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At least 667 records · Page 37

Laser powder bed fusion of ODS Fe–Cr–Al (0.3Zr, 0.3Y 2 O 3 ): Unveiling processing-microstructure- mechanical property relationships

Here, this study investigates the fabrication of oxide dispersion strengthened (ODS) Fe-Cr-Al alloys via laser powder bed fusion (LPBF) with strategic additions of 0.3 wt% Zr and 0.3 wt% Y 2 O 3 for enhanced mechanical performance in nuclear applications. Systematic processing parameter optimization yielded three distinct conditions: one low-density product with significant defects and two near-full-density materials with improved consolidation. Comprehensive characterization confirmed single-phase α-ferrite matrix formation with successful incorporation of Y-, Zr-, O-, and C-rich precipitates characteristic of ODS alloys. However, precipitate density remained low (∼10 7 cm −3 ), resulting in sink strength values substantially below optimal levels for radiation resistance. Microhardness values (mid-200s HV) correlated inversely with grain size following the Hall-Petch relationship, indicating grain boundary strengthening as the dominant mechanism rather than precipitation strengthening. The optimized processing conditions achieved excellent mechanical properties with room temperature yield strength of approximately 500 MPa and 30 % elongation, demonstrating superior strength-ductility synergy compared to other additively manufactured ODS materials and performance consistent with literature values for LPBF-processed ODS-FeCrAl alloys. This investigation reveals both the potential and limitations of LPBF processing for ODS Fe-Cr-Al alloys. While successful defect-free fabrication was achieved, results highlight the critical need for systematic optimization of processing parameters and post-processing heat treatments to enhance precipitate density for effective dispersion strengthening and radiation resistance while maintaining additive manufacturing advantages.

Additive manufacturing↗

Accelerated coupled Monte Carlo-Thermal hydraulic calculations using a hybrid GTF-diffusion-based prediction block: first results

Accurate predictions of spatial power and temperature distributions require the coupling of a neutron transport solver with a thermal-hydraulic (TH) feedback. Nowadays, Monte Carlo (MC) codes are widely coupled to TH solvers, typically via a Picard iteration (PI) method, due to the higher fidelity that such frameworks can produce. To speed up a PI, a prediction step can produce an improved initial guess for a source distribution and feed it to the MC code. Recent work investigated a prediction step that uses generalized transfer functions (GTFs) to predict the macroscopic cross sections' variations following a perturbation in TH properties, such as coolant density. The previous method also relied on first order perturbation (FOP) theory to predict perturbed power profiles, rather than using an expensive MC iterate. The implemented FOP method relied on generating a fission matrix from which the forward and adjoint Eigenmodes were extracted and later used to for power calculations. The generation of the fission matrix can introduce a significant computational overhead, therefore undermining the performance of the proposed hybrid technique when applied to high-dimensional problems, e.g., full core calculations. This work attempts to improve the GTF-FOP prediction step by replacing the FOP solver with a nodal diffusion solver, thus eliminating the need to calculate a fission matrix. The GTF-diffusion step was tested for various moderator density perturbations. In each case, the predicted power distribution showed good agreement with the reference case. The latter is attributed to the generally good prediction of most spatially distributed macroscopic cross sections, except the transport cross section, which will become the focus of future work. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Accelerated Coupled Monte Carlo-Thermal Hydraulic Calculations using a Hybrid GTF-Diffusion-based Prediction Block: First Results

Accurate predictions of spatial power and temperature distributions require the coupling of a neutron transport solver with a thermal-hydraulic (TH) feedback. Nowadays, Monte Carlo (MC) codes are widely coupled to TH solvers, typically via a Picard iteration (PI) method, due to the higher fidelity that such frameworks can produce. To speed up a PI, a prediction step can produce an improved initial guess for a source distribution and feed it to the MC code. Recent work [1, 2] investigated a prediction step that uses generalized transfer functions (GTFs) to predict the macroscopic cross sections’ variations following a perturbation in TH properties, such as coolant density. The previous method also relied on first order perturbation (FOP) theory to predict perturbed power profiles, rather than using an expensive MC iterate. The implemented FOP method relied on generating a fission matrix from which the forward and adjoint eigenmodes were extracted and later used to for power calculations. The generation of the fission matrix can introduce a significant computational overhead, therefore undermining the performance of the proposed hybrid technique when applied to high-dimensional problems, e.g., full core calculations. This work attempts to improve the GTF-FOP prediction step by replacing the FOP solver with a nodal diffusion solver, thus eliminating the need to calculate a fission matrix. The GTF-diffusion step was tested for various moderator density perturbations. In each case, the predicted power distribution showed good agreement with the reference case. The latter is attributed to the generally good prediction of most spatially distributed macroscopic cross sections, except the transport cross section, which will become the focus of future work.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Pyrolysis in Molten Salts Converts Plastics into a Mesoporous Electrocatalyst with a High Density of Atomic Fe–N–C Active Site

Upcycling plastic waste into value-added products is a promising strategy for both economic and environmental sustainability. However, achieving control over structure–property correlations during the upcycling process remains challenging. Here, in this study, we investigate the modulation of active site formation during pyrolytic conversion of plastics to carbon by composition-controlled molten salts. Using melamine formaldehyde (MF) foams as a precursor, we demonstrate that their pyrolysis in eutectic chloride molten salts with Fe 2+ , Na + , and K + ions directs the carbonization process toward the formation of mesoporous functional carbon enriched with atomically dispersed Fe–N–C sites, which are well-known for their catalytic activity in oxygen reduction reaction (ORR). Compared to pyrolysis in the FeCl 2 -only salt, the incorporation of alkali metal ions (Na + , K + ) in the eutectic mixture facilitates nitrogen retention in the carbon matrix and modulates iron speciation. This synergistic environment promotes a higher density and more uniform dispersion of Fe–N–C moieties within the carbon matrix. Consequently, the resulting catalyst exhibits a high surface area, hierarchical porosity, and improved electrochemical properties. When tested as an ORR catalyst, the Fe–N–C-enriched catalyst delivers a high half-wave potential (E 1/2 = 0.875 V vs RHE) with nearly exclusive 4e – pathway. These properties are comparable to those of commercial Pt/C catalysts, along with improved stability.

Fe−N−C active sites↗

An SYK-inspired model with density–density interactions: Spectral & wave function statistics, Green’s function and phase diagram

The Sachdev–Ye–Kitaev (SYK) model is a rare example of a strongly-interacting system that is analytically tractable. Tractability arises because the model is largely structureless by design and therefore artificial: while the interaction is restricted to two-body terms, interaction matrix elements are “randomized” and therefore the corresponding interaction operator does not commute with the local density. Unlike conventional density–density-type interactions, the SYK-interaction is, in this sense, not integrable. We here investigate a variant of the (complex) SYK model, which restores this integrability. It features a randomized single-body term and a density–density-type interaction. We present numerical investigations suggesting that the model exhibits two integrable phases separated by several intermediate phases including a chaotic one. The chaotic phase carries several characteristic SYK-signatures including in the spectral statistics and the frequency scaling of the Green’s function and therefore should be adiabatically connected to the non-Fermi liquid phase of the original SYK model. Thus, our model Hamiltonian provides a bridge from the SYK-model towards microscopic realism.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Tunable Magnetic and Optical Anisotropy in ZrO 2 ‐Co Vertically Aligned Nanocomposites

Abstract Metamaterials have gained great research interest in recent years owing to their potential for property tunability, multifunctionality, and property coupling. As a new group of self‐assembled thin films, vertically aligned nanocomposite (VAN)‐based hybrid metamaterials have been demonstrated with significant anisotropic physical properties and a broad range of property tailorability, such as optical anisotropy, magnetic anisotropy, hyperbolic dispersion, and enhanced second harmonic generation properties. Herein, self‐assembled ZrO 2 ‐Co nanocomposite films, with high epitaxial quality and ultra‐fine vertically aligned Co nanopillars (with an average diameter of ≈2 nm) embedded in a ZrO 2 matrix, are fabricated using a pulsed laser deposition (PLD) method. The Co pillar density can be effectively tuned by varying the Co concentration in the target, which results in tunable optical properties and magnetic properties. Specifically, a high saturation magnetization of 100 emu cm −3 , strong out‐of‐plane magnetic anisotropy and tailorable magnetization properties are achieved via tuning the Co nanopillar density. Coupled with hyperbolic dispersion of dielectric constant from 950 to 1500 nm in wavelength, plasmonic Co metal nanopillars, and the unique dielectric ZrO 2 matrix, this new nanoscale hybrid metamaterial shows great potential for future integrated optical and magnetic device designs.

36 MATERIALS SCIENCE↗

GPU acceleration of all-electron electronic structure theory using localized numeric atom-centered basis functions

We present an implementation of all-electron density-functional theory for massively parallel GPU-based platforms, using localized atom-centered basis functions and real-space integration grids. Special attention is paid to domain decomposition of the problem on non-uniform grids, which enables compute- and memory-parallel execution across thousands of nodes for real-space operations, e.g. the update of the electron density, the integration of the real-space Hamiltonian matrix, and calculation of Pulay forces. To assess the performance of our GPU implementation, we performed benchmarks on three different architectures using a 103-material test set. We find that operations which rely on dense serial linear algebra show dramatic speedups from GPU acceleration: in particular, SCF iterations including force and stress calculations exhibit speedups ranging from 4.5 to 6.6. For the architectures and problem types investigated here, this translates to an expected overall speedup between 3–4 for the entire calculation (including non-GPU accelerated parts), for problems featuring several tens to hundreds of atoms. Additional calculations for a 375-atom Bi2Se3 bilayer show that the present GPU strategy scales for large-scale distributed-parallel simulations.

42 ENGINEERING↗

Current Density Regulated Atomic to Nanoscale Process on Li Deposition and Solid Electrolyte Interphase Revealed by Cryogenic Transmission Electron Microscopy

Current density has been perceived to play a critical rule for controlling Li deposition morphology and solid electrolyte interphase (SEI). However, the atomic level mechanism of current density on Li deposition and the SEI remains unclear. In this work, based on cryogenic transmission electron microscopy imaging combined with energy dispersive X-ray spectroscopy and electron energy loss spectroscopy electronic structure analyses, we reveal the atomic level correlation of Li deposition morphology and SEI with current density. We discover that increasing current density leads to increased overpotential for Li nucleation and growth, leading to the transition from growth-limited to nucleation-limited mode for Li dendrite. Independence of current density, the electrochemically deposited Li metal (EDLi) exhibits crystalline whisker-like morphology. The SEI formed at low current density (0.1 mA cm -2 ) is monolithic amorphous; while, a current density of above 2 mA cm -2 leads to a mosaic structured SEI, featuring an amorphous matrix with Li 2 O and LiF dispersoids, and the thickness of the SEI increases with the increase of current density. Uniquely, the Li 2 O particles is spatially located at the top surface of the SEI, while LiF is spatially adjacent to the Li-SEI interface. These results highlight the possible tuning of crucial structural and chemical features of EDLi and SEI through altering deposit conditions and consequently direct correlation with electrochemical performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A convergent genus expansion for the plateau

We conjecture a formula for the spectral form factor of a double-scaled matrix integral in the limit of large time, large density of states, and fixed temperature. The formula has a genus expansion with a nonzero radius of convergence. To understand the origin of this series, we compare to the semiclassical theory of “encounters” in periodic orbits. In Jackiw-Teitelboim (JT) gravity, encounters correspond to portions of the moduli space integral that mutually cancel (in the orientable case) but individually grow at low energies. At genus one we show how the full moduli space integral resolves the low energy region and gives a finite nonzero answer.

2D Gravity↗

Polymer-assisted deposition of nanoparticle feedstocks for target fabrication

Traditional polymer-assisted deposition has been shown to produce highly uniform thin films of metal oxides, including actinide oxides. Furthermore, while producing thicker films for nuclear targets is possible through repeated coating application, we exchanged the dissolved metal species with nanoparticles to maximize the thickness that can be achieved with an individual layer. Using CeO 2 nanoparticles in a polyethyleneimine matrix, we produced targets with single-layer areal densities of 0.22 ± 0.01 mg·cm −2 (1σ) and thicknesses of 690 ± 80 nm (1σ). A custom 3D-printed spin coating chuck attachment with an inlay improved target homogeneity and will streamline future work with radioactive materials.

and nuclear chemistry↗

Disorder trapping and formation of antiphase nanodomains in Ni 3 Sn: in situ observation and high resolution characterization

Rapid solidification of the intermetallic Ni 3 Sn compound from an undercooled liquid was investigated using time-resolved synchrotron X-ray diffraction. Primary growth of an ordered and a disordered cubic solid was observed in situ at a low and a high undercooling, respectively. The disordered cubic solid was reordered after rapid solidification and experienced a solid-state transformation in cooling. A HRTEM study revealed high density of crystal defects and nanodomains in the transformed matrix. A HAADFSTEM study determined that the nanodomains are antiphase domains with chemical disorder. These observations indicated a possibility of online control of mechanical properties in additively manufactured intermetallics.

36 MATERIALS SCIENCE↗

Accurate additive manufacturing of lightweight and elastic carbons using plastic precursors

Despite groundbreaking advances in the additive manufacturing of polymers, metals, and ceramics, scaled and accurate production of structured carbons remains largely underdeveloped. This work reports a simple method to produce complex carbon materials with very low dimensional shrinkage from printed to carbonized state (less than 4%), using commercially available polypropylene precursors and a fused filament fabrication-based process. The control of macrostructural retention is enabled by the inclusion of fiber fillers regardless of the crosslinking degree of the polypropylene matrix, providing a significant advantage to directly control the density, porosity, and mechanical properties of 3D printed carbons. Using the same printed plastic precursors, different mechanical responses of derived carbons can be obtained, notably from stiff to highly compressible. This report harnesses the power of additive manufacturing for producing carbons with accurately controlled structure and properties, while enabling great opportunities for various applications.

36 MATERIALS SCIENCE↗

Synthesis of core/shell nanocrystals with ordered intermetallic single-atom alloy layers for nitrate electroreduction to ammonia

Structurally ordered intermetallic nanocrystals (NCs) and single-atom catalysts (SACs) are two emerging catalytic motifs for sustainable chemical production and energy conversion. However, both have synthetic limitations which can lead to the aggregation of NCs or metal atoms. Single-atom alloys (SAAs), which contain isolated metal atoms in a host metal, can overcome the aggregation concern because of the thermodynamic stabilization of single atoms on host metal surfaces. We report a direct solution-phase synthesis of Cu/CuAu core/shell NCs with tunable SAA layers. This synthesis can be extended to other Cu/CuM (M = Pt, Pd) systems, in which M atoms are isolated in the copper host. Using this method, the density of SAAs on a copper surface can be controlled, resulting in both low and high densities of single atoms. Alloying gold into the copper matrix introduced ligand effects that optimized the chemisorption of *NO 3 and *N. As a result, the densely packed Cu/CuAu material demonstrated a high selectivity toward NH 3 from the electrocatalytic nitrate reduction reaction with an 85.5% Faradaic efficiency while maintaining a high yield rate of 8.47 mol h -1 g -1 . This work advances the design of atomically precise catalytic sites by creating core/shell NCs with SAA atomic layers, opening an avenue for broad catalytic applications.

36 MATERIALS SCIENCE↗

An extended moments model of quantum efficiency for metals and semiconductors

The complexity of photocathode designs and detector materials, and the need to model their performance for short pulse durations, response to high frequency photons, presence of coatings and/or thinness of the absorptive layer, necessitates modifications to three-step and moments models of photoemission that are used in simulation codes. Here, methods to include input from computationally intensive approaches, such as density functional theory to model optical properties and transfer matrix approaches to treat emission from the surface or transport past coatings, by means of parametric models are demonstrated. First, a technique to accurately represent optical behavior so as to model reflectivity and penetration depth is given. Second, modifications to bulk models arising from the usage of thin film architectures, and a means to rapidly calculate them, is provided. Third, a parameterization to model the impact of wells associated with coatings and surface layers on the transmission probably is given. In all cases, the methods are computationally efficient and designed to allow for including input from numerically intensive approaches that would otherwise be unavailable for simulations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Double copy root of Hawking thermality

The Hawking radiation spectrum from a collapsing null shell can be derived via the double copy of a simpler gauge theory calculation. Analyzing the non-abelian Yang-Mills root of this process, we demonstrate that the radiation spectrum is thermal in the color charge eigenvalue 𝜆, not energy. Considering the 𝑆⁢𝑈⁡(𝑁 𝑐 ) gauge theory in the large 𝑁 𝑐 limit, we find the differential spectrum ⅆ⁢𝑁/ⅆ⁢𝜆 is a product of the gravitationally familiar Planck-like factor and the color phase space density, modeled here as the Wigner semicircle from random matrix theory. This reveals that apparent energy thermality in gravity is the direct dual of charge thermality in its underlying non-abelian gauge theory.

Carrasco, John Joseph M. [Northwestern University,↗

Quasi-deuteron model at low renormalization group resolution

The quasi-deuteron model introduced by Levinger is used to explain cross sections for knocking out high-momentum protons in photoabsorption on nuclei. This is within a framework we characterize as exhibiting high renormalization group (RG) resolution. Assuming a one-body reaction operator, the nuclear wave function must include two-body short-range correlations (SRCs) with deuteronlike quantum numbers. In Phys. Rev. C 104, 034311 (2021), we showed that SRC physics can be naturally accounted for at low RG resolution. We describe the quasi-deuteron model at low RG resolution and determine the Levinger constant, which is proportional to the ratio of nuclear photoabsorption to that for photodisintegration of a deuteron. We extract the Levinger constant based on the ratio of momentum distributions at high relative momentum. We compute momentum distributions evolved under similarity RG (SRG) transformations where the SRC physics is shifted into the operator as a universal two-body term. The short-range nature of this operator motivates using local-density approximations with uncorrelated wave functions in evaluating nuclear matrix elements, which greatly simplifies the analysis. The operator must be consistently matched to the RG scale and scheme of the interaction for a reliable extraction. We apply SRG transformations to different nucleon-nucleon (NN) interactions and use the deuteron wave functions and Weinberg eigenvalues to determine approximate matching scales. We predict the Levinger constant for several NN interactions and a wide range of nuclei comparing to experimental extractions. The predictions at low RG resolution are in good agreement with experiment when starting with a hard NN interaction and the initial operator. Similar agreement is found using soft NN interactions when the additional two-body operator induced by evolution from hard to soft is included.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

A Structural Perspective on the Alphavirus Life Cycle

Alphaviruses are mosquito-borne, enveloped viruses with a positive-sense, single-stranded RNA genome. Alphaviruses enter host cells via receptor-mediated endocytosis, using various cellular surface receptors such as matrix remodeling-associated protein 8 (MXRA8), low-density lipoprotein receptor class A domain-containing 3 (LDLRAD3), and very low-density lipoprotein receptor (VLDLR), which facilitate binding to the viral glycoproteins. Following entry, viral proteins are expressed and nonstructural proteins assemble into replication complexes in host cells, driving RNA synthesis and genome replication. Viral assembly occurs at the plasma membrane, where nascent virions bud from the host cell in a process driven by capsid and spike proteins. Recent combinatorial structural studies have provided detailed molecular insights into various steps of the alphavirus life cycle. These structural insights into the alphavirus life cycle enhance our understanding of viral replication and assembly, with significant implications for antiviral strategies and the development of alphavirus-based vaccine vectors.

RNA virus↗

Hyper Spectral Anomaly Detection

The HSA is a statistics based anomaly detection model. The model performs unsupervised anomaly detection, based on a datapoint's density and similarity within a dataset. Density and similarity data are encoded into an affinity matrix. The affinity matrix is evolved to summarize the data's structure on greater topographical scales within the data's function space. The set of evolved affinity matrices and an anomaly score vector are passed to a user defined penalized objective function. The penalized objective function of anomaly scores is then minimized. Data points where the absolute value of the z-scores of anomaly scores greater than a specified threshold are predicted as anomalies. A novel multi-filter feature has also been implemented. To reduce false positive rates, the multi-filter records the indexes of the HSA predictions. A new dataset and data loader are instantiated consisting of all the initial HSA predictions and non-anomalous data points in a 10% and 90% split respectively. The HSA is then run through this data set and a count of number of times a data point is predicted is kept. In this way the initial predictions may be compared with data spanning the entire dataset. After the multi-filter is complete, all datapoints will have an associated anomaly score, as well as a multi-filter prediction count to further filter the anomalous predictions.

Rogers, DempseyD [Idaho National Laboratory (INL),↗