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At least 73 records · Page 4

Influence of Thermal Treatment on Preceramic Polymer Grafted Nanoparticle Network Formation: Implications for Thermal Protection Systems and Aerospace Propulsion Components

Preceramic polymer grafted nanoparticles (PCP GNPs) offer potential advantages in the production of polymer-derived ceramic composites compared to neat preceramic polymers (PCPs), such as reduced thermal shrinkage and increased char yield. In comparison to traditional composites (particles + free polymer), PCPs avoid issues of compatibility, agglomeration, and phase separation during processing and provide routes to control nanoparticle arrangement. Prior literature has established that the conversion efficiency of PCPs and PCP GNPs to ceramics and ceramic composites is linked to the thermal pretreatment of these precursor polymers (e.g., curing). In this paper, we investigate the material transformations that occur when exposing PCP GNPs to a low-temperature thermal treatment (≤250 °C) prior to pyrolysis. The PCP GNPs explored in this study possessed silica nanoparticle cores but were distinct in their PCP coronas, having poly(1,1-dimethylpropylsilane) (allyl-GNP)- or poly(1,1-dimethylbenzylethylsilane) (styryl-GNP)-grafted polymers. After undergoing low-temperature thermal treatment, these PCP GNPs exhibited increased char yield at 800 °C; however, unlike commercial PCPs (e.g., allylhydridopolycarbosilane (SMP-10)), obvious cross-linkable sites are not present in the PCP corona structure. Differential scanning calorimetry, oscillatory rheology, and X-ray photon correlation spectroscopy were utilized to elucidate the thermally induced material changes in the allyl- and styryl-GNPs. Thermally induced changes to the structure and behavior of the PCP GNPs were determined to be linked to the chemical structure of the grafted polycarbosilane chains. Styryl-GNPs experienced a curing event between 180 and 250 °C, effecting the formation of a network, which contributed to char yield improvement (at 800 °C). The nanoscale dynamics of this material also shows a transition from diffuse behavior to ballistic behavior because of the cross-linking event. Conversely, the allyl-GNPs did not exhibit a curing event under heat treatment but did show an increase in thermally induced physical cross-linking. The allyl-GNP physical network is stronger after the first cycle of thermal treatment, and it is considered that this contributed to the improvement in char yield post thermal treatment. The advancements in the understanding of the cross-linking behavior of these hybrid materials are expected to advance the application of these materials to turbine engine, advanced friction, and heat-shielding components.

36 MATERIALS SCIENCE↗

Reversible to irreversible transitions for ac driven skyrmions on periodic substrates

Abstract Using atomistic simulations, we investigate the dynamical behavior of magnetic skyrmions in dimer and trimer molecular crystal arrangements, as well as bipartite lattices at 3/2 and 5/2 fillings, under ac driving over a square array of anisotropy defects. For low ac amplitudes, at all fillings reversible motion appears in which the skyrmions return to their original positions at the end of each ac drive cycle and the diffusion is zero. We also identify two distinct irreversible regimes. The first is a translating regime in which the skyrmions form channels of flow in opposing directions and translate by one substrate lattice constant per ac drive cycle. The translating state appears in the dimer and trimer arrangements, and produces pronounced peaks in the diffusivity in the direction perpendicular to the external drive. For larger ac amplitudes, we find chaotic irreversible motion in which the skyrmions can randomly exchange places with each other over time, producing long-time diffusive behavior both parallel and perpendicular to the ac driving direction.

36 MATERIALS SCIENCE↗

Compressive creep behavior of alloys based on B2 FeAl

Alloys based on FeAl are attractive alternate materials for environmental resistance at intermediate temperatures. Addition of small amounts of Nb, Hf, Ta, Mo, Zr, and B were shown to improve the compressive creep of this alloy at 1100 K. Boron, in particular, was found to have a synergistic effect along with Zr in providing properties substantially better than the binary alloy. This improvement seems to be related to the higher activation energy found for this alloy, suggesting a modification in the diffusion behavior due to the alloying additions.

Mantravadi, N.↗

Compressive creep behavior of alloys based on B2 FeAl

Alloys based on FeAl are attractive alternative materials for environmental resistance at intermediate temperatures. Addition of small amounts of Nb, Hf, Ta, Mo, Zr, and B were shown to improve the compressive creep of this alloy at 1100 K. Boron, in particular, was found to have a synergistic effect along with Zr in providing properties substantially better than the binary alloy. This improvement seems to be related to the higher activation energy found for this alloy, suggesting a modification in the diffusion behavior due to the alloying additions.

Mantravadi, N.↗

Li-Ion Diffusion Correlations in LiAlGeO 4 : Quasielastic Neutron Scattering and Ab Initio Simulation

Here, we investigated the impact of Li stoichiometry and host flexibility on Li + diffusion processes in LiAlGeO 4 at the microscopic level using quasielastic neutron scattering (QENS) and ab initio molecular dynamics (AIMD) simulations. Using sufficiently long AIMD trajectories, we could simulate the observed QENS signal and identify the localized dynamics of Li in crystalline LiAlGeO 4 . Such information is vital to identify the bottleneck of diffusion processes and design materials for battery application. Our AIMD simulations in LiAlGeO 4 reveal that the Li + conductivity can be significantly improved by manipulating the Li stoichiometry and/or host flexibility via amorphization. We determined that excess Li stoichiometry enhances the Coulomb repulsion of neighboring Li sites and softens the host structure to enable faster Li + diffusion along the hexagonal c-axis. In the amorphous structure, random orientations of AlO 4 and GeO 4 polyhedral units create a wide distribution of intersite distances and significantly soften the host structure, greatly enhancing the Li + diffusion. The simulations are used to understand the nature of diffusion, especially the role of the host structure, the possible hopping pathways, and the diffusion behavior in various structures of LiAlGeO 4 .

localized dynamics↗

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↗

High temperature stability and transport characteristics of hydrogen in alumina via multiscale computation

Here, the impact of hydrogen charge states on the stability and transport characteristics of hydrogen interstitials in alumina polymorphs is evaluated by multiscale computational methods including density functional theory (DFT), ab initio molecular dynamics (AIMD) and machine learned force fields. Thermodynamic calculations show that the protonic H i +1 interstitial is the most stable defect species for most values of the electronic bandgap in both and amorphous alumina (Al 2 O 3 ). Further, active learned Gaussian approximation potentials (GAP) were developed using AIMD data to study temperature dependent long time proton diffusion in alumina. Diffusivity calculations from GAP-MD simulations are found to be comparable with of the AIMD data, while being ~340 times faster and scalable to larger systems. Comparisons with diffusivity values for other interstitial charge states (H i 0 and H i -1 ) and published experimental literature indicate that H i +1 diffusion is the likely mechanism of hydrogen transport. A good agreement is obtained between H i +1 diffusivity calculated in α-Al 2 O 3 from DFT: 5.05 10 -3 exp(-0.81 eV/k B /T) cm 2 /s and reported experiment: 9.7X10 -4 exp(-0.83 eV/k B /T) cm 2 /s. Computationally and experimentally calculated energy barriers (0.81 and 0.83 eV respectively) only differ by 2.5%. Similarly, the pre-exponential diffusion coefficients only differ by 0.5 orders of magnitude. Moreover, the diffusivity of H i +1 in amorphous Al 2 O 3 in the 1000–2000 K range is calculated to be 2.53X10 -2 exp(-0.89 eV/k B /T), just one order of magnitude higher than the corresponding value in α-Al 2 O 3 . This suggests that local structural disorder does not significantly affect the energy landscape and diffusion behavior of H i +1 in Al 2 O 3 . Overall, these results show promise for the application of alumina polymorphs as hydrogen permeation barriers.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

The impact of nanoparticle softness on its tracer diffusion coefficient in all polymer nanocomposites

The diffusion of nanoparticles in a polymer matrix is an area of current interest. However, a complete understanding is still limited as it is often difficult to quantify the much slower motion of nanoparticles in a polymer matrix. To combat this problem, we have developed a protocol to measure the diffusion coefficient of soft nanoparticles in a linear polymer matrix. Recently developed synthetic control over soft nanoparticle structures combined with this protocol provides a pathway to separately elucidate the effects of the molecular weight and nanoparticle softness on its diffusive behavior. These results indicate that the nanoparticle softness and deformability dictate its motion. Increasing the cross-linking density of the nanoparticle for all molecular weights increases its hardness and suppresses its motion in the linear matrix. Additionally, the nanoparticle molecular weight dependence deviates from the exponential dependence for star polymers suggesting that these nanoparticles benefit from the cooperative motion of the matrix to open pathways for the nanoparticle. Finally, comparison of these experimentally determined values to the Stokes–Einstein theory demonstrates that the nanoparticles diffuse much slower than a hard sphere. This is interpreted to indicate that there exist additional interactions between the nanoparticle and polymer matrix that are not captured by Stokes–Einstein, including threading or entanglement of the linear chain with the nanoparticle.

Rostom, Sahar↗

Universality aspects of quantum corrections to transverse momentum broadening in QCD media

We study non-linear quantum corrections to transverse momentum broadening (TMB) of a fast parton propagating in dense QCD matter in the leading logarithmic approximation. These non-local corrections yield an anomalous super-diffusive behavior characterized by a heavy tailed distribution which is associated with Lévy random walks. Using a formal analogy with the physics of traveling waves, we show that at late times the transverse momentum distribution tends to a universal scaling regime. We derive analytic solutions in terms of an asymptotic expansion around the scaling limit for both fixed and running coupling. We note that our analytic approach yields a good agreement with the exact numerical solutions down to realistic values of medium length. Finally, we discuss the interplay between system size and energy dependence of the diffusion coefficient $\hat{q}$ and its connection with the gluon distribution function that is manifest at large transverse momentum transfer.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Predicting path-dependent diffusion barrier spectra in vast compositional space of multi-principal element alloys via convolutional neural networks

The emergent multi-principal element alloys (MPEAs) provide a vast compositional space to search for novel materials for technological advances. How to screen promising compositions from such an ample design space for targeted properties is a grand challenge. In this report, we demonstrate the state-of-the-art deep learning technology—convolutional neural network (CNN)—in predicting path-dependent vacancy migration energy barrier spectra, which are critical to diffusion behavior and many high-temperature properties, in the hyperdimensional composition space of MPEAs. The developed CNN model, fully capturing local chemical features surrounding each vacancy, accurately and efficiently predicts migration energy barrier of MPEAs with different degrees of chemical short-range order and at any unseen compositions. By varying the size of the local region encapsulating vacancy in the CNN model, we reveal that the length scale influencing vacancy migration is surprisingly extensive, up to its six nearest neighboring shells. The efforts of the CNN model make it promising for developing a database of diffusion barriers for various MPEA systems, which would have profound implications for accelerating alloy screening and discovering new compositions with desirable properties.

36 MATERIALS SCIENCE↗

Influences of Hydrogen Bonding-Based Stabilization of Bolaamphiphile Layers on Molecular Diffusion within Organic Nanotubes Having Inner Carboxyl Groups

This paper reports molecular diffusion behavior in two bolaamphiphile-based organic nanotubes having inner carboxyl groups with different inner dimeters (10 and 20 nm) and wall structures, COOH-ONT 10nm and COOH-ONT 20nm , using imaging fluorescence correlation spectroscopy (imaging FCS). Here, the results were compared to those previously obtained in a similar nanotube with inner amine groups (NH 2 -ONT 10nm ). COOH-ONT 10nm , as with NH 2 -ONT 10nm , were formed from a rolled bolaamphiphile layer incorporating triglycine moieties, whereas COOH-ONT 20nm consisted of four stacks of triglycine-free bolaamphiphile layers. Imaging FCS measurements were carried out for anionic sulforhodamine B (SRB), zwitterionic/cationic rhodamine B (RB) and cationic rhodamine-123 (R123) diffusing within ONTs (1–9 µm long) at different pH (3.4–8.4) and ionic strengths (1.6–500 mM). Diffusion coefficients (D) of these dyes in the ONTs were very small (0.01–0.1 µm 2 /s), reflecting the significant contributions of molecule-nanotube interactions to diffusion. The D of SRB was larger at higher pH and ionic strength, indicating the essential role of electrostatic repulsion that was enhanced by the deprotonation of the inner carboxyl groups. Importantly, the D of SRB was virtually independent of nanotube inner diameter and wall structure, indicating the diffusion of the hydrophilic molecule was controlled by short timescale adsorption/desorption processes onto the inner surface. In contrast, pH effects on D were less clear for relatively hydrophobic R123 and RB, suggesting the significant contributions of non-Coulombic interactions. Interestingly, the diffusion of these molecules in COOH-ONT 20nm was slower than in COOH-ONT 10nm . Slower diffusion in COOH-ONT20nm was attributable to relatively efficient partitioning of the hydrophobic dyes into the bolaamphiphile layers, which was reduced in COOH-ONT 10nm due to the stabilization of its layer by polyglycine-II-type hydrogen bonding networks. These results show that, by tuning the bolaamphiphile structures and their intermolecular interactions, unique environments can be created within the nanospaces for enhanced molecular separations and reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Robust Dissimilar Metal Friction Welded Spool for Enhanced Capability for Steam Power Components (Final Program Report)

This project successfully demonstrated the feasibility and advantages of producing durable, friction-welded dissimilar-metal spools, both with and without transition pieces, as well as the use of advanced oxidation-protective coatings for steam power applications. The work encompassed the optimization and full-scale production of NFA tubing, overcoming manufacturing and processing challenges to achieve enhanced strength, creep, and fatigue properties validated by extensive microstructural characterization. Optimized welding techniques were developed and refined for joining dissimilar materials, resulting in defect-free welds optimized for both low- and high-pressure boiler circuits. Systematic evaluation of welding parameters, coupled with heat treatments, ensured reliable performance and minimized weld defects such as banding and cracking. Comprehensive mechanical and non-destructive testing, including tensile, bend, fatigue, and CT scanning, confirmed the superior integrity and durability of the friction-welded joints under representative service conditions. To address oxidation-related degradation, a range of protective alloy coatings—such as IN625, APMT, Duplex 2507, and FeCrAlY—were selected and evaluated for their ability to counteract oxide notch formation at dissimilar metal interfaces. These coatings demonstrated improved oxidation resistance and long-term stability under thermal cycling, thereby extending weld service life. Thermal cyclic testing and long-term studies captured the phase stability and diffusion behavior of coated and uncoated configurations. Validated models for low-cycle fatigue (LCF), creep, and thermal mechanical fatigue (TMF) were developed to predict component life and failure modes. These models confirmed that friction-welded configurations exhibited significantly enhanced performance compared to conventional gas-tungsten arc welding (GTAW), with up to 7× improvement in creep resistance and at least 2× enhancement in fatigue properties. The introduction of a tailored transition piece further reduced thermally induced strains, enhancing fatigue life. The results demonstrate a robust pathway for retrofitting existing steam fleet components and upgrading future equipment to deliver substantially improved cold-start cycling behavior and reduction of unplanned outages due to premature weld failures.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Prediction of Self-Diffusion in Binary Fluid Mixtures Using Artificial Neural Networks

Artificial neural networks (ANNs) were developed to accurately predict the self-diffusion constants for individual components in binary fluid mixtures. The ANNs were tested on an experimental database of 4328 self-diffusion constants from 131 mixtures containing 75 unique compounds. The presence of strong hydrogen bonding molecules may lead to clustering or dimerization resulting in non-linear diffusive behavior. To address this, self- and binary association energies were calculated for each molecule and mixture to provide information on intermolecular interaction strength and were used as input features to the ANN. An accurate, generalized ANN model was developed with an overall average absolute deviation of 4.1%. Forward input feature selection reveals the importance of critical properties and self-association energies along with other fluid properties. Additional ANNs were developed with subsets of the full input feature set to further investigate the impact of various properties on model performance. The results from two specific mixtures are discussed in additional detail: one providing an example of strong hydrogen bonding and the other an example of extreme pressure changes, with the ANN models predicting self-diffusion well in both cases.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Microstructural features and deuterium diffusion in lithium penta-aluminate pellets under He + and D + ion irradiation

Lithium (Li) penta-aluminate (LiAl 5 O 8 ) is investigated as a potential tritium (T) breeding material, with a focus on microstructural response to ion irradiation and deuterium (D) diffusion behavior. Under high-fluence ion irradiation (2 x 10 17 (He + +D + )/cm 2 ) at 773 K, LiAl 5 O 8 exhibits significant disorder on the Li sublattice, as revealed by atomic-resolution scanning transmission electron microscopy, while the Al and O sublattices remain stable, demonstrating strong resistance to structural amorphization. Irradiation induces the formation of platelet-shaped antiphase boundaries (APBs), which may serve as effective D trapping sites. Atom probe tomography suggests the presence of 6 LiD clusters in the mass spectra, though definite conclusions regarding APB composition are hindered by signal overlap and limited data statistics. Time-of-flight secondary ion mass spectrometry reveals that D retention approaches to saturation at 3 x 10 17 (He + +D + )/cm 2 . Isothermal and isochronal annealing studies determine an average diffusivity of 1.6 x 10 -13 at 773 K and an effective activation energy of 0.8 ± 0.1 eV for D migration. Compared to γ-LiAlO 2 , LiAl 5 O 8 demonstrates superior irradiation resistance, minimal Li loss, and enhanced D retention, underscoring its potential as a durable breeder material for T production. In conclusion, these findings provide key insights into the microstructural evolution, defect dynamics, and D retention mechanisms in LiAl 5 O 8 under reactor-relevant conditions.

42 ENGINEERING↗

An optimization-based approach to parameter learning for fractional type nonlocal models

Nonlocal operators of fractional type are a popular modeling choice for applications that do not adhere to classical diffusive behavior; however, one major challenge in nonlocal simulations is the selection of model parameters. In this study we propose an optimization-based approach to parameter identification for fractional models with an optional truncation radius. We formulate the inference problem as an optimal control problem where the objective is to minimize the discrepancy between observed data and an approximate solution of the model, and the control variables are the fractional order and the truncation length. For the numerical solution of the minimization problem we propose a gradient-based approach, where we enhance the numerical performance by an approximation of the bilinear form of the state equation and its derivative with respect to the fractional order. Several numerical tests in one and two dimensions illustrate the theoretical results and show the robustness and applicability of our method.

97 MATHEMATICS AND COMPUTING↗

An optimization-based approach to parameter learning for fractional type nonlocal models

Nonlocal operators of fractional type are a popular modeling choice for applications that do not adhere to classical diffusive behavior; however, one major challenge in nonlocal simulations is the selection of model parameters. In this work we propose an optimization-based approach to parameter identification for fractional models with an optional truncation radius. We formulate the inference problem as an optimal control problem where the objective is to minimize the discrepancy between observed data and an approximate solution of the model, and the control variables are the fractional order and the truncation length. For the numerical solution of the minimization problem we propose a gradient-based approach, where we enhance the numerical performance by an approximation of the bilinear form of the state equation and its derivative with respect to the fractional order. Several numerical tests in one and two dimensions illustrate the theoretical results and show the robustness and applicability of our method.

97 MATHEMATICS AND COMPUTING↗

Application of electron backscatter diffraction techniques to quantify effects of aging on sub-grain and spatial heterogeneity in NMC cathodes

Identification and evaluation of structural heterogeneity in spent cathode materials is crucial to developing appropriate remediation strategies for novel recycling processes. Native heterogeneities may be exacerbated during the cell's operational lifetime, as sub-particle-scale variations induce anisotropic expansion and contraction upon cycling. Structural transformations resulting from repeated cycling and calendar aging predominantly occur at the secondary particle surface and at the grain boundaries (GBs) between primary particles. However, the diffusion and stress build up around and across GBs are poorly understood. In this study, electron backscatter diffraction (EBSD) is employed to track sub-grain lattice structure across a statistically relevant number of Li(Ni0.33Mn0.33Co0.33)O2 (NMC-111) particles. Specifically, differences in lattice misorientation – measured as the deviation from the grain's average orientation – are tracked as a function of position within the electrode (near current collector, middle, and near separator) and as a function of electrochemical cycling. Further, a novel method of structural analysis is developed, offering insight into sub-grain diffusion behavior by comparing lattice misorientation near the grain boundary versus in the grain bulk. The present results suggest that electrode-scale spatial heterogeneity in lattice structure is induced by initial manufacturing conditions, and that radial gradients in lattice misorientation evolve at the primary particle scale with repeated electrochemical cycling.

25 ENERGY STORAGE↗

Synthesis, structure, linear and nonlinear optical properties of noncentrosymmetric quaternary diamond-like semiconductors, Cu 2 ZnGeSe 4 (CZGSe) and the novel Cu 4 ZnGe 2 Se 7

In this work, two quaternary diamond-like semiconductors (DLSs) in the Cu-Zn-Ge-Se system, the known Cu 2 ZnGeSe 4 (also referred to as CZGSe) and the new Cu 4 ZnGe 2 Se 7 , are compared in terms of their crystal structures, electronic structures and physicochemical properties. Both compounds were prepared by high-temperature, solid-state synthesis at 800 degrees C. Single crystal X-ray diffraction was used to determine the structure of Cu 4 ZnGe 2 Se 7 . The structures of both Cu 2 ZnGeSe 4 and Cu 4 ZnGe 2 Se 7 can be considered as derivatives of cubic diamond. Cu 4 ZnGe 2 Se 7 , with a reduced symmetry due to the cation ordering pattern, adopts the Cu 4 NiSi 2 S 7 structure type, with space group C2. The corner-sharing tetrahedra in Cu 4 ZnGe 2 Se 7 are slightly distorted because the charge for some of the S 2 - anions is not compensated by the first-nearest-neighbor cations. Rietveld refinements using synchrotron X-ray powder diffraction data were used to assess the phase purity of the samples and confirm the bulk structural behavior. Diffuse reflectance UV/Vis/NIR spectroscopy shows that Cu 2 ZnGeSe 4 and Cu 4 ZnGe 2 Se 7 have direct optical bandgaps of 1.38 and 0.91 eV, respectively. Electronic structure calculations implementing density functional theory confirm the direct bandgap for Cu 4 ZnGe 2 Se 7 , with a calculated value of 0.62 eV. Both compounds are air stable, thermally stable up to relatively high temperatures, undergo phase transitions and have wide windows of optical clarity. The Kurtz-Perry powder technique was used to determine the second harmonic generation (SHG) responses using a commercial AgGaSe 2 standard. While Cu 4 ZnGe 2 Se 7 displays a weak SHG response, Cu 2 ZnGeSe 4 exhibits a response that is greater than several benchmark materials, with a large SHG coefficient, χ (2) , of 43 ± 6 pm/V at λ = 2900 nm.

36 MATERIALS SCIENCE↗