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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Best practices for first-principles simulations of epitaxial inorganic interfaces

Abstract At an interface between two materials physical properties and functionalities may be achieved, which would not exist in either material alone. Epitaxial inorganic interfaces are at the heart of semiconductor, spintronic, and quantum devices. First principles simulations based on density functional theory (DFT) can help elucidate the electronic and magnetic properties of interfaces and relate them to the structure and composition at the atomistic scale. Furthermore, DFT simulations can predict the structure and properties of candidate interfaces and guide experimental efforts in promising directions. However, DFT simulations of interfaces can be technically elaborate and computationally expensive. To help researchers embarking on such simulations, this review covers best practices for first principles simulations of epitaxial inorganic interfaces, including DFT methods, interface model construction, interface structure prediction, and analysis and visualization tools.

Physics↗
DOE OSTI2025

Simulations of edge and SOL turbulence in diverted negative and positive triangularity plasmas

Optimizing the performance of magnetic confinement fusion devices is critical to achieving an attractive fusion reactor design. Negative triangularity (NT) scenarios have been shown to achieve excellent levels of energy confinement, while avoiding edge localized modes. Modeling turbulent transport in the edge and SOL is key in understanding the impact of NT on turbulence and extrapolating the results to future devices and regimes. Previous gyrokinetic turbulence studies have reported beneficial effects of NT across a broad range of parameters. However, most simulations have focused on the inner plasma region, neglecting the impact of NT on the outermost edge. In this work, we investigate the effect of NT in edge and scrape-off layer simulations, including the magnetic X-point and separatrix. For the first time, we employ a multi-fidelity approach, combining global, non-linear gyrokinetic simulations with drift-reduced fluid simulations, to gain a deeper understanding of the underlying physics at play. First-principles simulations using the GENE-X code demonstrate that in comparable NT and PT geometries, similar profiles are achieved, while the turbulent heat flux is reduced by more than 50% in NT. Comparisons with results from the drift-reduced fluid turbulence code GRILLIX suggest that the turbulence is driven by trapped electron modes. The parallel heat flux width on the divertor targets is reduced in NT, primarily due to a lower spreading factor S.

GENE-X↗
DOE OSTI2025

The search for high-entropy fuel-cell catalysts using disorder descriptors

The transition to a hydrogen economy depends on efficient, affordable catalysts for fuel cells. Platinum—the industry standard for fuel-cell electrodes—is costly and scarce, highlighting the need for practical alternatives. High-entropy alloys offer vast compositional diversity and tunable properties that can mitigate these issues, yet their chemical complexity and configurational disorder have hindered rational discovery. Here, we introduce a data-driven framework that couples machine learning with first-principles disorder descriptors—including the entropy forming ability, disordered enthalpy-entropy descriptor, and electronic-structure similarity metrics to platinum—to predict alloy synthesizability and catalytic performance. These descriptors are applied for the first time in the context of fuel-cell catalyst discovery. The workflow rapidly screens more than 20 000 compositions and identifies several platinum-free candidates that are economically viable, readily scalable, and exhibit promising predicted activity. These results demonstrate that disorder descriptors are reliably predicted by machine learning models and can be effectively integrated into materials-discovery pipelines, accelerating innovation across complex compositional spaces.

fuel-cell catalysts↗
DOE OSTI2021

Modeling carrier mobility in graphene as a sensitive probe of molecular magnets

Carrier mobility in graphene on a GaAs substrate and its change due to the adsorption of molecular magnets, Mn 12 and [Mn 3 ] 2 , on the surface of graphene, is calculated from first principles. Phonon limited mobility is also calculated for comparison. For Mn 12 adsorption on graphene, the mobility is compared for different organic ligands of Mn 12 (-H, -CH 3 , and - CHCl 2 ), while for [Mn 3 ] 2 dimers, the mobility is calculated for different linkers that yield the ferromagnetic and anti-ferromagnetic configurations of [Mn 3 ] 2 , as well as for different orientations of the molecule. Significant changes in carrier mobility due to the adsorption of the molecules and due to differences in linkers suggest mobility measurement as a possible sensitive probe of magnetic molecules.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Heat transport in liquid water from first-principles and deep neural network simulations

In this work, we compute the thermal conductivity of water within linear response theory from equilibrium molecular dynamics simulations, by adopting two different approaches. In one, the potential energy surface (PES) is derived on the fly from the electronic ground state of density functional theory (DFT) and the corresponding analytical expression is used for the energy flux. In the other, the PES is represented by a deep neural network (DNN) trained on DFT data, whereby the PES has an explicit local decomposition and the energy flux takes a particularly simple expression. By virtue of a gauge invariance principle, established by Marcolongo, Umari, and Baroni, the two approaches should be equivalent if the PES were reproduced accurately by the DNN model. We test this hypothesis by calculating the thermal conductivity, at the GGA (PBE) level of theory, using the direct formulation and its DNN proxy, finding that both approaches yield the same conductivity, in excess of the experimental value by approximately 60%. Besides being numerically much more efficient than its direct DFT counterpart, the DNN scheme has the advantage of being easily applicable to more sophisticated DFT approximations, such as meta-GGA and hybrid functionals, for which it would be hard to derive analytically the expression of the energy flux. We find in this way that a DNN model, trained on meta-GGA (SCAN) data, reduces the deviation from experiment of the predicted thermal conductivity by about 50%, leaving the question open as to whether the residual error is due to deficiencies of the functional, to a neglect of nuclear quantum effects in the atomic dynamics, or, likely, to a combination of the two.

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

Thermodynamic and electron transport properties of Ca 3 Ru 2 O 7 from first-principles phonon calculations and Boltzmann transport theory

Here, this work demonstrates a first-principles-based approach to obtaining finite temperature thermal and electronic transport properties which can be employed to model and understand mesoscale structural evolution during electronic, magnetic, and structural phase transitions. A computationally tractable model was introduced to estimate electron relaxation time and its temperature dependence. The model is applied to Ca 3 Ru 2 O 7 with a focus on understanding its electrical resistivity across the electronic phase transition at 48 K. A quasiharmonic phonon approach to the lattice vibrations was employed to account for thermal expansion while the Boltzmann transport theory including spin-orbit coupling was used to calculate the electron-transport properties, including the temperature dependence of electrical conductivity.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Accidental persistent spin textures in the proustite mineral family

Persistent spin textures (PSTs) in momentum space have the potential to enable spintronic devices which are currently limited by spin lifetimes in nonmagnetic spin-orbit coupled materials. We perform a first-principles study on the proustite mineral family, Ag 3 ⁢B⁢Q 3 (B = As, Sb; Q = S, Se), and show these chalcogenides exhibit nonsymmetry-protected PSTs, which we refer to as symmetry-assisted PSTs. Chemical substitution can be used to tune the PST quality and properties, e.g., spin lifetime, and we find that a Rashba anisotropy criterion correlates with the PST area and spin lifetime for two of the three proustites examined. Last, we show that a first-order effective SOC Hamiltonian, often used in two-dimensional systems, is insufficient to describe the PST state in all proustites, suggesting that higher order models are necessary to fully describe PSTs in bulk three-dimensional materials.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Accuracy of ghost rotationally invariant slave-boson and dynamical mean field theory as a function of the impurity-model bath size

Here, we compare the accuracy of the ghost rotationally invariant slave-boson (g-RISB) theory and dynamical mean field theory (DMFT) on the single-band Hubbard model, as a function of the number of bath sites in the embedding impurity Hamiltonian. Our benchmark calculations confirm that the accuracy of g-RISB can be systematically improved by increasing the number of bath sites, similar to DMFT. With a few bath sites, we observe that g-RISB is systematically more accurate than DMFT for the ground-state observables. On the other hand, the relative accuracy of these methods is generally comparable for the quasiparticle weight and the spectral function. As expected, we observe that g-RISB satisfies the variational principle in infinite dimensions, as the total energy decreases monotonically towards the exact value as a function of the number of bath sites, suggesting that the g-RISB wave function may approach the exact ground state in infinite dimensions. Our results suggest that the g-RISB is a promising method for first-principles simulations of strongly correlated matter, which can capture the behavior of both static and dynamical observables, at a relatively low computational cost.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Lattice vibrations and energy landscape of the isoelectronic semiconductor series CuBr, ZnSe, GaAs, and Ge: The special case of CuBr and its $\mathcal{d}$-level chemistry

Here we have examined the lattice vibrations and the energy landscape of the isoelectronic diamond and zincblende semiconductor series CuBr, ZnSe, GaAs, and Ge. Vibrations are found to be an increasing function of ionicity, with the cation sublattice always vibrating more strongly than the anion sublattice. These findings are consistent with density functional theory (DFT) calculations of the energy landscape and temperature-dependent molecular dynamics simulations of the atomic-position fluctuations. For CuBr, inclusion of the Cu 3d Hubbard U term is found necessary to stabilize the zincblende structure and to bring its vibrational amplitudes into agreement with experiment. In addition, vibrations are found to strongly affect the CuBr near-edge x-ray absorption fine structure that we have successfully modeled by including displacements in our theoretical Bethe-Salpeter equation calculations. Reverse Monte Carlo structural refinements using large atomic configurations to simultaneously fit x-ray absorption and x-ray total-scattering data support these conclusions, and they reveal strong Cu-Br first-neighbor correlations and asymmetric distributions of interatomic distances in the temperature ranges of both negative and positive thermal expansion. Delineation of the CuBr valence band photoelectron spectrum into its Cu 3d and Br 4p states uniquely reveals their covalent mixing and further supports the DFT results.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Symbolic pregression: Discovering physical laws from distorted video

In this work, we present a method for unsupervised learning of equations of motion for objects in raw and optionally distorted unlabeled synthetic video (or, more generally, for discovering and modeling predictable features in time-series data). We first train an autoencoder that maps each video frame into a low-dimensional latent space where the laws of motion are as simple as possible, by minimizing a combination of nonlinearity, acceleration, and prediction error. Differential equations describing the motion are then discovered using Pareto-optimal symbolic regression. We find that our pre-regression (“pregression”) step is able to rediscover Cartesian coordinates of unlabeled moving objects even when the video is distorted by a generalized lens. Using intuition from multidimensional knot theory, we find that the pregression step is facilitated by first adding extra latent space dimensions to avoid topological problems during training and then removing these extra dimensions via principal component analysis. An inertial frame is autodiscovered by minimizing the combined equation complexity for multiple experiments.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Phase Diagram of a Deep Potential Water Model

Using the Deep Potential methodology, we construct a model that reproduces accurately the potential energy surface of the SCAN approximation of density functional theory for water, from low temperature and pressure to about 2400 K and 50 GPa, excluding the vapor stability region. The computational efficiency of the model makes it possible to predict its phase diagram using molecular dynamics. Satisfactory overall agreement with experimental results is obtained. Here, the fluid phases, molecular and ionic, and all the stable ice polymorphs, ordered and disordered, are predicted correctly, with the exception of ice III and XV that are stable in experiments, but metastable in the model. The evolution of the atomic dynamics upon heating, as ice VII transforms first into ice VII" and then into an ionic fluid, reveals that molecular dissociation and breaking of the ice rules coexist with strong covalent fluctuations, explaining why only partial ionization was inferred in experiments.

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

Uniaxial Strain Control of Bulk Ferromagnetism in Rare-Earth Titanates

The perovskite rare-earth titanates are model Mott insulators with magnetic ground states that are very sensitive to structural distortions. These distortions couple strongly to the orbital degrees of freedom and, in principle, it should be possible to tune the superexchange and the magnetic transition with strain. We investigate the representative system (Y,La,Ca)TiO 3 , which exhibits low crystallographic symmetry and no structural instabilities. From magnetic susceptibility measurements of the Curie temperature, we demonstrate direct, reversible, and continuous control of ferromagnetism by influencing the TiO 6 octahedral tilts and rotations with uniaxial strain. The relative change in T C as a function of strain is well described by ab initio calculations, which provides detailed understanding of the complex interactions among structural, orbital, and magnetic properties in rare-earth titanates. The demonstrated manipulation of octahedral distortions opens up far-reaching possibilities for investigations of electron-lattice coupling, competing ground states, and magnetic quantum phase transitions in a wide range of quantum materials.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Group Conductivity and Nonadiabatic Born Effective Charges of Disordered Metals, Warm Dense Matter, and Hot Dense Plasma

The average ionization state is a critical parameter in plasma models for charged particle transport, equations of state, and optical response. The dynamical or nonadiabatic Born effective charge (NBEC), calculated via first principles time-dependent density-functional theory, provides exact ionic partitioning of bulk electron response for both metallic and insulating materials. The NBEC can be transformed into a “group conductivity,” i.e., the electron conductivity ascribed to a subset of ions. We show that for disordered metallic systems, such as warm dense matter (WDM) and hot dense plasma, the static limit of the NBEC is different from the average ionization states, but that the ionization state can be extracted from the group conductivity even in mixed systems. Here we demonstrate this approach using a set of archetypical examples, including cold and warm aluminium, low- and high-density WDM carbon, and a WDM carbon-beryllium-hydrogen mixture.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

First-principles characterization of the magnetic properties of Cu 2 (OH) 3 Br

Low-dimensional spin-1/2 transition metal oxides and oxyhalides continue to be at the forefront of research investigating nonclassical phases such as quantum spin liquids. In this work, we examine the magnetic properties of the oxyhalide Cu 2 (OH) 3 Br in the botallackite structure using first-principles density functional theory, linear spin-wave theory, and exact diagonalization calculations. This quasi-two-dimensional system consists of Cu 2+ S = 1/2 moments arranged on a distorted triangular lattice. Our exact diagonalization calculations, which rely on a first-principles-based magnetic model, generate spectral functions consistent with inelastic neutron scattering data. By performing computational experiments to disentangle the chemical and steric effects of the halide ions, we find that the dominant effect of the halogen ions is steric in the Cu 2 (OH) 3 X series of compounds.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Calculated electron paramagnetic resonance g-tensor and hyperfine parameters for zinc vacancy and N related defects in ZnO

Various defects in ZnO, focused on substitutional N O and N 2 in various sites, O-site, interstitial and Zn-site are studied using first-principles calculations with the goal of understanding the electron paramagnetic resonance (EPR) center reported for N 2 in ZnO and substitutional N on the O-site. The g tensors are calculated using the gauge including projector augmented wave (GIPAW) method and compared with experiments. The g-tensor of the free $N^{+}_{2}$ and $N^{–}_{2}$ radicals and their various contributions within the GIPAW theory are analyzed first to provide a baseline reference for the accuracy of the method and for understanding the N 2 behavior in ZnO. Previous controversies on the site location of N 2 in ZnO for this EPR center and on the shallow or deep nature and donor or acceptor nature of this center are resolved. Here, we find that the N 2 on the Zn site is mostly zinc-vacancy like in its spin density and g-tensor, while for the O-site, a model with the N 2 axis lying in-the basal plane and the singly occupied π g -orbital along the c axis provides good agreement with experiment. For the interstitial location, if the N 2 is not strongly interacting with the surroundings, no levels in the gap are found and hence also no possible EPR center. The calculated g-tensors for N O and V Zn are also found to be in good agreement with experiment. The effects of different functionals affecting the localization of the spin density are shown to affect the g-tensor values.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Hybrid interatomic potential for Sn

To design materials for extreme applications, it is important to understand and predict phase transitions and their influence on material properties under high pressures and temperatures. Atomistic modeling can be a useful tool to assess these behaviors. However, this can be difficult due to the lack of fidelity of the interatomic potentials in reproducing this high pressure and temperature extreme behavior. Here, in this work, a hybrid EAM-R—which is the combination of embedded atom method (EAM) and rapid artificial neural network potential—for Tin (Sn) is described which is capable of accurately modeling the complex sequence of phase transitions between different metallic polymorphs as a function of pressure. This hybrid approach ensures that a basic empirical potential like EAM is used as a lower energy bound. By using the final activation function, the neural network contribution to energy must be positive, assuring stability over the whole configuration space. This implementation has the capacity to reproduce density functional theory results at 6 orders of magnitude slower than a pair potential for molecular dynamics simulation, including elastic and plastic characteristics and relative energies of each phase. Using calculations of the Gibbs free energy, it is demonstrated that the potential precisely predicts the experimentally observed phase changes at temperatures and pressures across the whole phase diagram. At 10.2 GPa, the present potential predicts a first-order phase transition between body-centered tetragonal (BCT) β-Sn and another polymorph of BCT-Sn. This structure transforms into body-centered cubic near the experimentally reported value at 33 GPa. Thus, the Sn potential developed in this paper can be used to study complex deformation mechanisms under extreme conditions of high pressure and strain rates unlike existing potentials. Moreover, the framework developed in this paper can be extended for different material systems with complex phase diagrams.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Synthesis and characterization of the novel breathing pyrochlore compound Ba 3 ⁢Tm 2⁢ Zn 5⁢ O 11

In this study, a novel material from the rare-earth based breathing pyrochlore family, Ba 3 ⁢Tm 2 ⁢Zn 5 ⁢O 11 , was successfully synthesized. Powder x-ray diffraction and high-resolution powder neutron diffraction confirmed phase purity and the $F\bar4$3⁢𝑚 breathing pyrochlore crystal structure, while thermogravimetric analysis revealed incongruent melting behavior compared to its counterpart, Ba 3 ⁢Yb 2⁢ Zn 5⁢ O 11 . High-quality single crystals of Ba 3 ⁢Tm 2 ⁢Zn 5 ⁢O 11 were grown using the traveling solvent floating zone technique and assessed using Laue x-ray diffraction and single crystal x-ray diffraction. Further, thermodynamic characterization indicated paramagnetic behavior down to 0.05 K, and inelastic neutron scattering measurements identified distinct dispersionless crystal electric field energy bands, with the fitted crystal electric field model predicting a single-ion singlet ground state and an energy gap of ∼9 meV separating it from the first excited (singlet) state. Additional low-energy excitation studies on single crystals revealed dispersionless bands at 0.8 and 1 meV. Computed phonon dispersions from first-principles calculations ruled out phonons as the origin of these modes, further illustrating the puzzling and unique properties of Ba 3 ⁢Tm⁢ 2 Zn 5 ⁢O 11 .

36 MATERIALS SCIENCE↗
DOE OSTI2022

Tools for Design and Scale-Up of Solar Thermochemical Reactors: Cooperative Research and Development Final Report, CRADA Number CRD-13-00530

NREL will be collaborating with the Participant on a United States - Australia Solar Energy Collaboration (USASEC) Project Number 1-USO034 "Tools for design and scale-up of solar thermochemical reactors." The grant funds for the Participant's 3.5 year project number 1-US034 commencing on 1 February 2013 have been awarded to the Participant by the Australian Renewable Energy Agency and NREL will be collaborating with the Participant during the final 28 months of this project. This project seeks to provide basic knowledge required to design solar thermochemical reactors able to perform the required energy conversions. In several proposed and demonstrated reactors, concentrated sunlight directly irradiates small solid particles suspended in fluid, enabling very high heat transfer rates to the particles which are the sites of chemical reaction. The reactors, therefore, involve the complex and couple dynamics of turbulent, chemically reacting, particle-laden flows and their interaction with concentrating solar radiation. A strong understanding of these coupled interactions will be crucial important in predicting and optimizing the performance of prototype reactors, but this understanding does not yet exist, since they have never been studied in any fundamental way. The project has a assembled an internationally leading team from The University of New South Wales (UNSW) and the University of Adelaide in Australia and the NREL in the United States to address this key gap in available know-how. The project will use U.S. Dept. of Energy (DOE) supercomputers, among the most powerful available worldwide, with cutting-edge software tools to perform first-principles simulations of the relevant interactions. These studies will be combined with detailed laser-based measurements in Australia to provide the first comprehensive databases concerning the governing phenomena in directly irradiated solar-thermochemical reactors. The outcomes will be the basic scientific knowledge, engineering knowhow and modeling tools necessary to design new reactor concepts and then scale up from the laboratory bench to practical size systems.

14 SOLAR ENERGY↗