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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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Electronic Band Structures of a Germanium Halide Perovskite Semiconductor

CsGeX 3 , a class of halide perovskites, is an emergent semiconductor with ferroelectricity and potential optoelectronic properties that can be harnessed for device applications. However, measurements of the electronic structure for this class of material are still lacking. Here, in this work, we report, for the first time, the experimental band structures of CsGeI 3 , a ferroelectric halide perovskite semiconductor, through angle-resolved photoemission spectroscopy (ARPES). The crystals were cleaved along both the (110) and (111) surfaces, facilitating the observation of clear valence band dispersions in several high-symmetry momentum directions. The observed valence band is characterized by a small hole effective mass of ∼0.1m 0 at the valence band maximum, without notable spectral signatures associated with the Rashba effect. Our experimental measurements are supported by electronic structure calculations in the DFT + G0W0 framework, enabling assessment of the band orbital characteristics, dispersion, and spin-splitting. This work unveils the intrinsic electronic and transport properties of CsGeX 3 , thereby advancing the optimization of the optoelectronic properties of this class of materials.

angle-resolved photoemission spectroscopy↗
DOE OSTI2020

Experimental and theoretical study of energy transfer in a chromophore triad: What makes modeling dynamics successful?

Simulation of electronic dynamics in realistically large molecular systems is a demanding task that has not yet achieved the same level of quantitative prediction already realized for its static counterpart. This is particularly true for processes occurring beyond the Born–Oppenheimer regime. Non-adiabatic molecular dynamics (NAMD) simulations suffer from two convoluted sources of error: numerical algorithms for dynamics and electronic structure calculations. While the former has gained increasing attention, particularly addressing the validity of ad hoc methodologies, the effect of the latter remains relatively unexplored. Indeed, the required accuracy for electronic structure calculations to reach quantitative agreement with experiment in dynamics may be even more strict than that required for static simulations. In this study, we address this issue by modeling the electronic energy transfer in a donor–acceptor–donor (D–A–D) molecular light harvesting system using fewest switches surface hopping NAMD simulations. In the studied system, time-resolved experimental measurements deliver complete information on spectra and energy transfer rates. Subsequent modeling shows that the calculated electronic transition energies are “sufficiently good” to reproduce experimental spectra but produce over an order of magnitude error in simulated dynamical rates. We further perform simulations using artificially shifted energy gaps to investigate the complex relationship between transition energies and modeled dynamics to understand factors affecting non-radiative relaxation and energy transfer rates.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Pulse width dependence of magnetic field generation using laser-powered capacitor coils

Megagauss magnetic fields were generated by a current flowing through a U-shaped coil connecting two parallel copper foils. Two kJ-class lasers at various pulse widths from 2 ns to 9.9 ns passed through holes in the front foil and were focused on the back foil with an intensity of ~1.7×10 16 W/cm 2 . The coil current and resulting magnetic fields were characterized using ultrafast proton radiography, timed at the end of the laser pulses. Additionally, the measurements show that magnetic field strength decays with increasing laser pulse width. A lumped-circuit model was developed and showed consistency with the experimental measurements, demonstrating an ion shorting effect: as the ion current neutralizes the electron current contribution to interplate voltage, the coil current peaks on a timescale close to the ion transit time t i = d/v ion . FLASH simulations of the coil current are performed, and the calculated resistance values are used to constrain ion speed as a function of hot electron temperature.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Predictive modeling of NSTX discharges with the updated multi-mode anomalous transport module

Abstract The objective of this study is twofold: firstly, to demonstrate the consistency between the anomalous transport results produced by updated Multi-Mode Model (MMM) version 9.0.4 and those obtained through gyrokinetic simulations; and secondly, to showcase MMM’s ability to predict electron and ion temperature profiles in low aspect ratio, high beta NSTX discharges. MMM encompasses a range of transport mechanisms driven by electron and ion temperature gradients, trapped electrons, kinetic ballooning, peeling, microtearing, and drift resistive inertial ballooning modes. These modes within MMM are being verified through corresponding gyrokinetic results. The modes that potentially contribute to ion thermal transport are stable in MMM, aligning with both experimental data and findings from linear CGYRO simulations. The isotope effects on these modes are also studied and higher mass is found to be stabilizing, consistent with the experimental trend. The electron thermal power across the flux surface is computed within MMM and compared to experimental measurements and nonlinear CGYRO simulation results. Specifically, the electron temperature gradient modes (ETGM) within MMM account for 2.0 MW of thermal power, consistent with experimental findings. It is noteworthy that the ETGM model requires approximately 5.0 ms of computation time on a standard desktop, while nonlinear CGYRO simulations necessitate 8.0 h on 8 K cores. MMM proves to be highly computationally efficient, a crucial attribute for various applications, including real-time control, tokamak scenario optimization, and uncertainty quantification of experimental data.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

An adaptive approach to machine learning for compact particle accelerators

Abstract Machine learning (ML) tools are able to learn relationships between the inputs and outputs of large complex systems directly from data. However, for time-varying systems, the predictive capabilities of ML tools degrade if the systems are no longer accurately represented by the data with which the ML models were trained. For complex systems, re-training is only possible if the changes are slow relative to the rate at which large numbers of new input-output training data can be non-invasively recorded. In this work, we present an approach to deep learning for time-varying systems that does not require re-training, but uses instead an adaptive feedback in the architecture of deep convolutional neural networks (CNN). The feedback is based only on available system output measurements and is applied in the encoded low-dimensional dense layers of the encoder-decoder CNNs. First, we develop an inverse model of a complex accelerator system to map output beam measurements to input beam distributions, while both the accelerator components and the unknown input beam distribution vary rapidly with time. We then demonstrate our method on experimental measurements of the input and output beam distributions of the HiRES ultra-fast electron diffraction (UED) beam line at Lawrence Berkeley National Laboratory, and showcase its ability for automatic tracking of the time varying photocathode quantum efficiency map. Our method can be successfully used to aid both physics and ML-based surrogate online models to provide non-invasive beam diagnostics.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Phase Diagrams and Piezoelectric Properties of Wurtzite Al1-x-yScxGdyN Heterostructural Alloys

Ternary nitride alloys based on wurtzite AlN are a promising platform to realize functional materials, particularly ferroelectrics and optical emitters, that can smoothly integrate with conventional microelectronics. Here, a strategic design is presented to enable multifunctional materials by substituting multiple elements into AlN to create quaternary nitride alloys. By combining computational predictions and combinatorial thin film synthesis, the phase diagram of these quaternary Al-Sc-Gd-N alloys (or pseudo-ternary heterostructural AlN-ScN-GdN alloys) is successfully predicted as a function of effective temperature, and we experimentally grow Al1-x-xScxGdyN thin films for the first time. It is revealed that Al1-x-xScxGdyN crystallizes in a wurtzite-derived structure for X + y <~ 0.35, consistent with the calculated phase diagram. The computational investigation explores whether co-substitution induces cooperative effects on these alloys' piezoelectric and ferroelectric properties, finding that it is beneficial for reducing the polarization switching barrier. We calculate that Al1-x-xScxGdyN thin films should display ferroelectric switching. This is supported by our experimental measurements of a high optical bandgap, enhanced piezoelectric coefficient, and a change in the calculated polarization switching mechanism, and we achieve preliminary ferroelectric switching that experimentally realizes the prediction. Overall, our work sets the foundation toward quaternary wurtzite-nitride-based multifunctional materials, including piezoelectrics, ferroelectrics, and possibly even multiferroics.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Resolving discrepancies in bang-time predictions for indirect-drive ICF experiments on the NIF: Insights from the Build-A-Hohlraum campaign

This study investigated discrepancies between measured and simulated x-ray drive in Indirect-Drive Inertial Confinement Fusion (ID-ICF) hohlraums at the National Ignition Facility. Despite advances in radiation-hydrodynamic simulations, a consistent “drive deficit” remains. Experimentally measured ID-ICF capsule bang-times are systematically 400–700 ps later than simulations predict. The Build-A-Hohlraum (BAH) campaign explored potential causes for this discrepancy by systematically varying hohlraum features, including laser entrance hole (LEH) windows, capsules, and gas fills. Overall, the agreement between simulated and experimental x-ray drive was found to be largely unaffected by these changes. The data allow us to exclude some hypotheses put forward to potentially explain the discrepancy. Errors in the local thermodynamic equilibrium (LTE) atomic modeling, errors in the modeling of LEH closure, and errors due to a lack of plasma species mix physics in simulations are shown to be inconsistent with our measurements. Instead, the data support the hypothesis that errors in NLTE emission modeling are a significant contributor to the discrepancy. X-ray emission in the 2–4 keV range is found to be approximately 30% lower than in simulations. This is accompanied by higher than predicted electron temperatures in the gold bubble region, pointing to errors in non-LTE modeling. Introducing an opacity multiplier of 0.87 on energy groups above 1.8 keV improves agreement with experimental data, reducing the bang-time discrepancy from 300 to 100 ps. These results underscore the need for refined NLTE opacity models to enhance the predictive power of hohlraum simulations.

Band emission↗
DOE OSTI2025

Bubbling Water–Treating DBD Plasma Device Optimization Using Experimental and Computational Methods

A dry air atmospheric pressure volume dielectric barrier discharge is employed to fix nitrogen in water. Producing nitrate for use as nitrogen fertilizer is the primary motivation. A 0D chemistry model is developed and informed by the electrical, and geometric characteristics of the device and the plasma gas temperature. Modeled ozone and nitrate densities are compared to those measured experimentally in the plasma effluent and treated liquid for a range of gas temperatures. Modeled and measured ozone densities are in good agreement; however, the model lacks the liquid chemistry to properly represent the measured nitrate density. A gas temperature-based shift from ozone to NO x producing regimes is observed in both experiment and model, and the reactions responsible are evaluated.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Quantitative measurements of dislocations in metals for advancing predictive simulations

LLNL applications require scientists to predict how materials evolve under various thermomechanical conditions. While this is achieved through physics-based simulations, uncertainty in the predictions of mechanical properties remains a serious challenge that limits the predictive capabilities of models because we lack methods to compare predictions of atomic-scale defects (dislocations) with experimental measurements. High energy X-ray diffraction (HEXRD) is the most relevant technique that can provide the necessary statistical information on dislocations. However, this technique is not yet quantitative because we lack a precise understanding of the relationship between X-ray diffraction patterns and the underlying material dislocation content and arrangements. To address this need, we used our novel computational X-ray diffraction method to simulate the effect of dislocations on the diffraction patterns. We compared virtual and experimental diffraction patterns. Results allowed us to clearly establish the relationship between X-ray diffraction patterns and the underlying dislocation structures, proving that it is feasible to quantitatively measure dislocation statistics with HEXRD. This project delivered a method that can provide the missing piece to LLNL’s mechanical property simulations in advanced metals by obtaining experimentally long-needed quantitative dislocation data, which could fully enable predictive capabilities.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Visualization and efficient generation of constrained high-dimensional theoretical parameter spaces

We describe a set of novel methods for efficiently sampling high-dimensional parameter spaces of physical theories defined at high energies, but constrained by experimental measurements made at lower energies. Often, theoretical models such as supersymmetry are defined by many parameters, $\mathcal{O}$(10 – 100), expressed at high energies, while relevant experimental constraints are often defined at much lower energies, preventing them from directly ruling out portions of the space. Instead, the low-energy constraints define a complex, potentially non-contiguous subspace of the theory parameters. Naive scanning of the theory space for points which satisfy the low-energy constraints is hopelessly inefficient due to the high dimensionality, and the inverse problem is considered intractable. As a result, many theoretical spaces remain under-explored. We introduce a class of modified generative autoencoders, which attack this problem by mapping the high-dimensional parameter space to a structured low-dimensional latent space, allowing for easy visualization and efficient generation of theory points which satisfy experimental constraints. An extension without dimensional compression, which focuses on limiting potential information loss, is also introduced.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Evaluation of semi-empirical soot models for nonpremixed flames with increased stoichiometric mixture fraction and strain

Due to the size and complexity of industrial-scale systems and computing limitations, semi-empirical soot models are often employed in CFD simulations rather than computationally-expensive detailed models. Many of these models were developed for specific applications with unique characteristic timescales and/or validated only under fuel-air combustion conditions. Hence, their use in different contexts, such as oxy-combustion, could lead to inaccurate predictions. In this study, twelve semi-empirical models (1-step or 2-step) are evaluated on their ability to respond to changes in stoichiometric mixture fraction (Z st ) and strain in a series of ethylene counterflow flames which span the experimental sooting-to-non-sooting (yellow to blue) transition. A unique approach of plotting soot formation rate in normalized, local equivalence ratio space is introduced to aid in the analysis. Results show that no existing model is able to predict a blue flame when Z st is increased beyond the experimentally-measured sooting limit. Many models give the counter-intuitive result of increasing peak and/or integrated soot volume fraction (svf) as Z st increased, contrary to experimental observations. Two models are able to successfully predict a blue flame upon increase of strain to the sooting limit value. For two-step models, the strong dependence of growth rate on surface area results in high sensitivity of svf to changing flame boundary conditions, but with mixed accuracy. There is still a significant need for a robust semi-empirical model which can accurately predict soot fraction in systems with oxygen-enrichment or variable strain.

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

Rheology of bi-disperse dense fiber suspensions

While significant progress has been made in the modeling and simulation of uniform fiber suspensions, no existing model has been validated for industrially-relevant concentrated suspensions containing fibers of multiple aspect ratios. In the present work, we investigate bi-disperse suspensions with two fiber populations in varying aspect ratios in a steady shear flow using direct numerical simulations. Moreover, we measure the suspension viscosity by creating a controlled length bidispersity for nylon fibers suspended in a Newtonian fluid. Here the results showed good agreement between the experimentally measured and numerically predicted viscosity for bi-disperse suspensions. The ratio between the aspect ratio of large to small fibers (size ratio) and the volume fraction of large fibers (composition) in bi-disperse systems strongly affected the rheological behavior of the suspension. The increment of relative viscosity associated with size ratio and composition can be explained by the decrease in the maximum flowable limit or jamming volume fraction. Moreover, the relative viscosity of bi-disperse suspensions collapses, when plotted against the reduced volume fraction, demonstrating the controlling influence of the jamming fraction in bi-disperse fiber suspensions.

42 ENGINEERING↗
DOE OSTI2025

Completion of Transport Property Measurements on Multiple Actinide Fluoride Mixtures

One of the missions of the US Department of Energy’s Office of Nuclear Energy (DOE-NE) Molten Salt Reactor (MSR) Campaign under the Advanced Reactor Technology program has been to experimentally measure thermophysical properties of MSR-relevent salt systems, with the intent of supporting the development of the Molten Salt Thermal Properties Database (MSTDB). This database is jointly funded by the DOE-NE Nuclear Energy Advanced Modeling and Simulation Program and the MSR Campaign. Multiple DOE national laboratories, including Oak Ridge National Laboratory (ORNL), have been conducting measurements of thermophysical properties to support MSTDB development and provide MSR developers with access to new data that has been measured using modern methodologies and more advanced sample characterization techniques. These data may either fill gaps in the database or provide updated higher quality data to replace legacy data. Researchers at ORNL have recognized significant gaps in the transport property data of actinide-bearing fluoride salt systems of MSR industry interest. Moreover, for the data present in MSTDB in this category, the uncertainty margins are generally high, leading to questionability in our current understanding of the thermophysical characterization of actinide fluoride mixtures. As such, the focus of this study has been to generate new transport property data of actinide fluoride mixtures that are of immediate interest to MSR developers. Specifically, the mixtures NaF-UF 4 (78 - 22 mol%) and NaF-KF-UF 4 (57-16.04-26.91 mol%) have been studied—NaF-UF 4 for thermal conductivity and viscosity and NaF-KF-UF 4 for viscosity. Thermal conductivity measurements have been conducted with a variable gap apparatus, whereas viscosity has been measured with a rolling ball viscometer. Methodological and calibration details are provided for both measurement processes, along with measurement system updates that have enabled easier manufacturing of components and fewer challenges associated with conducting the measurements themselves. The resultant data collected for NaF-UF 4 (78–22 mol%) and NaF-KF-UF 4 (57-16.04-26.91 mol%) have been compared with relevant mixture data within the thermophysical arm of the MSTDB (MSTDB-TP).

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

High-throughput ab initio design of atomic interfaces using InterMatch

Forming a hetero-interface is a materials-design strategy that can access an astronomically large phase space. However, the immense phase space necessitates a high-throughput approach for an optimal interface design. Here we introduce a high-throughput computational framework, InterMatch, for efficiently predicting charge transfer, strain, and superlattice structure of an interface by leveraging the databases of individual bulk materials. Specifically, the algorithm reads in the lattice vectors, density of states, and the stiffness tensors for each material in their isolated form from the Materials Project. From these bulk properties, InterMatch estimates the interfacial properties. We benchmark InterMatch predictions for the charge transfer against experimental measurements and supercell density-functional theory calculations. We then use InterMatch to predict promising interface candidates for doping transition metal dichalcogenide MoSe 2 . Finally, we explain experimental observation of factor of 10 variation in the supercell periodicity within a few microns in graphene/α-RuCl 3 by exploring low energy superlattice structures as a function of twist angle using InterMatch. We anticipate our open-source InterMatch algorithm accelerating and guiding ever-growing interfacial design efforts. Moreover, the interface database resulting from the InterMatch searches presented in this paper can be readily accessed online.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Availability and reactivity of N 2 ( v ) for NH 3 synthesis by plasma catalysis

Production of vibrationally excited N 2 (N 2 (v)) in atmospheric pressure nonthermal plasma and loss of N 2 (v) by gas-phase reactions and reactions on catalytic surfaces are analyzed to examine the role of N 2 (v) in NH 3 formation by plasma catalysis. Vibrational state-to-state kinetic models complemented with molecular beam mass spectrometry (MBMS) measurements demonstrate that N 2 (v> 0) is produced with densities 100× greater than the density of N radicals by a radiofrequency atmospheric pressure plasma jet. The experimentally measured loss of N 2 (v) corresponds with a state-to-state kinetic model that describes loss of N 2 (v) by surface-mediated vibrational relaxation without consideration of reactions that convert N 2 (v) to NH 3 over the catalyst surface. Rate constants for vibrational relaxation of N 2 (v) on catalyst surfaces exceed upper bounds on proposed rate constants for NH 3 formation reactions from N 2 (v) over Fe when v < 9, Ni when v < 18, and Ag when v < 39, which indicates that only higher vibrational levels can possibly contribute to catalytic NH 3 formation faster than they undergo vibrational relaxation on the surface. Densities of N 2 (v> 8), vibrational levels that can possibly react over Fe to form NH 3 faster than they undergo vibrational relaxation, are less than or similar to N densities at the inlet of the catalyst bed and measured NH 3 formation for the investigated conditions in this work, while densities of N 2 (v> 17) and N 2 (v> 38) are orders of magnitude below the N density at the inlet of the catalyst bed and the measured NH 3 formation. The loss of N 2 (v) by vibrational relaxation on the surface limits the ability of N 2 (v) to contribute to catalytic NH 3 formation and explains why N 2 (v) does not produce NH 3 in quantities that are comparable to NH 3 formation from N even though N 2 (v > 0) is more abundantly produced by the plasma.

state-to-state kinetic modeling↗
DOE OSTI2025

Data-driven analysis of dipole strength functions using artificial neural networks

Here, we present a data-driven analysis of dipole strength functions across the nuclear chart, employing an artificial neural network to model nuclear dipole responses. We train the network on a dataset of experimentally measured dipole strength functions for 216 different nuclei. To assess its predictive capability, we test the trained model on an additional set of 10 new nuclei, where experimental data exist. We demonstrate that the artificial neural network not only accurately reproduces known data but also identifies potential inconsistencies in experimental datasets, indicating which results may warrant further review or possible rejection. For nuclei where experimental data are sparse or unavailable, the network confirms theoretical calculations, reinforcing its utility as a predictive tool in nuclear physics. Finally, utilizing the predicted electric dipole polarizability, we extract the value of the symmetry energy at saturation density and find it consistent with results from the literature.

artificial neural networks↗
DOE OSTI2024

The precision measurement of the muon $g-2$ at Fermilab

The Muon $g-2$ Experiment at Fermilab aims to measure the magnetic anomaly of the muon with the unprecedented precision of 140 parts per billion. In April 2021, the collaboration published the first measurement based on the first year of data collection, which was found to be consistent with the previous experiment at Brookhaven. The new global average of the experimental measurements strengthens the long-standing tension with the data-driven Standard Model prediction to a combined discrepancy of 4.2$\sigma$. On the theory side, however, recent improvements in the theoretical calculation of the hadronic contribution based on Lattice-QCD techniques are introducing new tensions on the value predicted by the theory. The Muon $g-2$ Experiment at Fermilab has now concluded its sixth and final year of data taking and a new result based on the Run-2 and Run-3 data was published in August 2023. This paper briefly describes the precision measurement conducted by the Muon $g-2$ Experiment at Fermilab and its current status.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

A novel measurement of marginal Alfven Eigenmode stability during high power auxiliary heating in JET

The interaction of Alfven Eigenmodes (AEs) and energetic particles is one of many important factors determining the success of future tokamaks. In JET, eight in-vessel antennas were installed to actively probe stable AEs with frequencies ranging 25-250 kHz and toroidal mode numbers |n| < 20. During the 2019-2020 deuterium campaign, almost 7500 resonances and their frequencies f0, net damping rates \gamma < 0, and toroidal mode numbers were measured in almost 800 plasma discharges. From a statistical analysis of this database, continuum and radiative damping are inferred to increase with edge safety factor, edge magnetic shear, and when including non-ideal effects. Both stable AE observations and their associated damping rates are found to decrease with |n|. Active antenna excitation is also found to be ineffective in H-mode as opposed to L-mode; this is likely due to the increased edge density gradient's effect on accessibility and ELM-related noise's impact on mode identification. A novel measurement is reported of a marginally stable, edge-localized Ellipticity-induced AE probed by the antennas during high-power auxiliary heating (ICRH and NBI) up to 25 MW. NOVA-K kinetic-MHD simulations show good agreement with experimental measurements of f0, \gamma, and n, indicating the dominance of continuum and electron Landau damping in this case. Similar experimental and computational studies are planned for the recent hydrogen and ongoing tritium campaigns, in preparation for the upcoming DT campaign.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗