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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Adaptively driven X-ray diffraction guided by machine learning for autonomous phase identification

Machine learning (ML) has become a valuable tool to assist and improve materials characterization, enabling automated interpretation of experimental results with techniques such as X-ray diffraction (XRD) and electron microscopy. Because ML models are fast once trained, there is a key opportunity to bring interpretation in-line with experiments and make on-the-fly decisions to achieve optimal measurement effectiveness, which creates broad opportunities for rapid learning and information extraction from experiments. Here, we demonstrate such a capability with the development of autonomous and adaptive XRD. By coupling an ML algorithm with a physical diffractometer, this method integrates diffraction and analysis such that early experimental information is leveraged to steer measurements toward features that improve the confidence of a model trained to identify crystalline phases. We validate the effectiveness of an adaptive approach by showing that ML-driven XRD can accurately detect trace amounts of materials in multi-phase mixtures with short measurement times. The improved speed of phase detection also enables in situ identification of short-lived intermediate phases formed during solid-state reactions using a standard in-house diffractometer. Our findings showcase the advantages of in-line ML for materials characterization and point to the possibility of more general approaches for adaptive experimentation.

36 MATERIALS SCIENCE↗
DOE OSTI2013

Hot-electron generation from laser–pre-plasma interactions in cone-guided fast ignition

Two-dimensional particle-in-cell (PIC) simulations were performed for the cone-in-shell integrated fast-ignition experiments at the Omega Laser Facility [W. Theobald et al., Phys. Plasmas 18, 056305 (2011)]. The initial plasma density profile in the PIC simulations was taken from hydrodynamic simulations of the prepulse interaction with the gold cone. Hot-electron generation from laser–pre-plasma interactions and transport up to 100× the critical density (n c ) was studied. The simulation showed a mean divergence half-angle of 68° and 50% absorption for the hot electrons. The simulation results show that the generated hot electrons were dominated in number by low-energy electrons but in energy by multi-MeV electrons. Electron transport between 5 and 100 n c was ballistic. In the late stage of the simulation, all the results were largely independent of polarization, indicating a stochastic hot-electron–generation mechanism.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2015

Fast magnetic reconnection with large guide fields

In this letter, it is demonstrated using two-fluid simulations that low-β magnetic reconnection remains fast, regardless of the presence of fast dispersive waves, which have been previously suggested to play a critical role. To understand these results, a discrete model is constructed that offers scaling relationships for the reconnection rate and dissipation region (DR) thickness in terms of the upstream magnetic field and DR length. We verify these scalings numerically and show how the DR self-adjusts to process magnetic flux at the same rate that it is supplied to a larger region where two-fluid effects become important. The rate is therefore independent of the DR physics and is in good agreement with kinetic results.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Guiding the design of oxidation-resistant Fe-based single atom alloy catalysts with insights from configurational space

The high activity and selectivity of Fe-based heterogeneous catalysts toward a variety of reactions that require the breaking of strong bonds are offset in large part by their considerable instability with respect to oxidative deactivation. While it has been shown that the stability of Fe catalysts is considerably enhanced by alloying them with precious metals (even at the single-atom limit), rational design criteria for choosing such secondary metals are still missing. Since oxidative deactivation occurs due to the strong binding of oxygen to Fe and reduction by adsorbed hydrogen mitigates the deactivation, we propose here to use the binding affinity of oxygen and hydrogen adatoms as the basis for rational design. As it would also be beneficial to use cheaper secondary metals, we have scanned over a large subset of 3d–5d mid-to late transition metal single atoms and computationally determined their effect on the oxygen and hydrogen adlayer binding as a function of chemical potential and adsorbate coverage. We further determine the underlying chemical origins that are responsible for these effects and connect them to experimentally tunable quantities. Our results reveal a reliable periodic trend wherein oxygen binding is weakened greatest as one moves right and down the periodic table. Hydrogen binding shows the same trend only at high (but relevant) coverages and otherwise tends to have its binding slightly increased in all systems. Trends with secondary metal coverage are also uncovered and connected to experimentally tunable parameters.

Hensley, Alyssa↗
DOE OSTI2017

Adjoint-Based Sensitivity and Uncertainty Analysis for Density and Composition: A User’s Guide

The ability to perform sensitivity analyses using adjoint-based first-order sensitivity theory has existed for decades. This paper provides guidance on how adjoint sensitivity methods can be used to predict the effect of material density and composition uncertainties in critical experiments, including when these uncertain parameters are correlated or constrained. Two widely used Monte Carlo codes, MCNP6 (Ref. 2) and SCALE 6.2 (Ref. 3), are both capable of computing isotopic density sensitivities in continuous energy and angle. Additionally, Perkó et al. have shown how individual isotope density sensitivities, easily computed using adjoint methods, can be combined to compute constrained first-order sensitivities that may be used in the uncertainty analysis. This paper provides details on how the codes are used to compute first-order sensitivities and how the sensitivities are used in an uncertainty analysis. Constrained first-order sensitivities are computed in a simple example problem.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2014

A guide to designing future ground-based cosmic microwave background experiments

In this follow-up work to the high energy physics Community Summer Study 2013 (aka SNOWMASS), we explore the scientific capabilities of a future Stage IV cosmic microwave background polarization experiment under various assumptions on detector count, resolution, and sky coverage. We use the Fisher matrix technique to calculate the expected uncertainties of cosmological parameters in νΛCDM that are especially relevant to the physics of fundamental interactions, including neutrino masses, effective number of relativistic species, dark energy equation of state, dark matter annihilation, and inflationary parameters. To further chart the landscape of future cosmology probes, we include forecasted results from the baryon acoustic oscillation signal as measured by Dark Energy Spectroscopic Instrument to constrain parameters that would benefit from low redshift information. We find the following best 1σ constraints: σ(M {sub ν}) = 15 meV, σ(N {sub eff}) = 0.0156, dark energy figure of merit = 303, σ(p {sub ann}) = 0.00588 × 3 × 10{sup –26} cm{sup 3} s{sup –1} GeV{sup –1}, σ(Ω {sub K}) = 0.00074, σ(n{sub s} ) = 0.00110, σ(α {sub s}) = 0.00145, and σ(r) = 0.00009. We also detail the dependencies of the parameter constraints on detector count, resolution, and sky coverage.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

A Software Developer’s Guide to Informal Evaluation of Visual Analytics Environments Using VAST Challenge Information

The VAST Challenge has been a popular venue for academic and industry participants for over ten years. Many participants comment that the majority of their time in preparing VAST Challenge entries is discovering elements in their software environments that need to be redesigned in order to solve the given task. Fortunately, there is no need to wait until the VAST Challenge is announced to test out software systems. The Visual Analytics Benchmark Repository contains all past VAST Challenge tasks, data, solutions and submissions. This paper details the various types of evaluations that may be conducted using the Repository information. In this paper we describe how developers can do informal evaluations of various aspects of their visual analytics environments using VAST Challenge information. Aspects that can be evaluated include the appropriateness of the software for various tasks, the various data types and formats that can be accommodated, the effectiveness and efficiency of the process supported by the software, and the intuitiveness of the visualizations and interactions. Researchers can compare their visualizations and interactions to those submitted to determine novelty. In addition, the paper provides pointers to various guidelines that software teams can use to evaluate the usability of their software. While these evaluations are not a replacement for formal evaluation methods, this information can be extremely useful during the development of visual analytics environments.

evaluation↗
DOE OSTI2013

Physiologically guided approach to characterizing respiratory motion

Purpose: To characterize radiation therapy patient breathing patterns based on measured external surrogate information. Methods: Breathing surrogate data were collected during 4DCT from a cohort of 50 patients including 28 patients with lung cancer and 22 patients without lung cancer. A spirometer and an abdominal pneumatic bellows were used as the surrogates. The relationship between these measurements was assumed to be linear within a small phase difference. The signals were correlated and drift corrected using a previously published method to convert the signal into tidal volume. The airflow was calculated with a first order time derivative of the tidal volume using a window centered on the point of interest and with a window length equal to the CT gantry rotation period. The airflow was compared against the tidal volume to create ellipsoidal patterns that were binned into 25 ml × 25 ml/s bins to determine the relative amount of time spent in each bin. To calculate the variability of the maximum inhalation tidal volume within a free-breathing scan timeframe, a metric based on percentile volume ratios was defined. The free breathing variability metric (κ) was defined as the ratio between extreme inhalation tidal volumes (defined as >93 tidal volume percentile of the measured tidal volume) and normal inhalation tidal volume (defined as >80 tidal volume percentile of the measured tidal volume). Results: There were three observed types of volume-flow curves, labeled Types 1, 2, and 3. Type 1 patients spent a greater duration of time during exhalation withκ = 1.37 ± 0.11. Type 2 patients had equal time duration spent during inhalation and exhalation with κ = 1.28 ± 0.09. The differences between the mean peak exhalation to peak inhalation tidal volume, breathing period, and the 85th tidal volume percentile for Type 1 and Type 2 patients were statistically significant at the 2% significance level. The difference between κ and the 98th tidal volume percentile for Type 1 and Type 2 patients was found to be statistically significant at the 1% significance level. Three patients did not display a breathing stability curve that could be classified as Type 1 or Type 2 due to chaotic breathing patterns. These patients were classified as Type 3 patients. Conclusions: Based on an observed volume-flow curve pattern, the cohort of 50 patients was divided into three categories called Type 1, Type 2, and Type 3. There were statistically significant differences in breathing characteristics between Type 1 and Type 2 patients. The use of volume-flow curves to classify patients has been demonstrated as a physiological characterization metric that has the potential to optimize gating windows in radiation therapy.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2014

Crystal Structure of a CRISPR RNA-guided Surveillance Complex Bound to a ssDNA Target

In prokaryotes, RNA derived from type I and type III CRISPR loci direct large ribonucleoprotein complexes to destroy invading bacteriophage and plasmids. In Escherichia coli, this 405-kilodalton complex is called Cascade. We report the crystal structure of Cascade bound to a single-stranded DNA (ssDNA) target at a resolution of 3.03 angstroms. The structure reveals that the CRISPR RNA and target strands do not form a double helix but instead adopt an underwound ribbon-like structure. This noncanonical structure is facilitated by rotation of every sixth nucleotide out of the RNA-DNA hybrid and is stabilized by the highly interlocked organization of protein subunits. These studies provide insight into both the assembly and the activity of this complex and suggest a mechanism to enforce fidelity of target binding.

59 BASIC BIOLOGICAL SCIENCES↗