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Results for “Density functional theory simulations”

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 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Quantifying the hydration structure of sodium and potassium ions: taking additional steps on Jacob's Ladder

The ability to reproduce the experimental structure of water around the sodium and potassium ions is a key test of the quality of interaction potentials due to the central importance of these ions in a wide range of important phenomena. In this study, we simulate the Na + and K + ions in bulk water using three density functional theory functionals: (1) the generalized gradient approximation (GGA) based dispersion corrected revised Perdew, Burke, and Ernzerhof functional (revPBE-D3) (2) the recently developed strongly constrained and appropriately normed (SCAN) functional (3) the random phase approximation (RPA) functional for potassium. We compare with experimental X-ray diffraction (XRD) and X-ray absorption fine structure (EXAFS) measurements to demonstrate that SCAN accurately reproduces key structural details of the hydration structure around the sodium and potassium cations, whereas revPBE-D3 fails to do so. However, we show that SCAN provides a worse description of pure water in comparison with revPBE-D3. RPA also shows an improvement for K + , but slow convergence prevents rigorous comparison. Finally, we analyse cluster energetics to show SCAN and RPA have smaller fluctuations of the mean error of ion–water cluster binding energies compared with revPBE-D3.

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

Synthesis, crystal structure, EPR, and DFT studies of an unusually distorted vanadium(ii) complex

We report the synthesis and structure of the most highly distorted four-coordinate d 3 ion known to date that also serves as the second known example of a bis(biphenolato) transition metal complex. We demonstrate the application of density functional theory to calculate the magnetic parameters derived from the experimental and simulated EPR spectra.

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

Strain-driven oxygen vacancy ordering in LaNiO 3 thin films revealed by integrated differential phase contrast imaging in scanning transmission electron microscopy

Rare-earth nickelates, such as LaNiO 3 (LNO), exhibit complex electronic properties, with ordered oxygen vacancies (OOV) influencing conductivity and magnetic behavior. We investigate the structural stability of strain-induced OOV phases in LNO thin films grown on SrTiO 3 substrates and the impact of Ruddlesden–Popper (RP) faults. Using high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM) and integrated differential phase contrast (iDPC) STEM imaging, we conducted atomic-scale structural and compositional analyses of OOV. Geometric phase analysis (GPA) was employed to measure the strain in fault-free and RP fault regions, while density functional theory (DFT) calculations explored different OOV arrangements in the LNO phase. Simulated iDPC-STEM imaging of energy-stabilized structures was performed to correlate with experimental results. Here, our findings reveal superstructure modulation in the chemical composition and atomic-scale lattice structure in LNO, primarily due to the formation of the OOV in Ni–O layers of the LaNiO 2.5 phase. The out-of-plane compressive strain of about 2% stabilizes this phase, reducing the strain, diminishing OOV, and transforming them into LNO.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Enhanced extreme ultraviolet high-harmonic generation from chromium-doped magnesium oxide

High-order harmonic generation (HHG) from crystals is emerging as a new ultrashort source of coherent extreme ultraviolet (XUV) light. Doping the crystal structure can offer a new way to control the source properties. Here, we present a study of HHG enhancement in the XUV spectral region from an ionic crystal, using dopant-induced vacancy defects, driven by a laser centered at a wavelength of 1.55 μm. Our numerical simulations based on solutions of the semiconductor Bloch equations and density-functional theory are supported by our experimental observations and demonstrate an increase in the XUV high harmonic yield from doped bulk magnesium oxide (MgO) compared to undoped MgO, even at a low defect concentration. The anisotropy of the harmonic emission as a function of the laser polarization shows that the pristine crystal's symmetry is preserved. Our study paves the way toward the control of HHG in solids with complex defects caused by transition-metal doping.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Atomistic and mesoscale simulations to determine effective diffusion coefficient of fission products in SiC

The silicon carbide (SiC) layer in tristructural isotropic (TRISO) particles serves as the barrier to prevent escape of fission products produced in the fuel kernel. Knowing the diffusion coefficient of fission products through SiC is critical to determining whether fission gas can escape from the particle. It has been observed in experiments that Ag accumulated in grain boundaries and triple junctions in SiC. It is hypothesized that grain boundary diffusion is the primary pathway by which fission products penetrate the SiC layer. In this report, the effective diffusion coefficient of the fission product Ag through the grain boundary network is calculated using a combination of atomistic and phase-field methods. The grain boundary diffusion coefficient is calculated using molecular dynamics simulations. The bulk diffusion coefficient is determined using a combination of density functional theory and nudged elastic band methods. An effective diffusion coefficient is calculated, accounting for the grain structure using a phase-field method. The effective diffusion coefficient will be incorporated into Bison and fission product release calculations are compared to available experimental data.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS2018

Segregation and Phase Transformations Along Superlattice Intrinsic Stacking Faults in Ni-Based Superalloys

In this study, local chemical and structural changes along superlattice intrinsic stacking faults combine to represent an atomic-scale phase transformation. In order to elicit stacking fault shear, creep tests of two different single crystal Ni-base superalloys, ME501 and CMSX-4, were performed near 750 degrees Centigrade using stresses of 552 megapascals and 750 megapascals, respectively. Through high resolution Scanning Transmission Electron Microscopy (STEM) and state-of-the-art energy dispersive x-ray spectroscopy, ordered compositional changes were measured along SISFs (Superlattice Intrinsic Stacking Faults) in both alloys. For both instances, the elemental segregation and local crystal structure present along the SISFs are consistent with a nanoscale to D019 (ordering of a hexagonal close-packed crystal) phase transformation. Another notable observation is prominent Cr- and Co-rich Cottrell atmospheres and new evidence of more complex reordering processes responsible for the formation of these faults. These findings are further supported using density functional theory calculations and High Angle Annular Dark Field (HAADF) STEM image simulations.

STEM-EDS↗
DOE OSTI2026

pyRMG: A framework for high-throughput, large-cell DFT calculations on supercomputers

Exascale computing delivers the raw power to simulate ever larger and more chemically realistic systems, but realizing this potential requires codes that can efficiently use thousands of processors. Our real-space multigrid (RMG) density functional theory (DFT) code’s grid-decomposition approach scales nearly linearly with the number of graphics processing units (GPUs), even for simulations exceeding thousands of atoms. This scalability makes RMG a compelling tool for high-throughput DFT studies of materials that would otherwise be bottlenecked in other codes (for example, by global fast Fourier transforms in plane-wave DFT). However, the limited workflow infrastructure for RMG has thus far constrained its adoption to a small user community. In this work, we present pyRMG, a Python package designed to streamline the setup and execution of RMG DFT calculations. Built on the pymatgen and ASE (Atomic Simulation Environment) computational materials science Python packages, pyRMG automates input generation and convergence checking, and it integrates with modern job schedulers (e.g., Flux) on leadership-class platforms such as Frontier and Perlmutter. Here, we demonstrate pyRMG for a high-throughput study of strain effects in 2D 2L-Bi 2 Se 3 /2L-NbSe 2 heterostructures, which offers chemical insights into this system and shows that RMG-based workflows can converge with limited user intervention.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Ni and Co Incorporation in Forsterite: A Density Functional Theory Study with Hubbard Correction

Ni and Co are critical elements for the world economy and modern technologies. Mafic and ultramafic deposits represent low-grade yet abundant alternatives to traditional Ni and Co ores. Here, in this work, density functional theory (DFT) with the Hubbard U correction (DFT+U) was used to simulate the incorporation of Ni and Co in forsterite (Mg 2 SiO 4 ), the Mg endmember of olivine, a common mineral in mafic and ultramafic rocks. Hubbard U terms for Ni and Co were parametrized using a series of oxide, hydroxide, carbonate, silicate, and sulfide minerals relevant to extraction and recovery of Ni and Co from mafic and ultramafic deposits. Electronic, energetic, magnetic, and structural properties were considered in the parametrization. For each of Ni and Co, an effective Hubbard correction (U eff ) value that optimized agreement with either experimental data or a hybrid exchange-correlation functional for all of the minerals considered is reported. DFT+U ab initio molecular dynamics (AIMD) simulations of Ni and Co incorporated into the M1 and M2 octahedral sites of forsterite were then performed. Ni and Co substitution in the M1 site was more energetically favorable than substitution in the M2 site, in agreement with published partition coefficients. AIMD trajectories were used to compute extended X-ray absorption fine structure (EXAFS) spectra of Ni in the M1 and M2 sites for direct fitting to a published experimental spectrum of Ni in a natural San Carlos olivine sample. The results of the fit indicated that ordering of Ni in the M1 site was not as strong at the low Ni concentrations relevant to mafic and ultramafic silicate minerals as that at the higher concentrations of the Ni-Mg olivine solid solutions studied to date.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Gold–Thiolate Nanocluster Dynamics and Intercluster Reactions Enabled by a Machine Learned Interatomic Potential

Monolayer protected metal clusters comprise a rich class of molecular systems and are promising candidate materials for a variety of applications. While a growing number of protected nanoclusters have been synthesized and characterized in crystalline forms, their dynamical behavior in solution, including prenucleation cluster formation, is not well understood due to limitations both in characterization and first-principles modeling techniques. Recent advancements in machine-learned interatomic potentials are rapidly enabling the study of complex interactions such as dynamical behavior and reactivity on the nanoscale. Here, we develop an Au-S-C-H atomic cluster expansion (ACE) interatomic potential for efficient and accurate molecular dynamics simulations of thiolate-protected gold nanoclusters (Au n (SCH 3 ) m ). Trained on more than 30,000 density functional theory calculations of gold nanoclusters, the interatomic potential exhibits ab initio level accuracy in energies and forces and replicates nanocluster dynamics including thermal vibration and chiral inversion. Long dynamics simulations (up to 0.1 μs time scale) reveal a mechanism explaining the thermal instability of neutral Au 25 (SR) 18 clusters. Specifically, we observe multiple stages of isomerization of the Au 25 (SR) 18 cluster, including a chiral isomer. Additionally, we simulate coalescence of two Au 25 (SR) 18 clusters and observe series of clusters where the formation mechanisms are critically mediated by ligand exchange in the form of [Au-S] n rings.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Tight-Binding-Based Method for Simulations of Complex Materials with Accompanying Database

The NRL-Tight-Binding (NRL-TB) method has been applied successfully to many monatomic, binary, and a few ternary systems. The method consists of a fit to Density Functional Theory (DFT) results and has transferability beyond the fitted DFT database including performing tight-binding molecular dynamics simulations. We are working on a new website with a detailed guide of how to use the method in performing the fit to DFT results (Fitting Code) and obtaining non-orthogonal TB parameters expressed in a polynomial form as environment-dependent Slater-Koster parameters (on-site terms), and neighbor distance-dependent Hamiltonian and Overlap terms. These parameters are then used in a Static Code to verify or make predictions for large systems often beyond the computational capabilities of standard DFT codes. Our starting point was a website developed at NRL some years ago which NRL no longer supports. We have now been augmenting that website with new examples of expanding the original capabilities of the method such as incorporating in the codes f-electron states. Our website (esd.cos.gmu.edu/tb) contains two separate branches: One named NRL-TB with the full documentation of the method including source codes and examples. The other branch, named ESD-dB, is a library of electronic structure calculations for all the monatomic elements (a subset of the elements also found in a recent book by the author of this proposal. See reference 22) and an approximately 700 hundred compounds in specific crystal structures. We discuss below the progress made so far in improving and expanding the capabilities of our TB method and the plans for further extensions of our approach.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Toward alcohol synthesis from CO hydrogenation on Cu(111)-supported MoS 2 – predictions from DFT+KMC

In the quest for cheap and efficient catalysts for alcohol synthesis from syngas, a material of interest is single-layer MoS2 owing to its low cost, abundancy, and flexible structure. Because of the inertness of its basal plane, however, it is essential to find ways that make it catalytically active. Herein, by means of density functional theory based calculations of reaction pathways and activation energy barriers and accompanying kinetic Monte Carlo simulations, we show that while S vacancy row structures activate the MoS 2 basal plane, further enhancement of chemical activity and selectivity can be achieved by interfacing the MoS 2 layer with a metallic support. When defect-laden MoS2 is grown on Cu(111), there is not only an increase in the active region (surface area of active sites) but also charge transfer from Cu to MoS 2 , resulting in a shift of the Fermi level such that the frontier states (d orbitals of the exposed Mo atoms) appear close to it, making the MoS 2 /Cu(111) system ready for catalytic activity. Finally, our calculated thermodynamics of reaction pathways lead to the conclusion that the Cu(111) substrate promotes both methanol and ethanol as the products, while kinetic Monte Carlo simulations suggest a high selectivity toward the formation of ethanol.

2D materials↗
DOE OSTI2021

Phase Equilibrium of Water with Hexagonal and Cubic Ice Using the SCAN Functional

Machine learning models are rapidly becoming widely used to simulate complex physicochemical phenomena with ab initio accuracy. Here, we use one such model as well as direct density functional theory (DFT) calculations to investigate the phase equilibrium of water, hexagonal ice (Ih), and cubic ice (Ic), with an eye toward studying ice nucleation. The machine learning model is based on deep neural networks and has been trained on DFT data obtained using the SCAN exchange and correlation functional. We use this model to drive enhanced sampling simulations aimed at calculating a number of complex properties that are out of reach of DFT-driven simulations and then employ an appropriate reweighting procedure to compute the corresponding properties for the SCAN functional. This approach allows us to calculate the melting temperature of both ice polymorphs, the driving force for nucleation, the heat of fusion, the densities at the melting temperature, the relative stability of ices Ih and Ic, and other properties. We find a correct qualitative prediction of all properties of interest. In some cases, quantitative agreement with experiment is better than for state-of-the-art semiempirical potentials for water. Furthermore, our results also show that SCAN correctly predicts that ice Ih is more stable than ice Ic.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

An extended moments model of quantum efficiency for metals and semiconductors

The complexity of photocathode designs and detector materials, and the need to model their performance for short pulse durations, response to high frequency photons, presence of coatings and/or thinness of the absorptive layer, necessitates modifications to three-step and moments models of photoemission that are used in simulation codes. Here, methods to include input from computationally intensive approaches, such as density functional theory to model optical properties and transfer matrix approaches to treat emission from the surface or transport past coatings, by means of parametric models are demonstrated. First, a technique to accurately represent optical behavior so as to model reflectivity and penetration depth is given. Second, modifications to bulk models arising from the usage of thin film architectures, and a means to rapidly calculate them, is provided. Third, a parameterization to model the impact of wells associated with coatings and surface layers on the transmission probably is given. In all cases, the methods are computationally efficient and designed to allow for including input from numerically intensive approaches that would otherwise be unavailable for simulations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

X-ray absorption spectroscopy and theoretical investigations of the effect of extended ligands in potassium organic matter interaction

Potassium (K) is an essential nutrient for plant growth, and despite its abundance in soil, most of the K is structurally bound in minerals, limiting its bioavailability and making this soil K reservoir largely inaccessible to plants. Microbial biochemical weathering has been shown to be a promising pathway to sustainably increase plant available K. However, the mechanisms underpinning microbial K uptake, transformation, storage, and sharing are poorly resolved. Here, to better understand the controls on microbial K transformations, we performed K K-edge x-ray absorption near-edge structure (XANES) spectroscopy on K-organic salts, including acetate, citrate, nitrate, oxalate, and tartrate, which are frequently observed as low molecular weight organic acids secreted by soil microbes, as well as humic acid, which acts as a proxy for higher molecular weight organic acids. The organic salts display feature-rich K XANES spectra, each demonstrating numerous unique features spanning ~13 eV range across the absorption edge. In contrast, the spectra for humic acid have one broad, wide feature across the same energy range. We used a combination of time-dependent density functional theory and the Bethe–Salpeter equation based approach within the OCEAN code to simulate the experimental spectra for K-nitrate (KNO 3 ) and K-citrate [K 3 (C 6 H 5 O 7 )·H 2 O] to identify the electronic transitions that give rise to some of the outlying and unique spectral features in the organic salts. KNO 3 has both the lowest and highest lying energy features, and K 3 (C 6 H 5 O 7 )·H 2 O is produced by several soil microbes and is effective at mineral weathering. Our results analyze the K-organic salt bonding in detail to elucidate why the spectral shapes differ and indicate that the K K-edge XANES spectra are associated with the entire ligand despite similar first-shell bonding environments around the K center. The improved understanding of K bonding environments with organic ligands and their use for interpretation of the K-XANES spectra provides an important toolkit to understand how K is transformed by microbial processes and made bioavailable for plant uptake.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

The joint automated repository for various integrated simulations (JARVIS) for data-driven materials design

The Joint Automated Repository for Various Integrated Simulations (JARVIS) is an integrated infrastructure to accelerate materials discovery and design using density functional theory (DFT), classical force-fields (FF), and machine learning (ML) techniques. JARVIS is motivated by the Materials Genome Initiative (MGI) principles of developing open-access databases and tools to reduce the cost and development time of materials discovery, optimization, and deployment. The major features of JARVIS are: JARVIS-DFT, JARVIS-FF, JARVIS-ML, and JARVIS-tools. To date, JARVIS consists of ≈40,000 materials and ≈1 million calculated properties in JARVIS-DFT, ≈500 materials and ≈110 force-fields in JARVIS-FF, and ≈25 ML models for material-property predictions in JARVIS-ML, all of which are continuously expanding. JARVIS-tools provides scripts and workflows for running and analyzing various simulations. We compare our computational data to experiments or high-fidelity computational methods wherever applicable to evaluate error/uncertainty in predictions. In addition to the existing workflows, the infrastructure can support a wide variety of other technologically important applications as part of the data-driven materials design paradigm. The JARVIS datasets and tools are publicly available at the website: https://jarvis.nist.gov .

36 MATERIALS SCIENCE↗
DOE OSTI2021

Charge transfer effect on local lattice distortion in a HfNbTiZr high entropy alloy

We report it is often assumed that atoms are hard spheres in the estimation of local lattice distortion (LLD) in high-entropy alloys (HEAs). However, our study demonstrates that the hard sphere model misses the key effect, charge transfer among atoms with different electronegativities, in the understanding of the severely distorted local structure in the body-centered cubic (BCC) HfNbTiZr HEA. Through the characterization and simulations of the local structure of the HfNbTiZr HEA, we found that the LLD regions in HfNbTiZr have larger average size compared with face-centered cubic (FCC) HEAs, but the magnitude of LLD significantly varies from one atomic site to another because of electron transfer from larger atoms, Hf and Zr, to smaller ones, Nb and Ti. Our finding may form the basis for the design of high performance HEAs through tuning their site-to-site chemical heterogeneity.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Semi-Automated Creation of Density Functional Tight Binding Models through Leveraging Chebyshev Polynomial-Based Force Fields

Density functional tight binding (DFTB) is an attractive method for accelerated quantum simulations of condensed matter due to its enhanced computational efficiency over standard density functional theory (DFT) approaches. However, DFTB models can be challenging to determine for individual systems of interest, especially for metallic and interfacial systems where different bonding arrangements can lead to significant changes in electronic states. In this regard, we have created a rapid-screening approach for determining systematically improvable DFTB interaction potentials that can yield transferable models for a variety of conditions. Our method leverages a recent reactive molecular dynamics force field where many-body interactions are represented by linear combinations of Chebyshev polynomials. This allows for the efficient creation of multi-center representations with relative ease, requiring only a small investment in initial DFT calculations. Here, we have focused our workflow on TiH 2 as a model system and show that a relatively small training set based on unit-cell-sized calculations yields a model accurate for both bulk and surface properties. Our approach is easy to implement and can yield reliable DFTB models over a broad range of thermodynamic conditions, where physical and chemical properties can be difficult to interrogate directly and there is historically a significant reliance on theoretical approaches for interpretation and validation of experimental results.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗