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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 883 records · Page 49
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Guiding Principles for the Rational Design of Hybrid Materials: Use of DFT Methodology for Evaluating Non‐Covalent Interactions in a Uranyl Tetrahalide Model System

Abstract Together with the synthesis and experimental characterization of 14 hybrid materials containing [UO 2 X 4 ] 2− (X=Cl − and Br − ) and organic cations, we report on novel methods for determining correlation trends in their formation enthalpy (ΔH f ) and observed vibrational signatures. Δ H f values were analyzed through isothermal acid calorimetry and a Density Functional Theory+Thermodynamics (DFT+T) approach with results showing good agreement between theory and experiment. Three factors (packing efficiency, cation protonation enthalpy, and hydrogen bonding energy [ ]) were assessed as descriptors for trends in Δ H f . Results demonstrated a strong correlation between and Δ H f , highlighting the importance of hydrogen bonding networks in determining the relative stability of solid‐state hybrid materials. Lastly, we investigate how hydrogen bonding networks affect the vibrational characteristics of uranyl solid‐state materials using experimental Raman and IR spectroscopy and theoretical bond orders and find that hydrogen bonding can red‐shift U≡O stretching modes. Overall, the tightly integrated experimental and theoretical studies presented here bridge the trends in macroscopic thermodynamic energies and spectroscopic features with molecular‐level details of the geometry and electronic structure. This modeling framework forms a basis for exploring 3D hydrogen bonding as a tunable design feature in the pursuit of supramolecular materials by rational design.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Guiding Principles for the Rational Design of Hybrid Materials: Use of DFT Methodology for Evaluating Non‐Covalent Interactions in a Uranyl Tetrahalide Model System

Abstract Together with the synthesis and experimental characterization of 14 hybrid materials containing [UO 2 X 4 ] 2− (X=Cl − and Br − ) and organic cations, we report on novel methods for determining correlation trends in their formation enthalpy (ΔH f ) and observed vibrational signatures. Δ H f values were analyzed through isothermal acid calorimetry and a Density Functional Theory+Thermodynamics (DFT+T) approach with results showing good agreement between theory and experiment. Three factors (packing efficiency, cation protonation enthalpy, and hydrogen bonding energy [ ]) were assessed as descriptors for trends in Δ H f . Results demonstrated a strong correlation between and Δ H f , highlighting the importance of hydrogen bonding networks in determining the relative stability of solid‐state hybrid materials. Lastly, we investigate how hydrogen bonding networks affect the vibrational characteristics of uranyl solid‐state materials using experimental Raman and IR spectroscopy and theoretical bond orders and find that hydrogen bonding can red‐shift U≡O stretching modes. Overall, the tightly integrated experimental and theoretical studies presented here bridge the trends in macroscopic thermodynamic energies and spectroscopic features with molecular‐level details of the geometry and electronic structure. This modeling framework forms a basis for exploring 3D hydrogen bonding as a tunable design feature in the pursuit of supramolecular materials by rational design.

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

On the interplay between magnetic field and anisotropy in holographic QCD

We investigate the combined effects of anisotropy and a magnetic field in strongly interacting gauge theories by the gauge/gravity correspondence. Our main motivation is the quark-gluon plasma produced in off-central heavy-ion collisions which exhibits large anisotropy in pressure gradients as well as large external magnetic fields. We explore two different configurations, with the anisotropy either parallel or perpendicular to the magnetic field, focusing on the competition and interplay between the two. A detailed study of the RG flow in the ground state reveals a rich structure where depending on which of the two, anisotropy or magnetic field, is stronger, intermediate geometries with approximate AdS 4 × $\mathbb{R}$ and AdS 3 × $\mathbb{R}$ 2 factors arise. This competition is also manifest in the phase structure at finite temperature, specifically in the dependence of the chiral transition temperature on anisotropy and magnetic field, from which we infer the presence of inverse magnetic and anisotropic catalyses of the chiral condensate. Finally, we consider other salient observables in the theory, including the quark-antiquark potential, shear viscosity, entanglement entropy and the butterfly velocity. We demonstrate that they serve as good probes of the theory, in particular, distinguishing between the effects of the magnetic field and anisotropy in the ground and plasma states. We also find that the butterfly velocity, which codifies how fast information propagates in the plasma, exhibits a rich structure as a function of temperature, anisotropy and magnetic field, exceeding the conformal value in certain regimes.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

On the Solvability of a Matrix Boundary-Value Problem

We found solvability conditions and a construction of the generalized Green operator for a linear matrix boundary-value problem; we present an operator that reduces a linear matrix equation to the conventional linear Noether boundary-value problem. To solve a linear matrix system, we use the operator that reduces a linear matrix equation to a linear algebraic equation with a rectangular matrix.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Predictive capability of a leaf optical meter for determining leaf pigment status during senescence

We conducted an experiment to assess the predictive capability of a leaf optical meter for determining leaf pigment status of Acer mono Maxim., A. ginnala Maxim., Quercus mongolica Fisch., and Cornus alba displaying a range of visually different leaf colors during senescence. Concentrations of chlorophyll (Chl) a, Chl b, and total Chl decreased while the concentration of carotenoids (Car) remained relatively static for all species as leaf development continued from maturity to senescence. C. alba exhibited the lowest average concentration of total Chl, Chl a, and Car, but the highest relative anthocyanin concentration, while Q. mongolica exhibited the highest total Chl, Chl b, and the lowest relative anthocyanin concentration. A. mono exhibited the highest Chl a and Car concentrations. The relationships between leaf pigments and the values measured by the optical meter generally followed an exponential function. The strongest relationships between leaf pigments and optical measurements were for A. mono, A. ginnala, and Q. mongolica (R 2 ranged from 0.64 to 0.95), and the worst relationship in C. alba (R 2 ranged from 0.13 to 0.67). Moreover, optical measurements were more strongly related to Chl a than to Chl b or total Chl. Optical measurements were not related to Car or relative anthocyanin concentrations. We predicted that weak relationships between leaf pigments and optical measurements would occur under very low Chl concentrations or under very high anthocyanin concentrations; however, these factors could not explain the weak relationship between Chl and optical measurements observed in C. alba. Overall, our results indicated that optical meter can accurately estimate leaf pigment concentrations during leaf senescence — a time when pigment concentrations are dynamically changing — but that the accuracy of the estimate varies across species. Future research should investigate how species-specific leaf traits may influence the accuracy of pigment estimates derived from optical meters.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Chaos-based potentials in the one-dimensional tight-binding model probed by the inverse participation ratio

Chaos-based potentials are defined and implemented in the one-dimensional tight-binding model as a way of simulating disorder-controlled crystalline lattices. In this setting, disorder is handled with the aid of the chaoticity parameter. The inverse participation ratio (IPR) probes the response of the system to three different such potentials and shows consistent agreement with results given by the Lyapunov exponent Ly: the greater Ly(r) for the chaotic sequence as a function of the chaoticity parameter r, the greater the asymptotic value IPR(r) for the large-system ground state.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

q-coherent states associated with the noncommutative complex plane C{sub q{sup 2}} for the Biedenharn–Macfarlane q-oscillator

The q-coherent states associated with the noncommutative complex plane C{sub q{sup 2}} for the Biedenharn–Macfarlane q-oscillator are constructed by using a q-generalization of the Glauber’s unitary displacement operator. The q-deformed counterpart of the eigenvalue equation of undeformed harmonic oscillator coherent states is obtained. Some properties of the q-coherent states are considered. It is shown that super-Poissonian statistics and saturation of the uncertainty relation occur simultaneously with the nonclassical behaviors including antibunching effects with nonnegative values less than unity and the negative values, for the second-order intensity q-correlation function in the case of q>1. Furthermore, the nonclassical sub-Poissonian statistics is demonstrated simultaneously with bunching and antibunching effects such that in some regions of the coherence parameter the uncertainty inequality is satisfied, and violated elsewhere. We show that another nonclassical effect, the so-called strong squeezing effect, is exhibited by both quadrature variances in the latter issue.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

Upregulated circular RNA circ{sub 0}016760 indicates unfavorable prognosis in NSCLC and promotes cell progression through miR-1287/GAGE1 axis

Non-small cell lung cancer (NSCLC) is an aggressive malignancy with increasing worldwide incidence and is characterized by dismal prognosis due to its early recurrence and metastasis. Accumulating evidence documented that aberrantly expressed circular RNAs (circRNAs) are critically involved in tumorigenesis. In the current study, we focused on a novel circRNA, circ{sub 0}016760 in NSCLC. qRT-PCR was carried out to determine the expression level of circ{sub 0}016760 in tissue samples and cell lines. The clinical value of circ{sub 0}016760 was also investigated. The functions of circ{sub 0}016760 was explored by CCK-8, colony formation, flow cytometry, Transwell and animal experiments. Luciferase reporter assays were conducted to investigate the association between circ{sub 0}016760 and miR-1287 and miR-1287 and GAGE1. We found that circ{sub 0}016760 was enhanced in NSCLC tissues and cells and the upregulation of circ{sub 0}016760 is associated with advanced TNM stages, lymph node metastasis and adverse prognosis in NSCLC patients. Moreover, circ{sub 0}016760 could significantly promote cell growth and metastatic properties and inhibit cell apoptosis in NSCLC cells. In mechanism, circ{sub 0}016760 functioned as a sponge for miR-1287 and regulated the expression of GAGE1. Subsequently, functional assays illustrated that the oncogenic properties of circ{sub 0}016760 is partly attribute to the regulation of miR-1287/GAGE1 axis. In summary, circ{sub 0}016760/miR-1287/GAGE1 signaling might play vital roles in the tumorigenesis and progression of NSCLC.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Gradient flow based phase-field modeling using separable neural networks

Allen–Cahn equation is a reaction–diffusion equation and is widely used for modeling phase separation. Machine learning methods for solving the Allen–Cahn equation in its strong form suffer from inaccuracies in collocation techniques, errors in computing higher-order spatial derivatives, and the large system size required by the space–time approach. To overcome these challenges, we propose solving the gradient flow of the Ginzburg–Landau free energy functional, which is equivalent to the Allen–Cahn equation, thereby avoiding the second-order spatial derivatives associated with the Allen–Cahn equation. A minimizing movement scheme is employed to solve the gradient flow problem, eliminating the complexities of a space–time approach. We utilize a separable neural network that efficiently represents the phase field through low-rank tensor decomposition. As we use the minimizing movement scheme to numerically solve the gradient flow problem, we thus, refer to the proposed method as the Separable Deep Minimizing Movement (SDMM) method. The evaluation of the functional in the minimizing movement scheme using the Gauss quadrature technique bypasses the inaccuracies associated with collocation techniques traditionally used to solve partial differential equations. A hyperbolic tangent transformation is introduced on the phase field prior to the evaluation of the functional to ensure that it remains strictly bounded within the values of the two phases. For this transformation, theoretical guarantee for energy stability of the minimizing movement scheme is established. Our results suggest that this transformation helps to improve the accuracy and efficiency significantly. The proposed method resolves the challenges faced by state-of-the-art machine learning techniques, outperforming them in both accuracy and efficiency. It is also the first machine learning method to achieve an order of magnitude speed improvement over the finite element method. In addition to its formulation and computational implementation, several case studies illustrate the applicability of the proposed method.

42 ENGINEERING↗
DOE OSTI2018

A comparative study of shear band tracking strategies in three-dimensional finite elements with embedded weak discontinuities

We present a computational framework for the treatment of shear localization in metallic materials under dynamic loading, based on the integration of a shear band tracking strategy into an explicit 3D finite element formulation with embedded weak discontinuities. Within this computational framework, an embedded shear band’s mid-surface is represented by an iso-surface of a level set function, which is obtained by solving a heatconduction type boundary value problem (BVP). The solution of this BVP is carried out either globally over the entire problem domain, or locally at the level of individual elements in the mesh. In this paper, we present a detailed comparison of these global and local algorithmic implementations of the shear band tracking strategy. Numerical results obtained using these two implementations, and using a simplified formulation without shear band tracking, are presented and compared. Moreover, we compare the computational efficiency and parallel scaling performance of the local and global implementations. This comparative study shows that both implementations can simulate the initiation of two independent shear bands and their propagation past each other without merging, whereas only the global implementation can successfully simulate the merging of two branches of a single shear band. This study also confirms that the global implementation is more computationally intensive, since it requires a global system of linear equations associated with the level set BVP to be solved at each time step. Both implementations exhibit very good scalability in domain decomposition-based parallel simulations.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Kernel learning backward SDE filter for data assimilation

In this paper, we develop a kernel learning backward SDE filter method to estimate the state of a stochastic dynamical system based on its partial noisy observations. A system of forward backward stochastic differential equations is used to propagate the state of the target dynamical model, and Bayesian inference is applied to incorporate the observational information. Further, to characterize the dynamical model in the entire state space, we introduce a kernel learning method to learn a continuous global approximation for the conditional probability density function of the target state by using discrete approximated density values as training data. Numerical experiments demonstrate that the kernel learning backward SDE is highly effective.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

High-Performance Thermoelectrics from Cellular Nanostructured Sb 2 Si 2 Te 6

We introduce Sb 2 Si 2 Te 6 as a high-performance thermoelectric material. Single-crystal X-ray diffraction analysis indicates that Sb 2 Si 2 Te 6 has a layered twodimensional structure with Sb 3+ cations and [Si 2 Te 6 ] 6- units as building blocks adopting the Fe 2 P 2 Se 6 structure type. Sb 2 Si 2 Te 6 is a direct-band-gap semiconductor with valence-band maximum and conduction-band minimum at the Z point in the Brillouin zone, where the band is doubly degenerate. Polycrystalline bulk pellets of Sb 2 Si 2 Te 6 with randomly packed grains exhibit an intrinsically high thermoelectric figure of merit ZT of ~1.08 at 823 K. We then create a cellular nanostructure with ultrathin Si 2 Te 3 nanosheets covering the Sb 2 Si 2 Te 6 grains, which act as a hole-transmitting electron-blocking filter and at the same time cause extra phonon scattering. Lastly, this dual function of the cellular nanostructure achieves an ultralow thermal conductivity value of ~0.29 Wm -1 K -1 and a high ZT value of ~1.65 at 823 K for Sb 2 Si 2 Te 6 , along with a high average ZT value of ~0.98.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Identifying High Ionic Conductivity Compositions of Ionic Liquid Electrolytes Using Features of the Solvation Environment

Binary mixtures of ionic liquids with molecular solvents are gaining interest in electrochemical applications due to the improvement in their performance over neat ionic liquids. Dilution with suitable molecular solvents can reduce the viscosity and facilitate faster diffusion of ions, thereby yielding substantially higher ionic conductivity than that for a pure ionic liquid. Although viscosity and diffusion coefficients typically behave as monotonic functions of concentration, ionic conductivity often passes through a peak value at an optimum molar ratio of the molecular solvent to the ionic liquid. The ionic conductivity maximum is generally explained in terms of a balance between the ease of charge transport and the concentration of the charge carriers. In this work, fluctuation in the local environment surrounding an ion is invoked as a plausible explanation for the ionic conductivity mechanism with a binary mixture of 1-ethyl-3-methylimidazolium tetrafluoroborate and ethylene glycol as an example. The magnitude of the dynamism in the local environment is captured by measuring the spatial and temporal features of the solvation environment. Standard deviation in the number of ions in the solvation environment serves as a spatial feature, while the cage correlation lifetimes for oppositely charged ions within the first solvation shell serve as a temporal feature. Large standard deviations in the cluster ion population and short cage correlation lifetimes are indicators of highly dynamic ionic environment at the molecular level and consequently yield high ionic conductivity. Such compositions were found to be in good agreement with the optimum ionic liquid mole fractions obtained through experimental measurement. Short cage correlation lifetimes enable the identification of optimum mixture compositions using simulation trajectories significantly shorter than those required to implement the Nernst–Einstein or Einstein formalisms for calculating ionic conductivity. We validated the applicability of this approach across force fields and in six ionic liquid-molecular solvent electrolytes formed with combination of cations, anions, and solvents. We offer a computationally efficient approach of screening ionic liquid-molecular solvent binary mixture electrolytes to identify molar ratios that yield high ionic conductivity.

25 ENERGY STORAGE↗
DOE OSTI2020

Physical Bond Breaking in Associating Copolymer Liquids

We combine ideas from polymer and glassy liquid physics to construct a new model for the bond breaking time scale of attractive sticker groups in associating copolymer liquids that form transient networks. The activated event is argued to be a two-step process, involving first the release of the non-sticker dynamic caging constraints that defines the primary alpha relaxation, followed by attractive stickers surmounting an association free energy barrier subject to a local frictional resistance which can be strongly affected by relaxation-diffusion decoupling. Here, the ideas embedded in the model produce a consistent and good description of the bond breaking timescale for diverse polymer chemistries and architectures as a function of temperature and fraction of sticky groups. Chemically sensible values for association free energies are deduced. In strong contrast, the existing phenomenological models are shown to incur qualitative failures.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Engineering Magnetic Anisotropy and Emergent Multidirectional Soft Ferromagnetism in Ultrathin Freestanding LaMnO 3 Films

We report the combination of small coercive fields and weak magnetic anisotropy makes soft ferromagnetic films extremely useful for nanoscale devices that need to easily switch spin directions. However, soft ferromagnets are relatively rare, particularly in ultrathin films with thicknesses of a few nanometers or less. We have synthesized large-area, high-quality, ultrathin freestanding LaMnO 3 films on Si and found unexpected soft ferromagnetism along both the in-plane and out-of-plane directions when the film thickness was reduced to 4 nm. We argue that the vanishing magnetic anisotropy between the two directions is a consequence of two coexisting magnetic easy axes in different atomic layers of the LaMnO 3 film. Spectroscopy measurements reveal a change in Mn valence from 3+ in the film interior to approximately 2+ at the surfaces where considerable hydrogen infiltration occurs due to the water dissolving process. First-principles calculations show that protonation of LaMnO 3 decreases valence and Our the Mn switches the magnetic easy axis from in-plane to out-of-plane as the Mn valence approaches 2+ from its 3+ bulk value. Our work demonstrates that ultrathin freestanding films can exhibit functional properties that are absent in homogeneous materials, concomitant with their convenient compatibility with Si-based devices.

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

Nickel–Platinum Nanoparticles as Peroxidase Mimics with a Record High Catalytic Efficiency

While nanoscale mimics of peroxidase have been extensively developed over the past decade or so, their catalytic efficiency as a key parameter has not been substantially improved in recent years. Herein, we report a class of highly efficient peroxidase mimic–nickel–platinum nanoparticles (Ni–Pt NPs) that consist of nickel-rich cores and platinum-rich shells. The Ni–Pt NPs exhibit a record high catalytic efficiency with a catalytic constant (K cat ) as high as 4.5 × 10 7 s –1 , which is ~46- and 10 4 -fold greater than the K cat values of conventional Pt nanoparticles and natural peroxidases, respectively. Density functional theory calculations reveal that the unique surface structure of Ni–Pt NPs weakens the adsorption of key intermediates during catalysis, which boosts the catalytic efficiency. Furthermore, the Ni–Pt NPs were applied to an immunoassay of a carcinoembryonic antigen that achieved an ultralow detection limit of 1.1 pg/mL, hundreds of times lower than that of the conventional enzyme-based assay.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

A Darcy‐Brinkman‐Biot Approach to Modeling the Hydrology and Mechanics of Porous Media Containing Macropores and Deformable Microporous Regions

Abstract The coupled hydrology and mechanics of soft porous materials (such as clays, hydrogels, membranes, and biofilms) is an important research area in several fields, including water and energy technologies as well as biomedical engineering. Well‐established models based on poromechanics theory exist for describing these coupled properties, but these models are not adapted to describe systems with more than one characteristic length scale, that is, systems that contain both macropores and micropores. In this paper, we expand upon the well‐known Darcy‐Brinkman formulation of fluid flow in two‐scale porous media to develop a “Darcy‐Brinkman‐Biot” formulation: a general coupled system of equations that approximates the Navier‐Stokes equations in fluid‐filled macropores and resembles the equations for poroelasticity in microporous regions. We parameterized and validated our model for systems that contain either plastic (swelling clay) or elastic microporous regions. In particular, we used our model to predict the permeability of an idealized siliciclastic sedimentary rock as a function of pore water salinity and clay content. Predicted permeability values are well described by a single parametric relation between permeability and clay volume fraction that agrees with existing experimental data sets. Our novel formulation captures the coupled hydro‐chemo‐mechanical properties of sedimentary rocks and other deformable porous media in a manner that can be readily implemented within the framework of Digital Rock Physics.

Carrillo, Francisco J.↗
DOE OSTI2020

Exploring physics of ferroelectric domain walls via Bayesian analysis of atomically resolved STEM data

The physics of ferroelectric domain walls is explored using the Bayesian inference analysis of atomically resolved STEM data. We demonstrate that domain wall profile shapes are ultimately sensitive to the nature of the order parameter in the material, including the functional form of Ginzburg-Landau-Devonshire expansion, and numerical value of the corresponding parameters. The preexisting materials knowledge naturally folds in the Bayesian framework in the form of prior distributions, with the different order parameters forming competing (or hierarchical) models. Here, we explore the physics of the ferroelectric domain walls in BiFeO 3 using this method, and derive the posterior estimates of relevant parameters. More generally, this inference approach both allows learning materials physics from experimental data with associated uncertainty quantification, and establishing guidelines for instrumental development answering questions on what resolution and information limits are necessary for reliable observation of specific physical mechanisms of interest.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗