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DOE OSTI2021

Fast Na diffusion and anharmonic phonon dynamics in superionic Na 3 PS 4

The design of new solid electrolytes (SEs) hinges on identifying and tuning relevant descriptors. Phonons describe the atomic dynamics in crystalline materials and provide a basis to encode possible minimum energy pathways for ion migration, but anharmonic effects can be large in SEs. Identifying and controlling the pertinent phonon modes coupled most strongly with ionic conductivity, and assessing the role of anharmonicity, could therefore pave the way for discovering and designing new SEs via phonon engineering. In this work, we investigate phonons in Na 3 PS 4 and their coupling to fast Na diffusion, using a combination of neutron scattering, ab initio molecular dynamics (AIMD), and extended molecular dynamics based on machine-learned potentials. We identify that anharmonic soft-modes at the Brillouin zone boundary of the anharmonically stabilized cubic phase constitute key phonon modes that control the Na diffusion process in Na 3 PS 4 . We demonstrate how these strongly anharmonic phonon modes enable Na-ions to hop along the minimum energy pathways. Further, the quasi-elastic neutron scattering (QENS) measurements, supplemented with ab initio and machine-learned molecular dynamics simulations, probe the Na diffusivity and diffusion mechanism. These results offer detailed microscopic insights into the dynamic mechanism of fast Na diffusion and provide an avenue to search for further Na solid electrolytes.

42 ENGINEERING↗

DOE OSTI2025

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↗

DOE OSTI2021

Quantifying Anionic Diffusion in 2D Halide Perovskite Lateral Heterostructures

Anionic diffusion strongly impacts the stability of halide perovskite materials, but it is still not well understood. Here, a quantitative investigation of in-plane thermally driven anionic inter-diffusion in a series of novel 2D and quasi-2D halide perovskites lateral heterostructures is reported. The calculated diffusion coefficients (D) reveal the inhibition of Br–I inter-diffusion with bulky π-conjugated organic cations compared with short-chain aliphatic organic cations. Furthermore, halide diffusion is found to be faster in quasi-2D (n > 1) than 2D perovskites (n = 1). The increment becomes less apparent as the “n” number increases, akin to the quantum confinement effect observed for band gaps. These trends are rationalized by molecular dynamics simulations of free energy barriers for halide diffusion that reveal mechanisms for suppressing diffusion. We report this work provides important fundamental insights on the anionic migration and diffusion process in halide perovskite materials.

2D materials↗

DOE OSTI2025

Computational diagnostics and characterization of combustion recession in diesel sprays

While low-temperature combustion (LTC) strategies have been found to mitigate nitrogen oxides and particulate matter emissions in diesel engines, studies have also associated LTC with an increase in unburnt hydrocarbons. With more recent studies on diesel after end-of-injection (AEOI), combustion recession is identified as a phenomenon where at near nozzle region, high-temperature ignition (HTI) combustion can propagate back to the nozzle tip consuming the unburnt hydrocarbons AEOI. Current literature has suggested that combustion recession is controlled by auto-ignition. However, high-fidelity simulations and detailed analysis of such a mechanism are missing. In this study, comprehensive Large Eddy Simulations of a reacting spray at “Spray A” conditions are performed, where detailed analysis of combustion recession concerning flame morphology and propagation modes are included. In particular, this study demonstrated for the first time that while combustion recession is mainly auto-ignition dominated (consistent with the literature), a cool flame was found to deflagrate towards the richer regions of the mixture, promoting mixing and increasing the mixture temperature. This leads to HTI kernels, which then grow and develop as deflagrative waves, therefore sustaining the combustion recession process. The study also detailed the extinction mechanism of combustion: the entrainment wave will overlean the near-nozzle mixtures, rendering it unable to support HTI, which leads to the extinction of the upstream flame AEOI in lower reactivity mixtures. Combustion recession is also observed to be contingent on the chemical and diffusion processes, even at low scalar dissipation rates. Finally, a new criterion for combustion recession based on chemical explosive mode is proposed and validated with previous combustion recession index to quantify the extent of HTI in near-nozzle mixtures AEOI. The newly developed metric combined with a previous experimentally-based metric can provide simple but valuable measurements of the degree and propensity of the upstream flame AEOI.

CEMA↗

DOE OSTI2026

NOCI-F Electronic Couplings in Assemblies of Indolonaphthyridine Molecules: From Dimers to the Full Stack

Key electronic processes related to molecular excitonic states of finite stacks of indolonaphthyridine molecules are analyzed via the non-orthogonal configuration interaction with fragments (NOCI-F) method. Indolonaphthyridine is an organic chromophore that can undergo several electronic photoexcitation-related intermolecular processes, such as exciton and electron transfer. The structures studied here are noncrystalline arrangements built as either ordered stacks of indolonaphthyridine or stacks extracted from molecular dynamics simulations including thermal disorder. Taking dimers or trimers from either model, we performed CASSCF and NOCI-F calculations to quantify the intermolecular electronic couplings governing singlet fission, excited singlet and triplet diffusion, and hole and electron diffusion processes. Also, comparing the results for the different models, we studied the effect of structural disorder and distortion on these couplings. Finally, we present a newly developed, advanced postanalysis tool. It takes the NOCI-F data as input to carry out a multifragment full Hamiltonian procedure that involves the complete stack, providing physical information not available from the dimer/trimer models, hence giving access to additional insight into the material’s properties.

coupling reactions↗

DOE OSTI2023

Giant interfacial spin Hall angle from Rashba-Edelstein effect revealed by the spin Hall Hanle process

The Rashba-Edelstein effect (REE), which generates interfacial spin polarization and subsequent spin current, is a compelling spin-charge conversion mechanism for spintronic applications, since it’s not limited by the elemental spin-orbit couplings. In this work we demonstrate REE at Pt/ferroelectric interfaces by showing a positive correlation between polarization and effective spin Hall angle in the recently elucidated spin Hall Hanle effects (SHHE), in which a Larmor precession of spin polarization in a diffusion process from the interface manifest as magnetoresistance and Hall effect. We show that REE leads to a large enhancement of the effective spin Hall angle of ferroelectric interface Pt/h-LuFeO 3 compared with that of Pt/Al 2 O 3 , without obvious differences in the spin relaxation time. Modeling using SHHEs involving REE as an additional source of interfacial polarization suggests that REE can lead to an interfacial spin Hall angle (0.4 ± 0.1) in Pt/h-LuFeO 3 that is one order of magnitude larger than the bulk value of Pt. Our results demonstrate that a ferroelectric interface can produce large spin-charge conversion and that SHHEs are a sensitive tool for characterizing interfacial spin-transport properties.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Atomistic modeling of metal–nonmetal interphase boundary diffusion

Atomistic computer simulations are applied to investigate the atomic structure, thermal stability, and diffusion processes in Al–Si interphase boundaries as a prototype of metal–ceramic interfaces in composite materials. Some of the most stable orientation relationships between the phases found in this work were previously observed in epitaxy experiments. Here, a non-equilibrium interface can transform to a more stable state by a mechanism that we call interface-induced recrystallization. Diffusion of both Al and Si atoms in stable Al–Si interfaces is surprisingly slow compared with diffusion of both elements in Al grain boundaries but can be accelerated in the presence of interface disconnections. A qualitative explanation of the sluggish interphase boundary diffusion is proposed. Atomic mechanisms of interphase boundary diffusion are similar to those in metallic grain boundaries and are dominated by correlated atomic rearrangements in the form of strings and rings of collectively moving atoms.

36 MATERIALS SCIENCE↗

DOE OSTI2020

DNA Reaction–Diffusion Attractor Patterns

Abstract Living systems can form and recover complex chemical patterns with precisely sized features in the ranges of tens or hundreds of microns. We show how designed reaction–diffusion processes can likewise produce precise patterns, termed attractor patterns, that reform their precise shape after being perturbed. We use oligonucleotide reaction networks, photolithography, and microfluidic delivery to form precisely controlled attractor patterns and study the responses of these patterns to different localized perturbations. Linear and “hill”‐shaped patterns formed and stabilized into shapes and at time scales consistent with reaction–diffusion models. When patterns were perturbed in particular locations with UV light, they reliably reformed their steady‐state profiles. Recovery also occurred after repeated perturbations. By designing the far‐from‐equilibrium dynamics of a chemical system, this study shows how it is possible to design spatial patterns of molecules that are sustained and regenerated by continually evolving towards a specific steady state configuration.

Dorsey, Phillip James↗

DOE OSTI2020

DNA Reaction–Diffusion Attractor Patterns

Living systems can form and recover complex chemical patterns with precisely sized features in the ranges of tens or hundreds of microns. We show how designed reaction-diffusion processes can likewise produce precise patterns, termed attractor patterns, that reform their precise shape after being perturbed. We use oligonucleotide reaction networks, photolithography and microfluidic delivery to form precisely controlled attractor patterns and study the responses of these patterns to different localized perturbations. Linear and ‘hill’-shaped patterns formed and stabilized into shapes and at time scales consistent with reaction-diffusion models. When patterns were perturbed in particular locations with UV light, they reliably reformed their steady state profiles. Recovery also occurred after repeated perturbations. As a result, by designing the far-from-equilibrium dynamics of a chemical system, this study shows how it is possible to design spatial patterns of molecules that are sustained and regenerated by continually evolving towards a specific steady state configuration

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Acceleration of Pd-V intermetallic diffusion by hydrogen

Vanadium-based membranes have great potential for hydrogen purification due to their perfect selectivity, high permeability, and relatively low cost. With appropriate surface cleaning, V efficiently permeates hydrogen at elevated temperature, but performance declines due to its affinity to absorb impurities. Here, the application of palladium thin films maintains a clean surface that catalyzes hydrogen dissociation and recombination. Hydrogen permeation in Pd-V-Pd membranes initially reach theoretical permeability, but declines due to Pd-V interdiffusion. The objective of this work was to quantify the intermetallic diffusion process as a function of temperature and ambient. Pd-V composites were subjected to various annealing treatments and characterized using Auger electron spectroscopy, X-ray diffraction, and energy dispersive X-ray spectroscopy, as well as correlated to measurements of membrane permeability. In an inert environment Pd-V interdiffusion was observable as low as 300 °C, and the diffusion coefficient had an activation energy of 44 kJ/mol. Furthermore, the presence of hydrogen at partial pressures > 10 kPa accelerated interdiffusion six-fold at T = 400 °C. Membrane performance degraded with an activation energy 75 kJ/mol, suggesting that intermetallic diffusion leads to both a loss of catalytic activity and as well as degradation of bulk permeability. These findings provide a baseline for evaluating hydrogen permeable interdiffusion barriers to overcome these challenges.

08 HYDROGEN↗

DOE OSTI2026

FunDiff: diffusion models over function spaces for physics-informed generative modeling

Recent advances in generative modeling-particularly diffusion models and flow matching-have been widely used for synthesizing discrete data such as images and videos. However, adapting these models to physical applications remains challenging, as the quantities of interest are continuous functions governed by complex physical laws. To address this, we introduce FunDiff, an efficient and robust framework for generative modeling in function spaces. FunDiff combines a latent diffusion process with a function autoencoder architecture to handle input functions with varying discretizations, generates continuous functions that can be evaluated at arbitrary locations, and seamlessly incorporate physical priors. These priors are enforced through architectural constraints or physics-informed loss functions, ensuring that generated samples satisfy fundamental physical laws. We theoretically establish minimax optimality guarantees for density estimation in function spaces, demonstrating that diffusion-based estimators achieve optimal convergence rates under suitable regularity conditions. We further demonstrate the practical effectiveness of FunDiff across diverse applications in fluid dynamics and solid mechanics. Empirical results indicate that our method can generate physically consistent samples with high fidelity to the target distribution, and exhibit robustness to noisy and low-resolution data.

Wang, Sifan [Yale University, New Haven, CT (Unite↗

DOE OSTI2022

Coupled Interfacial and Bulk Kinetics Govern the Timescales of Multiphase Ozonolysis Reactions

Chemical transformations in aerosols impact the lifetime of particle phase species, the fate of atmospheric pollutants, and both climate- and health-relevant aerosol properties. Timescales for multiphase reactions of ozone in atmospheric aqueous phases are governed by coupled kinetic processes between the gas phase, the particle interface, and its bulk, which respond dynamically to reactive consumption of O 3 . However, models of atmospheric aerosol reactivity often do not account for the coupled nature of multiphase processes. Herein, to examine these dynamics, we use new and prior experimental observations of aqueous droplet reaction kinetics, including three systems with a range of surface affinities and ozonolysis rate coefficients ( trans -aconitic acid (C 6 H 6 O 6 ), maleic acid (C 4 H 4 O 4 ), and sodium nitrite (NaNO 2 )). Using literature rate coefficients and thermodynamic properties, we constrain a simple two-compartment stochastic kinetic model which resolves the interface from the particle bulk and represents O 3 partitioning, diffusion, and reaction as a coupled kinetic system. Our kinetic model accurately predicts decay kinetics across all three systems, demonstrating that both the thermodynamic properties of O 3 and the coupled kinetic and diffusion processes are key to making accurate predictions. An enhanced concentration of adsorbed O 3 , compared to gas and bulk phases is rapidly maintained and remains constant even as O 3 is consumed by reaction. Multiphase systems dynamically seek to achieve equilibrium in response to reactive O 3 loss, but this is hampered at solute concentrations relevant to aqueous aerosol by the rate of O 3 arrival in the bulk by diffusion. As a result, bulk-phase O 3 becomes depleted from its Henry's law solubility. This bulk-phase O 3 depletion limits reaction timescales for relatively slow-reacting organic solutes with low interfacial affinity (i.e., trans-aconitic and maleic acids, with k rxn ≈ 10 3 -10 4 M -1 s -1 ), which is in contrast to fast-reacting solutes with higher surface affinity (i.e., nitrite, with k rxn ≈ 10 5 M -1 s -1 ) where surface reactions strongly impact the observed decay kinetics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2019

Real Time Monitoring of the Dynamic Intracluster Diffusion of Single Gold Atoms into Silver Nanoclusters

Alloying metal materials with heterometal atoms is an efficient way to diversify the function of materials, but in-depth understanding of the dynamic heterometallic diffusion inside the alloying materials is rather limited, especially at the atomic level. Here, we report the real-time monitoring of the dynamic diffusion process of a single gold (Au) atom into an atomically precise silver nanocluster (Ag NC), Ag 25 (MHA) 18 (MHA = 6-mercaptohexanoic acid), by using in situ UV–vis absorption spectroscopy in combination with mass and tandem mass spectrometry. We found that the Au heteroatom first replaces the Ag atom at the surface Ag 2 (MHA) 3 motifs of Ag 25 (MHA) 18 . After that, the Au atom diffuses into the surface layer of the icosahedral Ag 13 kernel and finally occupies the center of the alloy NCs to form the thermodynamically stable [email protected] 24 (MHA) 18 product. Density functional theory (DFT) calculations reveal that the key thermodynamic driving force is the preference of the Au heteroatom for the central site of alloy NCs. Furthermore, the real-time monitoring approach developed in this study could also be extended to other metal alloy systems to reveal the reaction dynamics of intracluster diffusion of heteroatoms, as well as the formation mechanisms of metal alloy nanomaterials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2018

Hybrid DFT investigation of the energetics of Mg ion diffusion in α-MoO 3

We report that rechargeable batteries that utilize divalent Mg ions as the charge carrier species can in principle achieve substantially greater volumetric energy densities than conventional Li-ion batteries. One significant impediment to the development of commercially viable Mg-ion batteries is the slow rate of Mg ion diffusion through otherwise promising cathode materials. Accurate prediction of the activation energies associated with this diffusion process using density functional theory (DFT) is especially challenging due to self-interaction errors intrinsic to DFT that lead to over-delocalization of the d-electrons. One effective but highly computationally demanding approach to reducing self-interaction errors is the use of hybrid functionals, which incorporate a fraction of exact Hartree–Fock exchange. In this work, we assess the effects of exact exchange on computed activation energies for ion diffusion in one potential cathode material, α-MoO 3 . In contrast to previous studies that primarily utilize non-hybrid functionals, we perform nudged elastic band calculations in which the nuclear coordinates are fully converged using both hybrid functionals and k-point sampling. Additionally, it is found that while non-hybrid functionals indicate the existence of thermodynamically accessible channels for bulk Mg ion diffusion in all three dimensions, hybrid functionals predict that some of these channels are largely inaccessible under typical charge/discharge conditions. Furthermore, it is demonstrated that certain commonly used approximations for incorporating the effects of Hartree–Fock exchange are inadequate for this system, including DFT+U calculations and the use of single-point hybrid calculations using atomic positions obtained using non-hybrid functionals.

25 ENERGY STORAGE↗

DOE OSTI2023

Diffusion Probabilistic Modeling for Video Generation

Denoising diffusion probabilistic models are a promising new class of generative models that mark a milestone in high-quality image generation. This paper showcases their ability to sequentially generate video, surpassing prior methods in perceptual and probabilistic forecasting metrics. We propose an autoregressive, end-to-end optimized video diffusion model inspired by recent advances in neural video compression. The model successively generates future frames by correcting a deterministic next-frame prediction using a stochastic residual generated by an inverse diffusion process. We compare this approach against six baselines on four datasets involving natural and simulation-based videos. We find significant improvements in terms of perceptual quality and probabilistic frame forecasting ability for all datasets.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Kaon Femtoscopy with Lévy-Stable Sources from $\sqrt{s_{NN}}$ = 200 GeV Au+Au Collisions at RHIC

Femtoscopy has the capacity to probe the space-time geometry of the particle-emitting source in heavy-ion collisions. In particular, femtoscopy of like-sign kaon pairs may shed light on the origin of non-Gaussianity of the spatial emission probability density. The momentum correlations between like-sign kaon pairs are measured in data recorded by the STAR experiment, from $\sqrt{s_{NN}}$ = 200 GeV Au+Au collisions at RHIC, BNL. Preliminary results hint at the possible existence of non-Gaussian, Lévy-stable sources, with the likely presence of an anomalous diffusion process in the signal for the identically charged kaon pairs so produced. More statistically significant studies at lower centre-of-mass energies may contribute to the search for the critical end point of QCD.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2020

Edge States Drive Exciton Dissociation in Ruddlesden–Popper Lead Halide Perovskite Thin Films

Efficient photovoltaic cells based on thin films of solution-processed 2D Ruddlesden–Popper hybrid perovskites (RPPs) represent an exciting breakthrough due to their enhanced tunability and chemical stability relative to those fabricated from 3D phases. However, reports of efficient charge separation and current collection are in apparent contradiction with the well-known enhancement of the exciton binding energy in multilayered halide perovskites, which should lower the device’s internal quantum efficiency and voltage. This controversy has led to various proposals for the electronic and physical structure of RPP thin films, including phase inhomogeneity as the driving force for exciton dissociation and transport. We address this apparent paradox in high-quality hot-cast RPP films by correlating ultrafast transient absorption spectroscopy with X-ray scattering measurements. We show that a hot-casting fabrication method produces highly phase pure n = 3 (BA) 2 (MA) n-1 Pb n I 3n+1 RPP structures. The high-phase purity and large grain sizes allow us to observe vertical transport of excitons via a diffusive process and allow us to determine that charge separation is primarily driven by dissociation at surface localized subgap electronic states. Furthermore, we analyze the differential absorption kinetics in films of varying thickness to directly determine that the excitonic diffusion constant is ~0.18 cm 2 s –1 . We propose that a surface localized structural distortion, observed using surface selective grazing incidence X-ray scattering measurements, is responsible for the creation of the surface localized defect states. We find that the density and spatial distribution of these defect states is a function of preparation conditions.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

DOE OSTI2022

Random Walks and Sticky Surfaces: Single-Molecule Measurements of Solute Diffusion in Ethanol/Water-Filled Anodic Alumina Nanopores

Nanoporous anodic aluminum oxide (AAO) membranes are now being explored for use in advanced chemical separations, including in the dehydration of biofuels such as ethanol. Optimization of membrane performance requires an in-depth understanding of how solvent mixtures and solutes behave under nanoconfinement. In this work, the diffusion of rhodamine B (RhB) dye through 10 nm and 20 nm AAO nanopores filled with a series of ethanol/water mixtures (0 - 33% water) is explored by fluorescence correlation spectroscopy (FCS). RhB was found to diffuse through the pores by two distinct mechanisms with mean diffusion coefficients, $D_f$ and $D_s$, reflecting fast and slow diffusive motions, respectively, with values that differ by nearly two orders of magnitude. Further, both $D_f$ and $D_s$ increased with pore size and were significantly smaller than $D_b$, the RhB diffusion coefficient in bulk liquid. Mean $D_f$ values follow a composition-dependent trend that closely mimics the viscosity dependence of $D_b$. Additional slowing of fast RhB diffusion is attributed to both hydrodynamic drag and electrostatic interactions with the nanopore surface. The mean $D_s$ values exhibit a different trend with increasing water content, revealing an increase in $D_s$ and a decrease in the contributions of slow diffusion to the observed dynamics. The fluorescence time transient data used in the analysis show that the slow diffusion process is strongly hindered and likely involves frequent adsorption of RhB to the pore surfaces. These results provide new insights into the detailed molecular-level mechanisms of mass transport in nanoporous AAO membranes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗