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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 127 records · Page 7

Nuclear probes of an out-of-equilibrium plasma at the highest compression

We report the highest compression reached in laboratory plasmas using eight laser beams, E laser ≈ 12 kJ, $\tau$ laser = 2 ns in third harmonic on a CD2 target at the ShenGuang-II Upgrade (SGII-Up) facility in Shanghai, China. We estimate the deuterium density ρ D kg/cm 3 , and the average kinetic energy of the plasma ions less than 1 keV. The highest reached areal density Λρ D = 4.8 ± 1.5 g/cm 2 was obtained from the measured ratio of the sequential ternary fusion reactions (dd→t+p and t+d→α+n) and the two body reaction fusions (dd→ 3 He + n). At such high densities, sequential ternary and also quaternary nuclear reactions become important as well (i.e. n(14.1 MeV) + 12 C → n' + 12 C* etc.) resulting in a shift of the neutron (and proton) kinetic energies from their birth values. The Down Scatter Ratio (DSR-quaternary nuclear reactions) method, i.e. the ratio of the 10-12 MeV neutrons divided by the total number of 14.1 MeV neutrons produced, confirms the high densities reported above. The estimated lifetime of the highly compressed plasma is 52 ± 9 ps, much smaller than the lasers pulse duration.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Regional-scale Spatio-Temporal Analysis of Impacts of Weather on Traffic Speed in Chicago using Probe Data

Understanding a regional-scale impact of the weather on the transportation system and how that impact varies geographically, is important from a sustainability standpoint. In this work, we have performed a city-scale analysis on the impact of weather on the traffic speed for the City of Chicago. We have found that there is a significant variation in the average hourly speed due to different weather patterns which also varies geographically. We have also observed that the rainfall has an evident impact on the average hourly speed on the freeways that are influenced by urbanized residential and commercial areas, and non-urbanized areas. Also, low visibility has shown a significant reduction in the average hourly traffic speed during the congested hours on the freeways that are influenced by non urbanized areas. We anticipate the contributions of this work in estimating emission and fuel economy at a regional scale which are important sustainability measures for transportation.

Kurte, Kuldeep↗

Probing the Electronic Structure of a Thorium Nitride Complex by Solid-State 15N NMR Spectroscopy

The solid-state 15N NMR powder spectra of the thorium nitride complex, [K(18-crown-6)(THF)2][(R2N)3Th(m-15N)(Th(NR2)3] ([K][1-15N], R = SiMe3), and the thorium amide complex, [Th(NR2)3(15NH2)] (2-15N) were recorded. The spectrum for [K][1-15N] represents the first reported solid-state 15N NMR data for an actinide nitride complex. The experimentally measured tensor spans are 847 ppm for [K][1-15N] and 237 ppm for 2-15N. Both shielding tensors exhibit a near-zero asymmetry parameter, which for [K][1-15N] is consistent with a local rotational symmetry of its 15N-labelled nitride ligand. For 2-15N, the lack of asymmetry can be rationalized by a quasi-free Th-NH2 bond rotation in the solid-state. DFT calculations overestimate the tensor span somewhat for [K][1-15N], but provide isotropic shifts in good agreement with both the solid-state and solution values for both complexes. Natural localized molecular orbital (NLMO) analyses of the nuclear shielding reveal that the larger tensor span in [K][1-15N] vs. 2-15N is primarily a consequence of more pronounced covalency of the N-Th bonds, and large spin-orbit coupling due to significant Th 5f orbital contribution to those bonds, impacting the principal components of the shielding tensor perpendicular to the Th-N-Th axis. Overall, our analysis confirms the involvement of the 5f orbitals in Th-N multiple bonds, and further demonstrates the value of solid-state NMR spectroscopy for interrogating actinide-ligand bonding.

actinides, covalent bonding, Nuclear Magnetic Reso↗

Molecular Simulations Probing the Adsorption and Diffusion of Ammonia, Nitrogen, Hydrogen, and Their Mixtures in Bulk MFI Zeolite and MFI Nanosheets at High Temperature and Pressure

Recent advances in the synthesis of MFI zeolite nanosheets have led to highly selective membranes that are promising candidates for small-scale ammonia separation from ammonia/nitrogen/hydrogen mixtures in distributed green ammonia production plants. Using force-field-based molecular simulations, we evaluate the performance of bulk all-silica MFI zeolite and a 3 nm thick all-silica MFI nanosheet for ammonia/nitrogen/hydrogen separations at moderate temperature and pressure conditions (T = 373 K, p = 5 bar) as well as conditions relevant for a membrane-based reactor–separator process (T = 523 or 623 K, p = 80 bar). Isobaric–isothermal Gibbs ensemble Monte Carlo (GEMC) simulations were carried out to understand the selective adsorption behavior for these mixtures. Molecular dynamics simulations in the canonical ensemble were performed to examine the transport behavior of ammonia in a mixture with nitrogen or hydrogen at loadings obtained from the GEMC simulations. Our results show that both bulk MFI and the nanosheet with explicit surface silanols are highly selective toward ammonia adsorption, but the adsorption selectivity decreases by factors of 4 and 10 for ammonia/nitrogen and ammonia/hydrogen mixtures as the temperature is increased from 373 to 623 K. Conversely, the diffusion selectivities toward ammonia are more favorable at process-relevant temperatures and for the MFI nanosheet. Here, at T = 523 K and p = 80 bar, our simulations predict overall separation factors of 3.8 ± 0.2 and 4.5 ± 0.3 for ammonia/nitrogen and ammonia/hydrogen mixtures, respectively, in the bulk MFI zeolite, and separation factors of 8.6 ± 0.4 and 12.5 ± 0.8, respectively, for the MFI nanosheet.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Probing Accuracy-Speedup Tradeoff in Machine Learning Surrogates for Molecular Dynamics Simulations

The performance promise of machine learning surrogates of molecular dynamics simulations of soft materials is significant but generally comes at the cost of acquiring large training datasets to learn the complex relationships between input soft material attributes and output properties. Under the constraint of limited high-performance computing resources, optimizing the size of the training datasets becomes paramount. Using an artificial neural network based surrogate for molecular dynamics simulations of confined electrolytes, we explore the tradeoff between surrogate accuracy and computational gains. Accuracy is assessed by computing the root-mean-square errors between the surrogate predictions and the ground truth results obtained via molecular dynamics simulations. The computational performance is judged by evaluating the speedup which incorporates the training dataset creation time. Improvement in accuracy occurs with a loss of speedup, which scales as the inverse of the training dataset size. Furthermore, the link between surrogate generalizability and the accuracy-speedup tradeoff is assessed by examining the errors incurred in surrogate predictions on unseen, interpolated input variables and developing a net speedup metric to capture the associated gains.

Anions↗