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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 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
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 OSTI2025

Defluorination Mechanisms and Real-Time Dynamics of Per- and Polyfluoroalkyl Substances on Electrified Surfaces

Per- and polyfluoroalkyl substances (PFAS) are persistent environmental contaminants found in groundwater sources and a wide variety of consumer products. In recent years, electrochemical approaches for the degradation of these harmful contaminants have garnered a significant amount of attention due to their efficiency and chemical-free modular nature. However, these electrochemical processes occur in open, highly non-equilibrium systems, and a detailed understanding of PFAS degradation mechanisms in these promising technologies is still in its infancy. To shed mechanistic insight into these complex processes, we present the first constant-electrode potential (CEP) quantum calculations of PFAS degradation on electrified surfaces. These advanced CEP calculations provide new mechanistic details about the intricate electronic processes that occur during PFAS degradation in the presence of an electrochemical bias, which cannot be gleaned from conventional density functional theory calculations. We complement our CEP calculations with large-scale ab initio molecular dynamics simulations in the presence of an electrochemical bias to provide time scales for PFAS degradation on electrified surfaces. Taken together, our CEP-based quantum calculations provide critical reaction mechanisms for PFAS degradation in open electrochemical systems, which can be used to prescreen candidate material surfaces and optimal electrochemical conditions for remediating PFAS and other environmental contaminants.

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↗
DOE OSTI2022

Metal Halide Perovskites Demonstrate Radiation Hardness and Defect Healing in Vacuum

Herein, we subject formamidinium lead iodide films to oxygen-containing gases (flowing O 2 or free diffusion of lab atmosphere), inert gases (flowing He, Ar, or N 2 ), and vacuum. Our films are irradiated by Cu Ka X-rays and held at 75 °C while X-ray diffraction is recorded. Under all gas conditions, we observe a reproducible 1.1 ± 0.5 A 3 perovskite lattice contraction from an initial unit cell volume of 256.5 ± 0.8 A 3 concurrent with continuous perovskite loss and lead iodide growth. Oxygen-containing gases increase the reaction rates without materially altering perovskite structural changes. Under the same temperature and irradiation conditions in vacuo, a self-healing reaction is observed, exhibited by a reproducible (0.9 ± 0.3 A 3 ) lattice expansion and stabilization of the perovskite. Furthermore, interactions between the perovskite, defects, and minority phases are simulated by generalized gradient approximation Perdew-Burke-Ernzerhof (GGA-PBE) density functional theory. Lattice contraction indicates an increase in the concentration of Schottky defects-pairs of formamidinium and iodine vacancies. Under irradiation in every atmospheric condition, a solid solution of Schottky defects with a concentration of several percent diffuses and precipitates forming lead iodide and consuming the defects. In the presence of ionized gases, this framework is modified to include the continual loss of formamidinium and iodine ions from the perovskite forming Schottky defects.

14 SOLAR ENERGY↗
DOE OSTI2024

First-principles study of the magneto-Raman effect in van der Waals layered magnets

Magneto-Raman spectroscopy has been used to study spin-phonon coupling in two-dimensional (2D) magnets. Raman spectra of CrI 3 show a strong dependence on the magnetic order within a layer and between the layers. Here we carry out the first systematic theoretical investigation of the magneto-Raman effect in 2D magnets by performing density functional theory calculations and developing a generalized polarizability model. Our first-principles simulations well reproduce experimental Raman spectra of CrI 3 with different magnetic states. The model reveals how the change of spin orientation in each layer is coupled to the layer’s vibration to induce or eliminate the spin-dependent anti-symmetric off-diagonal terms in the Raman tensor for altering the selection rules. We also uncover that the correlation between phonon modes and magnetic orders is a universal phenomenon, which should exist in other phonon modes and 2D magnets. Our predictive simulations and modeling are expected to guide the research in 2D magnets.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Computing chemical potentials with machine-learning-accelerated simulations to accurately predict thermodynamic properties of molten salts

The successful design and deployment of next-generation nuclear technologies heavily rely on thermodynamic data for relevant molten salt systems. However, the lack of accurate force fields and efficient methods has limited the quality of thermodynamic predictions from atomistic simulations. Here we propose an efficient free energy framework for computing chemical potentials, which is the central free energy quantity behind many thermodynamic properties. We accelerate our simulations without sacrificing accuracy by using machine learning interatomic potentials trained on density functional theory (DFT) data. Using lithium chloride as our model system, we compute chemical potentials with DFT-accuracy for solid and liquid phases by transmuting ions into noninteracting particles. Notably, in the liquid phase, we demonstrate consistency whether we transmute one ion pair or the entire system into ideal gas particles. By locating the temperature where the chemical potential of solid and liquid phases cross, we predict a melting point of 880 ± 18 K for lithium chloride, which is remarkably close to the experimental value of 883 K. With this successful demonstration, we lay the foundation for high-throughput thermodynamic predictions of many properties that can be derived from the chemical potentials of the minority and majority components in molten salts.

Gibson, Luke D. [Oak Ridge National Laboratory (OR↗
DOE OSTI2023

Accuracy of DFT computed oxygen-vacancy formation energies and high-throughput search of solar thermochemical water-splitting compounds

The enthalpy change involved in metal oxide reduction is a key quantity in various processes related to energy conversion and storage, and is of particular interest for computational prediction. Often this prediction involves the simulation of a high temperature reduction process with a 0K methodology like density functional theory (DFT), and it is not infrequent for the high temperature and 0K stable crystal structures to differ. This introduces a conundrum with regards to the choice of crystal structure to utilize in the computation, with approaches in the literature varying and experimental validation remaining scarce. In this work we address both the crystal structure conundrum and the experimental validation, and then apply the insights we gain to guide a high-throughput search for new materials for solar thermochemical water-splitting applications. By computing the DFT+U oxygen vacancy formation energy (ΔE vf ) of a selection of ABO 3 compounds and comparing different crystal structures for each composition, we highlight the issues that arise when the structure utilized in the computation is dynamically unstable at 0K, namely the presence of an artificial lowering of ΔE vf , and the lack of convergence of ΔE vf with cell size. We solve these limitations by identifying and employing a suitable surrogate dynamically stable structure. We then validate the predictive power of our calculations against appositely generated experimental measurements of reduction enthalpy for a series of Hubbard U values, finding an accuracy ranging between 0.2-0.6 eV/O. In light of such conclusions, we revise and expand a previous a high-throughput DFT study on ABO 3 perovskite oxides. As a result, we provide a list of candidate STCH materials, highlight trends with redox-active cation and structural distortion, and identify Mn 4+ , Mn 3+ and Co 3+ as the most promising redox-active cations.

08 HYDROGEN↗
DOE OSTI2021

Uranium (VI) Adsorbate Structures on Portlandite [Ca(OH)2] Type Surfaces Determined by Computational Modelling and X-ray Absorption Spectroscopy

Portlandite [Ca(OH) 2 ] is a potentially dominant solid phase in the high pH fluids expected within the cementitious engineered barriers of Geological Disposal Facilities (GDF). This study combined X-ray Absorption Spectroscopy with computational modelling in order to provide atomic-scale data which improves our understanding of how a critically important radionuclide (U) will be adsorbed onto this phase under conditions relevant to a GDF environment. Such data are fundamental for predicting radionuclide mass transfer. Surface coordination chemistry and speciation of uranium with portlandite [Ca(OH) 2 ] under alkaline groundwater conditions (ca. pH 12) were determined by both in situ and ex situ grazing incidence extended X-ray absorption fine structure analysis (EXAFS) and by computational modelling at the atomic level. Free energies of sorption of aqueous uranyl hydroxides, [UO 2 (OH) n ] 2–n (n = 0–5) with the (001), (100) and (203) or (101) surfaces of portlandite are predicted from the potential of mean force using classical molecular umbrella sampling simulation methods and the structural interactions are further explored using fully periodic density functional theory computations. Although uranyl is predicted to only weakly adsorb to the (001) and (100) clean surfaces, there should be significantly stronger interactions with the (203/101) surface or at hydroxyl vacancies, both prevalent under groundwater conditions. The uranyl surface complex is typically found to include four equatorially coordinated hydroxyl ligands, forming an inner-sphere sorbate by direct interaction of a uranyl oxygen with surface calcium ions in both the (001) and (203/101) cases. In contrast, on the (100) surface, uranyl is sorbed with its axis more parallel to the surface plane. The EXAFS data are largely consistent with a surface structural layer or film similar to calcium uranate, but also show distinct uranyl characteristics, with the uranyl ion exhibiting the classic dioxygenyl oxygens at 1.8 Å and between four and five equatorial oxygen atoms at distances between 2.28 and 2.35 Å from the central U absorber. These experimental data are wholly consistent with the adsorbate configuration predicted by the computational models. These findings suggest that, under the strongly alkaline conditions of a cementitious backfill engineered barrier, there would be significant uptake of uranyl by portlandite to inhibit the mobility of U(VI) from the near field of a geological disposal facility.

36 MATERIALS SCIENCE↗
NASA NTRS1994

Center for modeling of turbulence and transition: Research briefs, 1993

This research brief contains the progress reports of the research staff of the Center for Modeling of Turbulence and Transition (CMOTT) from June 1992 to July 1993. It is also an annual report to the Institute for Computational Mechanics in Propulsion located at Ohio Aerospace Institute and NASA Lewis Research Center. The main objectives of the research activities at CMOTT are to develop, validate, and implement turbulence and transition models for flows of interest in propulsion systems. Currently, our research covers eddy viscosity one- and two-equation models, Reynolds-stress algebraic equation models, Reynolds-stress transport equation models, nonequilibrium multiple-scale models, bypass transition models, joint scalar probability density function models, and Renormalization Group Theory and Direct Interaction Approximation methods. Some numerical simulations (LES and DNS) have also been carried out to support the development of turbulence modeling. Last year was CMOTT's third year in operation. During this period, in addition to the above mentioned research, CMOTT has also hosted the following programs: an eighteen-hour short course on 'Turbulence--Fundamentals and Computational Modeling (Part I)' given by CMOTT at the NASA Lewis Research Center; a productive summer visitor research program that has generated many encouraging results; collaborative programs with industry customers to help improve their turbulent flow calculations for propulsion system designs; a biweekly CMOTT seminar series with speakers from within and without the NASA Lewis Research Center including foreign speakers. In addition, CMOTT members have been actively involved in the national and international turbulence research activities. The current CMOTT roster and organization are listed in Appendix A. Listed in Appendix B are the abstracts of the biweekly CMOTT seminar. Appendix C lists the papers contributed by CMOTT members.

Liou, William W.↗
DOE OSTI2022

Evidence for nitrogen binding to surface defects for topological insulator Bi 2 Se 3

Using scanning tunneling spectroscopy and theoretical simulations we have studied the effects of nitrogen gas exposure on the electronic density of states of Bi 2 Se 3 , a well-studied topological insulator. In carefully controlled measurements, Bi 2 Se 3 crystals were initially cleaved in a helium gas environment and then exposed to a 22 SCFH flow of ultra-high purity N 2 gas. We observe a resulting change in the spectral curves, with the exposure effect saturating after approximately 50 min, ultimately bringing the Dirac point about 50 meV closer to the Fermi level. Furthermore, these results are compared to density functional theory calculations, which support a picture of N 2 molecules physisorbing near Se vacancies. Furthermore, ab initio molecular dynamics simulations aided by a Blue Moon ensemble method reveal the dissociative adsorption of N 2 molecules which then bind strongly to Se vacancies at the surface. In this scenario, the binding of the N atom to a Se vacancy site removes the surface defect state created by the vacancy and changes the position of the Fermi energy with respect to the Dirac point.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A Cellular Automaton Simulation for Predicting Phase Evolution in Solid-State Reactions

New computational tools for solid-state synthesis recipe design are needed in order to accelerate the experimental realization of novel functional materials proposed by high-throughput materials discovery workflows. This work contributes a cellular automaton simulation framework for predicting the time-dependent evolution of intermediate and product phases during solid-state reactions as a function of precursor choice and amount, reaction atmosphere, and heating profile. The simulation captures the effects of reactant particle spatial distribution, particle melting, and reaction atmosphere. Reaction rates based on rudimentary kinetics are estimated using density functional theory data from the Materials Project and machine learning estimators for the melting point and the vibrational entropy component of the Gibbs free energy. The resulting simulation framework allows for the prediction of the likely outcome of a reaction recipe before any experiments are performed. We analyze five experimental solid-state recipes for BaTiO 3 , CaZrN 2 , and YMnO 3 found in the literature to illustrate the performance of the model in capturing reaction selectivity and reaction pathways as a function of temperature and precursor choice. This simulation framework offers an easier way to optimize existing recipes, aid in the identification of intermediates, and design effective recipes for yet unrealized inorganic solids in silico .

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

INSPIRED: Inelastic neutron scattering prediction for instantaneous results and experimental design

Inelastic neutron scattering (INS) has unique advantages in probing how atoms vibrate and how the vibrations propagate and interact. Such dynamic information is crucial in understanding various material properties, from heat capacity, thermal conductivity, phase transitions, and chemical reactions to more exotic quantum behavior. The analysis and interpretation of the INS spectra often start from a model structure of the sample, followed by a series of calculations to obtain the simulated spectra to compare with experiments. The conventional way to perform such calculations usually requires significant time, computing resources, and specialized expertise. Here, we present a new program named INSPIRED (Inelastic Neutron Scattering Prediction for Instantaneous Results and Experimental Design), which enables users to perform rapid INS simulations in several different ways on their personal computers in just a few clicks, with the crystal structure as the only input file. Specifically, the users can choose a pre-trained symmetry-aware neural network (coupled with an autoencoder) to predict the phonon density of states (DOS), 1D S(E) and 2D S(|Q|,E) spectra for any given structure. One can also choose an existing density functional theory (DFT) calculation from a database (containing over 12,000 crystals), and quickly obtain the simulated INS spectra for single crystals and powders. It is also possible to use pre-trained universal machine learning force fields to relax a given crystal structure, calculate the phonon dispersion and DOS, and, subsequently, the INS spectra. All these functions are implemented with a PyQt graphic user interface. Finally, we expect these new tools will benefit broad user communities and significantly improve the efficiency of experiment design, execution, and data analysis for INS.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Re-evaluation of the TSL for Yttrium Hydride

Yttrium hydride (YH x ) is of interest as a high-temperature moderator material in advanced nuclear reactor systems because of its superior ability to retain hydrogen at elevated temperatures. Thermal neutron scattering laws (TSL) for hydrogen bound in yttrium hydride (H-YH 2 ) and yttrium bound in yttrium hydride (Y-YH 2 ) were previously evaluated by Naval Nuclear Laboratory using the ab initio approach and released in ENDF/B-VIII.0. In that work, density functional theory, incorporating the generalized gradient approximation (GGA) for the exchange-correlation energy, was used to simulate the face-centered cubic structure of YH 2 and calculate the interatomic Hellmann-Feynman forces for a 2×2×2 supercell containing 96 atoms. Lattice dynamics calculations using PHONON were used to determine the phonon density of states. The calculated phonon density of states for H and Y in YH 2 were then used to prepare H-YH 2 and Y-YH 2 TSL evaluations, in the incoherent approximation, using the LEAPR module of NJOY. In addition, elastic scattering was assumed to be incoherent for both H and Y. While the incoherent elastic scattering approximation is appropriate for H-YH 2 , it introduces an undesirable approximation for Y-YH 2 . In this work, we re-evaluate the TSL for Y-YH 2 using FLASSH (Full Law Analysis Scattering System Hub). Y-YH 2 is evaluated using the FLASSH generalized coherent elastic scattering capability in order to capture the Bragg peaks associated with the YH 2 crystal structure which were neglected in the prior NJOY-based evaluation due to limitations in LEAPR. An experimental approach to validate the Y-YH 2 TSL using neutron transmission measurements is discussed.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRSDate not supplied

Quantum Hardware-Enabled Molecular Dynamics via Transfer Learning

The ability to perform ab initio molecular dynamics simulations using potential energy surfaces provided by quantum computers would open the door to virtually exact dynamics for a variety of chemical and biochemical systems, with impacts on catalysis and biophysics. Nonetheless, performing molecular dynamics on surfaces produced by quantum hardware has been hampered by the noisy energies typically produced by quantum computers and challenges associated with computing gradients and scaling to large systems interest. A recent set of advances in machine learning, known as transfer learning, provides a new path forward for molecular dynamics simulations on quantum hardware. Transfer learning offers a workaround, where one first trains models on larger, less accurate classical datasets and then refines them on smaller, more accurate quantum datasets. We explore this approach by training machine learning models to predict a molecule's potential energy based on its geometric structure using Behler-Parrinello neural networks. When successfully trained, the model enables energy gradient predictions necessary for dynamic simulations. To reduce the quantum resources needed, the model is initially trained with data derived from classical density functional theory and subsequently refined with a smaller dataset obtained from a variational quantum eigensolver optimization of the unitary coupled cluster ansatz. We show that this approach significantly reduces the size of the needed quantum training dataset while capturing the high accuracies needed within quantum chemistry simulations. The success of this two-step training method opens more opportunities to apply machine learning models on quantum data, a significant stride towards efficient quantum-classical hybrid computational models.

quantum computing↗
DOE OSTI2024

Development and application of hybrid AIMD/cDFT simulations for atomic-to-mesoscale chemistry

Many important chemical processes involve reactivity and dynamics in complex solutions. Gaining a fundamental understanding of these reaction mechanisms is a challenging goal that requires advanced computational and experimental approaches. However, important techniques such as molecular simulation have limitations in terms of scales of time, length, and system complexity. Furthermore, among the currently available solvation models, there are very few designed to describe the interaction between the molecular scale and the mesoscale. To help address this challenge, here, we establish a novel hybrid approach that couples first-principles plane-wave density functional theory with classical density functional theory (cDFT). In this approach, a region of interest described by ab initio molecular dynamics (AIMD) interacts with the surrounding medium described using cDFT to arrive at a self-consistent ground state. cDFT is a robust but efficient mesoscopic approach to accurate thermodynamics of bulk electrolyte solutions over a wide concentration range (up to 2M concentrations). Benchmarking against commonly used continuum models of solvation, such as SMD, as well as experiments, demonstrates that our hybrid AIMD–cDFT method is able to produce reasonable solvation energies for a variety of molecules and ions. With this model, we also examined the solvent effects on a prototype S N 2 reaction of the nucleophilic attack of a chloride ion on methyl chloride in the solution. The resulting reaction pathway profile and the solution phase barrier agree well with experiment, showing that our AIMD/cDFT hybrid approach can provide insight into the specific role of the solvent on the reaction coordinate.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗