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At least 1,045 records · Page 58

Optimization performance, fidelity, and cost: SIAM VQE

This dataset contains files storing results from classically-simulated quantum subroutines within a dynamical mean-field theory workflow, and jupyter notebooks processing the data in these files to generate plots. The files store: (1) Results from variational quantum eigensolver (VQE) simulations searching for optimal parameters allowing parametrized quantum circuits to prepare approximations to ground states of different Anderson impurity models (AIMs) (2) Results from simulations of a quantum Lanczos algorithm (QLA) estimating the Lanczos coefficients defining the continued-fraction representation of an (AIM) Green’s function Description: Any file named vqe_gs_results* stores approximations to the ground state and energy of a given AIM estimated using three different methods: (1) Numerical diagonalization (2) Ideal VQE simulation (3) VQE simulation with sampling noise For each VQE simulations metadata about the optimization (optimization results plus number of quantum circuits that would have been executed on real hardware) is also stored. Any file named qla_dos_results* estimations for the Lanczos coefficients defining the Green’s function of an AIM. The stored estimations are achieved using different methods: (1) Numerical Lanczos algorithm from initial states obtained from numerical diagonalization (2) Simulated quantum Lanczos algorithm from initial states prepared from parametrized quantum circuits yielded by corresponding ideal and noisy VQE subroutines. The dataset is used and described in M. Karabin et al., "Quantum solver for single-impurity Anderson models with particle-hole symmetry", Phys. Rev. Research 8, 033066 (2026). DOI: https://doi.org/10.1103/7ys3-tl4l

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Sum rules in the standard model effective field theory from helicity amplitudes

The dispersion relation of an elastic 4-point amplitude in the forward direction leads to a sum rule that connects the low energy amplitude to the high energy observables. We perform a classification of these sum rules based on massless helicity amplitudes. With this classification, we are able to systematically write down the sum rules for the dimension-6 operators of the Standard Model Effective Field Theory (SMEFT), some of which are absent in previous literatures. These sum rules offer distinct insights on the relations between the operator coefficients in the EFT and the properties of the full theory that generates them. Their applicability goes beyond tree level, and in some cases can be used as a practical method of computing the one loop contributions to low energy observables. They also provide an interesting perspective for understanding the custodial symmetries of the SM Higgs and fermion sectors.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Elevated temperature contact creep and friction of nickel-based superalloys using machine learning assisted finite element analysis

Nickel-based superalloys with superior thermochemical, mechanical, and tribological properties are highly utilized for critical components in several high temperature applications such as gas turbines and nuclear reactors. Inconel 617, in particular, is considered as one of the main candidate superalloys for tribo-components in very-high-temperature gas-cooled nuclear reactors. Recent findings indicate that this alloy grows unique surface oxide especially in a high-temperature helium environment with distinctive wear, friction, and contact properties. Here, this study investigates the high temperature contact area evolution and frictional behavior of Inconel 617 using finite element simulation and provides predictive models for the contact and friction performance at different normal loads, dwell times, and temperatures. High temperature helium-aged Inconel 617 top surface properties (up to 600 °C) are utilized along with a single asperity-based deformable elastic-plastic contact model under combined normal and tangential loading. Machine learning is used to assist the finite element results and to predict friction coefficient as well as contact area evolution. While a small difference is observed in the instantaneous friction coefficient (no dwell time) for all temperatures, friction coefficient increases considerably with dwell time. This shows that the effect of contact creep for longer dwell times significantly dominants the effect of high temperature variation in basic mechanical parameters such as modulus and yield strength. It is found that increasing temperature and dwell times lead to the friction coefficient increase, yet the dominance of dwell time effects decreases at higher temperatures and loads. While the analysis is presented for Inconel 617, the methodology is easy to be generalized and can be applied to other HT alloys.

36 MATERIALS SCIENCE↗

Tribological behavior of ceramic-alloy bearing contacts in molten salt lubrication for concentrating solar power

Molten salts are considered as candidate heat transfer fluids and thermal energy storage media for next generation concentrating solar power (CSP). A molten salt circulates inside the piping and heat exchanger and also functions as a lubricant for the sleeve bearings of the CSP pump. Furthermore, wear- and corrosion-resistant high-temperature bearing materials are critical for the pump efficiency and durability. This study evaluated the tribological performance of candidate bearing materials in lubrication of a molten chloride salt mixture (20% NaCl + 40% MgCl 2 + 40% KCl) at 750 °C in an inert argon gas (a simulative CSP pump environment). Six ceramic-alloy pairs were tested, zirconia and silicon nitride against Haynes 244, Hastelloy C276, and Tribaloy T900 alloy, and ranked by the friction coefficient and wear loss. Characterization of worn surfaces suggested the wear mechanism as a combination of abrasion, adhesion, and tribocorrosion. Results from this study provide fundamental insight for the development and selection of bearing materials for molten salt powered CSP pumps.

14 SOLAR ENERGY↗

High-specific-power flexible transition metal dichalcogenide solar cells

Abstract Semiconducting transition metal dichalcogenides (TMDs) are promising for flexible high-specific-power photovoltaics due to their ultrahigh optical absorption coefficients, desirable band gaps and self-passivated surfaces. However, challenges such as Fermi-level pinning at the metal contact–TMD interface and the inapplicability of traditional doping schemes have prevented most TMD solar cells from exceeding 2% power conversion efficiency (PCE). In addition, fabrication on flexible substrates tends to contaminate or damage TMD interfaces, further reducing performance. Here, we address these fundamental issues by employing: (1) transparent graphene contacts to mitigate Fermi-level pinning, (2) MoO x capping for doping, passivation and anti-reflection, and (3) a clean, non-damaging direct transfer method to realize devices on lightweight flexible polyimide substrates. These lead to record PCE of 5.1% and record specific power of 4.4 W g −1 for flexible TMD (WSe 2 ) solar cells, the latter on par with prevailing thin-film solar technologies cadmium telluride, copper indium gallium selenide, amorphous silicon and III-Vs. We further project that TMD solar cells could achieve specific power up to 46 W g −1 , creating unprecedented opportunities in a broad range of industries from aerospace to wearable and implantable electronics.

42 ENGINEERING↗

Beyond the hubble sequence – exploring galaxy morphology with unsupervised machine learning

We explore unsupervised machine learning for galaxy morphology analyses using a combination of feature extraction with a vector-quantized variational autoencoder (VQ-VAE) and hierarchical clustering (HC). We propose a new methodology that includes: (1) consideration of the clustering performance simultaneously when learning features from images; (2) allowing for various distance thresholds within the HC algorithm; (3) using the galaxy orientation to determine the number of clusters. This set-up provides 27 clusters created with this unsupervised learning that we show are well separated based on galaxy shape and structure (e.g. Sérsic index, concentration, asymmetry, Gini coefficient). These resulting clusters also correlate well with physical properties such as the colour–magnitude diagram, and span the range of scaling relations such as mass versus size amongst the different machine-defined clusters. When we merge these multiple clusters into two large preliminary clusters to provide a binary classification, an accuracy of $\sim 87{{\ \rm per\ cent}}$ is reached using an imbalanced data set, matching real galaxy distributions, which includes 22.7 per cent early-type galaxies and 77.3 per cent late-type galaxies. Comparing the given clusters with classic Hubble types (ellipticals, lenticulars, early spirals, late spirals, and irregulars), we show that there is an intrinsic vagueness in visual classification systems, in particular galaxies with transitional features such as lenticulars and early spirals. Based on this, the main result in this work is not how well our unsupervised method matches visual classifications and physical properties, but that the method provides an independent classification that may be more physically meaningful than any visually based ones.

79 ASTRONOMY AND ASTROPHYSICS↗

Inverse Method for Noninvasive Material Discrimination with Multienergy X-Ray Radiography

Active x-ray inspections have great potential for noninvasive detection of illicit materials. Dual-energy x-ray radiography, in particular, has been used to determine material composition by utilizing the energy-dependence of the x-ray attenuation coefficients. However, current implementations of this method are limited in their ability to determine the material composition of composite objects. Here, in this paper, we present an inverse algorithm that uses multienergy x-ray radiography data to noninvasively reconstruct the contents of a container. A critical feature of the current contribution is that material identification can be performed using conventional detectors and x-ray spectra with different endpoint energies produced by varying nothing more than the tube voltage. Adaptive regularization is used to increase the accuracy of material estimations from multienergy data sets. The utility of these methods is demonstrated with experimentally acquired radiographs obtained using a tunable x-ray source that produces spectra with endpoint energies of 100–450 keV. The object inspected is a scale model of a nuclear materials storage container composed of three-dimensional printed plastic and stainless-steel spheres inside a thin-walled steel container. Reconstructions of the steel sphere thicknesses are within a root-mean-square error of 0.37 cm.

47 OTHER INSTRUMENTATION↗

Modeling the Metabolic Costs of Heavy Military Backpacking

Existing predictive equations underestimate the metabolic costs of heavy military load carriage. Metabolic costs are specific to each type of military equipment, and backpack loads often impose the most sustained burden on the dismounted warfighter. This study aimed to develop and validate an equation for estimating metabolic rates during heavy backpacking for the US Army Load Carriage Decision Aid (LCDA), an integrated software mission planning tool. Thirty healthy, active military-age adults (3 women, 27 men; age, 25 ± 7 yr; height, 1.74 ± 0.07 m; body mass, 77 ± 15 kg) walked for 6–21 min while carrying backpacks loaded up to 66% body mass at speeds between 0.45 and 1.97 m·s -1 . A new predictive model, the LCDA backpacking equation, was developed on metabolic rate data calculated from indirect calorimetry. Model estimation performance was evaluated internally by k-fold cross-validation and externally against seven historical reference data sets. We tested if the 90% confidence interval of the mean paired difference was within equivalence limits equal to 10% of the measured metabolic rate. Estimation accuracy and level of agreement were also evaluated by the bias and concordance correlation coefficient (CCC), respectively. Estimates from the LCDA backpacking equation were statistically equivalent ( P < 0.01) to metabolic rates measured in the current study (bias, -0.01 ± 0.62 W·kg -1 ; CCC, 0.965) and from the seven independent data sets (bias, -0.08 ± 0.59 W·kg -1 ; CCC, 0.926). The newly derived LCDA backpacking equation provides close estimates of steady-state metabolic energy expenditure during heavy load carriage. These advances enable further optimization of thermal-work strain monitoring, sports nutrition, and hydration strategies.

59 BASIC BIOLOGICAL SCIENCES↗

Affinity of LDR Organics to Cementitious Materials: Sorption and Leaching Tests

SRNL is working to identify and test the physiochemical interactions of organic contaminants of potential concern with minerals in grout/cementitious materials. Organic species may interact with cementitious minerals including slag, fly ash, cement, and other components/dopants like carbon in fly ash. The identification of such interactions will support the solidification process design, performance assessments for the chemicals of concern, and a proposed Resource Conservation and Recovery Act (RCRA) treatment variance specified for the Land Disposal Restriction (LDR) organics associated with Hanford tank waste. Inably expected to be present LDR organics associated with Hanford tank waste (RPP-RPT-63493, Rev 1a) was screened by functional groups, octanol-water partitioning coefficients, and detection frequency in Hanford tank waste samples. A subset of 10 compounds, spanning the identified properties, were tested using sorption and leachate tests. These compounds were subjected to traditional batch sorption tests and leaching tests on/from Cast Stone cementitious material with and without activated carbon (a potential organic adsorption additive). The interactions between organic compounds were observed in traditional batch sorption and modified Toxic Characteristic Leaching Procedure (TCLP) leachate tests for a surrogate Cast Stone material with and without an activated carbon addition. Specifically, phthalic acids (negatively charged) and 4-chloroaniline (polar) sorbed strongly to unmodified Cast Stone and a group of 3 phenolic compounds (2,4,6-Trichlorophenol, Pentachlorophenol, o-Cresol) were sorbed to and were retained by Cast Stone with a 1% activated carbon amendment.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Gas Bubble Evolution in Polycrystalline UMo Fuels Under Elastic-Plastic Deformation: A Phase-Field Model With Crystal-Plasticity

In monolithic UMo fuels, the interaction between the Al cladding and large gas bubble volumetric swelling causes both elastic-plastic and creep deformation. In this work, a phase-field model of gas bubble evolution in polycrystalline UMo under elastic-plastic deformation was developed for studying the dynamic interaction between evolving gas bubble/voids and deformation. A crystal plasticity model, which assumes that the plastic strain rate is proportional to resolved shear stresses of dislocation slip systems on their slip planes, was used to describe plastic deformation in polycrystalline UMo. Xe diffusion and gas bubble evolution are driven by the minimization of chemical and deformation energies in the phase-field model, while evolving gas bubble structure was used to update the mechanical properties in the crystal plasticity model. With the developed model, we simulated the effect of gas bubble structures (different volume fractions and internal gas pressures) on stress-strain curves and the effect of local stresses on gas bubble evolution. The results show that 1) the effective Young’s modulus and yield stress decrease with the increase of gas bubble volume fraction; 2) the hardening coefficient increases with the increase of gas bubble volume fraction, especially for gas bubbles with higher internal pressure; and 3) the pressure dependence of Xe thermodynamic and kinetic properties in addition to the local stress state determine gas bubble growth or shrinkage. The simulated results can serve as a guide to improve material property models for macroscale fuel performance modeling.

36 MATERIALS SCIENCE↗

Material property characterization of 3D printed polypropylene wood plastic composites

Abstract Wood flour (WF) at 10 wt.% and 20 wt.% loadings was used as a reinforcing filler to enhance the applicability of polypropylene (PP) for 3D printing. After performing printability tests of PP wood plastic composites (WPCs), the mechanical properties of both injection‐molded and 3D‐printed PP WPC specimens were explored. Test specimens were prepared from 3D printed hexagons for analyzing the mechanical properties. Adding WF to neat PP increased the storage modulus and the glass transition temperature while decreasing the degree of crystallinity and the coefficient of thermal expansion, while enhancing the printability of neat PP. The tensile strength, tensile modulus of elasticity, flexural strength, and flexural modulus of elasticity of injection‐molded neat PP improved by up to 21%, 59%, 30%, and 56%, respectively, with 20 wt.% WF. However, the impact strength of injection‐molded neat PP decreased by 85%, with 20 wt.% WF. After 3D printing, the tensile strength and tensile modulus of elasticity of printed neat PP increased by up to 84% and 60%, respectively, with 20 wt.% WF. The flexural strength and flexural modulus of elasticity of neat printed PP remained unchanged compared to those of PP filled with 20 wt.% WF, while the impact strength decreased by 87%. Highlights WF was used as a reinforcement in polypropylene designed for 3D printing A pilot‐scale, pellet‐fed 3D printer was used to print hollow hexagons, and then test specimens were fabricated from these hexagons for mechanical properties The tensile and flexural properties of 3D printed neat polypropylene improved, while the impact strength decreased after adding 20 wt.% WF to the neat PP.

Hwang, Sungjun↗

Fiber/matrix debonding evaluation of SiCf/SiC composites using micropillar compression technique

Third-generation silicon carbide (SiC) composites reinforced by SiC fibers (Hi-Nicalon S [HNS] and Tyranno SA3 [SA3]) are attractive for use in next generation reactors owing to their high strength and chemical inertness at high temperatures, as well as enhanced radiation tolerance under neutron irradiation environments. To optimize composite performance, the interfacial mechanical properties of chemical vapor–infiltrated (CVI) SiC f /SiC composites are investigated in this effort by using a slant interface micropillar compression testing procedure. The micropillar test specimens, containing an inclined pyrolytic carbon (PyC) interphase, are prepared using a focused ion beam. The novel microcompression testing successfully quantifies the debond shear strength and internal friction coefficient of micropillar test samples by using the Mohr-Coulomb formulation. Furthermore, according to four types of SiCf/SiC composite microcompression test results, interfacial properties and debond mechanisms are significantly affected by the PyC layer thickness, the local bonding mechanism of the PyC interphase on the SiC fiber surface, and the surface roughness of fibers. Regardless of PyC thicknesses, SA3-reinforced CVI SiC f /SiC composites are found to have much higher debond shear strengths than HNS-reinforced SiC f /SiC CVI composites. By using this micropillar compression technique alongside analytical methods, we uncover new understandings of PyC interface properties. Additionally, the micropillar test results obtained are correlated with macroscopic mechanical properties of neutron-irradiated CVI SiCf/SiC composites.

42 ENGINEERING↗

An electrochemical mesoscale tool for modeling the corrosion of structural alloys by molten salt

Understanding the impact of microstructure on corrosion rates can aid the development of corrosion-resistant alloys for molten salt reactors. Here in this work, we develop an electrochemical phase-field model for capturing the microstructure-dependent corrosion of structural alloys by molten salts. As a demonstration problem, we apply this model to capture the selective depletion of Cr from Ni-Cr grain boundaries during corrosion in molten FLiBe salt. We perform sensitivity analysis and model verification on 1D simulations to confirm that the model predicts diffusion-limited kinetics. The model is validated using 1D, 2D, and 3D simulations against experimental data for Ni-5Cr and Ni-20Cr corrosion in molten FLiBe. The 1D simulations predict the corrosion behavior with reasonable accuracy when using an effective diffusion coefficient that accurately represents the grain boundary diffusion. 2D simulations that represent the grain structure underpredict the corrosion. 3D simulations that represent the grain structure predict the corrosion with reasonable accuracy. The corrosion rate predicted by the 3D simulations is proportional to the average grain size at the alloy/salt interface.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

A Noncentrosymmetric Polymorph of LuRuGe

In this work, we report a new polymorph of LuRuGe, obtained in indium flux. This phase exhibits the noncentrosymmetric ZrNiAl-type structure with the space group $Ρ\bar 62m$ as determined by single-crystal X-ray diffraction. This polymorph can convert into another centrosymmetric polymorph (TiNiSi-type structure, space group Pnma ) at high temperatures. In this work, we performed electrical transport, magnetization, and specific heat measurements on this new phase. It shows metallic behavior with a Hall sign change from negative at 2 K to positive at 125 K. LuRuGe exhibits Pauli paramagnetism as the ground state with no local magnetic moments from either the Ru or Lu site. The Debye temperature Θ = 348 K and electronic coefficient γ e = 3.6 mJ K –2 mol –1 are extracted from the low-temperature specific heat data in LuRuGe. We also carried out first-principles density functional theory calculations to map out the electronic band structure and density of states. There are several electronic bands crossing the Fermi level, supporting a multiband scenario consistent with the Hall sign change. The density of states around the Fermi level is mainly from Ru 4d and Ge 4p electrons, indicating a strong hybridization between those atomic orbitals.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Unravelling the room temperature growth of two-dimensional h-BN nanosheets for multifunctional applications

The room temperature growth of two-dimensional van der Waals (2D-vdW) materials is indispensable for state-of-the-art nanotechnology. Low temperature growth supersedes the requirement of elevated growth temperatures accompanied with high thermal budgets. Moreover, for electronic applications, low or room temperature growth reduces the possibility of intrinsic film-substrate interfacial thermal diffusion related deterioration of the functional properties and the consequent deterioration of the device performance. Here, we demonstrated the growth of ultrawide-bandgap boron nitride (BN) at room temperature by using the pulsed laser deposition (PLD) process, which exhibited various functional properties for potential applications. Comprehensive chemical, spectroscopic and microscopic characterizations confirmed the growth of ordered nanosheet-like hexagonal BN (h-BN). Functionally, the nanosheets show hydrophobicity, high lubricity (low coefficient of friction), and a low refractive index within the visible to near-infrared wavelength range, and room temperature single-photon quantum emission. In conclusion, our work unveils an important step that brings a plethora of potential applications for these room temperature grown h-BN nanosheets as the synthesis can be feasible on any given substrate, thus creating a scenario for “h-BN on demand” under a frugal thermal budget.

2D h-BN↗

Se diffusion in CdTe thin films for photovoltaics

Manipulating CdSeTe bandgrading to enhance photocurrent and carrier lifetime is an essential part of high-performance CdTe photovoltaics (PVs). Here, we examine Se diffusion kinetics in single-crystal and polycrystalline CdTe during deposition, thermal annealing, and CdCl 2 treatments. Se distributions are determined by dynamic secondary-ion-mass spectroscopy and Auger electron spectroscopy depth profiling and coupled with electron backscatter diffraction images of the crystalline structure. Effective bulk and grain boundary diffusion coefficients are determined by analytical models and discussed in the context of processing and film morphology. Se is found to diffuse in CdTe at much higher rates during CdCl 2 treatments than with thermal processing alone. GB diffusion also occurs at a significantly faster rate than bulk diffusion. As a result of these two effects, the near interface bulk and GB Se diffusion during CdCl 2 treatments dominates the bandgrading profiles in CdTe PVs.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A Novel Honeycomb-DD Multi Coil Design for Wireless Power Transfer Systems

Wireless power transfer (WPT) technology has received significant attention recently as an alternative charging method for batteries in a wide range of power levels. In the literature, many types of coil structures have been well-studied. Honeycomb coil arrays, which have been used mostly for low-power applications, have not been well-studied for high-power-level applications. In this paper, a novel honeycomb-DD coil design is proposed for high-power wireless battery charging systems. The proposed coil design with step by step design process is given and Finite Element Analysis (FEA) was performed to observe the full performance characteristics of the system for a 100 kW system. In addition, the misalignment tolerance of the proposed system was observed by shifting the secondary side charging pad at different misalignment positions, and the electromagnetic compatibility to the standards was investigated. The core and strand losses were obtained. The results show that the honeycomb coil array provides high coupling coefficient and better misalignment tolerance, making it a potential coil topology for WPT applications.

Aydin, Emrullah↗

Evaluation of a high-resolution regional climate simulation for surface and hub-height wind climatology over North America

Assessing the availability of key wind resources requires augmenting observations to support the implementation of wind energy infrastructure. However, observations are limited, necessitating the development of high-resolution, long-term gridded datasets. This study presents a robust, dynamically downscaled climatological dataset, offering 20 years of hourly wind data at a 4 km spatial resolution across North America, and evaluates its performance against observations, including meteorological towers and automated surface-observing system (ASOS) stations, as well as coarse-resolution reanalysis data (the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis version 5 (ERA5)). Results demonstrate that the downscaled high-resolution wind data outperform ERA5 in regions of complex terrain and coastal areas, with improved overlap coefficients for wind data distributions and reduced root mean square errors (RMSEs) for hub-height and near-surface diurnal wind patterns. The downscaled simulation also captures the synoptic drivers of seasonal wind direction patterns reasonably well, indicated by high wind rose similarity indices. This study also provides an analysis of interannual variability, utilizing the dataset's full 20-year period, and model uncertainty, generated by varying model initial conditions and physics parameterizations across 1-year ensemble members, which are key considerations for wind resource assessment in wind farm development.

17 WIND ENERGY↗