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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Fusion yield of plasma with velocity-space anisotropy at constant energy

Velocity-space anisotropy can significantly modify fusion reactivity. The nature and magnitude of this modification depends on the plasma temperature, as well as the details of how the anisotropy is introduced. For plasmas that are sufficiently cold compared to the peak of the fusion cross section, anisotropic distributions tend to have higher yields than isotropic distributions with the same thermal energy. At higher temperatures, it is instead isotropic distributions that have the highest yields. However, the details of this behavior depend on exactly how the distribution differs from an isotropic Maxwellian. Therefore, this paper describes the effects of anisotropy on fusion yield for the class of anisotropic distribution functions with the same energy distribution as a 3D isotropic Maxwellian and compares those results with the yields from bi-Maxwellian distributions. In many cases, especially for plasmas somewhat below reactor-regime temperatures, the effects of anisotropy can be substantial.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Prediction of stability constants of metal–ligand complexes by machine learning for the design of ligands with optimal metal ion selectivity

The new LOGKPREDICT program integrates HostDesigner molecular design software with the machine learning (ML) program Chemprop. By supplying HostDesigner with predicted log K values, LOGKPREDICT enhances the computer-aided molecular design process by ranking ligands directly by metal–ligand binding strength. Harnessing reliable experimental data from a historic National Institute of Standards and Technology (NIST) database and data from the International Union of Pure and Applied Chemistry (IUPAC), we train message passing neural net algorithms. The multi-metal NIST-based ML model has a root mean square error (RMSE) of 0.629 ± 0.044 (R 2 of 0.960 ± 0.006), while two versions of lanthanide-only IUPAC-based ML models have, respectively, RMSE of 0.764 ± 0.073 (R 2 of 0.976 ± 0.005) and 0.757 ± 0.071 (R 2 of 0.959 ± 0.007). For relative log K predictions on an out-of-sample set of six ligands, demonstrating metal ion selectivity, the RMSE value reaches a commendably low 0.25. Here we showcase the use of LOGKPREDICT in identifying ligands with high selectivity for lanthanides in aqueous solutions, a finding supported by recent experimental evidence. We also predict new ligands yet to be verified experimentally. Therefore, our ML models implemented through LOGKPREDICT and interfaced with the ligand design software HostDesigner pave the way for designing new ligands with predetermined selectivity for competing metal ions in an aqueous solution.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Using AI to predict calibration constants for the central drift chamber in GlueX at Jefferson Lab

The AI for Experimental Controls project team at Jefferson Lab has developed an AI system to control and calibrate a large drift chamber system in near-real time. The AI system will monitor environmental and experimental variables to recommend voltage settings that maintain consistent dE/dx gain and optimal resolution throughout the experiment. At present, calibrations are performed after data have been recorded and require a considerable amount of time and attention from experts. The calibrations currently require multiple iterations and depend on accurate tracking information. Our approach uses environmental data, such as atmospheric pressure and gas temperature, and beam conditions, such as the flux of incident particles, as inputs to a Gaussian Process Regression (GPR) model. For the data taken during the GlueX 2020 run period, the GPR is able to predict the existing gain correction factors to within 3.5%. This talk will briefly describe the development, testing, and future plans for this system at Jefferson Lab.

Jeske, Torri↗
DOE OSTI2020

Soft elastic constants from phonon spectroscopy in hole-doped Ba 1-x (K,Na) x Fe 2 As 2 and Sr 1-x Na x Fe 2 As 2

We report inelastic x-ray scattering measurements of the in-plane polarized transverse acoustic phonon mode propagating along q ∥ [ 100 ] in various hole-doped compounds belonging to the 122 family of iron-based superconductors. Additionally, the slope of the dispersion of this phonon mode is proportional to the square root of the shear modulus C 66 in the q → 0 limit and, hence, sensitive to the tetragonal to orthorhombic structural phase transition occurring in these compounds. In contrast to a recent report for Ba ( Fe 0.94 Co 0.06 ) 2 As 2 [Weber et al. , Phys. Rev. B 98 , 014516 (2018) ], we find qualitative agreement between values of C 66 deduced from our experiments and those derived from measurements of the Young modulus in Ba 1 - x ( K , Na ) x Fe 2 As 2 at optimal doping. These results provide an upper limit of about 50 Å for the nematic correlation length for the investigated optimally hole-doped compounds. Furthermore, we also studied compounds at lower doping levels exhibiting the orthorhombic magnetic phase, where C 66 is not accessible by volume probes, as well as the C 4 tetragonal magnetic phase.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Impact of the Li 6 asymptotic normalization constant onto α -induced reactions of astrophysical interest

Indirect methods have become the predominant approach in experimental nuclear astrophysics for studying several low-energy nuclear reactions occurring in stars, as direct measurements of many of these relevant reactions are rendered infeasible due to their low reaction probability. Such indirect methods, however, require theoretical input that in turn can have significant poorly quantified uncertainties, which can then be propagated to the reaction rates and have a large effect on our quantitative understanding of stellar evolution and nucleosynthesis processes. Here we present two such examples involving α-induced reactions, 13 C (α,n)⁢ 16 O and 12 C (α,γ)⁢ 16 O, for which the low-energy cross sections have been constrained with ( 6 Li,d) transfer data. In this Letter, we discuss how a first-principle calculation of 6 Li leads to a 21% reduction of the 12 C⁡(α,γ) ⁢ 16 O cross sections with respect to a previous estimation. This calculation further resolves the discrepancy between recent measurements of the 13 C (α,n)⁢ 16 O reaction and points to the need for improved theoretical formulations of nuclear reactions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗