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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 1,369 records · Page 76
All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

Presolar Organic Globules in Astromaterials

Presolar grains were identified in meteorite residues 20 years ago based on their exotic isotopic compositions [1]. Their study has provide new insights into stellar evolution and the first view of the original building blocks of the solar system. Organic matter in meteorites and IDPs is highly enriched in D/H and N-15/N-14 at micron scales, possibly due to presolar organic grains [2-4]. These anomalies are ascribed to the partial preservation of presolar cold molecular cloud material. Identifying the carriers of these anomalies and elucidating their physical and chemical properties may give new views of interstellar chemistry and better understanding of the original components of the protosolar disk. However, identifying the carriers has been hampered by their small size and the inability to chemically isolate them. Thanks to major advances in nano-scale analytical techniques and advanced sample preparation, we were able to show that in the Tagish Lake meteorite, the principle carriers of these isotopic anomalies are sub-microns, hollow organic globules [5]. The organic globules likely formed by photochemical processing of organic ices in a cold molecular cloud or the outermost regions of the protosolar disk [5]. Organic globules with similar physical, chemical, and isotopic properties are also recently found from Bells CM2 carbonaceous chondrite, in IDPs [6] and in the comet Wild-2 samples returned by Stardust [7]. These results support the view that microscopic organic grains were widespread constituents of the protoplanetary disk. Their exotic isotopic compositions trace their origins to the outermost portions of the protosolar disk or a presolar cold molecular cloud.

Nakamura-Messenger, K.↗
DOE OSTI2023

Hyperfine structure and isotope shifts of xenon measured for near-infrared transitions with Doppler-free saturated absorption spectroscopy

Hyperfine structure and isotope shifts of Xe were investigated with Doppler-free saturated absorption spectroscopy for all transitions in the 820-841 nm spectral interval. The Xe samples were commercial gases of natural isotopic abundances. The measurements were performed by employing a widely tunable narrow line Ti:sapphire laser. The hyperfine structures for 129 Xe and 131 Xe were well resolved. For the transitions with the wavelengths in vacuum near 820.860 nm and 841.150 nm also isotope shifts of the even isotopes were clearly observed. The modeling of the shapes of the observed absorption lines qualitatively reproduces experimental spectral profiles. The measured absorption peaks of the hyperfine structure and isotope shifts of Xe isotopes present characteristic spectral fingerprints for their identification. Eventually, quantitative spectral analysis will provide isotopic abundances of natural, as well as radioactive Xe gas samples.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

AI-NERD: Elucidation of relaxation dynamics beyond equilibrium through AI-informed X-ray photon correlation spectroscopy

Abstract Understanding and interpreting dynamics of functional materials in situ is a grand challenge in physics and materials science due to the difficulty of experimentally probing materials at varied length and time scales. X-ray photon correlation spectroscopy (XPCS) is uniquely well-suited for characterizing materials dynamics over wide-ranging time scales. However, spatial and temporal heterogeneity in material behavior can make interpretation of experimental XPCS data difficult. In this work, we have developed an unsupervised deep learning (DL) framework for automated classification of relaxation dynamics from experimental data without requiring any prior physical knowledge of the system. We demonstrate how this method can be used to accelerate exploration of large datasets to identify samples of interest, and we apply this approach to directly correlate microscopic dynamics with macroscopic properties of a model system. Importantly, this DL framework is material and process agnostic, marking a concrete step towards autonomous materials discovery.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Embedding physics domain knowledge into a Bayesian network enables layer-by-layer process innovation for photovoltaics

Process optimization of photovoltaic devices is a time-intensive, trial-and-error endeavor, which lacks full transparency of the underlying physics and relies on user-imposed constraints that may or may not lead to a global optimum. Herein, we demonstrate that embedding physics domain knowledge into a Bayesian network enables an optimization approach for gallium arsenide (GaAs) solar cells that identifies the root cause(s) of underperformance with layer-by-layer resolution and reveals alternative optimal process windows beyond traditional black-box optimization. Our Bayesian network approach links a key GaAs process variable (growth temperature) to material descriptors (bulk and interface properties, e.g., bulk lifetime, doping, and surface recombination) and device performance parameters (e.g., cell efficiency). For this purpose, we combine a Bayesian inference framework with a neural network surrogate device-physics model that is 100× faster than numerical solvers. With the trained surrogate model and only a small number of experimental samples, our approach reduces significantly the time-consuming intervention and characterization required by the experimentalist. As a demonstration of our method, in only five metal organic chemical vapor depositions, we identify a superior growth temperature profile for the window, bulk, and back surface field layer of a GaAs solar cell, without any secondary measurements, and demonstrate a 6.5% relative AM1.5G efficiency improvement above traditional grid search methods.

14 SOLAR ENERGY↗
DOE OSTI2024

Reduced-order model to approximate response matrices for filter stack spectrometers

We present a reduced-order model to calculate response matrices rapidly for filter stack spectrometers (FSSs). The reduced-order model allows response matrices to be built modularly from a set of pre-computed photon and electron transport and scattering calculations through various filter and detector materials. While these modular response matrices are not appropriate for high-fidelity analysis of experimental data, they encode sufficient physics to be used as a forward model in design optimization studies of FSSs, particularly for machine learning approaches that require sampling and testing a large number of FSS designs.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Extending the Nuclide Inventory Validation Basis for High-Burnup Fuel with New Radiochemical Assay Data

Efforts are underway at Oak Ridge National Laboratory to improve the nuclide inventory validation basis for spent nuclear fuel at high burnups. Recently conducted radiochemical assay experiments provided new measurement data for nine samples of fuel irradiated in a pressurized water reactor, with estimated sample burnups in the 30 to 70 GWd/t range. This type of destructive assay data is essential for validating computational methods, tools, and nuclear data applied in nuclear safety analyses and for improving our understanding of the bias and uncertainty in code predictions. The measurement data include key actinides and fission products that span a gamut of needs and interests for nuclear science and engineering applications in criticality safety, reactor physics, nuclide inventory, decay heat, and radiation shielding. The SCALE 6.3 code system with ENDF/B-VII.1 cross-section libraries was used to simulate the irradiation histories of the measured fuel samples. The calculated nuclide concentrations are compared to corresponding measurement data. The significance of the comparisons is discussed, emphasizing how the addition of the new measurement data fills gaps in the validation basis at high burnups and contributes to the decrease in bias and uncertainty for predicted nuclide concentrations. The discussion addresses the effect of the sample burnup used in the simulation—which is based on reactor operator records or on calibration to measured data for burnup indicator fission products—on the validation results.

Nuclide inventory↗
DOE OSTI2025

Polarization-shape alignment of IllustrisTNG star-forming galaxies

In star-forming disk galaxies, the radio continuum emission (1–10GHz) powered by star formation has an integrated polarization direction imperfectly aligned with the apparent disk minor axis. This polarization-shape alignment effect was previously observed in a small sample of local spirals. If this is prevalent for disk galaxies out to cosmological redshifts, novel measurements of cosmic birefringence and cosmic shear will be enabled by leveraging radio continuum surveys such as the Square Kilometre Array synergized with galaxy shape measurements. We calculate the polarization-shape misalignment angle for star-forming galaxies in the IllustrisTNG50 simulation at 0 < z < 2, assuming that additional polarized radio emission from an active galactic nucleus is negligible in at least a sizable fraction of the star-forming galaxies. The alignment found for z = 0 is consistent with local spiral data, but significantly deteriorates as redshift increases. Moreover, it degrades toward lower frequencies due to internal Faraday depolarization. Thanks to cosmic redshifting, observing higher-z galaxies at a fixed frequency greatly mitigates degradation due to reduced Faraday depolarization at the source-frame frequency. We present analytic fits to the non-Gaussian misalignment angle distribution, and evaluate Fisher information per galaxy for measuring a polarization rotation angle induced by cosmic birefringence. For observation at 4.8 GHz, the effective root-mean-square misalignment angle σα,eff is 18°, 23° and 33° at z = 0, 1 and 2, respectively. Analyzing N independent galaxies reduces the uncertainty on an isotropic cosmic birefringence signal to σ α,eff /√(N), providing competitive sensitivity once large samples are available. As accurate observation-driven models are not yet available for cosmological galaxy samples, our results motivate pilot observations to empirically characterize polarization-shape alignment, and can facilitate forecasts of cosmology and fundamental physics applications that exploit this effect.

axions↗
DOE OSTI2024

Prediction of the Cu Oxidation State from EELS and XAS Spectra Using Supervised Machine Learning

Electron energy loss spectroscopy (EELS) and X-ray absorption spectroscopy (XAS) provide detailed information about distributions and locations of atoms, their coordination numbers and oxidation states, and the bonding characteristics [1]. However, analysis of XAS/EELS data often relies on matching the spectra of an unknown experimental sample to a series of simulated or experimental spectra of standard samples. Here, this limits analysis throughput and the ability to extract quantitative information from a sample.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Thermal transport in compensated semimetals: Effect of electron-electron scattering on Lorenz ratio

It is well known that the electronic thermal conductivity of clean compensated semimetals can be greatly enhanced over the electric conductivity by the availability of an ambipolar mechanism of conduction, whereby electrons and holes flow in the same direction experiencing negligible Coulomb scattering as well as negligible impurity scattering. This enhancement—resulting in a breakdown of the Wiedemann-Franz law with an anomalously large Lorenz ratio—has been recently observed in two-dimensional monolayer and bilayer graphene near the charge neutrality point. In contrast to this, three-dimensional compensated semimetals such as WP 2 and Sb are typically found to show a reduced Lorenz ratio. Here, we investigate the reasons for this difference, focusing on the low-temperature regime where the electron-electron scattering is expected to dominate over other scattering mechanisms. We show that the different regimes of Fermi statistics (nondegenerate electron-hole liquid in graphene versus degenerate electron-hole liquid in compensated semimetals) are not sufficient to explain the reduction of the Lorenz ratio in the latter. We propose that the solution of the puzzle lies in the large separation of electron and hole pockets in momentum space, which allows compensated semimetals to sustain sizable regions of electron-hole accumulation near the contacts. These accumulations suppress the ambipolar conduction mechanism and effectively split the system into two independent electron and hole conductors. We present a quantitative theory of the crossover from ambipolar to unipolar conduction as a function of the size of the electron-hole accumulation regions, and show that it naturally leads to a sample-size-dependent thermal conductivity.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

GP Cosmology Surrogate v1.0

GP Cosmology Surrogate is a Python library for building and training a generalized multi-output Gaussian process (GP) framework of @takhtaganov2021cosmic. In this approach, the surrogate is constructed sequentially, guided by a Bayesian optimization acquisition function that targets reduction of emulation error in the regions most consistent with the observational data. This adaptive design concentrates computational resources where they have the greatest impact on inference accuracy. The library supports efficient training for separable GP kernels, which allows the use of Kronecker algebra to handle high-dimensional input spaces and large numbers of correlated outputs. This makes it well suited for applications such as modeling cosmological power spectra, large-scale physical simulations, and multi-output hyperparameter tuning. By combining scalable multi-output GP modeling with data-driven adaptive sampling, GPsurrogate enables parameter inference and optimization with substantially fewer simulations than conventional space-filling designs.

Lukic, Zarija [Lawrence Berkeley National Laborato↗
DOE OSTI2023

Single-pixel reconstructive mid-infrared micro-spectrometer

Miniaturized spectrometers in the mid-infrared (MIR) are critical in developing next-generation portable electronics for advanced sensing and analysis. The bulky gratings or detector/filter arrays in conventional micro-spectrometers set a physical limitation to their miniaturization. In this work, we demonstrate a single-pixel MIR micro-spectrometer that reconstructs the sample transmission spectrum by a spectrally dispersed light source instead of spatially grated light beams. The spectrally tunable MIR light source is realized based on the thermal emissivity engineered via the metal-insulator phase transition of vanadium dioxide (VO 2 ). We validate the performance by showing that the transmission spectrum of a magnesium fluoride (MgF 2 ) sample can be computationally reconstructed from sensor responses at varied light source temperatures. With potentially minimum footprint due to the array-free design, our work opens the possibility where compact MIR spectrometers are integrated into portable electronic systems for versatile applications.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

JSPEC: A Program for IBS and Electron Cooling Simulation

JSPEC (JLab Simulation Package on Electron Cooling) is an open-source C++ program developed at Jefferson Lab to simulate the evolution of the ion beam under the intrabeam scattering effect and/or the electron cooling effect. JSPEC includes various models of the ion beam, the electron beam, and the friction force, aiming to reflect the latest advances in the field and to provide a useful tool to the community. JSPEC has been benchmarked against other cooling simulation codes and experimental data. It has been used to support the cooler design for JLEIC, an earlier JLab design for the Electron-Ion Collider. A Python wrapper of the C++ code, pyJSPEC, for Python 3.x environment has also been developed and released. It allows users to run JSPEC simulations in a Python environment and makes it possible for JSPEC to collaborate with other accelerator and beam modeling programs, as well as plentiful Python tools in data visualization, optimization, machine learning, etc. In this report, we introduce the features of JSPEC, with a focus on the latest development, and demonstrate how to use JSPEC and pyJSPEC with sample codes and numerical examples.

Accelerator Physics↗
DOE OSTI2023

Use of Electronic Laboratory Notebooks (ELN) in a Laboratory Information Management System (LIMS) [Slides]

The Actinide Analytical Chemistry (CAAC) group at Los Alamos National Laboratory (LANL) uses the LabWare LIMS (LabWare 7) system to manage our samples and material at risk. The LIMS system also provides other functionality which the Plasma Spectroscopy (PS) team has developed along with our LIMS team to provide streamlining and automation of all sample related actions required by PS.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Available DT fusion neutron sources

For consideration for diagnostic and technology development for a deuterium and tritium (DT) fusion system, we briefly list here the available DT fusion systems, their characteristic information, such as yields, flux, the pulse width, rep rate and approximate spectrum. We also briefly list other neutron sources for comparison. This is not meant to be exhaustive but a sampling of recent and available sources.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Utilizing Bayesian Optimization for Efficient Dispersion Curve Feature Acquisition [Slides]

Locate features and densely sample near those features. This helps us calculate T 1 which is the magnitude of the deviation from the otherwise smooth monotonically increasing function. Get a generally good idea of the rest of the curve. Potentially incorporate the higher cost of sampling at higher frequencies and the fact that the features at higher frequencies are more valuable to identify. Create a useful physics informed mean function.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

LBNF Material Activation Study

This poster presents a study on material activation at the Fermilab Long-Baseline Neutrino Facility (LBNF), focusing on understanding how high-energy beams interact with surrounding materials to produce radioactive isotopes. Using a simplified model of the LBNF-20 bunker and the FLUKA Monte Carlo simulation tool, the project quantifies isotope production at key locations inside and outside the shielding structures. The study employs a two-step simulation process, tracking primary and secondary particles, and explores the impact of different geometric and material configurations on activation rates. Results include preliminary comparisons of simulated activation rates and suggest methods for refining geometry, improving accuracy, and efficiently simulating future configurations. This work informs the design and operation of the LBNF facility, aiding in radiation safety and shielding optimization. Future efforts will focus on sample iteration, automated simulations, and detailed residual isotope analyses to further enhance the understanding of material activation in high-energy physics environments.

Pietraszek, Jacob [Unlisted, US]↗
NASA NTRS1973

A study of degradation of plates for nickel-cadmium spacecraft cells

The relative merits of coining and not coining of sintered nickel-oxide and cadmium plates was investigated. A survey of the industry including cell manufactures and users was made and results summarized. Sample plate materials from most commercial cell suppliers were obtained and characterized for properties that may correlate with the tendency toward physical disintegration during handling and over long periods of time in the cell. Special test methods were developed to obtain comparative data in a short time. A wide range of physical properties and coining thicknesses was observed, resulting in a range of responses. The stronger, less brittle materials resisted loss of sinter better than weaker materials whether or not coined. Coining improved handling and resistance to electrochemical cycling in all materials tested. An apparent exception was found to be due to improper coining of a tapered edge.

Scott, W. R.↗
NASA NTRS1974

A study of degradation of plates for nickel-cadmium spacecraft cells

The relative merits of coining and not coining of sintered nickel oxide and cadmium plates was investigated. Sample plate materials from most commercial cell suppliers were obtained and characterized for properties that may correlate with the tendency toward physical disintegration during handling and over long periods of time in the cell. Special test methods were developed to obtain comparative data in a short time. A wide range of physical properties and coining thickness was observed, resulting in a range of responses. The stronger materials resisted loss of sinter better than weaker materials whether or not coined. Coining improved handling and resistance to electrochemical cycling of weaker materials. The mechanism of break-down of positive plate edges under cycling appears to be the same as that of thickening and blistering. Brittle, nonadherent sinter, resulting from certain impregnation processes, is the most vulnerable to degradation. It is concluded that the latter type of materials should be coined, but coining of strong materials is optional.

Scott, W. R.↗