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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Weyl semimetal in the rare-earth hexaboride family supporting a pseudonodal surface and a giant anomalous Hall effect

Rare-earth hexaborides offer a rich tapestry for exploring the interplay of topological orders, magnetism, and electron-correlation effects associated with protected quantum phenomena. Using first-principles modeling, we identify in cerium hexaboride (CeB 6 ) a topological state that harbors a pseudonodal surface (PNS) along with double-Weyl fermions. An analysis of the electronic states in the vicinity of the Fermi level reveals the presence of M z -mirror-symmetry-protected band crossings that involve itinerant (d) and localized (f) states of Ce. These band crossings are found to remain nearly gapless as one goes away from the mirror plane, driving the formation of PNS states. We also demonstrate the presence of coexisting double-Weyl fermions with chiral charges of ±2 on the C 4z rotational axis. By analyzing the Berry curvature field associated with the topological states, we predict that CeB 6 supports a giant anomalous Hall conductivity of -1840Ω -1 cm -1 in the slightly electron-doped regime, which would be larger than the values reported to date in magnetic Weyl semimetals. Our study thus indicates that CeB 6 , which combines ferromagnetic order with topological physics in a heavy-fermion matrix, would provide a promising playground for investigating topological magnetic states with giant anomalous Hall responses.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Low-energy interband transition in the infrared response of the correlated metal SrVO 3 in the ultraclean limit

We studied the low-energy electronic response of the prototypical correlated metal SrVO 3 in the ultraclean and disordered limit using infrared spectroscopy and density functional theory plus dynamical mean field theory calculations (DFT+DMFT). A strong optical excitation at 70 meV is observed in the optical response of the ultraclean samples but is hidden by the low-energy Drude-like response from intraband excitations in the more disordered samples. DFT+DMFT calculations reveal that this optical excitation originates from interband transitions between the bands split by orbital off-diagonal hopping, which has often been ignored in cubic systems, such as SrVO 3 . A memory function analysis of the optical data shows that this interband transition can lead to deviations of optical self-energy from the expected Fermi-liquid behavior. Our findings demonstrate that analysis schemes employed to extract many-body effects from optical spectra may be oversimplified to study the true electronic ground state and that improvements in material quality can guide efforts to refine theoretical approaches.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Accelerating self-consistent field iterations in Kohn-Sham density functional theory using a low-rank approximation of the dielectric matrix

We present an efficient preconditioning technique for accelerating the fixed-point iteration in real-space Kohn-Sham density functional theory (DFT) calculations. The preconditioner uses a low-rank approximation of the dielectric matrix (LRDM) based on Gâteaux derivatives of the residual of fixed-point iteration along appropriately chosen direction functions. We develop a computationally efficient method to evaluate these Gâteaux derivatives in conjunction with the Chebyshev filtered subspace iteration procedure, an approach widely used in large-scale Kohn-Sham DFT calculations. Further, we propose a variant of LRDM preconditioner based on adaptive accumulation of low-rank approximations from previous self-consistent field iterations, and also extend the LRDM preconditioner to spin-polarized Kohn-Sham DFT calculations. We demonstrate the robustness and efficiency of the LRDM preconditioner against other widely used preconditioners on a range of benchmark systems with sizes ranging from ~100 to 1100 atoms (~500–20,000 electrons). The benchmark systems include various combinations of metal-insulating-semiconducting heterogeneous material systems, nanoparticles with localized d orbitals near the Fermi energy, nanofilm with metal dopants, and magnetic systems. In all benchmark systems, the LRDM preconditioner converges robustly within 20–30 iterations. In contrast, other widely used preconditioners show slow convergence in many cases, as well as divergence of the fixed-point iteration in some cases. Lastly, we demonstrate the computational efficiency afforded by the LRDM method, with up to 3.4-fold reduction in computational cost for the total ground-state calculation compared to other preconditioners.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Unusual Exchange Couplings and Intermediate Temperature Weyl State in Co 3 Sn 2 S 2

Understanding magnetism and its possible correlations to topological properties has emerged to the forefront as a difficult topic in studying magnetic Weyl semimetals. Co 3 Sn 2 S 2 is a newly discovered magnetic Weyl semimetal with a kagome lattice of cobalt ions and has triggered intense interest for rich fantastic phenomena. In this study, we report the magnetic exchange couplings of Co 3 Sn 2 S 2 using inelastic neutron scattering and two density functional theory (DFT) based methods: constrained magnetism and multiple-scattering Green’s function methods. Co 3 Sn 2 S 2 exhibits highly anisotropic magnon dispersions and linewidths below T C , and paramagnetic excitations above T C . The spin-wave spectra in the ferromagnetic ground state is well described by the dominant third-neighbor “across-hexagon” J d model. Our density functional theory calculations reveal that both the symmetry-allowed 120° antiferromagnetic orders support Weyl points in the intermediate temperature region, with distinct numbers and the locations of Weyl points. Our study highlights the important role Co 3 Sn 2 S 2 can play in advancing our understanding of kagome physics and exploring the interplay between magnetism and band topology.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Spin-Dependent $\pi$$\pi$* Gap in Graphene on a Magnetic Substrate

Here, we present a detailed analysis of the electronic properties of graphene/Eu/Ni(111). By using angle- and spin-resolved photoemission spectroscopy and ab initio calculations, we show that the intercalation of Eu in the graphene/Ni(111) interface gives rise to a gapped freestanding dispersion of the $\pi$$\pi$* Dirac cones at the K point with an additional lifting of the spin degeneracy due to the mixing of graphene and Eu states. The interaction with the magnetic substrate results in a large spin-dependent gap in the Dirac cones with a topological nature characterized by a large Berry curvature and a spin-polarized Van Hove singularity, whose closeness to the Fermi level gives rise to a polaronic band.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Density functional studies of defects and defect-related luminescence in M g 3 N 2

M g 3 N 2 is a promising material for light-emitting-diode applications. However, the microscopic origin of the broad yellow photoluminescence in M g 3 N 2 remains unknown. In this study, defect properties and defect-related optical transitions are investigated based on the hybrid functional calculation. Our results show that the nitrogen vacancy introduces multiple localized defect states within the band gap, which play a dominant role in luminescent properties of M g 3 N 2 . Common impurities like hydrogen, oxygen, and carbon and their complexes with native defects are also studied. Compared with isolated V Mg , V Mg -H and V Mg – O N complexes have shallower transition levels. Our calculated optical excitation and emission peaks associated with isolated V N are in good agreement with those observed in experiments. In addition, the impurity C N is also a potential source for the observed yellow emission in M g 3 N 2 .

36 MATERIALS SCIENCE↗
DOE OSTI2022

Understanding the fundamental driver of semiconductor radiation tolerance with experiment and theory

Space is the operating environment of a multitude of systems that our society is heavily reliant on today, however, maintaining operability there necessitates special consideration of the electronic systems' tolerance of space radiation. Electronic systems are critically dependent on the electronic properties of their semiconductor components, which are modified by space radiation with an adverse impact on the space system performance. What innate property allows some semiconductors to sustain little damage while others accumulate defects rapidly with dose is poorly understood, which limits the extent to which radiation tolerance can be implemented as a design criterion. Here, to gain insight into what properties are drivers of semiconductor radiation tolerance, the first step is to generate a dataset of the relative radiation tolerance of a broad sampling of semiconductors. To accomplish this, Rutherford backscatter channeling experiments are used to compare the displaced lattice atom buildup in InAs, InP, GaP, GaN, ZnO, MgO, and Si as a function of stepwise alpha particle dose. With this experimental information on radiation-induced incorporation of interstitial defects in hand, hybrid density functional theory electron densities (and their derived quantities) are calculated and their gradient and Laplacian are evaluated to obtain key fundamental information about the interactions in each material. It is shown that simple, undifferentiated values (which are typically used to describe bond strength) are insufficient to predict radiation tolerance. Instead, the curvature of the electron density at bond critical points provides a measure of radiation tolerance consistent with the experimental results obtained. This curvature and associated forces surrounding bond critical points have the potential to disfavor the localization of displaced lattice atoms at these points, favoring their diffusion toward perfect lattice positions. With this criterion to predict radiation tolerance, simple density functional theory simulations can be conducted on potential new materials to gain insight into how they may operate in demanding high radiation environments.

36 MATERIALS SCIENCE↗
DOE OSTI2022

First-principles study of the T center in silicon

The T center in silicon is a well-known carbon-based color center that has been recently considered for quantum technology applications. Using first-principles computations, we show that the excited state is formed by a defect-bound exciton made of a localized defect state occupied by an electron to which a hole is bound. The localized state is of strong carbon p character and reminiscent of the localization of the unpaired electron in the ethyl radical molecule. The radiative lifetime for the defect-bound exciton is calculated to be on the order of microseconds, much longer than for other quantum defects such as the nitrogen vacancy center in diamond and in agreement with experiments. The longer lifetime is associated with the small transition dipole moment as a result of the very different nature of the localized and delocalized states forming the defect-bound exciton. Finally, we use first-principles calculations to assess the stability of the T center. Here, we find the T center to be stable against decomposition into simpler defects when keeping the stoichiometry fixed. However, we identify that the T center is easily prone to (de)hydrogenation and so requires very precise annealing conditions (temperature and atmosphere) to be efficiently formed.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Intrinsic ferromagnetism and restrictive thermodynamic stability in MA$_{2}$N$_{4}$ and Janus VSiGeN$_{4}$ monolayers

The seminal experimental discovery of the remarkably stable MoSi 2 N 4 monolayer has led to a handful of predicted magnetic two-dimensional (2D) materials in the MA 2 Z 4 family (M = transition metals, A = Si, Ge, and Z = N, P, As). These magnetic monolayers were predicted to be dynamically stable, but none of them has been synthesized to date. In this Research Letter, from first-principles thermodynamic stability analysis, we demonstrate that only the nitrides are thermodynamically stable and this occurs under N-rich conditions. Based on this finding, we propose two ferromagnetic, semiconducting Janus monolayers in the family: VSiGeN 4 and VSiSnN 4 . They are both dynamically and thermally stable, but only the former is thermodynamically stable. Intriguingly, Janus VSiGeN 4 and VSiSnN 4 monolayers show weak in-plane anisotropy compared with the VSi 2 N 4 monolayer. Furthermore, these two emerging Janus magnetic semiconductors offer opportunities for studying 2D magnetism and spin control for spintronics applications.

2-dimensional systems↗
DOE OSTI2023

Defect-induced states, defect-induced phase transition, and excitonic states in bent tungsten disulfide (WS 2 ) nanoribbons: Density functional vs. many body theory

Two-dimensional (2D) transition metal dichalcogenide (TMD) materials have versatile electronic and optical properties. TMD nanoribbons exhibit interesting properties due to reduced dimensionality, quantum confinement, and edge states, which make them suitable for various electronic and optoelectronic applications. In a previous work conducted by our group, we demonstrated that the edge bands evolved with bending can tune the optical properties for various widths of TMD nanoribbons. Defects are commonly present in 2D TMD materials, and can dramatically change the material properties. Here, in this following work, we investigate the interaction between the edge and the defect states in tungsten disulfide (WS 2 ) nanoribbons with lines of W- or S-atom vacancies defects under different bending conditions, using density functional theory (DFT). To gain understanding about the limits of density functional approximations, we compare results on band gaps and energies of defect states with quasiparticle GW. We reveal interesting semiconductor-metal phase transitions, suggesting potential applications in nanoelectronics or molecular electronics. We also calculate the optical absorption of the bent and defective nanoribbons with the many-body GW-BSE (Bethe-Salpeter equation) approach, revealing a tunable optical spectrum and diverse exciton states in the defective WS 2 nanoribbons.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Controlling 4 f antiferromagnetic dynamics via itinerant electronic susceptibility

Optical manipulation of magnetism holds promise for future ultrafast spintronics, especially with lanthanides and their huge, localized 4 f magnetic moments. These moments interact indirectly by spin polarizing the conduction electrons (the Ruderman-Kittel-Kasuya-Yosida exchange interaction), influenced by interatomic orbital overlap, and the conduction electron's susceptibility around the Fermi level. Here, we study this influence in a series of 4 f antiferromagnets, Gd T 2 Si 2 ( T = Co, Rh, Ir), using ultrafast resonant x-ray diffraction. We observe a twofold increase in the ultrafast intersublattice angular momentum transfer rate between the materials, originating from modifications in the conduction electron susceptibility, as confirmed by first-principles calculations. Published by the American Physical Society 2024

36 MATERIALS SCIENCE↗
DOE OSTI2021

Kohn-Sham Solver (KSSOLV) v2.0

KSSOLV is a MATLAB toolbox for solving Kohn-Sham density functional theory based electronic structure eigenvalue problems. It uses an object oriented features of MATLAB to represent atom, molecules, wavefunctions and Hamiltonians and their operations. It is designed to make it easier for users to prototype and test new algorithms for solving the Kohn-Sham problem. KSSOLV2.0 contains significant improvement over the original KSSOLV described in a paper published in ACM Transaction on Mathematical Software (attached). In addition to performing ground state calculation for small molecules, it can also perform geometry optimization for both molecules and solids. It uses standard pseudopotentials and implements local density approximation, generalized gradient approximation and hybrid functionals. Future releases will also include time-dependent DFT and post DFT calculations such as the GW quasi-particle energy calculation and Bethe-Salpeter equation solver for optical absorption.

Yang, Chao↗
DOE OSTI2024

Putting error bars on density functional theory dataset

This dataset contains submission files and raw output files from high-throughput DFT simulations to analyze the systemic errors in lattice constant, bulk moduli and formation energy predictions for a range of binary and ternary oxides using four exchange correlation functionals (LDA, PBE, PBEsol and vdW-DF-C09). This data was then used as the basis for employing materials informatics methods to predict the expected errors in the lattice constants of the studied compounds. Predicted errors were also used to better the DFT-predicted lattice parameters. Our results emphasize the link between the computed errors and the electron density and hybridization errors of a functional. In essence, these results provide “error bars” for choosing a functional for the creation of high-accuracy, high-throughput datasets as well as avenues for the development of XC functionals with enhanced performance, thereby enabling the accelerated discovery and design of new materials.

36 MATERIALS SCIENCE↗
DOE OSTI2024

HydraGNN_Predictive_GFM_2024 - Ensemble of predictive graph foundation models for ground state atomistic materials modeling

We provide the ensemble of fifteen pre-trained graph foundation models (GFMs) for atomistic materials modeling applications. Each one of the fifteen GFMs has been trained on five open-source datasets that (once aggregated) amount to over 154 million atomistic structures, which cover over two-thirds of the natural elements of the periodic table and that comprises a broad set of organic and inorganic compounds. This vast set of atomistic structures comprises ground state configurations that are dynamically stable (i.e., equilibrated structures with atomic forces approximately close to zero values) as well as dynamically unstable structures (i.e., non-equilibrium structures with non-negligible non-zero values of atomic forces). The ensemble of datasets aggregated does NOT include excited states. The datasets have been curated to remove atomistic structures with spectral norm of the force tensor above 100 eV/angstrom. Moreover, a linear term of the energy was computed for each dataset using a linear regression model that uses the chemical concentration of each natural element as regressor. The linear term predicted by the linear regression model has been subtracted from each original energy value to perform a re-alignment of the energy values across different electronic structures approximation theories performed to generate the diverse multi-source, multi-fidelity datasets. The folder "ADIOS_files" contains the set of pre-processed datasets in Adaptable I/O System (ADIOS) format (https://www.exascaleproject.org/research-project/adios/) that have been used for the development and training of GFMs in this work. The "ADIOS_files" directory contains 6 sub-directories named as follows: - ANI1x-v3.bp - MPTrj-v3.bp - OC2020-20M-v3.bp - OC2020-v3.bp - OC2022-v3.bp - qm7x-v3.bp Each sub-directory contains the pre-processed datasets converted in Adaptable I/O System (ADIOS) format (https://www.exascaleproject.org/research-project/adios/) that have been used to the development, training, and performance testing of the ensemble go predictive graph foundation models. Each GFM was developed using HydraGNN (https://github.com/ORNL/HydraGNN) as underlying graph neural network (GNN) architecture. The multi-task learning (MTL) capability of HydraGNN was used to simultaneously train the GFMs on labeled values for direct predictions of energy (a total system property of an atomistic structure that measures the chemical stability) and atomic forces (an atomic level property of an atomistic structure that measures the dynamical stability). The hyper parameters of the GFM have been tuned using scalable hyperparameter optimization (HPO) algorithms implemented in the software DeepHyper (https://github.com/deephyper/deephyper). The pre-training of each HPO trial was performed using distributed data parallelism (DDP) to scale the training across 128 compute nodes of the exascale OLCF supercomputer Frontier. Each HPO trial was trained only for 10 epochs and an early stopping was performed to avoid wasting significant computational resources on GNN architectures that were clearly underperforming. For each HPO trial, the 'omnistat' tool developed by (AMD Research - Advanced Micro Device) was used to measure the total energy consumption in kWh. The ensemble of GFMs was obtained by selecting the fifteen best performing HPO trials. Four models have been selected for their clear advantage in accuracy, and these are the GFMs with IDs 229, 156, 147, 260. Additional eleven models have been selected based on judicious balance between accuracy and energy consumption needed for training, and these are the GFMs with IDs 165, 78, 137, 1, 175, 171, 181, 67, 179, 167, 351. Each selected GFM of the ensemble was continued to cumulate a total of at most 30 epochs. In some cases, the total number of epochs actually performed was les than 30 due to two combined factors: (1) the size of the GFM (i.e., the number of model parameters to train) and (2) the total wall-clock time for which the computational resources could be allocated on OLCF-Frontier. The "Ensemble_of_models" directory contains 15 sub-directories named as follows: - gfm_0.229 - gfm_0.156 - gfm_0.147 - gfm_0.260 - gfm_0.165 - gfm_0.78 - gfm_0.137 - gfm_0.1 - gfm_0.175 - gfm_0.171 - gfm_0.181 - gfm_0.67 - gfm_0.179 - gfm_0.167 - gfm_0.351 Each one of these sub-directories refers to one of the fifteen HPO trials that have been selected to continue the pre-training with at most 30 epochs. With each sub-directory associated with a specific HPO trial, the following files can be found: - config.json: file for argument parsing to develop and train an HydraGNN architecture - gfm_0.ID_epoch_N.pk: file with model parameters for HPO ID trial after N epochs of training The ensemble of fifteen GFM architectures was used for (1) ensemble averaging to stabilize the predictions of energy and atomic forces after pre-training for post-processing analysis and (2) ensemble uncertainty quantification (UQ). The code used to develop, pre-train, and load the pre-trained models for post-processing analysis is available on the ORNL-GitHub at the following link: https://github.com/ORNL/HydraGNN/tree/Predictive_GFM_2024

36 MATERIALS SCIENCE↗