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DOE OSTI2025

Investigating Morphology and Diffusion in Simulations of Precise Anion-Conducting Polymers

Using atomistic molecular dynamics simulations, we investigate the morphology and transport properties of a new class of polymers which are functionalized with quaternary ammonium groups for use as anion exchange membranes. The polymers are precision polyolefins with either a trimethylammonium (p5CNMe3) or a dimethyl-hexyl ammonium (p5CNMe2Hx) pendant group at every fifth carbon along a polyethylene backbone. Simulations are performed at hydration levels of 5, 10, 15, and 20 water molecules per ammonium group. The hydrated polymers form nanoscale, percolated hydrophilic domains (water channels) in the hydrophobic polymer matrix that become wider with increasing water content. Water and hydroxide anion diffusion coefficients also increase with increasing water content. The morphology of the water domains is similar in both polymers, while the diffusion coefficients are somewhat lower in p5CNMe2Hx at fixed water content. Furthermore, the diffusion coefficients in both polymers fall on the same curve as a function of the fractal dimension of the percolated water channels, which appears to be a useful scalar measure of the effects of the nanoscale morphology on water and hydroxide anion transport.

Anion exchange membrane↗

DOE OSTI2025

Permanent Nanobubbles in Water: Liquefied Hollow Carbon Spheres Break the Limiting Diffusion Current of Oxygen Reduction Reaction

Porous liquids have traditionally been designed with sterically hindered solvents. Alternatively, recent efforts rely on dispersing microporous frameworks in simpler solvents like water. Here we report a unique strategy to construct macroporous water by selectively incorporating hydrophilicity on the surfaces of hydrophobic hollow carbon spheres (HCS). Specifically, we show that the stable dispersion surface ionized HCS in water while retaining the inherent porosity. The electrocatalytic conversion of small gas molecules in aqueous electrolytes is limited by the concentration and diffusion rates of gas molecules in water. In this case, macroporous water exhibited 6 times gas uptake compared to nonporous (pure) water. Furthermore, by leveraging the high gas capacity and enhanced diffusion kinetics, the limiting diffusion current of oxygen reduction reaction (ORR) in macroporous water is 2 times that in nonporous water, offering promising prospects for sustainable energy conversion technologies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Observation of a Knotted Electron Diffusion Region in Earth's Magnetotail Reconnection

Magnetic reconnection is a fundamental plasma process that alters the magnetic field topology and releases magnetic energy. Most numerical simulations and spacecraft observations assume a two‐dimensional diffusion region, with the electron diffusion region (EDR) embedded in the same plane as the ion diffusion region (IDR) and a uniform guide field throughout. Using observations from Magnetospheric Multiscale mission, we report a non‐coplanar, knotted EDR in Earth's magnetotail current sheet. The reconnection plane of the knotted EDR deviates by approximately 38° from that of the IDR, with the guide field exhibiting both a 38° directional shift and a twofold increase in amplitude. Moreover, the Hall magnetic field is bipolar in the EDR but quadrupolar in the IDR, indicating different Hall current structures at electron and ion scales. These observations highlight the importance of three‐dimensional effects and illustrate the complexity of multiscale coupling between the EDR and IDR during reconnection studies.

diffusion region↗

DOE OSTI2025

Diffusion-mediated passing of molecular species in linear nanopores constrained by orientational alignment

For diffusion-mediated catalytic conversion reactions in materials with narrow linear nanopores, e.g., mesoporous silica MCM-41, a key parameter is the propensity for product species to be able to pass reactant species and thus to efficiently exit the pore. For elongated species, this can require orientational alignment with the pore axis. In this work, we perform benchmark analyses for such solution-phase systems where one of these species is elongated in order to quantify the dependence of this passing propensity, P, on pore diameter and on the rotational diffusion coefficient, Dr, of the elongated species. In particular, we consider the passing of a spherical and an elongated spherocylindrical shaped species in a cylindrical pore in an implicit solvent, where these species cannot overlap. Passing is mediated by diffusive Brownian motion of these species as described by strongly damped Langevin dynamics. We quantify scaling of P for pore width just above the threshold where passing is sterically blocked, and also reveal a significant decrease in P for lower Dr. We also consider the dependence of P on the aspect ratio of the elongated species and obtain an exact result in the limiting regime of large aspect ratio.

Brownian motion↗

DOE OSTI2026

Atomistic modeling of lanthanide diffusion in refractory body-centered cubic molybdenum

Lanthanide fission products can strongly interact with candidate cladding alloys, but their transport properties in refractory metals remain poorly understood. Here, in this work, we investigate the atomic-scale diffusion behavior of La, Ce, Pr, and Nd in body-centered cubic (bcc) molybdenum, a potential candidate for advanced nuclear cladding. Self-consistent mean-field transport modeling is performed to evaluate the fission product transport and vacancy mobility, informed by first-principles and nudged elastic band calculations of vacancy formation energies, migration barriers, and solute–vacancy binding characteristics. Compared with bcc Fe, lanthanide solutes in bcc Mo exhibit slower tracer diffusion due to higher vacancy formation and migration energies. Furthermore, the calculations reveal that the influence of fission products on migration barriers in bcc Mo are not as extensive in range compared to bcc Fe. Among the studied lanthanides, La exhibits the strongest vacancy binding while also being the fastest diffuser in Mo. These findings highlight how refractory bcc alloys can reduce fission product infiltration, offering valuable insight into the development of durable cladding systems for advanced reactors.

36 - MATERIALS SCIENCE↗

DOE OSTI2025

Integral X-ray diffuse scattering for studying irradiation-induced dislocation loops in single crystals

Numerical diffuse scattering cross-section calculations are used to establish a rigorous basis for determining the concentration and size distribution of dislocation loops in irradiated single crystals from integral X-ray diffuse scattering (XRDS) measurements. Differential XRDS intensities for prismatic {111} type dislocation loops are numerically calculated as a function of loop radius R and wavevectors q relative to Bragg reflections in tungsten. The results show the well known 1/q 2 Huang scattering form at small q that transitions to a ∼1/q 4 dependence associated with the Stokes–Wilson approximation for q ≳ 1/R. More importantly, they show further that the 1/q 4 falloff is not the asymptotic large-q form of the diffuse scattering for small loops (R < 200 Å) as has often been assumed. Rather, for loop sizes as small as R ≃ 5 Å with strong curvature, the calculations show definitively that the scattering transitions to a robust 1/q 5 falloff at larger q that arises due to the local strains near the dislocation core defining the circumference of the dislocation loops. The presence of this 1/q 5 asymptotic form for both small and large loops is experimentally confirmed using an integral XRDS measurement around the 110 reflection on self-ion-irradiated tungsten combined with numerically calculated integral XRDS cross-sections. Accordingly, the historical two-region theoretical treatment of the cross-sections for integral XRDS is extended to a three-region model that has direct sensitivity to the (first-moment) dislocation line lengths of dislocation loops. In conclusion, these developments enable the use of both numerical and analytically modeled cross-sections to make accurate integral XRDS determinations of dislocation loop sizes and concentrations using modest-intensity laboratory X-ray sources.

42 ENGINEERING↗

DOE OSTI2025

First-Principles Studies of Tritium Species Diffusivity Across the Interfaces of Ni-NiZr Alloy-Zircaloy-4

A tritium producing assembly, also known as tritium producing burnable absorber rods (TPBARs), consists of a metal getter tube located between the cladding and γ-LiAlO2 pellets. The metal getter tube is composed of a nickel (Ni) layer coated on Zircaloy-4. The getter assembly is used to capture tritium (3H) species (mainly 3H2 and 3H2O) generated from γ-LiAlO2 pellets during irradiation. Exploring 3H species (3H2, 3H2O) dissociation on the Ni surface and diffusion in the Ni layer and across the interface of Ni-plated Zircaloy-4 getters can provide insights on tritium transport and retention in the pellets and the getter materials. . In FY25, based on the ideal interface model of Ni-Zircaloy-4 generated in FY24, we will further explore the diffusion pathways of 3H across such Ni-ZrNi-alloy layer-Zircalory-4 interfaces under different conditions, including with oxide/hydroxide clusters on the Ni layer, and impurities located in ZrNi-alloy and Zircalory-4 layers. Due to the size limitation of DFT simulation, we will separate the 3-layer system into 3 sub-systems: Ni-ZrNi interface, ZrNi alloy layer, ZrNi-alloy-Zircaloy-4 interface, and simulate the diffusion barriers for tritium.

diffusion barrier↗

DOE OSTI2026

Effect of Magnetic Islands on Neoclassical Heat Diffusivity in a Global Tokamak Simulation

Resonant magnetic perturbations (RMPs) alter magnetic field topology via island formation and can modify core transport in toroidal fusion devices. Using the global gyrokinetic particle‐in‐cell code XGC‐S, originally developed for stellarator geometries, we quantify how island topology affects neoclassical heat transport in a circular tokamak with ($m,n$) = (5,2) RMP‐induced islands. Electron radial heat diffusivity exhibits a two‐peak structure with a dominant enhancement near the O/X‐point region and a secondary peak at the outer island boundary, whereas ion transport remains close to the neoclassical prediction. The observed electron diffusivity is strongly enhanced over the neoclassical baseline but remains well below the Rechester–Rosenbluth estimate, consistent with the non‐ergodic character of the island topology. The density dependence of diffusivity is weaker inside the islands than outside, indicating the presence of topology‐driven transport channels that do not depend strongly on collisionality. Two‐dimensional heat flux maps reveal an up–down antisymmetric structure at the island separatrices consistent with magnetic gradient and curvature drift effects, in contrast to the symmetric temperature flattening inside the islands. These results identify topology‐dependent avenues for electron heat transport in RMP‐perturbed cores and suggest regimes in which island geometry, rather than collisions alone, governs radial transport.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

Modeling inter‐reader variability in clinical target volume delineation for soft tissue sarcomas using diffusion model

Abstract Background Accurate delineation of the clinical target volume (CTV) is essential in the radiotherapy treatment of soft tissue sarcomas. However, this process is subject to inter‐reader variability due to the need for clinical assessment of risk and extent of potential microscopic spread. This can lead to inconsistencies in treatment planning, potentially impacting treatment outcomes. Most existing automatic CTV delineation methods do not account for this variability and can only generate a single CTV for each case. Purpose This study aims to develop a deep learning‐based technique to generate multiple CTV contours for each case, simulating the inter‐reader variability in the clinical practice. Methods We employed a publicly available dataset consisting of fluorodeoxyglucose positron emission tomography (FDG‐PET), x‐ray computed tomography (CT), and pre‐contrast T1‐weighted magnetic resonance imaging (MRI) scans from 51 patients with soft tissue sarcoma, along with an independent validation set containing five additional patients. An experienced reader drew a contour of the gross tumor volume (GTV) for each patient based on multi‐modality images. Subsequently, two additional readers, together with the first one, were responsible for contouring three CTVs in total based on the GTV. We developed a diffusion model‐based deep learning method that is capable of generating arbitrary number of different and plausible CTVs to mimic the inter‐reader variability in CTV delineation. The proposed model incorporates a separate encoder to extract features from the GTV masks, leveraging the critical role of GTV information in accurate CTV delineation. Results The proposed diffusion model demonstrated superior performance with the highest Dice Index (0.902 compared to values below 0.881 for state‐of‐the‐art models) and the best generalized energy distance (GED) (0.209 compared to values exceeding 0.221 for state‐of‐the‐art models). It also achieved the second‐highest recall and precision metrics among the compared ambiguous image segmentation models. Results from both datasets exhibited consistent trends, reinforcing the reliability of our findings. Additionally, ablation studies exploring different model structures and input configurations highlighted the significance of incorporating prior GTV information for accurate CTV delineation. Conclusions The proposed diffusion model successfully generates multiple plausible CTV contours for soft tissue sarcomas, effectively capturing inter‐reader variability in CTV delineation.

Dong, Yafei [Yale Biomedical Imaging Institute Yal↗

DOE OSTI2025

Integration of hydrophobic gas diffusion layers for zero-gap electrolyzers to enable highly energy-efficient CO 2 electrolysis to C 2 products

Electrochemical CO 2 reduction (eCO2R) is an attractive route for mitigating global CO 2 emissions while producing value-added chemicals. Ethylene is one product of eCO2R and is an essential industrial precursor with a global market of $230 billion. The large-scale implementation of C 2 H 4 -selective CO 2 electrolyzers remains challenging because of low energy efficiencies. In this work, we develop the design principles necessary for incorporating an expanded polytetrafluoroethylene (ePTFE) electrode into a zero-gap electrolyzer while simultaneously developing an integrated electrical front contact that reduces the ohmic resistances inherent to electrically insulating gas diffusion layers. By co-designing the catalyst layer, gas diffusion medium, and operating conditions for a zero-gap ePTFE gas diffusion electrode (GDE), we achieved a full-cell voltage of 2.5 V at 200 mA cm −2 at 25 cm 2 geometric area cell with Faradaic efficiencies of 48% for ethylene and 40% for ethanol. This work highlights strategies for developing a scalable, stable, and highly energy-efficient eCO2R for C 2 products.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Stable low diffusion flux splitting schemes on unstructured meshes

Shock instabilities are shown to manifest in modern low-diffusion flux-vector splitting (FVS) schemes when used on unstructured meshes, or situations where shocks do not align with the mesh lines. These instabilities occur irrespective of the Mach number of the shock. Three types of dissipative mechanisms that suppress these instabilities are presented. These mechanisms are carefully designed in order to affect only problematic regions of the flux-splittings. The AUSM + and LDFSS schemes are stabilized using the proposed modifications. It is shown that the added dissipation improves the shock behavior of AUSM and LDFSS on unstructured meshes. It is also shown that the AUSM + -up scheme is prone to the “carbuncle” instability, a specific type of shock instability, when used on unstructured meshes. The modifications proposed in this work do not lead to carbuncle instabilities for the problems considered here. Furthermore, the modified schemes are shown to satisfy certain properties that are crucial for accurate shear layer computations, such as stationary contact preservation. Using benchmark problems, it is demonstrated that despite the diffusion added for stabilization, these schemes are not overly diffusive. Furthermore, due to these advantages, the modified FVS schemes presented here are promising candidates for high-speed compressible flow computations on unstructured meshes.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Multinuclear PFGSTE NMR description of 39 K, 23 Na, 7 Li, and 1 H specific activation energies governing diffusion in alkali nitrite solutions

While pulsed field gradient stimulated echo nuclear magnetic resonance (PFGSTE NMR) spectroscopy has found widespread use in the quantification of self-diffusivity for many NMR-active nuclei, extending this technique to uncommon nuclei with unfavorable NMR properties remains an active area of research. Potassium-39 ( 39 K) is an archetypical NMR nucleus exhibiting an unfavorable gyromagnetic ratio combined with a very low Larmor frequency. Despite these unfavorable properties, this work demonstrates that 39 K PFGSTE NMR experiments are possible in aqueous solutions of concentrated potassium nitrite. Further, analysis of the results indicates that 39 K NMR diffusometry is feasible when the nuclei exhibit spin–lattice and spin–spin relaxation coefficients on the order of 60–100 ms and 50–100 ms, respectively. The diffusivity of 39 K followed Arrhenius behavior, and comparative 23 Na, 7 Li, and 1 H PFGSTE NMR studies of equimolal sodium nitrite and lithium nitrite solutions led to correlations between the enthalpy of hydration with the activation energy governing self-diffusion of the cations and also of water. Realizing the feasibility of 39 K PFGSTE NMR spectroscopy has a widespread impact across energy sciences because potassium is a common alkali element in energy storage materials and other applications.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2024

Measuring thermal diffusivity and gap conductance in uranium nitride and Zircaloy relevant for microreactor applications

Heat transfer across nuclear fuels and structural interfaces is an important factor for evaluating the performance of nuclear power systems. Specifically, heat generated as nuclear fuel fissions must be transported through the cladding material and through the reactor to reach the steam turbine for power generation. As new microreactor designs emerge, maximizing the efficiency of this heat transfer process becomes crucial to make them commercially viable. This article examines thermal diffusivity and gap conductance in uranium nitride (UN) fuel and Zircaloy-4 (Zry4) cladding using light flash analysis (LFA). Thermal diffusivity measurements were made on monolithic UN pellets and Zry4 exposed to carbon at peak operating temperatures of microreactors and show that carbon ingress has a minimal effect on thermal diffusivity when compared with identical materials not exposed to carbon. Evaluation of gap conductance at the UN-Zry4 interface was done using one-dimensional two-layer thermal transport models as a function of applied pressure. Here the results show that increasing pressure on the UN-Zry4 interface leads to gains in gap conductance per unit area in fuel-cladding assemblies at microreactor operating temperatures. While many other variables are expected to influence UN-Zry4 interfacial gap conductance (e.g. contact surface roughness, porosity, localized heating, environmental gas pressure), the work offers a demonstration of using a conventional LFA apparatus to determine this parameter at elevated temperatures.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2026

Room temperature sodium diffusion in sodium iron phosphate investigated with neutron scattering

Sodium iron phosphate, Na x FePO 4 , is currently one of the most promising cathode materials for sodium ion batteries. Here we employ a systematic approach using three neutron scattering techniques to investigate temperature dependent properties with a focus on the charge transfer processes. Two distinct Na + diffusive motions are observed with quasielastic neutron scattering, including room temperature motion. These processes correspond to rapid double jumps through extrinsic vacancy sites of ∼6 Å along with the more fundamental nearest neighbor jumps of 3.1 Å. Experimental observations of room temperature ionic diffusion are highly desirable, as the diffusion pathways are naturally well suited for efficient transport. Inelastic neutron scattering was used to probe the vibrational density of states that assist in the ionic and electronic (polaronic) transport processes, which are further supported with density functional theory. Neutron diffraction examines the disordering of the sodium sublattice upon transition to the solid-solution phase, which is believed to enhance the overall kinetics during sodium insertion/extraction. Finally, 57 Fe Mössbauer spectroscopy measurements probes polaron hopping and the local structural evolution that modifies the electron density surrounding the redox active iron sites. This study sheds light on the temperature induced atomic scale dynamics that occur in olivine Na x FePO 4 .

Novak, Eric [Swarthmore College, Swarthmore, PA (U↗

DOE OSTI2024

Intermittent cluster dynamics and temporal fractional diffusion in a bulk metallic glass

Glassy solids evolve towards lower-energy structural states by physical aging. This can be characterized by structural relaxation times, the assessment of which is essential for understanding the glass’ time-dependent property changes. Conducted over short times, a continuous increase of relaxation times with time is seen, suggesting a time-dependent dissipative transport mechanism. By focusing on micro-structural rearrangements at the atomic-scale, we demonstrate the emergence of sub-diffusive anomalous transport and therefore temporal fractional diffusion in a metallic glass, which we track via coherent x-ray scattering conducted over more than 300,000 s. At the longest probed decorrelation times, a transition from classical stretched exponential to a power-law behavior occurs, which in concert with atomistic simulations reveals collective and intermittent atomic motion. Our observations give a physical basis for classical stretched exponential relaxation behavior, uncover a new power-law governed collective transport regime for metallic glasses at long and practically relevant time-scales, and demonstrate a rich and highly non-monotonous aging response in a glassy solid, thereby challenging the common framework of homogeneous aging and atomic scale diffusion.

42 ENGINEERING↗

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 OSTI2026

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

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

Atomistic models↗

DOE OSTI2025

First-principles investigation of the resistive switching energetics in monolayer MoS 2 : insights into metal diffusion and adsorption

A deeper understanding of resistive switching (RS) in 2D materials is essential for advancing neuromorphic computing. The Dissociation-Diffusion-Adsorption (DDA) model offers a useful framework for probing RS mechanisms in non-volatile memory (NVM) and in-memory computing. We have employed first-principles density functional theory (DFT) to explore dissociation, diffusion, and adsorption phenomena within the DDA model, focusing on the interactions between exemplary metal atoms (Au, Ag, Cu) and monolayer MoS 2 . Nudged elastic band (NEB) calculations evaluated diffusion barriers in pristine and sulfur-vacancy MoS 2 . Charged systems were modeled to assess the impact of applied bias on migration pathways. We also examined metal dissociation from bulk electrodes and adsorption at S vacancies. Ag/MoS 2 shows the lowest dissociation barrier (~0.034 eV), while Au and Cu exhibit similar values (~0.32 eV). These insights highlight Ag as a promising candidate for low-energy RS applications and provide guidance for optimizing switching efficiency in 2D memory devices.

Atomistic models↗