effectiveness. This gap leads to suboptimal precursor selection and predictions, especially for reactions forming competing phases with similar formation energies, where ion diffusion is a critical influence. Here we demonstrate an inorganic synthesis framework by incorporating machine learning-derived transport properties through ‘liquid-like’ product layers into a thermodynamic cellular reaction model. In the Ba–Ti–O system, known for its competitive polymorphism, we obtain accurate predictions of phase formation with varying BaO:TiO2 ratios as a function of time and temperature. We find that diffusion–thermodynamics interplay governs phase compositions, with cross-ion transport coefficients critical for predicting diffusion-limited selectivity. This work bridges length scales and timescales by integrating solid-state reaction kinetics with first-principles thermodynamics and spatial reactivity.

Atomistic models↗
DOE OSTI2022

Eddy diffusivity operator in homogeneous isotropic turbulence

Here, we use the recently developed macroscopic forcing method to compute the scale-dependent eddy diffusivity characterizing ensemble-averaged scalar and momentum transport in incompressible homogeneous isotropic turbulence. For scales larger than the energy containing eddies, eddy diffusivity is found to be constant and consistent with the Boussinesq approximation. However, for small scales eddy diffusivity is found to vanish inversely proportional to the wave number. Behavior at all scales is reasonably captured by a nonlocal eddy diffusivity operator modeled as D/$\sqrt{I - l^2∇^2}$, where D is the eddy diffusivity in the Boussinesq limit, and l is a constant on the order of the large-eddy length. These results present a direct measurement of eddy diffusivity in turbulence with implications in turbulence modeling.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Scientific Development of Core Block and Monolith Materials (FY2020 Progress)

This report presents the status of an effort to investigate welding and joining techniques for microreactor monolith structural materials. Previously reported results have demonstrated the potential to tier weld sub-scale components using electron beam welding. Tier welding has been investigated on larger scale test articles, and results indicate that tier welding is not feasible for larger components due to the penetration depth that is required. Additional techniques to produce full length parts have been examined, including diffusion bonding and gundrilling. Evaluations of these techniques are ongoing, and have shown early success on sub-scale components. These results indicate that while issues still exist for manufacturing microreactor structures, these challenges are better understood and solutions are in development.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

High-dimensional and permutation invariant anomaly detection

Methods for anomaly detection of new physics processes are often limited to low-dimensional spaces due to the difficulty of learning high-dimensional probability densities. Particularly at the constituent level, incorporating desirable properties such as permutation invariance and variable-length inputs becomes difficult within popular density estimation methods. In this work, we introduce a permutation-invariant density estimator for particle physics data based on diffusion models, specifically designed to handle variable-length inputs. We demonstrate the efficacy of our methodology by utilizing the learned density as a permutation-invariant anomaly detection score, effectively identifying jets with low likelihood under the background-only hypothesis. To validate our density estimation method, we investigate the ratio of learned densities and compare to those obtained by a supervised classification algorithm.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Single molecule characterization of anomalous transport in a thin, anisotropic film

Here, the diffusion of small, charged molecules incorporated in an anisotropic polyelectrolyte multilayers (PEMs) was tracked in three dimensions by combining single-molecule fluorescence localization (to characterize lateral diffusion) with Förster resonance energy transfer (FRET) between diffusing molecules and the supporting surface (to measure diffusion in the surface-normal direction). Analysis of the surface-normal diffusion required model-based statistical analysis to account for the inherently noisy FRET signal. Combining these distinct single-molecule methods, which are inherently sensitive to different length scales, permitted simultaneous characterization of severely anisotropic diffusion, which was more than three orders of magnitude slower in the surface-normal direction. We hypothesize that the anomalously slow surface-normal diffusion was related to the periodic distribution of charge in the PEM, which created electrostatic barriers. The motion was strongly subdiffusive, with anomalous temporal scaling exponents in lateral and normal directions, suggesting a connection to the transient, random fractal conformation of polymer chains in the film’s matrix.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Numerical validation of scaling laws for stratified turbulence

Recent theoretical progress using multiscale asymptotic analysis has revealed various possible regimes of stratified turbulence. Notably, buoyancy transport can either be dominated by advection or diffusion, depending on the effective Péclet number of the flow. Two types of asymptotic models have been proposed, which yield measurably different predictions for the characteristic vertical velocity and length scale of the turbulent eddies in both diffusive and non-diffusive regimes. The first, termed a ‘single-scale model’, is designed to describe flow structures having large horizontal and small vertical scales, while the second, termed a ‘multiscale model’, additionally incorporates flow features with small horizontal scales, and reduces to the single-scale model in their absence. By comparing predicted vertical velocity scaling laws with direct numerical simulation data, we show that the multiscale model correctly captures the properties of strongly stratified turbulence within regions dominated by small-scale isotropic motions, whose volume fraction decreases as the stratification increases. Meanwhile its single-scale reduction accurately describes the more orderly, layer-like, quiescent flow outside those regions.

Mechanics↗
DOE OSTI2023

Hindered segmental dynamics in associative protein hydrogels studied by neutron spin-echo spectroscopy

Transient binding between associating macromolecules can cause qualitative changes to chain dynamics, including modes of conformational relaxation and diffusion, through tethering effects imparted by long-range connectivity. Here, in this work, the role of binding on short-time segmental dynamics in associative polymer gels is investigated by neutron spin-echo (NSE) measurements on a class of model artificial coiled-coil proteins with a systematically varied architecture, probing timescales of 0.1–130 ns, and length scales close to the molecular radius of gyration. The results illustrate effects of transient cross-linking on chain dynamics on different timescales, manifested in changes in segmental relaxation behavior with variations in strand length, chain concentration, and sticker distribution (endblock- vs midblock-functionalized). In all gels, a short-time cooperative diffusion mode is seen over all wave vectors, analogous to a semidilute solution, with no transitions seen at any known structural length scale. However, the diffusion coefficients are found to decrease with increasing junction density across all gels, with the strand length and number of stickers per chain in each gel appearing to play a relatively minor role. The slowing of cooperative diffusion with junction density contrasts with classical predictions of a greater restoring force for fluctuation dissipation due to the increased elasticity, suggesting additional effects of the coiled-coil junctions such as an enhancement in local viscosity that slows dynamics. Notably, the relaxation rates for all gels can be rescaled by the interjunction spacing inferred from small-angle neutron scattering, where they collapse onto a master curve suggestive of self-similar dynamics even in networks with different strand lengths and chain architectures. On long timescales (but shorter than the junction exchange time), a slowing of network relaxation is observed, resulting in a nondecaying plateau in the spin-echo amplitude attributed to a freezing of chain dynamics due to tethering. A characteristic length scale corresponding to the extent of dynamic fluctuations is estimated for each gel, which appears to be smaller than the interjunction spacing but similar to the correlation blob size of the overlapping strands. The results indicate an important role of transient binding on molecular-scale dynamics in associative polymer gels, even on timescales shorter than the junction exchange time, in addition to its effects on long-range self-diffusion previously observed.

36 MATERIALS SCIENCE↗
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 OSTI2025

Consistent solutions of the radiation diffusion equation in spherical and cylindrical geometries

We have extended the radiation diffusion model of Hammer and Rosen [Phys. Plasmas 10, 1829 (2003)] to diverging spherical and cylindrical geometries. The effect of curvilinear geometry on the supersonic, expanding wavefront increases as the internal radius of a spherical or cylindrical shell approaches zero. Small spherical geometries are important for modeling systems at the size scale of inertial confinement fusion capsules, at these scales existing quasi-analytic models for planar geometry significantly disagree with the results of simulation. With this method, the benefits of rapid iteration can be applied to common spherical systems at much smaller length scales. We present comparisons between numerical diffusion solutions and the analytic model to give ranges of applicability for the model.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Mass Transport Limitations and Kinetic Consequences of Corn Stover Deacetylation

Alkaline pretreatment of herbaceous feedstocks such as corn stover prior to mechanical refining and enzymatic saccharification improves downstream sugar yields by removing acetyl moieties from hemicellulose. However, the relationship between transport phenomena and deacetylation kinetics is virtually unknown for such feedstocks and this pretreatment process. Here, we report the development of an experimentally validated reaction–diffusion model for the deacetylation of corn stover. A tissue-specific transport model is used to estimate transport-independent kinetic rate constants for the reactive extraction of acetate, hemicellulose and lignin from corn stover under representative alkaline conditions (5–7 g L -1 NaOH, 10 wt% solids loadings) and at low to mild temperatures (4–70°C) selected to attenuate individual component extraction rates under differential kinetic regimes. The underlying transport model is based on microstructural characteristics of corn stover derived from statistically meaningful geometric particle and pore measurements. These physical descriptors are incorporated into distinct particle models of the three major anatomical fractions (cobs, husks and stalks) alongside an unsorted, aggregate corn stover particle, capturing average Feret lengths of 917–1239 μm and length-to-width aspect ratios of 1.8–2.9 for this highly heterogeneous feedstock. Individual reaction–diffusion models and their resulting particle model ensembles are used to validate and predict anatomically-specific and bulk feedstock performance under kinetic-controlled vs. diffusion-controlled regimes. In general, deacetylation kinetics and mass transfer processes are predicted to compete on similar time and length scales, emphasizing the significance of intraparticle transport phenomena. Critically, we predict that typical corn stover particles as small as ~2.3 mm in length are entirely diffusion-limited for acetate extraction, with experimental effectiveness factors calculated to be 0.50 for such processes. Debilitatingly low effectiveness factors of 0.021–0.054 are uncovered for cobs—implying that intraparticle mass transfer resistances may impair observable kinetic measurements of this anatomical fraction by up to 98%. These first-reported quantitative maps of reaction vs. diffusion control link fundamental insights into corn stover anatomy, biopolymer composition, practical size reduction thresholds and their kinetic consequences. These results offer a guidepost for industrial deacetylation reactor design, scale-up and feedstock selection, further establishing deacetylation as a viable biorefinery pretreatment for the conversion of lignocellulosics into value-added fuels and chemicals.

09 BIOMASS FUELS↗
DOE OSTI2022

Molecular engineering of fluoroether electrolytes for lithium metal batteries

Fluoroether solvents are promising electrolyte candidates for high-energy-density lithium metal batteries, where high ionic conductivity and oxidative stability are important metrics for design of new systems. Recent experiments have shown that these performance metrics, particularly stability, can be tuned by changing the fraction of ether and fluorine content. However, little is known about how different molecular architectures influence the underlying ion transport mechanisms and conductivity. Here, we use all-atom molecular dynamics simulations to elucidate the ion transport and solvation characteristics of fluoroether chains of varying length, and having different ether segment and fluorine terminal group contents. The design rules that emerge from this effort are that solvent size determines lithium-ion transport kinetics, solvation structure, and solvation energy. In particular, the mechanism for lithium-ion transport is found to shift from ion hopping between solvation sites located in different fluoroether chains in short-chain solvents, to ion–solvent co-diffusion in long-chain solvents, indicating that an optimum exists for molecules of intermediate length, where hopping is possible but solvent diffusion is fast. Consistent with these findings, our experimental measurements reveal a non-monotonic behavior of the effects of solvent size on lithium-ion conductivity, with a maximum occurring for medium-length solvent chains. Finally, a key design principle for achieving high ionic conductivity is that a trade-off is required between relying on shorter fluoroether chains having high self-diffusivity, and relying on longer chains that increase the stability of local solvation shells.

25 ENERGY STORAGE↗