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DOE OSTI2023

Synchronous Rotation in the (136199) Eris–Dysnomia System

We combine photometry of Eris from a 6 month campaign on the Palomar 60 inch telescope in 2015, a 1 month Hubble Space Telescope WFC3 campaign in 2018, and Dark Energy Survey data spanning 2013–2018 to determine a light curve of definitive period 15.771 ± 0.008 days (1σ formal uncertainties), with nearly sinusoidal shape and peak-to-peak flux variation of 3%. This is consistent at part-per-thousand precision with the P = 15.785 90 ± 0.00005 day sidereal period of Dysnomia's orbit around Eris, strengthening the recent detection of synchronous rotation of Eris by Szakáts et al. with independent data. Photometry from Gaia are consistent with the same light curve. We detect a slope of 0.05 ± 0.01 mag per degree of Eris's brightness with respect to illumination phase averaged across g, V, and r bands, intermediate between Pluto's and Charon's values. Variations of 0.3 mag are detected in Dysnomia's brightness, plausibly consistent with a double-peaked light curve at the synchronous period. The synchronous rotation of Eris is consistent with simple tidal models initiated with a giant-impact origin of the binary, but is difficult to reconcile with gravitational capture of Dysnomia by Eris. The high albedo contrast between Eris and Dysnomia remains unexplained in the giant-impact scenario.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

Correlation between thickness dependent nanoscale structural chemistry and superconducting properties of ultrathin epitaxial NbN films

NbN-based superconductors have attracted interest for superconducting circuits, quantum computation and high frequency devices. The superconducting properties of NbN films are predominately reliant on the microstructure, therefore, an atomic-level understanding of the structure-chemistry is required to achieve high quality epitaxial NbN films. Here, in this study, the thickness-dependent superconducting properties of NbN films (5, 10, and 50 nm) within NbN/AlN/Al 2 O 3 heterostructures are investigated. NbN and AlN were epitaxially grown by an industrial scale physical vapor deposition technique. The role of nanoscale chemistry on the ultrathin NbN superconducting film is investigated at the atomic level for the first time via atom probe tomography, providing three-dimensional atomic distribution, chemical homogeneity, effect of impurities, specially, in secondary phase formations and interfacial abruptness. The NbN film with 5 nm of thickness demonstrates a superconducting transition temperature of 11.2 K as compared to 50 nm NbN films with a transition temperature of 15.3 K. These thickness dependent variation of superconducting properties are associated with the chemical inhomogeneity in terms of in-plane N:Nb distribution, secondary phase formations and NbN/AlN interfacial abruptness as a function of the NbN films thicknesses. The analysis depicts the interplay between the surface/interface and the superconducting properties of ultrathin NbN films. These results provide insights on material design and growth that will enable the development of optimized superconducting NbN films for quantum devices.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Thermal management of a high temperature sodium sulphur battery stack

The sodium sulfur battery is an advanced secondary battery with high potential for grid-level storage due to their high energy density, low cost of the reactants, and high open-circuit voltage. However, as the operating temperature of the battery is high (about 300 °C), effective thermal management is required to prevent thermal runaway under high current density operation. Here, to develop efficient thermal management strategies, a detailed, thermo-electrochemical, non-isothermal, distributed dynamic model of a sodium-sulfur battery stack is developed. Models of three thermal management strategies are developed and analyzed in this work: active cooling, passive cooling, and hybrid cooling. The active cooling strategy uses air as the cooling medium whereas, the passive cooling strategy uses a phase change material. In the hybrid cooling strategy, both active and passive cooling strategies are used. Due to the high operating temperature of the sodium sulfur batteries, the rejected heat can be utilized effectively and consequently a high variability in the heat rejection rate may not be acceptable. Performance of these strategies is analyzed under high current density operation by evaluating the variability in the cell temperature during charge/discharge cycles, temperature difference between the cells based on their locations, and variability in the heat rejection rate. The phase change-based hybrid thermal management strategy with an embedded controller maintained the temperature variation within ±/- 2.8 °C. Considering the tradeoff between the capital cost for PCM, fan power requirement, and variability in the heat rejection rate, the optimal quantity of the PCM and the maximum air velocity for the maximum current density of 260 mA/cm 2 (0.55 C-rate) were found be 0.74 g/Wh and 3 m/s, respectively.

25 ENERGY STORAGE↗

DOE OSTI2023

ESCARGOT: Mapping Vertical Phase Spiral Characteristics Throughout the Real and Simulated Milky Way

Abstract The recent discovery of a spiral pattern in the vertical kinematic structure in the solar neighborhood provides a prime opportunity to study nonequilibrium dynamics in the Milky Way from local stellar kinematics. Furthermore, results from simulations indicate that even in a limited volume, differences in stellar orbital histories allow us to trace variations in the initial perturbation across large regions of the disk. We present ESCARGOT , a novel algorithm for studying these variations in both simulated and observed data sets. ESCARGOT automatically extracts key quantities from the structure of a given phase spiral, including the time since perturbation and the perturbation mode. We test ESCARGOT on simulated data and show that it is capable of accurately recovering information about the time since the perturbation occurred as well as subtle differences in phase spiral morphology due to stellar locations in the disk at the time of perturbation. We apply ESCARGOT to kinematic data from data release 3 of the Gaia mission in bins of guiding radius. We show that similar structural differences in morphology occur in the Gaia phase spirals as a function of stellar orbital history. These results indicate that the phase spirals are the product of a complex dynamical response in the disk with large-scale coupling between different regions of phase space.

Darragh-Ford, Elise (ORCID:0000000288005652)↗

DOE OSTI2022

Nanolignin-based high internal phase emulsions for efficient protection of curcumin against UV degradation

As an emulsifier, lignin exhibits excellent UV resistance on drug-loaded emulsion systems for drug delivery. However, due to the structural variation and complexity of lignins from various origins, their UV shielding performance varies with the techniques for lignin extraction, which impacts properties and the protection efficiency of lignin-based HIPEs (high internal phase emulsions). In this work, lignin nanoparticles, prepared from three lignin preparations of Eucalyptus, were used in HIPEs delivery systems to protect curcumin from degradation by UV radiation. Structures of the lignin preparations were characterized using 2D HSQC (heteronuclear single-quantum coherence) NMR (nuclear magnetic resonance), 31 P NMR, and GPC (gel permeation chromatography). The residual curcumin level after 36h UV exposure in the nanolignin-based HIPEs was over 72%, much higher than that (< 10% after 24 h UV exposure) in the oil phase without lignin, indicating that the nanolignin-based HIPEs with enhanced UV shielding ability protect curcumin better. Of the three lignin preparations, AL (alkali lignin), with the lowest molecular weight, highest contents of phenolic hydroxyl and carboxyl groups, and highest S/G ratio, displayed the best anti-UV radiation ability and the most uniform nanoparticle size.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Investigating the crust of neutron stars with neural-network quantum states

An accurate description of low-density nuclear matter is crucial for explaining the physics of neutron star crusts. In the density range between approximately 0.01 fm −3 and 0.1 fm −3 , matter transitions from neutron-rich nuclei to various higher-density pasta shapes, before ultimately reaching a uniform liquid. In this work, we introduce a variational Monte Carlo method based on a neural Pfaffian-Jastrow quantum state, which allows us to model the transition from the liquid phase to neutron-rich nuclei microscopically. At low densities, nuclear clusters dynamically emerge from the microscopic interactions among protons and neutrons, which we model based on pionless effective field theory. Our variational Monte Carlo approach represents a significant improvement over the state-of-the-art auxiliary-field diffusion Monte Carlo method, which is severely hindered by the fermion-sign problem in this low-density regime and cannot capture the onset of clusters. In addition to computing the energy per particle of symmetric nuclear matter and pure neutron matter, we analyze an intermediate isospin-asymmetry configuration to elucidate the formation of nuclear clusters. We also provide evidence that the presence of such nuclear clusters influences the amount of protons in the crust compared to protons in beta-equilibrated, neutrino-transparent matter.

Nuclear astrophysics↗

DOE OSTI2023

Industrial PLC Network Modeling and Parameter Identification Using Sensitivity Analysis and Mean Field Variational Inference

A multiple input multiple output (MIMO) power line communication (PLC) model for industrial facilities was developed that uses the physics of a bottom-up model but can be calibrated like top-down models. The PLC model considers 4-conductor cables (three-phase conductors and a ground conductor) and has several load types, including motor loads. The model is calibrated to data using mean field variational inference with a sensitivity analysis to reduce the parameter space. The results show that the inference method can accurately identify many of the model parameters, and the model is accurate even when the network is modified.

47 OTHER INSTRUMENTATION↗

DOE OSTI2025

Towards robust surrogate models: Benchmarking machine learning approaches to expediting phase field simulations of brittle fracture

Data-driven approaches have the potential to make modeling complex, nonlinear physical phenomena significantly more computationally tractable. For example, computational modeling of fracture is a core challenge where machine learning techniques have the potential to provide a much needed speedup that would enable progress in areas such as multi-scale modeling and uncertainty quantification. Currently, phase field modeling (PFM) of fracture is one such approach that offers a convenient variational formulation to model crack nucleation, branching and propagation. To date, machine learning techniques have shown promise in approximating PFM simulations. While standard fracture benchmarks represent realistic scenarios frequently observed in practice, they typically do not provide sufficiently challenging tests for data-driven methods. Here, to address this gap, we introduce a challenging dataset based on PFM simulations designed to benchmark and advance ML methods for fracture modeling. This dataset includes three energy decomposition methods, two boundary conditions, and 1000 random initial crack configurations for a total of 6000 simulations. Each sample contains 100 time steps capturing the temporal evolution of the crack field. Alongside this dataset, we also implement and evaluate Physics Informed Neural Networks (PINN), Fourier Neural Operators (FNO), and UNet models as baselines, and explore the impact of ensembling strategies on prediction accuracy. With this combination of our dataset and baseline models drawn from the literature we aim to provide a standardized and challenging benchmark for evaluating machine learning approaches to solid mechanics. Our results highlight both the promise and limitations of popular current models, and demonstrate the utility of this dataset as a testbed for advancing machine learning in fracture mechanics research.

Benchmark dataset↗

DOE OSTI2024

The role of Li doping in layered/layered Na x Li y Ni 0.4 Fe 0.2 Mn 0.4 O 2 intergrowth electrodes for sodium ion batteries

Here, the layered NaTMO 2 (TM = Ni, Fe, Mn) materials with the O3-type structure are attractive as positive electrodes for sodium ion batteries because of their high theoretical capacity. Additionally, Li doping in these materials has been shown to offer substantial enhancements to their electrochemical properties by promoting the formation of intergrowth structures, which are combinations of specific phases. However, the mechanism by which the intergrowth modifies the electrochemical properties is often unclear. Systematic variation of Li content in Na x Li y Ni 0.4 Fe 0.2 Mn 0.4 O 2 (NFM-Li y ) was conducted to identify its role in structural modification and electrochemical performance. Li contents of 0.15 and greater generate a layered/layered Na-O3/Li-O’3 intergrowth structure. 7 Li and 23 Na nuclear magnetic resonance and x-ray absorption spectroscopy identify that when the total solubility for alkali ions in the layered structure is exceeded, Li continues to form the Li-O’3 phase while the excess Na forms residual sodium compounds such as Na 2 O. Higher Li content is associated with improved capacity retention in the initial cycles from the superior stability of the mechanically linked NaO3/Li-O’3 structure that suppresses the P3 to OP2 phase transition during charge. However, high Li contents are associated with increased rates of parasitic side reactions that reduce long-term cycling stability. These side reactions are associated with the instability of the cathode-electrolyte interphase, which can be partially mitigated by atomic layer deposition (ALD) coating with alumina, which significantly enhances the capacity retention and Coulombic efficiency over many cycles. Overall, we find that the layered/layered Na-O3/Li-O’3 intergrowth structure is able to provide structural stability and suppress undesired phase transformations but is overwhelmed by the increased reactivity of the surface if not protected by surface coating.

25 ENERGY STORAGE↗

DOE OSTI2021

Nonadiabatic molecular dynamics analysis of hybrid Dion–Jacobson 2D leads iodide perovskites

The past six years have witnessed the rapid growth of interest in Dion–Jacobson (DJ) phase two-dimensional (2D) hybrid halide perovskites as optoelectronic materials with considerable intrinsic stability. The precise relationships between structural variations and the resulting charge carrier dynamics at finite temperature in these materials are keys to practical applications and are not yet completely understood. Here, we study 3-(aminomethyl) piperidinium (3AMP) and 4-(aminomethyl) piperidinium (4AMP) spacer cation-based lead iodide DJ phase systems and find these spacer cations to have a profound impact on the structural dynamics. Particularly, large conformational dynamics of the 3AMP-based perovskite compared to that of the 4AMP at room temperature leads to pronounced state energy fluctuation near band edges and further results in a shorter quantum coherence. The faster quantum decoherence of the 3AMP spacer-based perovskite underpins a longer nonradiative lifetime, offering insight into its superior performance as an optoelectronic material. This work sheds light on the relationship between structural fluctuations and charge carrier dynamics that can help in designing 2D perovskites with superior photophysical properties.

Wang, Ying (ORCID:0000000349048227)↗

DOE OSTI2025

Algorithms for coordinate reconstruction in position-sensitive virtual Frisch-grid detectors

Arrays of position-sensitive virtual Frisch-grid (VFG) CdZnTe (CZT) detectors provide a cost-effective solution for integrating large-area arrays for gamma-ray imaging and spectroscopy. These detectors employ high-aspect ratio CZT crystals (bars) with thicknesses up to 50 mm and cross-sections of up to 10 × 10 mm 2 . Despite the long drift distances of charge carriers in such crystals, the detectors have demonstrated excellent performance, achieving energy resolutions better than 1 % full width at half maximum (FWHM) at 662 keV and 3D position resolutions finer than 1 mm. The high spatial resolution is a critical feature of these detectors, as it enables correction of response non-uniformities caused by crystal defects, which remain present even in the highest-quality CZT material. Dislocations and dislocation walls are the primary defects responsible for variations in charge carrier losses as they drift from the interaction points toward the charge-collecting electrodes. The mechanism by which these defects affect carrier transport is generally well understood. Dislocations and sub-grain boundaries act as sinks for carrier-trapping centers, primarily impurities and secondary phases such as tellurium inclusions and precipitates. Here, these regions exhibit significantly higher carrier-trapping rates, leading to variations in the μτ-products. Because the locations of these micron-sized regions are fixed within the detector volume, fluctuations in the total collected charge arise from the random distribution of interaction sites. This results in non-uniform detector responses and degradation of energy resolution. However, by measuring the interaction-site locations with sufficient precision, charge-loss variations can be accurately corrected, allowing recovery of nearly intrinsic energy resolution.

47 OTHER INSTRUMENTATION↗

DOE OSTI2022

Reducing the cost of energy estimation in the variational quantum eigensolver algorithm with robust amplitude estimation

Quantum chemistry and materials is one of the most promising applications of quantum computing. Yet much work is still to be done in matching industry-relevant problems in these areas with quantum algorithms that can solve them. Most previous efforts have carried out resource estimations for quantum algorithms run on large-scale fault-tolerant architectures, which include the quantum phase estimation algorithm. In contrast, few have assessed the performance of near-term quantum algorithms, which include the variational quantum eigensolver (VQE) algorithm. Recently, a large-scale benchmark study [Gonthier et al. 2020] found evidence that the performance of the variational quantum eigensolver for a set of industry-relevant molecules may be too inefficient to be of practical use. This motivates the need for developing and assessing methods that improve the efficiency of VQE. In this work, we predict the runtime of the energy estimation subroutine of VQE when using robust amplitude estimation (RAE) to estimate Pauli expectation values. Under conservative assumptions, our resource estimation predicts that RAE can reduce the runtime over the standard estimation method in VQE by one to two orders of magnitude. Despite this improvement, we find that the runtimes are still too large to be practical. These findings motivate two complementary efforts towards quantum advantage: 1) the investigation of more efficient near-term methods for ground state energy estimation and 2) the development of problem instances that are of industrial value and classically challenging, but better suited to quantum computation.

Johnson, Peter D.↗

DOE OSTI2022

Vapor-Phase Aggregation of Cerium Oxide Nanoparticles in a Rapidly Cooling Plasma

Local conditions, such as temperature and oxygen availability, have a pronounced effect on the formation and evolution of fallout following a nuclear explosion. While the behavior of nuclear-relevant materials such as uranium has begun to be explored under a wider range of environments, little is known about the behavior of plutonium. Here, using cerium as a surrogate, we track the vapor-phase aggregation of cerium oxide nanoparticles created in a plasma flow reactor under conditions of controlled temperature at two different oxygen fugacities. In situ optical emission spectroscopy is used to measure the variations in the spectral intensity of atomic and molecular species with temperature and oxygen content. We find that the relative rate of gas-phase oxidation of cerium is highly dependent on both temperature and local redox conditions within the flow reactor, to the extent that doubling the oxygen availability effectively doubles the amount of vapor-phase cerium monoxide at high temperatures (>2000 K). Condensed cerium oxide nanoparticles are also collected and analyzed ex situ via transmission electron microscopy and grazing-incidence small-angle X-ray scattering to determine their elemental composition, crystal structure, and size distribution. The size and morphology of the condensed nanoparticles are independent of local redox conditions, forming the same crystal type with the same size distribution regardless of oxygen availability. Postcondensation particle evolution, however, is found to be predominantly driven by temperature, with the average particle size increasing as particles cool and subsequently aggregate. These results expand our understanding of the chemical and physical behavior of refractory oxides that form during the early stages of fallout formation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

The influence of cooling rates on strain phase diagrams and domain structures of ferroelectric thin films: A case study of PbTiO 3

Strain engineering has been established as an effective approach to control phase equilibria, domain configurations, and functional properties of ferroelectric thin films. Temperature-strain phase diagrams have been used as powerful tools for providing insights into strain engineering. However, almost all existing phase diagrams established using the phase-field approach assume quenching conditions without considering actual cooling rates during the post-deposition annealing process of ferroelectric thin films. Within this work, we systematically investigate the influence of cooling rates on domain structures and the strain-phase diagram of ferroelectric thin films using phase-field simulations, taking PbTiO 3 thin films as a model system. We found that both the position of phase boundaries in the strain phase diagrams and the domain morphology are significantly influenced by the cooling rates. It is revealed that while the paraelectric-ferroelectric phase boundary remains invariant, the phase boundaries between single-phase and multi-phase regions tend to shift toward the corresponding multi-phase region as the cool rate reduces. Slow cooling generally leads to more ordered domain structures with increased domain size. Using the obtained equilibrium domain structures, we calculated effective thermal conductivities and found significant variations that can be tuned by the cooling rates. In conclusion, this work reveals an underexplored yet critical impact of cooling rates on phase equilibria and domain structures in ferroelectric thin films, which may inspire further fine-tuning of domains and domain walls in low-dimensional ferroelectrics for multifunctional applications.

Domain structures↗

DOE OSTI2025

Distinctive features of structural evolution and thermodynamic response in wide-bandgap semiconductors driven by intense electronic excitation

Radiation-tolerant material selection requires balancing lattice rigidity, defect dynamics, and electronic stability, as shown by covalent SiC outperforming ionic Ga 2 O 3 and GaN under extreme environments. Responding to intense electronic excitation, irradiation-driven phase segregation (β → δ/κ in Ga 2 O 3 ) and core–shell track (disordered structure in GaN), accompanied by elemental redistribution, contrastingly, exceptional radiation tolerance manifested by comparatively minimal lattice distortion (0.17 % strain variation) was demonstrated in SiC. These differential responses are primarily attributed to two fundamental mechanisms: (i) thermodynamic driving forces governing defect migration and phase separation, and (ii) the synergistic effects of robust covalent bonding composition coupled with efficient defect recombination processes. Here, the stronger electron–phonon (e-ph) coupling in Ga 2 O 3 (4.34 × 1018 W m −3 K −1 ) and GaN (3.55 × 10 18 W m −3 K −1 ) enhances lattice energy deposition, triggering thermal spikes (ΔT ≫ T m ) and structural transition behaviors, whereas weaker e-ph coupling in SiC (3.69 × 10 18 W m −3 K −1 ), relatively high thermodynamic parameters and efficient energy dissipation suppress thermal spikes to maintaining lattice integrity. The photoresponse degradation driven by enhanced radiative recombination is dominant in N-doped SiC, while V-doped systems achieve defect-mediated photoconduction optimization characterized by abrupt current transitions, matching fluorescence yield evolutions, and directly connecting defect engineering to optoelectronic performance.

Intense electronic excitation↗

DOE OSTI2025

Directed energy deposition of radially functionally graded nickel based superalloys IN625 and IN738: Microstructure and mechanical properties

This study investigates the microstructure and mechanical properties of radially functionally graded (RFG) materials fabricated from nickel-based superalloys IN625 and IN738 using directed energy deposition (DED). RFG cylindrical deposits with radial gradients of IN625-IN738 and IN738-IN625 were successfully fabricated and confirmed to be crack-free through tailored composition grading, scan strategy and process parameters that minimized thermal gradients and solidification velocities. Microstructural analysis revealed distinct variations across the gradient, characterized by differences in dendrite arm spacing, microsegregation, and the formation of distinct γ' precipitates and carbide/boride phases (MC, M 6 C, M 2 C, and MB 2 ) in as-deposited (AD) conditions, which evolved into M 23 C 6 and M 2 B upon subsequent heat treatment (HT). EBSD showed predominant columnar grains with a [100] texture, while microhardness profiles demonstrated consistent variation across the gradients. Mechanical testing highlighted the synergy of the graded structure, combining IN738's strength with IN625's ductility, resulting in enhanced properties such as a yield strength of 1131 MPa, ultimate tensile strength of 1382 MPa, and elongation of 12 % for HT IN625-IN738 grading. Numerical simulations employing CALPHAD thermodynamic calculations and finite element thermal modeling are used to establish phase evolution and microstructural feature correlation with thermal profiles, aiding in the optimization of process-structure-property relationship.

Additive manufacturing↗

DOE OSTI2023

Modeling starch dynamics from seasonal variations of photosynthesis, growth and respiration

Abstract Nonstructural carbohydrates (NSCs) buffer differences in plant carbon supply (photosynthesis) and demand (respiration, growth, etc.), but the regulation of their dynamics remains unresolved. Seasonal variations in NSCs are well-documented, but differences in the time-average, amplitude, phase and other characteristics across ecosystems and functional types lack explanation; furthermore, observed dynamics do not always match expectations. The failure to match observed and expected dynamics has stimulated debate on whether carbon supply or demand drives NSC dynamics. To gain insight into how carbon supply and demand drive seasonal NSC dynamics, we derive a simple model of NSC dynamics based on carbon mass balance and linearizing the NSC demand to determine how supply-driven and demand-driven seasonal NSC dynamics differ. We find that supply-driven and demand-driven dynamics yield distinct timings of seasonal extrema, and supply overrides demand when carbon supply is low in winter (e.g., at high latitudes). Our results also suggest that NSC dynamics often lag changes carbon mass balance. We also predict differences in NSC dynamics across mass, suggesting that saplings are more dynamic and respond more quickly to the environment than mature trees. Our findings suggest that substrate-dependent regulation with environmental variation is sufficient to generate complex NSC dynamics.

Forestry↗

DOE OSTI2020

Residual Stress Modeling with Phase Transformation for Wire Arc Additive Manufacturing of B91 Steel

Wire arc additive manufacturing (WAAM) is an energy-efficient manufacturing technique used for near-net-shape production of functional industrial components. However, heat accumulation during deposition and the associated mechanical and metallurgical changes result in complex residual stress profiles across the cross section of the fabricated components. These residual stresses are detrimental to the service life of the components. In this study, sequentially coupled thermomechanical analysis of WAAM B91 steel is conducted to quantify the residual stress variation across the component. The thermomechanical analysis includes a transient heat transfer model and a static stress model that incorporates the transformation-induced plasticity due to martensitic phase transformation. Here, the experimentally calibrated heat transfer model mirrors the temperature variation of the system during the deposition. The results from the stress model are validated via x-ray diffraction measurements, and the numerical results are in good agreement with the experimental data.

20 FOSSIL-FUELED POWER PLANTS↗