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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 1,189 records · Page 66
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

The Coordination Chemistry and Stoichiometry of Extracted Diglycolamide Complexes of Lanthanides in Extraction Chromatography Materials

Industrial rare earth element (REE) separations predominantly utilize solvent extraction processes tailored toward conventional resources such as bastnäsite, monazite, and ion adsorption clays. Advances in diglycolamide (DGA) chemistry have shown effective extraction characteristics for REE separations. However, limitations associated with traditional DGA solvent extraction techniques, such as third-phase formation and gelling, have hindered commercial viability. By supporting DGA extractants on porous resins such as polystyrene divinyl benzene (PS-DVB), the desirable combination of solvent extraction selectivity and ease of operation of sorbent columns can be achieved. To design a low-cost model for such solid-supported DGAs, extraction characteristics as influenced by the underlying coordination chemistry must be explored to achieve efficient functional systems. Within this study, we report novel DGA resin materials, each incorporating one of the DGAs N,N,N’,N’-tetra-(1-octyl)-3-oxapentane-1,5-diamide (TODGA), N,N'-dimethyl-N,N'-dioctyl-3-oxapentane-1,5-diamide (DMDODGA), and 2,2'-oxybis(1-(3-(((2-ethylhexyl)thio)methyl)-4-methylpyrrolidin-1-yl)ethan-1-one) (DEHPDGA). The affinity of DGAs across the lanthanide (Ln) series was evaluated for both hydrochloric acid and nitric acid media with varying Ln feed concentrations to study distribution ratios and loading characteristics. Focusing on dysprosium, extended X-Ray Absorption Fine Structure (EXAFS) and density functional theory (DFT) calculations were also utilized to explore coordination chemistry and their effects on ligand performance. The general trend for both acid media resulted in DMDODGA having the highest extraction strength of all three DGAs at varying acid concentrations. Coordination-chemistry analysis supported by loading data, DFT calculations, and EXAFS results under forced loading conditions posited less than the expected 3:1 ligand-to-metal coordination.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Equation of state for Hf, Ta, W, Re, Os, Ir, Pt, and Au to multi-terapascal pressures from density-functional theory

We present the zero-temperature equation of state (pressure dependence of compression) and phase stability predictions for the 5d-transition metals obtained from all-electron density-functional theory (DFT) calculations. The results compare favorably with experiments but extend beyond current experimental capabilities to 10 TPa. Our study reveals phase changes that are explained from the calculated electronic structure. The cubic face-centered and body-centered structures (fcc and bcc), together with two-, three-, and four-layered hexagonal structures, play major roles under compression. The results’ dependence on the electron exchange and correlation in the DFT approach is investigated, and it is shown that the impact of the choice, while significant at lower pressures, diminishes in the terapascal regime. We further illustrate that the normal parabolic trends in atomic volume and bulk modulus with atomic number, due to the occupation of bonding and anti-bonding 5d states, break down at TPa pressures, suggesting drastically different chemical bonding at these extreme conditions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Magnetic interactions and spin excitations in van der Waals ferromagnet VI 3

Using a combination of density functional theory (DFT) and spin-wave theory methods, we investigate the magnetic interactions and spin excitations in semiconducting VI 3 . Exchange parameters of monolayer, bilayer, and bulk forms are evaluated by mapping the magnetic energies of various spin configurations, calculated using DFT + U, onto the Heisenberg model. The intralayer couplings remain largely unchanged in three forms of VI 3 , while the interlayer couplings show stronger dependence on the dimensionality of the materials. We calculate the spin-wave spectra within a linear spin-wave theory and discuss how various exchange parameters affect the magnon bands. Here, the magnon–magnon interaction is further incorporated, and the Curie temperature is estimated using a self-consistently renormalized spin-wave theory. To understand the roles of constituent atoms on magnetocrystalline anisotropy energy (MAE), we resolve MAE into sublattices and find that a strong negative V-I inter-sublattice contribution is responsible for the relatively small easy-axis MAE in VI 3 .

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Correlation matrix renormalization theory in multi-band lattice systems

An appropriate treatment of electronic correlation effects plays an important role in accurate descriptions of physical and chemical properties of real materials. The recently proposed correlation matrix renormalization theory with sum rule correction (CMR) for studying correlated-electron materials has shown good performance in molecular systems and a periodic hydrogen chain in comparison with various quantum chemistry and quantum Monte Carlo calculations. Additionally, this work gives a detailed formulation and computational code implementation of CMR in multi-band periodic lattice systems. This lattice CMR ab initio theory is highly efficient, has no material specific adjustable parameters, and has no double counting issues faced by the hybrid approaches like LDA + U, DFT + DMFT and DFT + GA type theories. Benchmark studies on materials with s and p orbitals in this study show that CMR in its current implementation consistently performs well for these systems as the electron correlation increases from the bonding region to the bond breaking region.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Exploring metastable states in UO 2 using hybrid functionals and dynamical mean field theory

A detailed exploration of the f-atomic orbital occupancy space for UO2 is performed using a first principles approach based on density functional theory (DFT), employing a full hybrid functional within a systematic basis set. Specifically, the PBE0 functional is combined with an occupancy biasing scheme implemented in a wavelet-based algorithm which is adapted to large supercells. The results are compared with previous DFT + U calculations reported in the literature, while dynamical mean field theory is also performed to provide a further base for comparison. This work shows that the computational complexity of the energy landscape of a correlated f-electron oxide is much richer than has previously been demonstrated. The resulting calculations provide evidence of the existence of multiple previously unexplored metastable electronic states of UO 2 , including those with energies which are lower than previously reported ground states.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Metal–insulator transition in composition-tuned nickel oxide films

Abstract Thin films of the solid solution Nd 1 − x La x NiO 3 are grown in order to study the expected 0 K phase transitions at a specific composition. We experimentally map out the structural, electronic and magnetic properties as a function of x and a discontinuous, possibly first order, insulator–metal transition is observed at low temperature when x = 0.2. Raman spectroscopy and scanning transmission electron microscopy show that this is not associated with a correspondingly discontinuous global structural change. On the other hand, results from density functional theory (DFT) and combined DFT and dynamical mean field theory calculations produce a 0 K first order transition at around this composition. We further estimate the temperature-dependence of the transition from thermodynamic considerations and find that a discontinuous insulator–metal transition can be reproduced theoretically and implies a narrow insulator–metal phase coexistence with x . Finally, muon spin rotation ( µ SR) measurements suggest that there are non-static magnetic moments in the system that may be understood in the context of the first order nature of the 0 K transition and its associated phase coexistence regime.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Quantitative Predictive Theories through Integrating Quantum, Statistical, Equilibrium, and Nonequilibrium Thermodynamics

Today's thermodynamics is largely based on the combined law for equilibrium systems and statistical mechanics derived by Gibbs in 1873 and 1901, respectively, while irreversible thermodynamics for nonequilibrium systems resides essentially on the Onsager Theorem as a separate branch of thermodynamics developed in 1930s. Between them, quantum mechanics was invented and was quantitatively solved in terms of density functional theory (DFT) in 1960s. Furthermore, these three scientific domains operate based on different principles and are very much separated from each other. In analogy to the parable of the blind men and the elephant articulated by Perdew, they individually represent different portions of a complex system and thus are incomplete by themselves alone, resulting in the lack of quantitative agreement between their predictions and experimental observations. Over the last two decades, the author's group has developed a multiscale entropy approach (recently termed as zentropy theory) that integrates DFT-based quantum mechanics and Gibbs statistical mechanics and is capable of accurately predicting entropy and free energy of complex systems. Furthermore, in combination with the combined law for nonequilibrium systems developed by Hillert, the author developed the theory of cross phenomena beyond the phenomenological Onsager Theorem. The zentropy theory and theory of cross phenomena jointly provide quantitative predictive theories for systems from electronic to any observable scales as reviewed in the present work.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

First-principles calculation of Hubbard U for Terbium metal under high pressure

Abstract Using density functional theory (DFT) and linear response approaches, we compute the on-site Hubbard interaction U of elemental Terbium (Tb) metal in the pressure range ∼ 0–65 GPa. The resulting first-principles U values with experimental crystal structures enable us to examine the magnetic properties of Tb using a DFT+U method. The lowest-energy magnetic states in our calculations for different high-pressure Tb phases—including hcp, α -Sm, and dhcp—are found to be compatible with the corresponding magnetic ordering vectors reported in experiments. The result shows that the inclusion of Hubbard U substantially improves the accuracy and efficiency in modeling correlated rare-earth materials. Our study also provides the necessary U information for other quantum many-body techniques to study Tb under extreme pressure conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Parameterizing empirical interatomic potentials for predicting thermophysical properties via an irreducible derivative approach: the case of ThO 2 and UO 2

The accuracy of classical physical property predictions using molecular dynamics simulations is determined by the quality of the interatomic potentials. Here we introduce a training approach for empirical interatomic potentials (EIPs) which is well suited for capturing phonons and phonon-related properties. Our approach is based on direct comparisons of the second- and third-order irreducible derivatives (IDs) between an EIP and the Born–Oppenheimer potential within density functional theory (DFT) calculations. IDs fully exploit space group symmetry and allow for training without redundant information. We demonstrate the fidelity of our approach in the context of ThO 2 and UO 2 , where we optimize parameters of an embedded-atom method potential in addition to core–shell interactions. Our EIPs provide thermophysical properties in good agreement with DFT and outperform widely utilized EIPs for phonon dispersion and thermal conductivity predictions. Reasonable estimates of thermal expansion and formation energies of Frenkel pairs are also obtained.

empirical interatomic potential↗
DOE OSTI2023

Modeling plasma-induced surface charge effects on CO 2 activation by single atom catalysts supported on reducible and irreducible metal oxides

Abstract The accumulation of negative surface charge on catalytic surfaces in the presence of low-temperature plasma (LTP) could influence catalytic performance. However, it is difficult to disentangle the role of surface charging and other LTP catalytic effects in experiment. Herein, we use density functional theory (DFT) modeling to understand the effect of plasma-induced surface charging on CO 2 activation by atomically dispersed single atom (SA) catalysts on both reducible and irreducible metal oxide supports. We model CO 2 adsorption strength and CO 2 dissociation barriers for Co 1 , Ni 1 , Cu 1 , Rh 1 , Pd 1 , and Ag 1 SAs on both reducible and irreducible supports, namely, CeO 2 (100), TiO 2 (101), and γ -Al 2 O 3 (110), to elucidate trends. We find that accumulated surface charge on the SA increases the CO 2 adsorption strength and decreases the CO 2 dissociation barrier for all studied SA/support combinations. For both charged and uncharged (neutral) systems, SAs on the reducible CeO 2 (100) support generally adsorb CO 2 more weakly compared to when on irreducible supports like γ -Al 2 O 3 (110). SAs on γ -Al 2 O 3 (110) typically have larger barriers for CO 2 dissociation for both charged and uncharged systems compared to TiO 2 (101) and CeO 2 (100). The magnitude of surface charging effects on CO 2 binding energies and dissociation barriers depends sensitively on both the SA and the support. In some cases, the CO 2 activation trends qualitatively change between neutral and charged systems for a fixed SA across different supports. This DFT modeling study demonstrates that surface charging should be considered in strong electric fields because it can have a large effect on molecule adsorption and bond-breaking on catalytic surfaces.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Decoupling plasma, catalyst, and gaseous mechanisms for non-oxidative methane conversion

Direct non-oxidative methane (CH 4 ) conversion to value-added hydrogen (H 2 ) and C 2 products remains hindered by fundamental catalytic scaling constraints and rapid surface deactivation at elevated temperatures. Plasma-enabled catalysis offers a promising route to overcome the thermodynamic and kinetic barriers of direct non-oxidative methane upgrading at mild conditions, yet control over C–C product selectivity and catalyst stability remains elusive. Here, we establish a unified mechanistic framework including Langmuir–Hinshelwood (L–H) and Langmuir–Rideal (L–R) mechanisms that disentangles the roles of plasma excitation (including vibrationally activated species and radicals), surface temperature (T sur ), and catalyst binding energy in steering CH 4 conversion to H 2 and C 2 hydrocarbons. Through a combination of density functional theory (DFT) informed microkinetic modeling, in situ and ex situ surface characterization, and product quantification under dielectric barrier discharge conditions, we show that vibrationally excited CH 4 lowers activation barriers selectively for dissociative chemisorption, enabling surface activation across a wide range of transition metal catalysts at low thermal energy input. We find that once CH 4 is dissociatively chemisorbed, the branching between C 2 H 2 , C 2 H 4 , and C 2 H 6 is governed by surface properties (carbon binding energy, T sur , etc), regardless of plasma excitation. The DFT informed microkinetic model decouples the effects of molecular activation from surface properties and indentifies operating windows that maximize target yields while suppressing carbon accumulation and subsequent catalytic inactivation. Experiments on polycrystalline Cu/Al 2 O 3 , Ni/Al 2 O 3 , and Pt/Al 2 O 3 validate these predictions, revealing catalyst-dependent branching toward ethane or ethylene and distinct deactivation profiles. We unify these trends into a generalized three-dimensional plasma-thermal-catalytic design space, from which reduced descriptors such as T vib /T sur in the limit of vibrationally excited L–H pathways emerge as predictive metrics. These results enable rational tuning of methane conversion pathways and unlock selective C 2 formation using earth-abundant metals under mild plasma conditions.

catalyst inactivation↗
DOE OSTI2021

Electronic properties of single-layer CoO 2 /Au(111)

Here we report direct measurements via angle-resolved photoemission spectroscopy (ARPES) of the electronic dispersion of single-layer (SL) CoO 2 . The Fermi contour consists of a large hole pocket centered at the $\overline{\Gamma}$ point. To interpret the ARPES results, we use density functional theory (DFT) in combination with the multi-orbital Gutzwiller Approximation (DFT+GA), basing our calculations on crystalline structure parameters derived from x-ray photoelectron diffraction and low-energy electron diffraction. Our calculations are in good agreement with the measured dispersion. We conclude that the material is a moderately correlated metal. We also discuss substrate effects, and the influence of hydroxylation on the CoO 2 SL electronic structure.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Hubbard-corrected oxide formation enthalpies without adjustable parameters

A density functional theory (DFT) approach to computing transition metal oxide heat of formation without adjustable parameters is presented. Different degrees of d-electron localization in oxides are treated within the DFT+U approach with site-dependent, first-principles Hubbard U-parameters obtained from linear response theory, and delocalized states in the metallic phases are treated without Hubbard corrections. Comparison of relative stabilities of these differently treated phases is enabled by a local d-electron density matrix-dependent model, which was found by genetic programming against experimental reference formation enthalpies. This mathematically simple model does not explicitly depend on the Hubbard-corrected ionic species and is shown to reproduce the heats of formation of the Mott insulators Ca 2 RuO 4 and Y 2 Ru 2 O 7 within ~3% of experimental results, where the experimental training data did not contain Ru oxides. This newly developed method thus absolves from the need for element-specific corrections fitted to experiments in existing Hubbard-corrected approaches to the prediction of reaction energies of transition metal oxides and metals. The absence of fitting parameters opens up here the possibility to predict relative thermodynamic stabilities and reaction energies involving d-states of varying degree of localization at transition metal oxide interfaces and defects, where site-dependent U-parameters will be particularly important and devising a fitting scheme against experimental data with predictive power would be exceedingly difficult.

transition metal oxides↗
DOE OSTI2023

Simulations with machine learning potentials identify the ion conduction mechanism mediating non-Arrhenius behavior in LGPS

Abstract Li 10 Ge(PS 6 ) 2 (LGPS) is a highly concentrated solid electrolyte, in which Coulombic repulsion between neighboring cations is hypothesized as the underlying reason for concerted ion hopping, a mechanism common among superionic conductors such as Li 7 La 3 Zr 2 O 12 (LLZO) and Li 1.3 Al 0.3 Ti 1.7 (PO 4 ) 3 (LATP). While first principles simulations using molecular dynamics (MD) provide insight into the Li + transport mechanism, historically, there has been a gap in the temperature ranges studied in simulations and experiments. Here, we used a neural network potential trained on density functional theory (DFT) simulations, to run up to 40-nanosecond long MD simulations at DFT-like accuracy to characterize the ion conduction mechanisms across a range of temperatures that includes previous simulations and experimental studies. We have confirmed a Li + sublattice phase transition in LGPS around 400 K, below which the ab -plane diffusivity D a b ∗ is drastically reduced. Concomitant with the sublattice phase transition near 400 K, there is less cation-cation (cross) correlation, as characterized by Haven ratios closer to 1, and the vibrations in the system are more harmonic at lower temperature. Intuitively, at high temperature, the collection of vibrational modes may be sufficient to drive concerted ion hops. However, near room temperature, the vibrational modes available may be insufficient to overcome electrostatic repulsion, thus resulting in less correlated ion motion and comparatively slower ion conduction. Such phenomena of a sublattice phase transition, below which concerted hopping plays a less significant role, may be extended to other highly concentrated solid electrolytes such as LLZO and LATP.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Global perspectives of the bulk electronic structure of URu 2 Si 2 from angle-resolved photoemission

Previous high-resolution angle-resolved photoemission (ARPES) studies of URu 2 Si 2 have characterized the temperature-dependent behavior of narrow-band states close to the Fermi level ( E F ) at low photon energies near the zone center, with an emphasis on electronic reconstruction due to Brillouin zone folding. A substantial challenge to a proper description is that these states interact with other hole-band states that are generally absent from bulk-sensitive soft x-ray ARPES measurements. Here we provide a more global k -space context for the presence of such states and their relation to the bulk Fermi surface (FS) topology using synchrotron-based wide-angle and photon energy-dependent ARPES mapping of the electronic structure using photon energies intermediate between the low-energy regime and the high-energy soft x-ray regime. Small-spot spatial dependence, f -resonant photoemission, Si 2 p core-levels, x-ray polarization, surface-dosing modification, and theoretical surface slab calculations are employed to assist identification of bulk versus surface state character of the E F -crossing bands and their relation to specific U- or Si-terminations of the cleaved surface. The bulk FS topology is critically compared to density functional theory (DFT) and to dynamical mean field theory calculations. In addition to clarifying some aspects of the previously measured high symmetry Γ, Z and X points, incommensurate 0.6 a * nested Fermi-edge states located along Z – N – Z are found to be distinctly different from the DFT FS prediction. The temperature evolution of these states above T HO , combined with a more detailed theoretical investigation of this region, suggests a key role of the N -point in the hidden order transition.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Multi-task graph neural networks for simultaneous prediction of global and atomic properties in ferromagnetic systems *

Abstract We introduce a multi-tasking graph convolutional neural network, HydraGNN, to simultaneously predict both global and atomic physical properties and demonstrate with ferromagnetic materials. We train HydraGNN on an open-source ab initio density functional theory (DFT) dataset for iron-platinum with a fixed body centered tetragonal lattice structure and fixed volume to simultaneously predict the mixing enthalpy (a global feature of the system), the atomic charge transfer, and the atomic magnetic moment across configurations that span the entire compositional range. By taking advantage of underlying physical correlations between material properties, multi-task learning (MTL) with HydraGNN provides effective training even with modest amounts of data. Moreover, this is achieved with just one architecture instead of three, as required by single-task learning (STL). The first convolutional layers of the HydraGNN architecture are shared by all learning tasks and extract features common to all material properties. The following layers discriminate the features of the different properties, the results of which are fed to the separate heads of the final layer to produce predictions. Numerical results show that HydraGNN effectively captures the relation between the configurational entropy and the material properties over the entire compositional range. Overall, the accuracy of simultaneous MTL predictions is comparable to the accuracy of the STL predictions. In addition, the computational cost of training HydraGNN for MTL is much lower than the original DFT calculations and also lower than training separate STL models for each property.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Benchmarking machine learning interatomic potentials via phonon anharmonicity

Abstract Machine learning approaches have recently emerged as powerful tools to probe structure-property relationships in crystals and molecules. Specifically, machine learning interatomic potentials (MLIPs) can accurately reproduce first-principles data at a cost similar to that of conventional interatomic potential approaches. While MLIPs have been extensively tested across various classes of materials and molecules, a clear characterization of the anharmonic terms encoded in the MLIPs is lacking. Here, we benchmark popular MLIPs using the anharmonic vibrational Hamiltonian of ThO 2 in the fluorite crystal structure, which was constructed from density functional theory (DFT) using our highly accurate and efficient irreducible derivative methods. The anharmonic Hamiltonian was used to generate molecular dynamics (MD) trajectories, which were used to train three classes of MLIPs: Gaussian approximation potentials, artificial neural networks (ANN), and graph neural networks (GNN). The results were assessed by directly comparing phonons and their interactions, as well as phonon linewidths, phonon lineshifts, and thermal conductivity. The models were also trained on a DFT MD dataset, demonstrating good agreement up to fifth-order for the ANN and GNN. Our analysis demonstrates that MLIPs have great potential for accurately characterizing anharmonicity in materials systems at a fraction of the cost of conventional first principles-based approaches.

interatomic potentials↗
DOE OSTI2025

Toward machine learning interatomic potentials for modeling uranium mononitride

Uranium mononitride (UN) is a promising accident-tolerant fuel because of its high fissile density and high thermal conductivity. In this study, we developed the first machine learning interatomic potentials for reliable atomic-scale modeling of UN at finite temperatures. We constructed a training set using density functional theory (DFT) calculations that was enriched through an active learning procedure, and two neural network potentials were generated. Both potentials successfully reproduce key thermophysical properties of interest, such as temperature-dependent lattice parameter, specific heat capacity, and bulk modulus. We also evaluated the energy of stoichiometric defect reactions and defect migration barriers and found close agreement with DFT predictions, demonstrating that our potentials can be used for modeling defects in UN. Additional tests provide evidence that our potentials are reliable for simulating diffusion, noble gas impurities, and radiation damage.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗