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At least 181 records · Page 10

A Frequency Domain Methodology for Quantitative Evaluation of Diffuse Wavefield With Applications to Seismic Imaging

Abstract Ambient Noise Imaging (ANI) of subsurface structures relies on seismic interferometry of diffuse seismic wavefields. However, the lack of effective methods to quantify and identify highly diffuse waves hampers applications of ANI, particularly in evaluating seismic attenuation and monitoring structural changes with high temporal resolution. Conventional ANI approaches require data normalization, which effectively suppresses the non‐diffuse component with large amplitude but also results in significant loss of amplitude and phase information in the continuous seismic records. In this study, we propose a frequency domain method to quantitatively evaluate the degree of diffuseness of seismic wavefields by analyzing their statistical characteristics of modal amplitudes for stationarity and randomness. Tests on synthetic waveform and field nodal records show that the proposed method can effectively distinguish between diffuse and non‐diffuse waveforms for either single‐ or three‐component data. As an application, we identify a 60‐s‐long diffuse coda of a local M 2.2 earthquake recorded by a dense nodal array on the San Jacinto Fault Zone, and successfully extract high‐quality dispersion curve andQ‐value without performing data normalization. These results are consistent with those obtained by conventional methods that assess the correlation between coherency and the Green's function, and by modeling ballistic waves generated by road traffic. Our proposed method can advance the imaging of subsurface velocity and attenuation structures as well as monitoring temporal changes for scientific studies and engineering applications.

Geochemistry & Geophysics↗

Ion diffusion retarded by diverging chemical susceptibility

Abstract For first-order phase transitions, the second derivatives of Gibbs free energy (specific heat and compressibility) diverge at the transition point, resulting in an effect known as super-elasticity along the pressure axis, or super-thermicity along the temperature axis. Here we report a chemical analogy of these singularity effects along the atomic doping axis, where the second derivative of Gibbs free energy (chemical susceptibility) diverges at the transition point, leading to an anomalously high energy barrier for dopant diffusion in co-existing phases, an effect we coin as super-susceptibility. The effect is realized in hydrogen diffusion in vanadium dioxide (VO 2 ) with a metal-insulator transition (MIT). We show that hydrogen faces three times higher energy barrier and over one order of magnitude lower diffusivity when it diffuses across a metal-insulator domain wall in VO 2 . The additional energy barrier is attributed to a volumetric energy penalty that the diffusers need to pay for the reduction of latent heat. The super-susceptibility and resultant retarded atomic diffusion are expected to exist universally in all phase transformations where the transformation temperature is coupled to chemical composition, and inspires new ways to engineer dopant diffusion in phase-coexisting material systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Surface diffusion manifestation in electrodeposition of metal anodes

Metal anode-based battery systems have been deemed indispensable towards energy storage renaissance engendering extensive research into strategies countering dendritic growth of metal electrodeposition. Fundamentally, the morphological evolution of a material is uniquely characterized by the heights of its self-diffusion barrier across multiple pathways. Herein, based on a coarse-grained kinetic Monte Carlo method, we derive insights into the nucleation and growth of metallic electrodeposits in liquid electrolytes, governed by surface self-diffusion characteristics cognizant of the diverse diffusion routes including terrace, away from step and interlayer pathways. We deconvolve the roles played by each of these surface diffusion mechanisms in conjunction with the electrochemical reaction rate on the deposition morphology regime (film vs. mossy vs. fractal). We identify interlayer diffusion as the predominant morphology-determining mechanism; dendrite-free deposition even at moderate current rates constrains this diffusion barrier to an upper limit. Additionally, we highlight subtle features amidst the realm of the morphological growth assortment that connect to the cell's electrochemical performance. Finally, we delineate morphological features of Li, Na, Mg and Al based on their respective surface diffusion barriers and applied overpotentials, and provide a baseline for the interpretation of experimental observations. This fundamental study sheds light on the mesoscale underpinnings of morphological variances in mono-valent and multi-valent metal electrodeposition.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Efficient diffusion of superdense lithium via atomic channels for dendrite-free lithium–metal batteries

The non-uniform aggregation of fast-diffused Li on an anode surface would aggravate its tip-effect-induced nucleation/growth, leading to the notorious dendrite growth in Li metal batteries (LMBs). Tuning the Li diffusion on the anode surface has been regarded previously as a mainstream method to induce its uniform deposition, while the diffusion of Li in the anode bulk is usually ignored. In this study, conceptually different from the classic surface modification, we propose a molecular tunnelling strategy to construct atomic channels in graphite bulk, which enables the fast diffusion of superdense Li. Density functional theory calculations and ab initio molecular dynamics simulations prove that the bulk diffusion through atomic channels could become a new and dominating path. Its reversible and efficient diffusion has been further visualized by in situ transmission electron microscopy. As a result, when coupled with high-loading LiFePO 4 cathodes (20 mg cm –2 ), a high areal capacity and 100% capacity retention are achieved over 370 cycles. Through this work a new strategy is developed based on the bulk-diffusion of superdense Li for dendrite-free LMBs, which can be pervasive in other high-performance energy storage systems.

25 ENERGY STORAGE↗

Topology driven and soft phonon mode enabled Na-ion diffusion in quaternary chalcogenides, Na 3 ZnGaX 4 (X = S, and Se)

The compounds Na 3 ZnGaX 4 (X = S, Se) are potential solid electrolyte materials in sodium-based batteries, which have certain advantages over oxide materials and have shown significant ionic conductivity at ambient temperature. In this paper, we bring out atomic-level features of the diffusion process in these new materials using the microscopic techniques of inelastic neutron scattering (INS), quasielastic neutron scattering (QENS), and ab initio molecular dynamics (AIMD) simulations. The insights obtained from these techniques are unique and not available from other macroscopic experiments. Neutron scattering experiments have been performed at temperatures from 100 to 700 K. The simulations have been carried out up to 900 K. We have calculated the phonon spectra and the space–time correlation functions and found good agreement with the results of the neutron scattering experiments. The simulations enable detailed analysis of the atomic-site dependent dynamical information. We observe low-energy phonon modes of ~6 meV involving the vibrations of certain Na atoms in the lattice. This reveals that the Na at 32g Wyckoff sites (Na2) has sufficiently shallow potential among the two available crystallographic sites. This shallow potential facilitates diffusion. Furthermore, the specific structural topology of the network of interconnected zig-zag chains of the Na2 atomic sites provides the low-barrier energy pathways for diffusion. A small fraction of vacancy defects appears essential for diffusion. We further observe that the Na2 atoms undergo jump-like diffusion to the vacant next or the 2nd next neighbour sites at ~4 Å. While the QENS experiments reveal the jump-like diffusion and its time scale, detailed analysis of the AIMD simulations shows that the jumps appear mostly along zig-zag chains of the Na2 sites in the tetragonal ab-plane, as well as between the chains along the c-axis. In conclusion, the net diffusion is essentially 3-dimensional, with little anisotropy despite the anisotropy of the tetragonal crystal structure.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Probing exciton diffusion dynamics in photosynthetic supercomplexes via exciton–exciton annihilation

Photosynthesis converts solar energy into chemical energy through coordinated energy transfer between light-harvesting complexes and reaction centers (RCs). Understanding exciton motion, particularly the exciton diffusion length, is essential for optimizing energy efficiency in photosystems. In this work, we combine intensity-cycling transient absorption spectroscopy with kinetic Monte Carlo (kMC) simulation to investigate exciton motion in the C2S2 photosystem II supercomplex of spinach. Using exciton–exciton annihilation, revealed in the fifth-order response, we experimentally estimate an exciton diffusion length of 10.9 nm based on a 3D normal diffusion model, suggesting the ability of excitons to traverse the supercomplex. However, kMC simulations reveal that exciton motion is sub-diffusive because of spatial constraints and the strong RC traps. An anomalous diffusion model analysis of the experimental data yields a diffusion length of 9.7 nm, while the simulated diffusion length is 7.4 nm. The variable exciton residence time across subunits, partly influenced by their connectivity to the trap, indicates inhomogeneous annihilation probability and suggests how plants balance efficient light harvesting with photoprotection. We also explore the influence of specific assumptions in the annihilation simulation, which are challenging to access in more complex environments, such as the thylakoid membrane. Our study provides a framework for studying exciton dynamics using exciton–exciton annihilation, which can be extended to understand the light-harvesting efficiencies of larger, more complex photosynthetic assemblies.

Zhang, Kunyan (ORCID:000000026830409X)↗

Proposed Material Properties, Allowable Stresses, and Design Curves of Diffusion Bonded Alloy 800H for the ASME Code Section III Division 5

Abstract Increased interest in compact heat exchangers (CHXs) to serve as intermediate heat exchangers of very high temperature reactors resulted in significant research and development on their design, analysis, and construction. Printed circuit heat exchangers are a type of CHXs with high thermal efficiency and compactness achieved through diffusion bonding a stack of etched plates with millimeter scaled channels. The diffusion bonding process changes the microstructural and mechanical properties of the wrought metal plates. The current nonnuclear design code ASME section VIII, division 1 captures the material property change through a “joint efficiency factor.” However, the current nuclear design code ASME section III, division 5 does not address or support the diffusion bonded material properties. Hence, there is a need to develop allowable stresses, isochronous curves, and fatigue life curves for various diffusion bonded alloys. In this study, Alloy 800H material was selected to establish the diffusion bonded material properties under tension, creep, fatigue, and creep-fatigue loads at elevated temperatures in the range 550–760 °C. A set of tests on diffusion bonded Alloy 800H (DB 800H) were performed and the acquired data are used in developing allowable stresses Sy, Su, Sr, Sm, St, Smt, So, isochronous curves and fatigue life curves according to the ASME section III, division 5 requirements. This paper also presents detailed procedures used in developing the ASME code section III division 5 design provisions for diffusion bonded Alloy 800H.

Engineering↗

Efficient Reformulation of Linear and Nonlinear Solid-Phase Diffusion in Lithium-ion Battery Models using Symmetric Polynomials: Mass Conservation and Computational Efficiency

Lithium-ion batteries are typically modeled using porous electrode theory coupled with various transport and reaction mechanisms, along with suitable discretization or approximations for the solid-phase diffusion equation. The solid-phase diffusion equation represents the main computational burden for typical pseudo-2-dimensional (p2D) models since these equations in the pseudo r -dimension must be solved at each point in the computational grid. This substantially increases the complexity of the model as well as the computational time. Traditional approaches towards simplifying solid-phase diffusion possess certain significant limitations, especially in modeling emerging electrode materials which involve phase changes and variable diffusivities. A computationally efficient representation for solid-phase diffusion is discussed in this paper based on symmetric polynomials using Orthogonal Collocation and Galerkin formulation (weak form). A systematic approach is provided to increase the accuracy of the approximation (p form in finite element methods) to enable efficient simulation with a minimal number of semi-discretized equations, ensuring mass conservation even for non-linear diffusion problems involving variable diffusivities. These methods are then demonstrated by incorporation into the full p2D model, illustrating their advantages in simulating high C-rates and short-time dynamic operation of Lithium-ion batteries.

25 ENERGY STORAGE↗

A First-Principles Study of the Vacancy-Mediated Silver Impurity Diffusion in fcc Nickel

In this report, ab initio techniques (Density Functional Theory, DFT) are used to calculate the vacancy-mediated self-diffusion coefficient and impurity diffusion coefficient of silver (Ag) in pure fcc nickel (Ni). Prediction of diffusion coefficients is one of the most stringent tests of the ability of DFT calculations, because of the complex interplay of lattice constant, vacancy formation enthalpy, solute-vacancy binding enthalpy, and vibrational frequencies. The Ag diffusion and Ni self-diffusion coefficients calculated in the present work compare very favorably to previous experimental self-diffusion and Ag diffusion data. Extension of the methodology to nickel alloys is envisioned in future work.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Ab Initio Simulations of Tritium Diffusion in Al 2 O and Intermetallic Al 12 (TM) 2.34 Aluminide Coating Phases

Density functional theory simulations have been carried out to investigate the diffusion of interstitial tritium in Al 12 (TM) 2.34 and Al 2 O bulk phases. In Al 12 (TM) 2.34 the transition metal (TM) sites are occupied on average by 58.93 at.% Fe, 18.52 at.% Cr, and 22.54 at.% Ni. While the insertion of interstitial tritium in Al 2 O lead to a strong disordering of the structure, we only investigated interstitial tritium in Al 12 (TM) 2.34 and its iron end-member (i.e., Al 12 Fe 2.34 ). Nine diffusion pathways have been investigated along the a-, b-, and c -axis of Al 12 (TM) 2.34 . The direction of fastest diffusion for interstitial tritium is found to be along the b-axis, with a calculated diffusion coefficient of ≈10 -10 m 2 .s -1 at 600 K, which is at least one order of magnitude faster than those previously calculated for interstitial tritium in other Al-rich phases such as Fe2Alx, Fe4Al13, and FeNiAl5 for which D T =10 -11 m 2 .s -1 , ≈10 -12 m 2 .s -1 , and D T ≈10 -13 m 2 .s -1 respectively. The comparison of the energy landscape between Al 12 (TM) 2.34 and Al 12 Fe 2.34 for the fastest diffusion pathways in each axis direction, found that some pathways are not sensitive to transition metal mixing, while other are more affected, leading to higher energy barrier in Al 12 Fe 2.34 in part due to a more energetically favorable formation of Fe—T bond compared to Ni—T. However, we found that both materials have similar diffusion coefficients as the fastest diffusion pathways occurs along pathways that are not very sensitive to transition metal mixing.

36 MATERIALS SCIENCE↗

Determination of the Diffusion Coefficients of Binary CH4 and C2H6 in a Supercritical CO2 Environment (500–2000 K and 100–1000 atm) by Molecular Dynamics Simulations

The self-diffusion coefficients of carbonaceous fuels in a supercritical CO2 environment provide transport information that can help us understand the Allam Cycle mechanism at a high pressure of 300 atm. The diffusion coefficients of pure CO2 and binary CO2/CH4 and CO2/C2H6 at high temperatures (500 K~2000 K) and high pressures (100 atm~1000 atm) are determined by molecular dynamics simulations in this study. Increasing the temperature leads to an increase in the diffusion coefficient, and increasing the pressure leads to a decrease in the diffusion coefficients for both methane and ethane. The diffusion coefficient of methane at 300 atm is approximately 0.012 cm2/s at 1000 K and 0.032 cm2/s at 1500 K. The diffusion coefficient of ethane at 300 atm is approximately 0.016 cm2/s at 1000 K and 0.045 cm2/s at 1500 K. The understanding of diffusion coefficients potentially leads to the reduction in fuel consumption and minimization of greenhouse gas emissions in the Allam Cycle.

Energy & Fuels↗

Hydraulically opened cone vertical tube diffuser with slanted anti-siphon hole

A diffuser for a water heater fill tubes having a tube wall with an outside diameter. The diffuser includes an elongated flexible diffuser body for positioning at the outlet end of the fill tube. The diffuser body has a sealing end for sealing with an outside surface of the fill tube wall closest to the inlet end of the fill tube, and an open end for positioning at an end closest to the outlet end of the fill tube. The open end has a diameter larger than an outside diameter of the tube wall, thereby creating an diffuser water outlet opening between the diffuser body and the tube wall for redirecting radial water flow emanating from the fill tube water outlet opening(s) toward the diffuser outlet opening. A fill tube assembly for a water heater, a water heater, and a method for heating water are also disclosed.

Rendall, Joseph D.↗

An extension of the localized artificial diffusivity method for immiscible and high density ratio flows

The localized artificial diffusivity (LAD) method is widely regarded as the preferred multi-material regularization scheme for the compact finite difference method, because it is conservative, easy to implement, and generally robust for a wide range of multi-material problems. However, traditional LAD methods face significant challenges when applied to flows with large density ratios and when maintaining thermodynamic equilibrium across material interfaces. These limitations arise from the formulation of the artificial diffusivity flux and the reliance on enthalpy diffusion for interface regularization. Additionally, traditional LAD methods struggle to ensure stability under large density ratio conditions, fail to maintain a finite interface thickness, and are therefore unsuitable for modeling immiscible interfaces. Here, in this work, we discuss the origins of these issues in traditional LAD methods and propose modifications which enable the simulation of large density ratio and immiscible flows. The proposed method targets the artificial diffusion fluxes at gradients and ringing in the volume fraction, rather than the mass fraction in traditional methods, to consistently regularize large density ratio interfaces. Furthermore, the proposed method introduces an artificial bulk density diffusion term to enforce equilibrium conditions across interfaces. To address the challenge of modeling immiscible flows, a conservative diffuse interface term is incorporated into the formulation to ensure a finite interface thickness. Specific consideration is taken in the design of the method to ensure that these crucial properties are maintained for N -material flows. The effectiveness of the proposed method is demonstrated through a series of canonical test cases, and its accuracy is validated by comparison with experimental data on micro-bubble collapse in water. These results highlight the method’s robustness and its ability to overcome the limitations of traditional LAD approaches.

Artificial diffusivity↗

Modeling of fission gas diffusion and release for Gd 2 O 3 doped UO 2

Uranium dioxide (UO 2 ) is the primary nuclear fuel in light water reactors, and its excess neutronic reactivity can be controlled by adding burnable absorbers, such as Gd 2 O 3 . This burnable absorber has a large neutron absorption cross-section, lowering the high reactivity of the reactor's initial fuel load. However, there needs to be more understanding of how added Gd 2 O 3 influences the properties of UO 2 under irradiation. To understand the behavior of defects and fission gas in the UO 2 /Gd 2 O 3 system under irradiation, we use cluster dynamics modeling supported by density functional theory calculations. First, we calculate the formation energies of Gd point and cluster defects, and evaluate the temperature-dependent defect concentrations using the defect formation energies and entropies. We show that Gd is soluble in UO 2 , introducing a negative charge in the system. Using this information, we adapted the cluster dynamics code Centipede to model the influence of Gd on U self-diffusion and Xe diffusion in UO 2 with 10 wt% Gd 2 O 3 . Also, we analyzed the Xe diffusion as a function of Gd 2 O 3 concentration, showing that the Xe diffusivity is decreased, which means that the athermal diffusivity due to electronic stopping persists at higher temperatures. In conclusion, the decrease in Xe diffusion means that more Xe stays in the matrix, decreasing the Xe release, and lowering its influence of fission gas release on the thermomechanical properties of UO 2 .

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Understanding copper diffusion in CuInSe 2 with first-principles based atomistic and continuum models

We investigate the diffusion of copper in CuInSe 2 using thermodynamic and kinetic models based on density functional theory calculations, attempting to reconcile large differences in reported experimental diffusivities. We find that observations of rapid chemical diffusion can be explained by large thermodynamic factors, which we calculate using a compositionally constrained model of intrinsic point defect formation. We further characterize how copper diffusion coefficients depend on material synthesis conditions and exhibit their variation across the CuInSe 2 secondary phase diagram. In doing so, we identify stable off-stoichiometries that are dominated by either vacancy- or interstitial-mediated diffusion mechanisms. These results are employed in the development of a continuum reaction–diffusion model, which we use to simulate experimental depth profiles.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A Finite Difference informed Random Walk solver for simulating radiation defect evolution in polycrystalline structures with strongly inhomogeneous diffusivity

Diffusivity of species and defects on grain boundaries is usually several orders of magnitude larger than that inside grains. Such strongly inhomogeneous diffusivity requires prohibitively high computational demands for modeling microstructural evolution. Here, this paper presents a highly-efficient numerical solver, combining the Finite Difference method and Random Walk model, designed for accurately modeling strongly inhomogeneous diffusion within polycrystalline structures. The proposed solver, termed Finite Difference informed Random Walk (FDiRW), integrates a customized Finite Difference (cFD) scheme tailored for fast diffusion along thin grain boundaries represented by a single-layer of nodes. Numerical experiments demonstrate that the FDiRW solver achieves an impressive efficiency gain of 1560x compared to traditional Finite Difference methods while maintaining accuracy, making it feasible for personal computer machines to handle diffusional systems with strongly inhomogeneous diffusivity across static polycrystalline microstructures. The model has been successfully applied to simulate radiation defect evolution, showcasing its scalability to engineering scales in both length and time dimensions.

36 MATERIALS SCIENCE↗

Effect of lithium diffusion into Ga 2 O 3 thin films

The integration of lithium based compounds (e.g., Li:NiO/Ga 2 O 3 , LiGa 5 O 8 /Ga 2 O 3 ) in Ga 2 O 3 based pn-heterojunctions raises concerns about interface stability, i.e., Li diffusion effects on Ga 2 O 3 properties. In this work the ex-situ diffusion of Li is investigated in three different Ga 2 O 3 epilayers systems [(001) κ-Ga 2 O 3 and (−201) β-Ga2O3 heteroepitaxy on (001) α-Al 2 O 3 , and (010) β-Ga 2 O 3 homoepitaxy] at relevant temperatures for the synthesis / processing of Li-based epilayers. It is here experimentally demonstrated and quantified the Li diffusion in all the investigated Ga 2 O 3 epilayers systems and Li bulk (D Li,bulk ) and 2D defects (D Li,2D ) diffusion coefficients are provided. In the case of the (010) β-Ga 2 O 3 homoepitaxial layer (nominally free of structural defects), hybrid functional theory calculations foresee a diffusion mechanism mediated by Ga vacancies (VGa). Moreover, in the (010) β-Ga 2 O 3 homo-layer a significant effect on its functional properties (e.g., additional Raman vibrational modes, induced conductivity in an otherwise insulating sample) upon the Li-diffusion process is experimentally highlighted and tentatively related to the passivation of acceptor defects (i.e., formation of V Ga -nLi complexes).

Defects↗

Denoising diffusion algorithm for inverse design of microstructures with fine-tuned nonlinear material properties

Here we introduce a denoising diffusion algorithm to discover microstructures with nonlinear fine-tuned properties. Denoising diffusion probabilistic models are generative models that use diffusion-based dynamics to gradually denoise images and generate realistic synthetic samples. By learning the reverse of a Markov diffusion process, we design an artificial intelligence to efficiently manipulate the topology of microstructures to generate a massive number of prototypes that exhibit constitutive responses sufficiently close to designated nonlinear constitutive behaviors. To identify the subset of microcstructures with sufficiently precise fine-tuned properties, a convolutional neural network surrogate is trained to replace high-fidelity finite element simulations to filter out prototypes outside the admissible range. Results of this study indicate that the denoising diffusion process is capable of creating microstructures of fine-tuned nonlinear material properties within the latent space of the training data. More importantly, this denoising diffusion algorithm can be easily extended to incorporate additional topological and geometric modifications by introducing high-dimensional structures embedded in the latent space. Numerical experiments are conducted on the open-source mechanical MNIST data set (Lejeune, 2020). Consequently, this algorithm is not only capable of performing inverse design of nonlinear effective media, but also learns the nonlinear structure–property map to quantitatively understand the multiscale interplay among the geometry, topology, and their effective macroscopic properties.

42 ENGINEERING↗