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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

Local order, disorder, and everything in between: using 91 Zr solid-state NMR spectroscopy to probe zirconium-based metal–organic frameworks

Characterization of metal centers in metal–organic frameworks (MOFs) is critical for rational design and further understanding of structure–property relationships. The short-range structure about Zr atoms is challenging to properly elucidate in many Zr MOFs, particularly when local disorder is present. Static 91 Zr solid-state NMR spectra of the seven zirconium MOFs UiO-66, UiO-66-NH 2 , UiO-67, MOF-801, MOF-808, DUT-68 and DUT-69 have been acquired at high magnetic fields of 35.2 T and 19.6 T, yielding valuable information on the local structure, site symmetry and order about Zr. 91 Zr NMR is very sensitive to differences in MOF short-range structure caused by guest molecules, linker substitution and post-synthetic treatment. Complementary density functional theory (DFT) calculations assist in the interpretation and assignment of 91 Zr solid-state NMR spectra, lend insight into structural origins of 91 Zr NMR parameters and enable determination of local Zr coordination environments. This approach can be extended to many other materials containing zirconium.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A competition between 2D and 3D magnetic orderings in novel mixed valent copper frameworks

Low-dimensional hybrid inorganic–organic frameworks exhibit high structural flexibility and allow for the inclusion of various magnetic and optically-active species into their host structures. The emergence of copper-based hybrid structures for various optical applications provides a promising foundation for exploring the integration of magnetic sublattices, paving the way for advancements in magneto-optical coupling and multifunctional materials. Herein, we introduce a novel class of hybrid copper frameworks with covalently-connected alternating magnetic 2D copper(II) formate and non-magnetic copper(I) bromide layers. The anionic framework is stabilized by A + cations to form ACu 5 Br 4 (COOH) 4 (A + = Na + , K + , Rb + , NH 4 + ) semiconductors (bandgaps 2.1–2.2 eV) with optical transitions suitable for optoelectronic applications. Comprehensive magnetometry studies show that ACu 5 Br 4 (COOH) 4 compounds exhibit low-dimensional 2D short-range antiferromagnetic order within the formate layers, characterized by strong exchange coupling (J/k B ∼ −100 K). Upon further temperature reduction, interactions between Cu(II) layers give rise to 3D long-range magnetic order at ∼40 K, despite the large (8.6–8.8 Å) spatial separation of the magnetic Cu(II) formate layers by nonmagnetic Cu(I)–Br bridging layers. This transition is further supported by electron paramagnetic resonance (EPR) spectroscopy. In conclusion, this study expands our understanding of low-dimensional hybrid frameworks and opens new avenues for the design of 2D multifunctional materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Classical eighth- and lower-order Runge-Kutta-Nystroem formulas with a new stepsize control procedure for special second-order differential equations

New Runge-Kutta-Nystrom formulas of the eighth, seventh, sixth, and fifth order are derived for the special second-order (vector) differential equation x = f (t,x). In contrast to Runge-Kutta-Nystrom formulas of an earlier NASA report, these formulas provide a stepsize control procedure based on the leading term of the local truncation error in x. This new procedure is more accurate than the earlier Runge-Kutta-Nystrom procedure (with stepsize control based on the leading term of the local truncation error in x) when integrating close to singularities. Two central orbits are presented as examples. For these orbits, the accuracy and speed of the formulas of this report are compared with those of Runge-Kutta-Nystrom and Runge-Kutta formulas of earlier NASA reports.

Fehlberg, E.↗

Comparisons among second-order, fourth-order, and pseudospectral advection techniques in a mesoscale numerical model

The reported investigation is concerned with mesoscale squall-line simulation utilizing numerical techniques. Particular attention is given to fourth-order results and their implications for the dynamical evolution of mesoscale squall-line systems which contain severe local storms. An adiabatic inviscid set of prognostic equations is utilized in a z coordinate system for the fundamental experiment. The fourth-order advection is employed for all time-dependent equations. The Euler-backward time marching scheme is utilized with a 60 second time step. The horizontal mesh length is 42 km. Horizontal diffusion is accomplished by utilizing a smoother-desmoother. Lateral boundary conditions are designed to reduce the development of strong gradients in dependent variables near the boundaries by bringing interior values from the grid to the boundaries.

Kaplan, M.↗

Partially coherent scattering in stellar chromospheres. II - The first-order escape probability method. III - A second-order escape probability method

Approximate analytic expressions are derived for resonance-line wing diagnostics, accounting for frequency redistribution effects, for homogeneous slabs, and slabs with a constant Planck function gradient. Resonance-line emission profiles from a simplified conceptual standpoint are described in order to elucidate the basic physical parameters of the line-forming layers prior to the performance of detailed numerical calculations. An approximate analytic expression is derived for the dependence on stellar surface gravity of the location of the Ca II and Mg II resonance-line profile peaks. An approximate radiative transfer equation using generalized second-order escape probabilities, applicable even in the presence of nearly coherent scattering in the damping wings of resonance lines, is derived. Approximate analytic solutions that can be applied in special regimes and achieve good agreement with accurate numerical results are found.

Gayley, K. G.↗

Low-order design and high-order simulation of active closed-loop control for aerospace structures under construction

Partially constructed/assembled structures in space are complicated enough but their dynamics will also be operating in closed-loop with feedback controllers. The dynamics of such structures are modeled by large-scale finite element models. The model dimension L is extremely large (approximately 10,000) while the numbers of actuators (M) and sensors (P) are small. The model parameters M(sub m) mass matrix, D(sub o) damping matrix, and K(sub o) stiffness matrix, are all symmetric and sparse (banded). Thus simulation of open-loop structure models of very large dimension can be accomplished by special integration techniques for sparse matrices. The problem of simulation of closed-loop control of such structures is complicated by the addition of controllers. Simulation of closed-loop controlled structures is an essential part of the controller design and evaluation process. Current research in the following areas is presented: high-order simulation of actively controlled aerospace structures; low-order controller design and SCI compensation for unmodeled dynamics; prediction of closed-loop stability using asymptotic eigenvalue series; and flexible robot manipulator control experiment.

Balas, Mark J.↗

Molecular Static Third-Order Polarizabilities of Carbon-Cage Fullerenes and their Correlation with Three Geometric Parameters: Group Order, Aromaticity, and Size

Calculations were performed on the valence contribution to the static molecular third-order polarizabilities (gamma) of thirty carbon-cage fullerenes (C60, C70, five isomers of C78, and twenty-three isomers of C84). The molecular structures were obtained from B3LYP/STO-3G calculations. The values of the tensor elements and an associated numerical uncertainty were obtained using the finite-field approach and polynomial expansions of orders four to eighteen of polarization versus static electric field data. The latter information was obtained from semiempirical calculations using the AM1 hamiltonian.

Moore, Craig E.↗

Updating High-Order Aeroservoelastic Models from Low-Order System Identification Results

Estimating aircraft models from test data requires several simplifying assumptions that introduce biases into the parameter estimates. In this paper, these biases are defined and a method for estimating the biases is discussed. Having an estimate of the bias allows the parameters estimated from test to be integrated into a high-order model. The Integrated Adaptive Wing Technology Maturation (IAWTM) wind tunnel model is discussed and the bias is demonstrated for one of the testing configurations. The methodology was able to estimate these biases and apply corrections to high-order aeroelastic models to improve the fit to test data. The consideration of the biases allows more meaningful comparisons and avoids the erroneous differences between pretest predictions and the fitted model.

Jeffrey Ouellette↗

Updating High-Order Aeroservoelastic Models from Low-Order System Identification Results

Estimating aircraft models from test data requires several simplifying assumptions that introduce biases into the parameter estimates. In this paper, these biases are defined and a method for estimating the biases is discussed. Having an estimate of the bias allows the parameters estimated from test to be integrated into a high-order model. The Integrated Adaptive Wing Technology Maturation (IAWTM) wind tunnel model is discussed and the bias is demonstrated for one of the testing configurations. The methodology was able to estimate these biases and apply corrections to high-order aeroelastic models to improve the fit to test data. The consideration of the biases allows more meaningful comparisons and avoids the erroneous differences between pretest predictions and the fitted model.

Jeffrey Ouellette↗

Machine Learning Reduced Order Model for Cost and Emission Assessment of a Pyrolysis System

Biomass pyrolysis is a promising approach for producing economic and environmentally-friendly fuels and bioproducts. Biomass pyrolysis experiments show that feedstock properties have a significant impact on product yields and composition. Scientists are developing detailed chemical reaction mechanisms to capture the relationships between biomass composition and pyrolysis yields. These mechanisms can be computationally intensive. In this study, we investigate the use of a machine learning reduced order model (ROM) for assessing the costs and emissions of a pyrolysis biorefinery. Here, we developed a Kriging-based ROM to predict pyrolysis yields of 314 feedstock samples based on the results of a detailed chemical kinetic pyrolysis mechanism. The ROM is integrated into a chemical process model for calculating mass and energy yields in a commercial-scale (2000 tonne/day) biorefinery. The ROM estimated biofuel yields of 65 to 130 gallons per ton of dry biomass. This results in biofuel minimum fuel-selling prices of $2.62 to $5.43 per gallon and emissions of -13.62 to 145 kg of CO 2 per MJ. The ROM achieved an average mean square error of 1.8e-20 and a mean absolute error of 0.53%. These results suggest that ROMs can facilitate rapid feedstock screening for biorefinery systems.

09 BIOMASS FUELS↗