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At least 415 records · Page 23

IoT-based retrofit information diffusion in future smart communities

Community-scale building retrofits are not merely scaled-up versions of single-building retrofits. They involve complex challenges, such as reconciling individual interests with collective goals and managing the dynamic interplay between buildings through mechanisms like power grids and social connections. Internet of Things (IoT) connectivity holds the potential to leverage these interplays to balance individual and collective interests effectively in smart communities. One critical aspect of this interplay is information diffusion, which shapes how retrofit decisions spread among neighbors, influencing individual choices and ultimately impacting community-level retrofit outcomes. In other words, IoT-based smart devices automatically push tailored retrofit notifications to homeowners, which completely changes the format of information diffusion in the future. To investigate this influence by such information diffusion, the study used CityBES to simulate energy performance for different retrofits and applied an information diffusion model to analyze how decisions spread in a networked community of 192 buildings. The diffusion process was modeled on a weighted, directed network, capturing the dynamics of information flow and decision-making across 16 scenarios. Individual retrofit benefits were evaluated through payback years, while community-level retrofit outcomes were assessed using greenhouse gas (GHG) emission reductions. The results demonstrate that easier information diffusion among neighbors encourages households to prioritize retrofit measures that align with the majority’s optimal choices, even at the expense of individual financial benefits. In this case, such collective prioritization enhanced community-level retrofit performance, increasing GHG emission reductions by up to 29.4 %. However, this improvement came with trade-offs, as the average payback period for households extended by approximately 1.74 years. These findings highlight the potential of IoT-based information diffusion in future smart communities to coordinate individual interests with collective goals, ultimately accelerating community-level building retrofits.

Shu, Lei↗

Hydrogen diffusion induced dislocation transformations in a nickel superalloy

The diffusion of hydrogen in metals and alloys induces embrittlement that can adversely affect the structural properties. We examine the adsorption and diffusion of hydrogen in Inconel-718 (IN-718), and scrutinize the ensuing effects on the dislocation behavior in the alloy to elucidate the fundamental mechanisms of hydrogen-microstructure interactions from classical molecular simulations. Hydrogen adsorption increases with time until the surface saturates, while hydrogen diffusion exhibits strong temperature dependence, with diffusion coefficients converging above 1300 K regardless of the initial hydrogen concentration in the alloy. The diffusion in IN-718 is significantly sluggish than in pure Ni, Fe, or Cr, and is strongly impacted by hydrogen concentrations, resulting in an order of magnitude higher diffusion coefficient for hydrogen (10-14 m2/s relative to 10-15 m2/s) at high concentrations, especially below 600 K. Hydrogen diffusion coefficient varies from 10-12 to 10-15 m2/s in IN-718 depending on temperature (500–1400 K). More critically, our results reveal that increasing hydrogen concentration induces microstructural changes in the alloy, transforming perfect dislocations into stair-rods and Shockley partials, with higher temperatures favoring the latter. The results are significant for hydrogen fuel applications to gain insights into the materials chemistry for designing safer and more efficient propulsion systems, particularly in high-performance environments related to controlled hydrogen combustion applications.

Banerjee, Tanumoy↗

Simulation of radiation driven fission gas diffusion in UO 2 , ThO 2 and PuO 2

Below 1000 K it is thought that fission gas diffusion in nuclear fuel during irradiation occurs through atomic mixing due to radiation damage. Here we present a molecular dynamics (MD) study of Xe, Kr, Th, U, Pu and O diffusion due to irradiation. It is concluded that the ballistic phase does not sufficiently account for the experimentally observed diffusion. Thermal spike simulations are used to confirm that electronic stopping remedies the discrepancy with experiment and the predicted diffusivities lie within the scatter of the experimental data. Here, our results predict that the diffusion coefficients are ordered such that D* 0 > D* Kr > D* Xe > D* U . For all species >98.5% of diffusivity is accounted for by electronic stopping. Fission gas diffusivity was not predicted to vary significantly between ThO 2 , UO 2 and PuO 2 , indicating that this process would not change greatly for mixed oxide fuels.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Atomistic modeling of out-of-pile xenon diffusion by vacancy clusters in UO 2

We report that diffusion of Xe atoms in UO 2 fuel is important for nuclear fuel performance, and is enabled by interaction with U and O vacancies. Previous work using atomistic calculations based on density functional theory (DFT) and empirical potentials (EP) focused on the role of small vacancy clusters (Xe U2Oy , y = 0, 1, 2) for Xe transport, but the model predictions failed to reproduce the experimental observations by consistently underestimating Xe diffusivity. In this work, where we focused on out-of-pile conditions (i.e. in the absence of irradiation), we have explored two of the uncertainties associated with the model: the DFT methodology and the types of clusters considered. Additionally, we found that using the energy barriers obtained with GGA + U DFT allows to reconcile simulation results and experimental observations in the intrinsic regime (i.e. out-of-pile conditions). The Xe UO cluster is the preferred configuration at high temperature, while the mobile Xe U2O cluster takes over below 1720 K. The latter cluster is also the main contributor to Xe diffusion and good agreement is obtained with current models empirically fitted to experiments for diffusion at high temperature. A simple expression that captures most of Xe diffusivity is proposed, relying on Xe UO and Xe U2O clusters only. We also determined the out-of-pile concentration and diffusivity of extended clusters Xe U z O y , 3 ≤ x ≤ 9, and determined that these do not contribute significantly to the overall diffusivity under intrinsic conditions. However, we speculate that the Xe U 4 O 3 and Xe U 8 O 9 clusters, which have relatively low migration barrier, may play a role under irradiation conditions, because the radiation-induced enhanced vacancy concentration would rapidly increase the fraction of large Xe-vacancy clusters.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Diffusion behavior of lanthanide-additive compounds (Ce 4 Sb 3 , Ce 2 Sb, and CeTe) against HT9 and Fe

Antimony and tellurium have been identified as promising additives in metallic fuel, which can immobilize free-lanthanide fission products into stable intermetallic compounds in order to mitigate the fuel-cladding chemical interaction. Ce 4 Sb 3 , Ce 2 Sb, and CeTe are the primary compounds formed by Sb or Te with the lanthanide Ce present in the fuel. If these compounds are present at the outer periphery of the fuel, they will come in contact with and react with the cladding after the fuel swells. The present study investigates the reactivity of these compounds with two cladding materials, HT9 and Fe. The diffusion couple tests between these compounds and HT9 or Fe were conducted at 853 K. Scanning electron microscopy and transmission electron microscopy were used to analyze the morphology, microstructure, and phase distribution of the diffusion region. It was observed that the diffusion region thickness formed by the three compounds was significantly reduced compared to free Ce. Moreover, there was no observed diffusion or reaction between Ce 4 Sb 3 or Ce 2 Sb with either HT9 or Fe. CeTe was found to diffuse and react with HT9, forming Cr 3 Te 4 and TeFe at the diffusion region, as well as to penetrate into Fe, mainly by intergranular diffusion.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Raman Spectroscopy of Isotopic Water Diffusion in Ultraviscous, Glassy, and Gel States in Aerosol by Use of Optical Tweezers

The formation of ultraviscous, glassy, and amorphous gel states in aqueous aerosol following the loss of water results in nonequilibrium dynamics due to the extended time scales for diffusive mixing. Existing techniques for measuring water diffusion by isotopic exchange are limited by contact of samples with the substrate, and methods applied to infer diffusion coefficients from mass transport in levitated droplets requires analysis by complex coupled differential equations to derive diffusion coefficients. Here, we present a new technique that combines contactless levitation with aerosol optical tweezers with isotopic exchange (D 2 O/H 2 O) to measure the water diffusion coefficient over a broad range (D w ≈ 10 -12 -10 -17 m 2 s -1 ) in viscous organic liquids (citric acid, sucrose, and shikimic acid) and inorganic gels (magnesium sulfate, MgSO 4 ). For the organic liquids in binary and ternary mixtures, D w depends on relative humidity and follows a simple compositional Vignes relationship. In MgSO 4 droplets, water diffusivity decreases sharply with water activity and is consistent with predictions from percolation theory. These measurements show that, by combining micrometer-sized particle levitation (a contactless measurement with rapid mixing times) with an established probe of water diffusion, D w can be simply and directly quantified for amorphous and glassy states that are inaccessible to existing methods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Machine Learning Predictions of Simulated Self-Diffusion Coefficients for Bulk and Confined Pure Liquids

Diffusion properties of bulk fluids have been predicted using empirical expressions and machine learning (ML) models, suggesting that predictions of diffusion also should be possible for fluids in confined environments. The ability to quickly and accurately predict diffusion in porous materials would enable new discoveries and spur development in relevant technologies such as separations, catalysis, batteries, and subsurface applications. Here in this work, we apply artificial neural network (ANN) models to predict the simulated self-diffusion coefficients of real liquids in both bulk and pore environments. The training data sets were generated from molecular dynamics (MD) simulations of Lennard-Jones particles representing a diverse set of 14 molecules ranging from ammonia to dodecane over a range of liquid pressures and temperatures. Planar, cylindrical, and hexagonal pore models consisted of walls composed of carbon atoms. Our simple model for these liquids was primarily used to generate ANN training data, but the simulated self-diffusion coefficients of bulk liquids show excellent agreement with experimental diffusion coefficients. ANN models based on simple descriptors accurately reproduced the MD diffusion data for both bulk and confined liquids, including the trend of increased mobility in large pores relative to the corresponding bulk liquid.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Diffusion-Limited Kinetics in Reactive Systems

A proper representation of chemical kinetics is vital to understanding, modeling, and optimizing many important chemical processes. In liquid and surface phases, where diffusion is slow, the rate at which the reactants diffuse together limits the overall rate of many elementary reactions. Commonly, the textbook Smoluchowski theory is utilized to estimate effective rate coefficients in the liquid phase. On surfaces, modelers commonly resort to much more complex and expensive Kinetic Monte Carlo (KMC) simulations. Here, in this study, we extend the Smoluchowski model to allow the diffusing species to undergo chemical reactions and derive analytical formulas for the diffusion-limited rate coefficients for 3D, 2D, and 2D/3D interface cases. With these equations, we are able to demonstrate that when species react faster than they diffuse they can react orders of magnitude faster than predicted by Smoluchowski theory, through what we term “the reactive transport effect”. We validate the derived steady-state equations against particle Monte Carlo (PMC) simulations, KMC simulations, and non-steady-state solutions. Furthermore, using PMC and KMC simulations, we propose corrections that agree with all limits and the computed data for the 2D and 2D/3D interface steady-state equations, accounting for unique limitations in the associated derived equations. Additionally, we derive equations to handle couplings between diffusion-limited rate coefficients in reaction networks. We believe these equations should make it possible to run much more accurate mean-field simulations of liquids, surfaces, and liquid–surface interfaces accounting for diffusion limitations and the reactive transport effect.

Johnson, Matthew Sean↗

Dynamics and diffusion mechanism of low-density liquid silicon

A first-order phase transition from a high-density liquid to a low-density liquid has been proposed to explain the various thermodynamic anomies of water. It also has been proposed that such liquid–liquid phase transition would exist in supercooled silicon. Computer simulation studies show that, across the transition, the diffusivity drops roughly 2 orders of magnitude, and the structures exhibit considerable tetrahedral ordering. The resulting phase is a highly viscous, low-density liquid silicon. Investigations on the atomic diffusion of such a novel form of liquid silicon are of high interest. Here we report such diffusion results from molecular dynamics simulations using the classical Stillinger–Weber (SW) potential of silicon. We show that the atomic diffusion of the low-density liquid is highly correlated with local tetrahedral geometries. We also show that atoms diffuse through hopping processes within short ranges, which gradually accumulate to an overall random motion for long ranges as in normal liquids. There is a close relationship between dynamical heterogeneity and hopping process. We point out that the above diffusion mechanism is closely related to the strong directional bonding nature of the distorted tetrahedral network. Here, our work offers new insights into the complex behavior of the highly viscous low density liquid silicon, suggesting similar diffusion behaviors in other tetrahedral coordinated liquids that exhibit liquid–liquid phase transition such as carbon and germanium.

36 MATERIALS SCIENCE↗

Diffusion and photon-stimulated desorption of CO on TiO2(110)

Thermal diffusion of CO adsorbed on rutile TiO2(110) was studied in the 20 - 110 K range using photon-stimulated desorption (PSD), temperature programmed desorption (TPD) and scanning tunneling microscopy. During UV irradiation, CO desorbs from certain photoactive sites (e.g. oxygen vacancies). This phenomenon was exploited to study CO thermal diffusion in three steps: first empty these sites during a first irradiation cycle, then replenish them with CO during annealing, and finally probe the active site occupancy in the second PSD cycle. The PSD and TPD experiments show that the CO diffusion rate correlates with the CO adsorption energy – stronger binding corresponds to slower diffusion. Increasing the CO coverage or hydroxylation of the surface decreases the CO binding and increases the CO diffusion rate. Relative to the reduced surface, the CO adsorption energy increases and the diffusion decreases on the oxidized surface. The CO diffusion kinetics can be modeled satisfactorily as an Arrhenius process with a “normal” prefactor (i.e. = 1012 s 1) and a Gaussian distribution of activation energies where the peak of the distribution is ~0.28 eV and the full width at half maximum (FWHM) is 0.1 eV at the lowest coverages. The observations are consistent with a significant electrostatic component of the CO binding energy on the TiO2(110) surface which is affected by changes in the surface dipole and dipole-dipole interactions.

Petrik, Nikolay G.↗

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↗

Evidence for percolation diffusion of cations and reordering in disordered pyrochlore from accelerated molecular dynamics

Diffusion in complex oxides is critical to ionic transport, radiation damage evolution, sintering, and aging. In complex oxides such as pyrochlores, anionic diffusion is dramatically affected by cation disorder. However, little is known about how disorder influences cation transport. Here, we report results from classical and accelerated molecular dynamics simulations of vacancy-mediated cation diffusion in Gd 2 Ti 2 O 7 pyrochlore, on the microsecond timescale. We find that diffusion is slow at low levels of disorder, while higher disorder allows for fast diffusion, which is then accompanied by antisite annihilation and reordering, and thus a slowing of cation transport. Cation diffusivity is therefore not constant, but decreases as the material reorders. We also show that fast cation diffusion is triggered by the formation of a percolation network of antisites. This is in contrast with observations from other complex oxides and disordered media models, suggesting a fundamentally different relation between disorder and mass transport.

74 ATOMIC AND MOLECULAR PHYSICS↗

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↗

A model for the compositions of non-stoichiometric intermediate phases formed by diffusion reactions, and its application to Nb 3 Sn superconductors

In this work we explore the compositions of non-stoichiometric intermediate phases formed by diffusion reactions: a mathematical framework is developed and tested against the specific case of Nb 3 Sn superconductors. In the first part, the governing equations for the bulk diffusion and interphase interface reactions during the growth of a compound are derived, numerical solutions to which give both the composition profile and growth rate of the compound layer. The analytic solutions are obtained with certain approximations made. In the second part, we explain an effect that the composition characteristics of compounds can be quite different depending on whether it is the bulk diffusion or grain boundary diffusion that dominates in the compounds, and that “frozen” bulk diffusion leads to unique composition characteristics that the bulk composition of a compound layer remains unchanged after its initial formation instead of varying with the diffusion reaction system; here the model is modified for the case of grain boundary diffusion. Lastly, we apply this model to the Nb 3 Sn superconductors and propose approaches to control their compositions.

36 MATERIALS SCIENCE↗

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↗

Energetics, diffusion, and magnetic properties of cobalt atom in a monolayer graphene: An ab initio study

We use ab initio methods to study the binding, diffusion, and magnetic properties of cobalt atom embedded in graphene vacancies. We investigate the diffusion of Co-monovacancy (Co-MV) and Co-divacancy (Co-DV) defect complexes, and determine the minimum energy path (MEP), as well as the activation energy barrier of migration. We obtained similar activation energy barriers, of ∼5.8 eV, for Co-MV and Co-DV diffusion, respectively. Our calculations also suggest that, at electron–irradiation energy of 200 keV as used in a related experiment, the maximum energy transfer to the Co atom, of approximately 9.0 eV is sufficiently high to break metal-carbon bonding. The incident electron energy is also high enough to displace graphene's carbon atoms from their lattice positions. The breaking of metal-carbon bonding and the displacement of graphene atoms may act to facilitate the migration of Co. We conclude therefore that the detrapping and diffusion of cobalt as observed experimentally is likely to be radiation-induced, similar to what has been observed for Au and Fe in electron-irradiated graphene. Furthermore, we show that Co migration in graphene is such that its magnetic moment varies along the diffusion path. The magnetic moment of Co is consistently higher in Co-DV diffusion when compared to that of Co-MV diffusion.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗