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At least 829 records · Page 46
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Cooperative diffusion in body-centered cubic iron in Earth and super-Earths’ inner core conditions

Abstract The physical chemistry of iron at the inner-core conditions is key to understanding the evolution and habitability of Earth and super-Earth planets. Based on full first-principles simulations, we report cooperative diffusion along the longitudinally fast ⟨ 111 ⟩ directions of body-centered cubic (bcc) iron in temperature ranges of up to 2000–4000 K below melting and pressures of ∼300–4000 GPa. The diffusion is due to the low energy barrier in the corresponding direction and is accompanied by mechanical and dynamical stability, as well as strong elastic anisotropy of bcc iron. These findings provide a possible explanation for seismological signatures of the Earth’s inner core, particularly the positive correlation between P wave velocity and attenuation. The diffusion can also change the detailed mechanism of core convection by increasing the diffusivity and electrical conductivity and lowering the viscosity. The results need to be considered in future geophysical and planetary models and should motivate future studies of materials under extreme conditions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2018

Bragg coherent diffraction imaging of iron diffusion into gold nanocrystals

Understanding how diffusion takes place within nanocrystals is of great importance for their stability and for controlling their synthesis. In this study, we used the strain sensitivity of Bragg coherent diffraction imaging (BCDI) to study the diffusion of iron into individual gold nanocrystals in situ at elevated temperatures. The BCDI experiments were performed at the I-07 beamline at Diamond Light Source, UK. The diffraction pattern of individual gold nanocrystals was measured around the (11-1) Bragg peak of gold before and after iron deposition as a function of temperature and time. Phase retrieval algorithms were used to obtain real space reconstructions of the nanocrystals from their measured diffraction patterns. Alloying of iron with gold at sample temperatures of 300 °C–500 °C and dealloying of iron from gold at 600 °C were observed. The volume of the alloyed region in the nanocrystals was found to increase with the dose of iron. However, no significant time dependence was observed for the structure following each iron deposition, suggesting that the samples reached equilibrium relatively quickly. The resulting phase distribution within the gold nanocrystals after the iron depositions suggests a contraction due to diffusion of iron. Furthermore, our results show that BCDI is a useful technique for studying diffusion in three dimensions and alloying behaviour in individual crystalline grains.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Diffusion energy barrier of Au on Bi 2 Se 3 : theory and experiment

The stability and diffusion of ultra-thin thermally deposited Au films on Bi 2 Se 3 was studied using scanning tunneling microscopy and density functional theory calculations. The Au/Bi 2 Se 3 interface is of interest as gold is predicted to provide excellent electrical contact while maintaining the spin-polarized characteristics of the electronic states in Bi 2 Se 3 that make the material attractive for spintronic applications. When deposited at room temperature, Au 10 covers the surface with tightly packed islands of nanometer scale dimension. The surface morphology is stable up to 400K. At this annealing temperature, Au atoms have sufficient energy to diffuse across the surface and aggregate into larger nanostructures. At 550K, the Bi 2 Se 3 surface is only sparsely covered, and the Au has formed clusters with length scales 5-10 times larger than the original islands formed at room temperature. Comparison of the experiment and first principle calculation lead to the conclusion that the diffusion energy barrier for Au on Bi 2 Se 3 is as high as 0.47 eV, 15 which is much larger than diffusion barriers on other van der Waals materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Prediction of L⁢i 3 ⁢F⁡e 8 ⁢B 8 compound with rapid one-dimensional ion diffusion channels

Using a computational crystal structure search in the Li-Fe-B ternary system, we predict a stable phase of L⁢i 3 ⁢F⁡e 8 ⁢B 8 , featuring 1D channels that enable rapid Li-ion transport. Ab initio molecular dynamics simulations show that the Li-ion diffusion coefficient in L⁢i 3 ⁢F⁡e 8⁢ B 8 surpasses that of common electrode and conductive additive materials by several orders of magnitude. The high diffusion in L⁢i 3 ⁢F⁡e 8 ⁢B 8 can be explained by the Frenkel–Kontorova model, which describes an incommensurate state between the Li diffusion chain and the periodic potential field caused by the FeB backbone structure. The favorable lithium-ion diffusivity and mechanical properties of L⁢i 3 ⁢F⁡e 8 ⁢B 8 make it a promising conductive additive for battery materials. Furthermore, an external magnetic field can further manipulate the properties of this material due to its predicted itinerant ferromagnetism, which also offers a platform for exploring spin-dependent phenomena.

1-dimensional systems↗
DOE OSTI2025

External Magnetic Field Suppression of Carbon Diffusion in Iron

External magnetic fields reduce diffusion of carbon in BCC iron, but the physical mechanism is not understood. Using DFT calculations with magnetic moments sampled from a Heisenberg model, we calculate diffusivities of carbon in iron at high temperatures and with field. Our model reproduces the measured suppression of diffusivity from field. Here, we find that increasing magnetic disorder flattens the electron density of states compared with the ferromagnetic case, which distorts the octahedral cages around carbon, lowering the activation barrier to diffusion; an applied field reverses these trends.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Multiphonon diffuse scattering in solids from first principles: Application to layered crystals and two-dimensional materials

Time-resolved diffuse scattering experiments have gained increasing attention due to their potential to reveal nonequilibrium dynamics of crystal lattice vibrations with full momentum resolution. Although progress has been made in interpreting experimental data on the basis of one-phonon scattering, understanding the role of individual phonons can be sometimes hindered by multiphonon excitations. In Ref. [M. Zacharias, H. Seiler, F. Caruso, D. Zahn, F. Giustino, P. C. Kelires, and R. Ernstorfer, Phys. Rev. Lett. 127, 207401 (2021)], we have introduced a rigorous approach for the calculation of the all-phonon inelastic scattering intensity of solids from first-principles. In the present work, we describe our implementation in detail and show that multiphonon interactions are captured efficiently by exploiting translational and time-reversal symmetries of the crystal. We demonstrate its predictive power by calculating the scattering patterns of monolayer molybdenum disulfide (MoS 2 ), bulk MoS 2 , and black phosphorus (bP), and we obtain excellent agreement with our measurements of thermal electron diffuse scattering. Remarkably, our results show that multiphonon excitations dominate in bP across multiple Brillouin zones, while in MoS 2 they play a less pronounced role. We expand our analysis for each system and examine the effect of individual atomic and interatomic vibrational motion on the diffuse scattering signals. We further demonstrate the high-throughput capability of our approach by reporting all-phonon scattering maps of two-dimensional MoSe 2 , WSe 2 , WS 2 , graphene, and CdI 2 , rationalizing in each case the effect of multiphonon processes. As a side point, we show that the special displacement method reproduces the thermally distorted configuration that generates precisely the all-phonon diffuse pattern. In conclusion, the present methodology opens the way for systematic calculations of the scattering intensity in crystals and the accurate interpretation of static and time-resolved inelastic scattering experiments.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
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 OSTI2020

Statistically averaged molecular dynamics simulations of hydrogen diffusion in magnesium and magnesium hydrides

Magnesium has a different crystal structure from its dihydride with hydrogenation leading to a phase transition from the hexagonal closely packed Mg into a tetragonal α-MgH 2 rutile type structure. Such materials exhibit complex hydrogen uptake and release kinetics because hydrogen diffusivities significantly change when the crystal structure changes. To provide a foundational understanding of (de)hydrogenation kinetics that is applicable to all stages of the reaction, we performed statistically averaged molecular dynamics simulations to derive hydrogen diffusivities as a function of temperature and hydrogen content for both magnesium and magnesium hydride. Furthermore, our studies confirm that hydrogen diffusivities in magnesium hydride are much lower than in magnesium, in agreement with experimental data. Additionally, we observe that in either magnesium or magnesium hydride, higher hydrogen compositions result in reduced diffusivities. The latter was not revealed by prior experiments, which were conducted at fixed hydrogen composition. Finally, we discover a non-Arrhenius behavior in magnesium hydride. The physical origin of this behavior is also discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Internal protein motions in molecular-dynamics simulations of Bragg and diffuse X-ray scattering

Molecular-dynamics (MD) simulations of Bragg and diffuse X-ray scattering provide a means of obtaining experimentally validated models of protein conformational ensembles. This paper shows that compared with a single periodic unit-cell model, the accuracy of simulating diffuse scattering is increased when the crystal is modeled as a periodic supercell consisting of a 2 × 2 × 2 layout of eight unit cells. The MD simulations capture the general dependence of correlations on the separation of atoms. There is substantial agreement between the simulated Bragg reflections and the crystal structure; there are local deviations, however, indicating both the limitation of using a single structure to model disordered regions of the protein and local deviations of the average structure away from the crystal structure. Although it was anticipated that a simulation of longer duration might be required to achieve maximal agreement of the diffuse scattering calculation with the data using the supercell model, only a microsecond is required, the same as for the unit cell. Rigid protein motions only account for a minority fraction of the variation in atom positions from the simulation. The results indicate that protein crystal dynamics may be dominated by internal motions rather than packing interactions, and that MD simulations can be combined with Bragg and diffuse X-ray scattering to model the protein conformational ensemble.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Antimony diffusion in CdTe

Group V dopants may be used for next-generation high-voltage cadmium telluride (CdTe) solar photovoltaics, but fundamental defect energetics and kinetics need to be understood. Here, antimony (Sb) diffusion is studied in single-crystal and polycrystalline CdTe under Cd-rich conditions. Diffusion profiles are determined by dynamic secondary ion mass spectroscopy and analyzed with analytical bulk and grain-boundary diffusion models. Slow bulk and fast grain-boundary diffusion are found. Density functional theory is used to understand formation energy and mechanisms. Lastly, the theory and experimental results create new understanding of group V defect kinetics in CdTe.

14 SOLAR ENERGY↗
DOE OSTI2016

WE-FG-202-11: Longitudinal Diffusion MRI for Treatment Assessment of Sarcoma Patients with Pre-Operative Radiation Therapy

Purpose: Diffusion weighted MRI (DWI) is a promising imaging technique for early prediction of tumor response to radiation therapy. A recently proposed longitudinal DWI strategy using a Co-60 MRI guided RT system (MRIgRT) may bring functional MRI guided adaptive radiation therapy closer to clinical utility. We report our preliminary results of using this longitudinal DWI approach performed on the MRIgRT system for predicting the response of sarcoma patient to preop RT. Methods: Three sarcoma patients who underwent fractionated IMRT were recruited in this study. For all three patients DWI images were acquired immediately following his/her treatment. For each imaging session, ten slices were acquired interleaved with the b values covering the gross tumor volume (GTV). The diffusion images were processed to obtain the ADC maps using standard exponential fitting for each voxel. Regions of interest were drawn in the tumor on the diffusion images based on each patient’s clinical GTV contours. Each patient subsequently underwent surgery and the tumor necrosis score was available from standard pathology. The ADC values for each patient were compared to the necrosis scores to assess the predictive value of our longitudinal DWI for tumor response. Results: Each patient underwent 3 to 5 diffusion MRI scans depending on their treatment length. Patient 1 had a relatively unchanged ADC during the course of RT and a necrosis score of 30% at surgery. For patient 2, the mean ADC values decreased from 1.56 × 10-3 to 1.12 × 10-3 mm2/s and the patient’s necrosis score was less than 10%. Patient 3 had a slight increase in the ADC values from 0.59 × 10-3 to 0.71 × 10-3 mm2/s and patient’s necrosis score was 50%. Conclusion: Based on limited data from 3 patients, our longitudinal changes in tumor ADC assessed using the MRIgRT system correlated well with pathology results.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Diffusion of Ag, Sn, and Pb over Atomically Clean Ge(111) Surface

Auger electron spectroscopy and low-energy electron diffraction were used to study the diffusion of Ag, Sn, and Pb over the Ge (111) surface. The mechanisms of diffusion of atoms of these elements over the Ge(111) surface are determined, and the temperature dependences of the diffusion coefficients are measured. The parameters of diffusion of these elements over the Ge(111) and Si (111) surfaces are compared.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2016

Halogen diffusion on a Ga-stabilized ζ-GaAs(001)–(4 × 2) surface

The atomic and electronic structure of a Ga-stabilized GaAs(001) surface with the ζ(4 × 2) reconstruction and halogens in a number of symmetric sites on the surface are calculated by the plane-wave projector augmented wave method. The energy barriers of halogen-atom diffusion on this surface are calculated, which allow determination of the most preferred paths of their migration. It is shown that there is a low barrier (0.17–0.23 eV) for the diffusion of all halogens under consideration (I, Br, Cl, F) along the surface gallium dimer, whereas the barrier is significantly higher for diffusion between adjacent gallium dimers. In general, the energy barriers for halogen diffusion in both directions ([110] and [1-10]) point to their high surface mobility, despite high binding energies at a number of surface adsorption sites.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Grassmannian Diffusion Maps--Based Dimension Reduction and Classification for High-Dimensional Data

This work introduces the Grassmannian diffusion maps (GDMaps), a novel nonlinear dimensionality reduction technique that defines the affinity between points through their representation as low-dimensional subspaces corresponding to points on the Grassmann manifold. Here, the method is designed for applications, such as image recognition and data-based classification of constrained high-dimensional data where each data point itself is a high-dimensional object (i.e., a large matrix) that can be compactly represented in a lower-dimensional subspace. The GDMaps is composed of two stages. The first is a pointwise linear dimensionality reduction wherein each high-dimensional object is mapped onto the Grassmann manifold representing the low-dimensional subspace on which it resides. The second stage is a multipoint nonlinear kernel-based dimension reduction using diffusion maps to identify the subspace structure of the points on the Grassmann manifold. To this end, an appropriate Grassmannian kernel is used to construct the transition matrix of a random walk on a graph connecting points on the Grassmann manifold. Spectral analysis of the transition matrix yields low-dimensional Grassmannian diffusion coordinates embedding the data into a low-dimensional reproducing kernel Hilbert space. Further, a novel data classification/recognition technique is developed based on the construction of an overcomplete dictionary of reduced dimension whose atoms are given by the Grassmannian diffusion coordinates. Three examples are considered. First, a "toy" example shows that the GDMaps can identify an appropriate parametrization of structured points on the unit sphere. The second example demonstrates the ability of the GDMaps to revealing the intrinsic subspace structure of high-dimensional random field data. In the last ex- ample, a face recognition problem is solved considering face images subject to varying illumination conditions, changes in face expressions, and occurrence of occlusions. The technique presented high recognition rates (i.e., 95% in the best case) using a fraction of the data required by conventional methods.

42 ENGINEERING↗
DOE OSTI2023

A Generalization of Threshold-Based and Probability-Based Models of Information Diffusion

Diffusion of information through complex networks is of interest in studies such as propagation prediction and influence maximization, both of which have applications in viral marketing and rumor controlling. There are a variety of information diffusion models, all of which simulate the adoption and spread of information over time. However, there is a lack of understanding of whether, despite their conceptual differences, these models represent the same underlying generative structures. For instance, if two different models utilize different conceptual mechanisms, but generate the same results, does the choice of model matter? A classification of diffusion of information models is developed based on the neighbor knowledge of the model infection requirement and the stochasticity of the model. This classification allows for the identification of models that fall into each respective category. The study involves the analysis of the following agent-based models on directed scale-free networks: (1) a linear absolute threshold model (LATM), (2) a linear fractional threshold model (LTFM), (3) the independent cascade model (ICM), (4) Bass-Rand-Rust model (BRRM) (5) a stochastic linear absolute threshold model (SLATM) (6) a stochastic fractional threshold model (SLFTM), and (7) Dodds–Watts model (DWM). Through the execution of simulations and analysis of the experimental results, the distinctive properties of each model are identified. Our analysis reveals that similarity in conceptual design does not imply similarity in behavior concerning speed, final state of nodes and edges, and sensitivity to parameters. Therefore, we highlight the importance of considering the unique behavioral characteristics of each model when selecting a suitable information diffusion model for a particular application.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Estimating the Diffusion Coefficient of Lithium in Graphite: Extremely Fast Charging and a Comparison of Data Analysis Techniques

Galvanostatic intermittent titration experiments were performed in three-electrode cells to characterize the effect of C/2, 2-C and 4-C charge rates on the observed lithium diffusion coefficient. As part of the data analysis process, we compared the classic Weppner-Huggins analysis of polarization data with a newer (Wang et al.) analysis method for depolarization data. At low values of x in Li x C 6 , both analysis methods showed the same general trend in the apparent lithium diffusion coefficient, 4-C > 2-C > C/2. The two techniques differed in the magnitude of the estimated diffusion coefficient by about a factor of 100. The observed increase in diffusion coefficient does not last over a large compositional range. Since the estimates from the method of Weppner and Huggins may contain artifacts due to the use of particulate electrodes and high charge rates, the method of Wang et al. may produce better values.

25 ENERGY STORAGE↗
DOE OSTI2022

Extension of the PINN diffusion model to k-eigenvalue problems

This paper extends our recent work on the Physics-Informed Neural Networks (PINN) approach for the fixed source diffusion models and applies it to the diffusion theory based k-eigenvalue problems. To make the PINN equitable for the eigenvalue problems, we introduce a novel integral regularization term to the loss function in the framework, and allow the direct inference of the principal eigenvalue and the associated eigenfunction. The regularization term enforces a pre-defined value on the integration of the model predictions, and this value can be directly related to a physical property of the system. We also introduce an additional learnable parameter to approximate the principal eigenvalue. As a proof of principle, we solve the one-group two-dimensional k-eigenvalue neutron diffusion equation in this work. We then provide two numerical examples to demonstrate the applicability of the PINN approach. In each example, we solve the k-eigenvalue diffusion equation in a multi-region configuration constrained with a set of Robin boundary conditions for generality. We use a FEM solution based on the power-iteration method to verify the results of the PINN solution. The results showed relative percentage error in the predicted eigenvalue of about 0.77% and about 1.2% for example 1 and example 2, respectively. The mean absolute error in the predicted flux for example 1 is ∼ 0.002 and for example 2 is ∼ 0.0024. These results indicate some preliminary successes of the PINN application to k-eigenvalue problems. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2017

Predicting Ga and Cu Profiles in Co-Evaporated Cu(In,Ga)Se 2 Using Modified Diffusion Equations and a Spreadsheet

Cu(In,Ga)Se 2 (CIGS) photovoltaic absorbers frequently develop Ga gradients during growth. These gradients vary as a function of growth recipe, and are important to device performance. Prediction of Ga profiles using classic diffusion equations is not possible because In and Ga atoms occupy the same lattice sites and thus diffuse interdependently, and there is not yet a detailed experimental knowledge of the chemical potential as a function of composition that describes this interaction. Here, we show how diffusion equations can be modified to account for site sharing between In and Ga atoms. The analysis has been implemented in an Excel spreadsheet, and outputs predicted Cu, In, and Ga profiles for entered deposition recipes. A single set of diffusion coefficients and activation energies are chosen, such that simulated elemental profiles track with published data and those from this study. Extent and limits of agreement between elemental profiles predicted from the growth recipes and the spreadsheet tool are demonstrated.

14 SOLAR ENERGY↗