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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Piezochromic Behavior of 2,4,6-Triphenylpyrylium Tetrachloroferrate

In advanced photonics, there is a growing interest in piezochromic luminescent materials that exhibit multicolor switching, driven by their potential applications in optical recording, memory, and sensors. Here, the piezochromic behavior of 2,4,6-triphenylpyrylium tetrachloroferrate (Py-FeCl 4 ) under high pressures from 0 to 9 GPa is reported. The observed multicolor changing properties of Py-FeCl 4 (yellow–orange–red–maroon–black) are found to be fully reversible upon decompression to ambient conditions. The mechanism of Py-FeCl 4 piezochromism is investigated via Raman, infrared, and UV–vis spectroscopy combined with powder X-ray Diffraction. The absence of structural phase transitions as well as the abrupt shifts of bandgap values together with characteristic Raman and IR peaks within 0-9 GPa suggests that the Py-FeCl 4 multicoloring switching behavior is driven by an electron transfer between the inorganic FeCl 4 – anion and the organic pyrylium cation. The obtained results demonstrate that Py-FeCl 4 dye is a good candidate for developing high-pressure sensing technologies designed to function in extreme environments. Moreover, due to the inherent role of molecular-structure relationships in the pyrylium salt's photophysical properties, findings suggest the potential discovery of piezochromic behavior in other pyrylium compounds.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

Reconstruction of Six-Dimensional Phase Space

A phase space is a mathematical representation of all possible physical states of a system. Particle beams at Fermilab exist within a six-dimensional (6D) phase space defined by three positional components, (x, y, z) and three momentum components, (px, py, pz). To reconstruct this space implies taking measurement data from detectors and mapping out particle behavior using computational methods. The beam detectors, however, are only able to detect spatial distribution among the events of the beam, therefore being limited to positional data. Also, due to the vast number of events in a particle beam, it is extremely difficult to analyze and differentiate every single one’s behavior. However, with Machine Learning (ML), which can distinguish between patterns and map out particle behavior more efficiently. We first used the particle beam software, G4beamline, to simulate a 10,000-event muon beam, adjusting parameters such as initial momentum magnitude (p¬0) and virtual detector position. Using ten virtual detectors, we analyzed p0 values such that minimum 9,990 events were analyzed by every detector. We then input the data from these beam simulations to a C++ program, that randomly selects 100 events, and creates a 2D histogram based on spatial distribution, detector position, and event intensity. This process is repeated 100 times to create 100 histograms per p0 value. These images were then input to a modified ResNet18 Convolutional Neural Network (CNN) for training, and to predict p0 from some unseen set of histograms. The model was accurate when trained on momentum increments of 5 MeV/c and provided with denser training samples around highly variable test values. These results displayed machine learning being able to accurately predict p0 from being trained on different particle behaviors.

Shirlee, Jermain [Fermilab]↗
DOE OSTI2023

Establishing metrics to quantify spatial similarity in spherical and red blood cell distributions

As computational power increases and systems with millions of red blood cells can be simulated, it is important to note that varying spatial distributions of cells may affect simulation outcomes. Since a single simulation may not represent the ensemble behavior, many different configurations may need to be sampled to adequately assess the entire collection of potential cell arrangements. In order to determine both the number of distributions needed and which ones to run, we must first establish methods to identify well-generated, randomly placed cell distributions and to quantify distinct cell configurations. We utilize metrics to assess (1) the presence of any underlying structure to the initial cell distribution and (2) similarity between cell configurations. We propose the use of the radial distribution function to identify long-range structure in a cell configuration and apply it to a randomly distributed and structured set of red blood cells. To quantify spatial similarity between two configurations, we make use of the Jaccard index, and characterize sets of red blood cell and sphere initializations. As an extension to our work submitted to the International Conference on Computational Science, we significantly increase our data set size from 72 to 1048 cells, include a similar set of studies using spheres, compare the effects of varying sphere size, and utilize the Jaccard index distribution to probe sets of extremely similar configurations. Our results show that the radial distribution function can be used as a metric to determine long-range structure in both distributions of spheres and RBCs. We determine that the ideal case of spheres within a cube versus bi-concave shaped cells within a cylinder affects the shape of the Jaccard index distributions, as well as the range of Jaccard values, showing that both the shape of particle and the domain may play a role. Furthermore, we also find that the distribution is able to capture very similar configurations through Jaccard index values greater than 95% when appending several nearly identical configurations into the data set.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Second harmonic generation in topological insulators under quantizing magnetic fields

We theoretically investigate the second harmonic generation (SHG) of topological insulator surface states in a perpendicular magnetic field. Our theory is based on the microscopic expression of the second-order magneto-optical conductivity developed from the density matrix formalism, taking into account hexagonal warping effects on the surface states' band structure. Using numerically exact Landau-level energies and wave functions including hexagonal warping, we calculate the spectrum of SHG conductivities under normal incidence for different values of magnetic field and chemical potential. The imaginary parts of the SHG conductivities show prominent resonant peaks corresponding to one-photon and two-photon inter-Landau-level transitions. Treating the hexagonal warping term perturbatively, these transitions are clarified analytically within a perturbation theory from which approximate selection rules for the allowable optical transitions for SHG are determined. Furthermore, our results show extremely high SHG susceptibility that is easily tunable by magnetic field and doping level for topological surface states in the far-infrared regime, exceeding that of many conventional nonlinear materials. This work highlights the key role of hexagonal warping effects in generating second-order optical responses and provides insights into the nonlinear magneto-optical properties of the topological insulators.

Landau levels↗
DOE OSTI2021

Power Distribution Designing For Resilience Application

The number of power outages have been on the rise as extreme weather patterns have been occurring more frequently due to climate change. These outages have an economic impact in the billions of dollar. The modernization of the power grid and adoption of high penetration of distributed generation such as wind and solar have the potential to reduce the number and length of time of these power outages. However, planners and operators need a way to value the resilience the distributed assets provide to the grid. PowDDeR is a tool that allows them to evaluate the resilience each asset provides as well as how they provide resilience over the connected network.

Phillips, TylerB↗
DOE OSTI2025

Machine learning for fundamental spectroscopic and thermodynamic data of actinides and lanthanides

Accurately modeling optical spectra with absolute radiometric intensities is vital for nuclear forensics applications that depend on characterizing optical emissions from energetic nuclear phenomena. This requires precise knowledge of the individual atomic transition probabilities, known as Einstein A-coefficients, for each emission line. Obtaining these values theoretically or experimentally is often impractical due to the complex electronic structures and the number of transitions involved in atoms relevant to nuclear applications. In this study, we explore the use of machine learning to predict the Einstein A coefficients for atomic transitions. Seven models were evaluated that ranged from deep learning to decision tree algorithms, and found that gradient boosting performed best, specifically the Extreme Gradient Boosting (XGB) architecture, achieving a precision of 86% across transitions of 36 elements. Furthermore, the model was cross-validated using published transition probabilities reported in the literature and applied to estimate Pu plasma temperatures from a previous experiment conducted at Savannah River National Laboratory.

Atomic spectroscopy↗
DOE OSTI2026

Optimized matching conditions for self-guided laser wakefield accelerators

We revisit the matching conditions for self-guided laser pulse propagation in plasma and refine their formulation to maximize the energy of electrons produced via laser wakefield acceleration. Bayesian optimization, combined with particle-in-cell simulations carried out in a quasi-three-dimensional geometry and a Lorentz-boosted frame, is employed. The optimization identifies the maximum electron energy that a self-guided laser wakefield accelerator, driven by a laser of a given energy, can produce, together with the corresponding acceleration distance. Our results further demonstrate that electrons with energies close to the maximum value can be obtained across a relatively wide range of input parameters and without the need for their precise tuning. This provides substantial flexibility for experimental implementation and significantly relaxes the operational constraints associated with self-guided laser wakefield accelerators.

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

Glass transition temperature studies of planetary ball milled glasses: Accessing the rapidly cooled glassy state in Na 4 P 2 S 7-x O x , 0 ≤ x ≤ 7, Oxy-thio phosphate glasses

This paper details the very first in-depth study of the glass transition temperature (T g ) for planetary balled milled (PBM) Na 4 P 2 S 7-x O x (NaPSO), where 0 ≤ x ≤ 7, glasses. For 0 ≤ x ≤ 5, fully amorphous, homogeneous, and chemically reacted compositions can be prepared. For samples with 5 < x ≤ 7, partially amorphous but fully chemically reacted glass-ceramics can be produced. The reproducible, thermally cyclable onset T g and the onset crystallization temperature, T c , were investigated as a function of the composition and of the short-range order (SRO) structures of the glasses. Additionally, we examined the extreme sub-T g exothermic relaxations present due to the high energy milling processing and correspondingly high effective quenching rate. Using a differential scanning calorimeter (DSC) and scanning from well below the onset T g , the glasses are observed to relax exothermally below T g . The integrated relaxation enthalpy, ΔH rel , is ~ 0 for the x = 2 glass, but is significantly exothermic for lower and higher values of x. Once the high fictive state of these glasses has been erased by scanning to above the T g , but below the T c of the glass, the DSC scans of the glasses recover normal behavior for a normally cooled glass without any relaxation exotherm. The T g s of these glasses remain relatively constant for 0 ≤ x ≤ 3, but for glasses with 3 < x ≤ 5, T g increases sharply following the combined effects of the phosphate chain length increasing caused by the formation of bridging oxygens and the increasing concentration of more charge dense non-bridging oxygens (NBOs). For x > 5, both T g and Tc decrease sharply, becoming nearly identical at x = 7 where glass formation essentially ceases. For smaller values of x, T c increases with both chain length and the structural complexity of the composition but decreases sharply for glass-ceramics of x > 5.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Synthesis and Thermal Oxidation Resistance of Boron-Rich Boron–Carbide Material

A boron-rich boron–carbide material (B4+δC) was synthesized by spark plasma sintering of a ball-milled mixture of high-purity boron powder and graphitic carbon at a pressure of 7 MPa and a temperature of 1930 °C. This high-pressure, high-temperature synthesized material was recovered and characterized by X-ray diffraction, X-ray photoelectron spectroscopy, Raman spectroscopy, Vickers hardness measurements, and thermal oxidation studies. The X-ray diffraction studies revealed a single-phase rhombohedral structure (space group R-3m) with lattice parameters in hexagonal representation as a = 5.609 ± 0.007 Å and c = 12.082 ± 0.02 Å. The experimental lattice parameters result in a value of δ = 0.55, or the composition of the synthesized compound as B4.55C. The high-resolution scans of boron binding energy reveal the existence of a B-C bond at 188.5 eV. Raman spectroscopy reveals the existence of a 386 cm−1 vibrational mode representative of C-B-B linear chain formation due to excess boron in the lattice. The measured Vickers microhardness at a load of 200 gf shows a high hardness value of 33.8 ± 2.3 GPa. Thermal gravimetric studies on B4.55C were conducted at a temperature of 1300 °C in a compressed dry air environment, and its behavior is compared to other high-temperature ceramic materials such as high-entropy transition metal boride. The high neutron absorption cross section, high melting point, high mechanical strength, and thermal oxidation resistance make this material ideal for applications in extreme environments.

36 MATERIALS SCIENCE↗
DOE OSTI2024

MgO Nanostructures on Cu(111): Understanding Size- and Morphology-Dependent CO 2 Binding and Hydrogenation

To design and optimize cost-effective technologies for the capture, utilization, and storage of carbon dioxide (CO 2 ), we need a fundamental knowledge and control of chemical interactions associated with the capture and conversion of the molecule into high-value chemicals, minerals, and all kinds of materials. Bulk magnesium oxide (MgO) is frequently used for the trapping and storage of CO 2 by generation of magnesium carbonates. In this study, the growth and reactivity of MgO nanostructures on a Cu 2 O/Cu(111) substrate were investigated using scanning tunneling microscopy (STM) and synchrotron-based ambient-pressure X-ray photoelectron spectroscopy (AP-XPS). For extremely small concentrations of Mg (~ 0.01 monolayer (ML)), a well-ordered film of copper oxide with small clusters (0.2-0.5 nm in width, 0.4-0.6 Å in height) of embedded MgO was seen. At a coverage of 0.1 ML, MgO nanoparticles with a width of 0.4 to 1 nm and a height of ~ 1.5 Å were randomly distributed on the copper oxide. Further, random distribution was also observed when the MgO coverage was raised to 0.25 ML, with the width of the MgO particles increasing to 2-2.5 nm and the height reaching 2 Å. These oxide nanostructures displayed a high reactivity towards CO 2 and H 2 that is not seen for bulk MgO. Dissociation of H 2 was observed at room temperature with reaction of the H adatoms with CuO x and C-containing groups. On the small MgO nanostructures (< 1 nm in width), instead of plain carbonate formation, there was dissociation of CO 2 into CO and C species, opening reaction channels for the conversion of this harmful molecule into oxygenates and light alkanes.

03 NATURAL GAS↗
DOE OSTI2021

Magnetic and dielectric property control in the multivalent nanoscale perovskite Eu 0.5 Ba 0.5 TiO 3

We report nanoscale Eu 0.5 Ba 0.5 TiO 3 , a multiferroic in the bulk and candidate in the search to quantify the electric dipole moment of the electron. Eu 0.5 Ba 0.5 TiO 3 , in the form of nanoparticles and other nanostructures is interesting for nanocomposite integration, biomedical imaging and fundamental research, based upon the prospect of polarizability, f-orbital magnetism and tunable optical/radio luminescence. We developed a [non-hydrolytic]sol–[H 2 O-activated]gel route, derived from in-house metallic Ba (s) /Eu (s) alkoxide precursors and Ti{(OCH(CH 3 ) 2 } 4 . Two distinct nanoscale compounds of Ba:Ti:Eu with the parent perovskite crystal structure were produced, with variable dielectric, magnetic and optical properties, based on altering the oxidizing/reducing conditions. Eu 0.5 Ba 0.5 TiO 3 prepared under air/O 2 atmospheres produced a spherical core–shell nanostructure (30–35 nm), with perovskite Eu 0.5 Ba 0.5 TiO 3 nanocrystal core-insulating oxide shell layer (~3 nm), presumed a pre-pyrochlore layer abundant with Eu 3+ . Fluorescence spectroscopy shows a high intensity 5 D 0 → 7 F 2 transition at 622 nm and strong red fluorescence. The core/shell structure demonstrated excellent capacitive properties: assembly into dielectric thin films gave low conductivity (2133 GΩ mm -1 ) and an extremely stable, low loss permittivity of ε eff ~25 over a wide frequency range (tan δ < 0.01, 100 kHz–2 MHz). Eu 0.5 Ba 0.5 TiO 3 prepared under H 2 /argon produced more irregular shaped nanocrystals (20–25) nm, with a thin film permittivity around 4 times greater ( ε eff 101, tan δ < 0.05, 10 kHz–2 MHz, σ ~59.54 kΩ mm -1 ). Field-cooled magnetization values of 0.025 emu g -1 for EBTO-Air and 0.84 emu g -1 for EBTO-Argon were observed. X-ray photoelectron spectroscopy analysis reveals a complex interplay of Eu II/III /Ti III/IV configurations which contribute to the observed ferroic and fluorescence behavior.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2025

Enhancing Drinking Water Quality Modeling: Leveraging Physics Informed Neural Networks for Learning with Imperfect Reaction Models and Partial Data

Chemical kinetics models, typically formulated as systems of ordinary or partial differential equations, are valuable tools for simulating drinking water quality. However, these models often face inaccuracies due to discrepancies between the laboratory and the real-world conditions, as well as limitations in experimental analytical methods, hindering the accurate representation of the true underlying chemical mechanisms. In this study, we propose a Physics Informed Neural Network (PINN), using the eXtreme Theory of Functional Connections, to improve the prediction of chemical concentrations over time. The PINN method accounts for imperfect chemical models and incorporates partial data to improve predictions. Focusing on reactions describing water disinfection residual and disinfectant byproduct formation, which are crucial for public health and regulatory compliance, we demonstrate that the PINN model is able to accurately predict the concentrations of chemical species across various pH values. Notably, the model extends its accuracy to predict concentrations of chemical species not originally included in its training data. The developed method can be extended to a variety of chemical systems, offering a wide array of potential applications.

13 HYDRO ENERGY↗
DOE OSTI2020

Unravelling competing microscopic interactions at a phase boundary: A single-crystal study of the metastable antiferromagnetic pyrochlore Yb 2 Ge 2 O 7

We report inelastic neutron scattering measurements from our newly synthesized single crystals of the structurally metastable antiferromagnetic pyrochlore Yb 2 Ge 2 O 7 . We determine the four symmetry-allowed nearest-neighbor anisotropic exchange parameters via fits to linear spin wave theory supplemented by fits of the high-temperature specific heat using the numerical linked-cluster expansion method. The exchange parameters so-determined are strongly correlated to the values determined for the g-tensor components, as previously noted for the related Yb pyrochlore Yb 2 Ti 2 O 7 . To address this issue, we directly determined the g-tensor from electron paramagnetic resonance of 1% Yb-doped Lu 2 Ge 2 O 7 , thus enabling an unambiguous determination of the exchange parameters. Our results show that Yb 2 Ge 2 O 7 resides extremely close to the classical phase boundary between an antiferromagnetic Γ 5 phase and a splayed ferromagnet phase. By juxtaposing our results with recent ones on Yb 2 Ti 2 O 7 , our work illustrates that the Yb pyrochlore oxides represent ideal systems for studying quantum magnets in close proximity to classical phase boundaries.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

High efficiency Al/Sc-based multilayer coatings in the EUV wavelength range above 40 nanometers

In this Letter, we have developed new and highly efficient periodic multilayer mirrors Al/Sc, Al/Sc/SiC, and Mo/Al/Sc with optimized reflectance at wavelengths between 40 and 65 nm. We have reached record values in measured peak reflectance: 57.5% at 44.7 nm and 46.5% at 51 nm, with Al/Sc/SiC at near-normal incidence. Furthermore, to the best of our knowledge, we have achieved the largest reported bandwidth with Mo/Al/Sc at 57 nm and the narrowest bandwidth with Al/Sc at a 60 nm wavelength. These new and promising results demonstrate that Al/Sc-based multilayer coatings are excellent candidates for future generations of extreme ultraviolet (EUV) instruments for solar physics, EUV lasers, and attosecond science, in a wavelength range that has not been fully explored.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Effects of grain size and small-scale bedform architecture on CO 2 saturation from buoyancy-driven flow

Small-scale (mm-dm scale) heterogeneity has been shown to significantly impact CO 2 migration and trapping. To investigate how and why different aspects of small-scale heterogeneity affect the amount of capillary trapping during buoyancy-driven upward migration of CO 2 , we conducted modified invasion percolation simulations on heterogeneous domains. Realistic simulation domains are constructed by varying two important aspects of small-scale geologic heterogeneity: sedimentary bedform architecture and grain size contrast between the matrix and the laminae facies. Buoyancy-driven flow simulation runs cover 59 bedform architecture and 40 grain size contrast cases. Simulation results show that the domain effective CO 2 saturation is strongly affected by both grain size and bedform architecture. At high grain size contrasts, bedforms with continuous ripple lamination at the cm scale tend to retain higher CO 2 saturation than bedforms with discontinuous or cross lamination. In addition, the “extremely well sorted” grain sorting cases tend to have lower CO 2 saturation than expected for cross-laminated domains. Finally, both a denser CO 2 phase and greater interfacial tension increase CO 2 saturation. Again, variation in fluid properties seems to have a greater effect on CO 2 saturation for cross-laminated domains. This result suggests that differences in bedform architecture can impact how CO 2 saturation values respond to other variables such as grain sorting and fluid properties.

58 GEOSCIENCES↗
DOE OSTI2025

An integrated integral projection model ( IPM 2 ) to disentangle size‐structured harvest and natural mortality

Abstract Body size is one of the most important traits governing individual‐level demographic rates and modulating population‐level processes. Multiple size‐dependent demographic rates can simultaneously change population structure, so distinguishing their individual contributions to overall population dynamics remains a challenge. Disentangling size‐dependent harvest rates from other demographic rates is critical for assessing the impact of removal on populations of invasive species. Inference about invasive populations can be difficult, however, as observations are often collected opportunistically as part of removal programs, rather than experimentally designed. Yet accurate inference is essential for understanding the feasibility of population suppression and optimising management decisions. We develop an integrated integral projection model (IPM 2 ) that leverages the strengths of the integrated population model and integral projection model to enable inference about complex, size‐structured demographic rates from imperfect observations. We apply the IPM 2 in the context of invasive European green crab ( Carcinus maenas ), a species for which individual body size strongly regulates both the observation‐generating process and latent, population dynamics. The IPM 2 facilitates the distinct estimation of green crab size‐structured harvest and natural mortality rates, parameters for which no explicit data is collected and that are unidentifiable in component datasets of the integrated population model. The model represents how the green crab population changes over time, providing the first estimates of size‐structured abundance of this high‐priority species. By forecasting the stable size distribution and equilibrium population size under varying removal efforts, we demonstrate that extremely high levels of removal effort can reduce the equilibrium green crab population size. Yet these high mortality rates also shift the stable size distribution and increase the equilibrium abundance of smaller crabs, since size‐selective removal alters intraspecific interactions. The ecological outcome of this shift in size structure will be variable, as green crab size modulates only some of its interactions with other species. These results highlight the value of the IPM 2 framework for inferring complex population dynamics with information needs that outpace information in individual observational datasets, providing a path forward for accurate assessment of conservation programs.

Keller, Abigail G. [Department of Environment Scie↗
DOE OSTI2020

Pseudoscalar pair production via off-shell Higgs in composite Higgs models

We propose a new type of search for a pseudoscalar particle $\eta$ pair produced via an off-shell Higgs, $pp$ → $h*$ → $\eta\eta$. The search is motivated by a composite Higgs model in which the $\eta$ is extremely narrow and decays almost exclusively into Z in the mass range 65 $\lesssim$ GeV $m_{\eta}$ $\lesssim$ 160 GeV. We devise an analysis strategy to observe the novel Zγ Zγ channel and estimate potential bounds on the Higgs-$\eta$ coupling. The experimental sensitivity to the signatures depends on the power to identify fake photons and on the ability to predict large photon multiplicities. This search allows us to exclude large values of the compositeness scale $f$, being thus complementary to other typical processes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗