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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

The seeds and homogeneous nucleation of photoinduced nonthermal melting in semiconductors due to self-amplified local dynamic instability

Laser-induced nonthermal melting in semiconductors has been studied over the past four decades, but the underlying mechanism is still under debate. Here, by using an advanced real-time time-dependent density functional theory simulation, we reveal that the photoexcitation-induced ultrafast nonthermal melting in silicon occurs via homogeneous nucleation with random seeds originating from a self-amplified local dynamic instability. Because of this local dynamic instability, any initial small random thermal displacements of atoms can be amplified by a charge transfer of photoexcited carriers, which, in turn, creates a local self-trapping center for the excited carriers and yields the random nucleation seeds. Because a sufficient amount of photoexcited hot carriers must be cooled down to band edges before participating in the self-amplification of local lattice distortions, the time needed for hot carrier cooling is the response for the longer melting time scales at shorter laser wavelengths. This finding provides fresh insights into photoinduced ultrafast nonthermal melting.

42 ENGINEERING↗
DOE OSTI2024

Interfacial charge transfer and its impact on transport properties of LaNiO 3 /LaFeO 3 superlattices

Charge transfer or redistribution at oxide heterointerfaces is a critical phenomenon, often leading to remarkable properties such as two-dimensional electron gas and interfacial ferromagnetism. Despite studies on LaNiO 3 /LaFeO 3 superlattices and heterostructures, the direction and magnitude of the charge transfer remain debated, with some suggesting no charge transfer due to the high stability of Fe 3+ (3d 5 ). Here, we synthesized a series of epitaxial LaNiO 3 /LaFeO 3 superlattices and demonstrated partial (up to ~0.5 e - /interface unit cell) charge transfer from Fe to Ni near the interface, supported by density functional theory simulations and spectroscopic evidence of changes in Ni and Fe oxidation states. The electron transfer from LaFeO 3 to LaNiO 3 and the subsequent rearrangement of the Fe 3d band create an unexpected metallic ground state within the LaFeO 3 layer, strongly influencing the in-plane transport properties across the superlattice. Moreover, we establish a direct correlation between interfacial charge transfer and in-plane electrical transport properties, providing insights for designing functional oxide heterostructures with emerging properties.

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

Electro–Oxidation of Nitroxide Radicals: Adsorption–Mediated Charge Transfer Probed Using SERS and Potentiometry

Organic compounds containing nitroxide radicals such as 4–hydroxy–2,2,6,6–tetramethylpiperidine–1–oxyl (4–hydroxy–TEMPO) are redox–active and are of interest for potential applications in redox flow batteries. The mechanisms governing charge–transfer reactions of such compounds are not well understood. Specifically, the anodic charge transfer coefficient (αa) corresponding to the electro–oxidation of 4–hydroxy–TEMPO in an aqueous medium is ~0.9, i.e., αa deviates considerably from the expected value (0.5) for a symmetric single–step one–electron transfer redox reaction. In a previous publication (J. Electrochem. Soc., 2020, 167, 143505), we have proposed a reaction mechanism to explain such asymmetric behavior by invoking adsorption–desorption processes. In the proposed mechanism, reversible oxidation of 4–hydroxy–TEMPO leads to the adsorption of the oxidation product, which then undergoes slow rate–limiting desorption from the electrode surface. In the present contribution, supporting evidence is provided for this mechanism. In situ surface–enhanced Raman spectroscopy combined with density functional theory simulations are employed to confirm the presence of surface–adsorbed species at a Au electrode during electro–oxidation of 4–hydroxy–TEMPO. Furthermore, we employ chronopotentiometry to track the gradual re–equilibration of the electrode–electrolyte interface following the electro–oxidation of 4–hydroxy–TEMPO. Analysis of the chronopotentiometry data further suggests the presence of adsorbed species, which were previously proposed and are now confirmed by direct spectroscopic evidence.

25 ENERGY STORAGE↗
DOE OSTI2023

Reaction nanoscopy of ion emission from sub-wavelength propanediol droplets

Abstract Droplets provide unique opportunities for the investigation of laser-induced surface chemistry. Chemical reactions on the surface of charged droplets are ubiquitous in nature and can provide critical insight into more efficient processes for industrial chemical production. Here, we demonstrate the application of the reaction nanoscopy technique to strong-field ionized nanodroplets of propanediol (PDO). The technique’s sensitivity to the near-field around the droplet allows for the in-situ characterization of the average droplet size and charge. The use of ultrashort laser pulses enables control of the amount of surface charge by the laser intensity. Moreover, we demonstrate the surface chemical sensitivity of reaction nanoscopy by comparing droplets of the isomers 1,2-PDO and 1,3-PDO in their ion emission and fragmentation channels. Referencing the ion yields to gas-phase data, we find an enhanced production of methyl cations from droplets of the 1,2-PDO isomer. Density functional theory simulations support that this enhancement is due to the alignment of 1,2-PDO molecules on the surface. The results pave the way towards spatio-temporal observations of charge dynamics and surface reactions on droplets.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

First-Principles Study of Tritium Trapping by Point Defects in Fe-Al Aluminide Coating Phases

Density functional theory simulations have been carried out to investigate the potential for tritium trapping by metal vacancies in five different Fe-Al aluminide coating phases. It was found that tritiation of Fe and Ni vacancies is generally less favorable than the tritiation of Al vacancies. However, for the first tritiation, a trend in the defect formation energy can be obtained such that metal defects in the Fe 2 Al x family of materials (i.e., Fe 2 Al 4 , Fe 2 Al 5 , and Fe 2 Al 6 ) trap tritium species more favorably than metal vacancies in Fe 4 Al 13 and FeNiAl 5 . Further investigations using ab initio thermodynamics calculations confirmed that trend for a range of tritium partial pressure at a temperature of 700 K. Especially, it was shown that the energy difference between tritiated and non-tritiated metal vacancies is smaller and more favorable for the Fe 2 Al x family, followed by Fe 4 Al 13 , and FeNiAl 5 . While this study shows that tritium interacts differently in the various Fe-Al aluminide phases, it also suggests that tritium trapping and retention could be more efficient if metal defects are present in some Fe-Al phases.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Predicted thermophysical properties of UN, PuN and (U,Pu)N

Molecular dynamics and density functional theory simulations are used to predict the lattice and electronic contributions of thermophysical properties for UN, PuN, and mixed (U,Pu)N systems. The properties predicted include the lattice parameter, linear thermal expansion, enthalpy, and specific heat capacity, as a function of temperature. The simulation predictions for high temperature specific heat capacity are compared against experimental measurements to understand the behavior, and why differences in the experimental measurements are observed. The influence of adding U vacancies, N interstitials, and Pu to UN is also examined. For this, a new PuN potential parameter set is developed and used with the Kocevski UN potential, enabling the dynamics of mixed (U,Pu)N systems to be studied. How defects impact the thermophysical properties is important for understanding fuel behavior under different reactor conditions, and these mechanistic predictions can be used to support fuel performance codes where data is scarce.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Thermodynamics of Tritium Trapping by Point Defects in Intermetallic Al 12 (TM) 2.35 Aluminide Coating Phase

Density functional theory simulations have been carried out to investigate the potential for tritium trapping by metal vacancies in intermetallic Al 12 (TM) 2.35 phase (TM = Fe, Cr, and Ni) as function of temperature and tritium partial pressure. It was found that tritium could be favorably trapped by Fe and Ni vacancies and not favorably trapped by Al and Cr vacancies. However, due to the presence of partially occupied Al sites in bulk Al 12 (TM) 2.35 , leading to the approximate number of ~255 Al atoms in the unit cell, 86 sites were found energetically favorable to the creation of an Al vacancy. While adding a tritium atom in an Al vacancy is not energetically favorable, the tritiated defect still has a negative Gibbs free energy because the energy gain for creating an Al vacancy overcome the energy cost of adding the tritium species. Based on the calculated Gibbs free energy, the first tritiation of a metal vacancy, at conditions relevant to in-reactor operations, should be more favorable for Al, followed Fe, Ni, and Cr vacancies. By comparing the behavior of tritium in Al 12 (TM) 2.35 with previously studied Fe-Al coating phases (i.e., FeNiAl 5 , Fe 4 Al 13 , and Fe 2 Al 5.6 ), we found that there is a correlation between interstitial tritium solubility and the potential for vacancy trapping. The current trend suggests that if the insertion of an interstitial tritium cost more than 0.3 eV, then trapping by metal vacancies should be preferred. By combining the simulations results obtained to date, we noticed different trapping mechanisms of tritium in the Al coating. Tritium is mostly trapped by Fe and Ni vacancies in the outer Fe-Al coating phase Al 12 (TM) 2.35 while tritium should be preferentially trapped by Al and Fe vacancies for the inner Fe-Al coating phases (FeNiAl 5 , Fe 4 Al 13 , Fe 2 Al 5.6 ). Altogether, these studies show that tritium interacts differently with the various Fe-Al aluminide phases, they also suggest that tritium trapping and retention could be more efficient if metal defects are present and if the solubility of interstitial tritium in the different phases is low.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Predicting Elastic Constants of Refractory Complex Concentrated Alloys Using Machine Learning Approach

Refractory complex concentrated alloys (RCCAs) have drawn increasing attention recently owing to their balanced mechanical properties, including excellent creep resistance, ductility, and oxidation resistance. The mechanical and thermal properties of RCCAs are directly linked with the elastic constants. However, it is time consuming and expensive to obtain the elastic constants of RCCAs with conventional trial-and-error experiments. The elastic constants of RCCAs are predicted using a combination of density functional theory simulation data and machine learning (ML) algorithms in this study. The elastic constants of several RCCAs are predicted using the random forest regressor, gradient boosting regressor (GBR), and XGBoost regression models. Based on performance metrics R-squared, mean average error and root mean square error, the GBR model was found to be most promising in predicting the elastic constant of RCCAs among the three ML models. Additionally, GBR model accuracy was verified using the other four RHEAs dataset which was never seen by the GBR model, and reasonable agreements between ML prediction and available results were found. The present findings show that the GBR model can be used to predict the elastic constant of new RHEAs more accurately without performing any expensive computational and experimental work.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Morphological-informed Thermal Property Prediction in the Engineering Domain

Using first-principle, atomic scale methods to predict thermal carrier (electron and phonon) behavior at nanoscale yields highly resolved thermal properties. Density functional theory simulations can model myriad effects on the transport of phonons and electrons (e.g., phonon and electron coupling, electron correlation, defect presence, carrier scattering), and yield thermal properties for small geometric domains such as thermal and electrical conductivity, or heat capacity. While these thermal properties are accurate in atomistic and nanoscopic systems, they must be scaled up to the microstructural domain to be a useful predictor for experimental basis, as the microscale is where myriad changes and physical phenomenon occur within a material (e.g., grain boundaries, precipitate aggregations, interfaces, defect clusters). My talk will discuss the necessity of thermal property predictions for nuclear fuels applications and more. Additionally I will discuss the necessity in developing multi-physics, multi-scale methods for future applications in predictions for not only nuclear fuels, but other materials applications.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Elevating density functional theory to chemical accuracy for water simulations through a density-corrected many-body formalism

Abstract Density functional theory (DFT) has been extensively used to model the properties of water. Albeit maintaining a good balance between accuracy and efficiency, no density functional has so far achieved the degree of accuracy necessary to correctly predict the properties of water across the entire phase diagram. Here, we present density-corrected SCAN (DC-SCAN) calculations for water which, minimizing density-driven errors, elevate the accuracy of the SCAN functional to that of “gold standard” coupled-cluster theory. Building upon the accuracy of DC-SCAN within a many-body formalism, we introduce a data-driven many-body potential energy function, MB-SCAN(DC), that quantitatively reproduces coupled cluster reference values for interaction, binding, and individual many-body energies of water clusters. Importantly, molecular dynamics simulations carried out with MB-SCAN(DC) also reproduce the properties of liquid water, which thus demonstrates that MB-SCAN(DC) is effectively the first DFT-based model that correctly describes water from the gas to the liquid phase.

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

Erratum: “DFTB+, a software package for efficient approximate density functional theory based atomistic simulations” [J. Chem. Phys. 152, 124101 (2020)]

The implementation of the GPU support in DFTB+, as described in Sec. III C of the original publication,1 was developed based on a previous unpublished implementation by Jacek Jakowski. In order to acknowledge his work on this first implementation, the authors of the original publication wish to include J. Jakowski as co-author. The scientific content of the original publication is not affected.

42 ENGINEERING↗
DOE OSTI2022

Towards Ab-Initio Simulations of Crystalline Defects at the Exascale Using Spectral Quadrature Density Functional Theory

Defects in crystalline solids play a crucial role in determining properties of materials at the nano, meso- and macroscales, such as the coalescence of vacancies at the nanoscale to form voids and prismatic dislocation loops or diffusion and segregation of solutes to nucleate precipitates, phase transitions in magnetic materials via disorder and doping. First principles Density Functional Theory (DFT) simulations can provide a detailed understanding of these phenomena. However, the number of atoms needed to correctly simulate these systems is often beyond the reach of many widely used DFT codes. The aim of this article is to discuss recent advances in first principles modeling of crystal defects using the spectral quadrature method. The spectral quadrature method is linear scaling with respect to the number of atoms, permits spatial coarse-graining, and is capable of simulating non-periodic systems embedded in a bulk environment, which allows the application of appropriate boundary conditions for simulations of crystalline defects. In this article, we discuss the state-of-the-art in ab-initio modeling of large metallic systems of the order of several thousand atoms that are suitable for utilizing exascale computing resourses.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Exploring the Structural, Dynamic, and Functional Properties of Metal–Organic Frameworks through Molecular Modeling

This review spotlights the role of atomic-level modeling in research on metal-organic frameworks (MOFs), especially the key methodologies of density functional theory (DFT), Monte Carlo (MC) simulations, and molecular dynamics (MD) simulations. The discussion focuses on how periodic and cluster-based DFT calculations can provide novel insights into MOF properties, with a focus on predicting structural transformations, understanding thermodynamic properties and catalysis, and providing information or properties that are fed into classical simulations such as force field parameters or partial charges. Classical simulation methods, highlighting force field selection, databases of MOFs for high-throughput screening, and the synergistic nature of MC and MD simulations, are described. By predicting equilibrium thermodynamic and dynamic properties, these methods offer a wide perspective on MOF behavior and mechanisms. Additionally, the incorporation of machine learning (ML) techniques into quantum and classical simulations is discussed. These methods can enhance accuracy, expedite simulation setup, reduce computational costs, as well as predict key parameters, optimize geometries, and estimate MOF stability. By charting the growth and promise of computational research in the MOF field, the aim is to provide insights and recommendations to facilitate the incorporation of computational modeling more broadly into MOF research.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Unraveling the solvation phenomena of Ln 3+ cations in room-temperature ionic liquids: A computational study

Rare-earth elements (REEs), classified as critical materials, are difficult to separate due to their similar chemical properties and slight differences in ionic radius. Room-temperature ionic liquids (RTILs) have gained significant attention for REE separation because of their unique physicochemical properties and environmental advantages. In this study, we have investigated the solvation mechanisms of two RE cations (Ln 3+ ), Nd 3+ (light REE) and Yb 3+ (heavy REE), in two 1-butyl-3-methylimidazolium ([BMIM] + )-based RTILs using bis(trifluoromethylsulfonyl)imide ([NTf 2 ] − ) and acetate ([OAc] − ) as the respective anions, employing classical molecular dynamics (MD) simulations and density functional theory (DFT) techniques. From MD simulations, it is evident that Ln 3+ cations are primarily solvated by RTIL anions in the first solvation shell, while [BMIM] + cations form the second solvation shell with their numbers depending on the size and composition of the first solvation shell. The neutralizing [NO 3 − ] counterions are mainly solvated by [BMIM] + cations in their first solvation shell. Relative free energy change of solvation calculations using thermodynamic integration (TI) method indicate that Yb 3+ is more strongly solvated than Nd 3+ in both RTILs, a trend further supported by DFT calculations. While both methods predict consistent qualitative behavior, differences in models and energy evaluations lead to variations in absolute values. Overall, this study provides a comprehensive understanding of the solvation behavior of Ln 3+ cations in RTILs, demonstrating a stronger solvation preference for the heavy Ln 3+ cation (Yb 3+ ). In conclusion, these findings have implications for the design of RTIL-based separation processes for REEs.

Ash, Tamalika [Ames Lab., and Iowa State Univ., Am↗
DOE OSTI2020

Multiscale computational understanding and growth of 2D materials: a review

Abstract The successful discovery and isolation of graphene in 2004, and the subsequent synthesis of layered semiconductors and heterostructures beyond graphene have led to the exploding field of two-dimensional (2D) materials that explore their growth, new atomic-scale physics, and potential device applications. This review aims to provide an overview of theoretical, computational, and machine learning methods and tools at multiple length and time scales, and discuss how they can be utilized to assist/guide the design and synthesis of 2D materials beyond graphene. We focus on three methods at different length and time scales as follows: (i) nanoscale atomistic simulations including density functional theory (DFT) calculations and molecular dynamics simulations employing empirical and reactive interatomic potentials; (ii) mesoscale methods such as phase-field method; and (iii) macroscale continuum approaches by coupling thermal and chemical transport equations. We discuss how machine learning can be combined with computation and experiments to understand the correlations between structures and properties of 2D materials, and to guide the discovery of new 2D materials. We will also provide an outlook for the applications of computational approaches to 2D materials synthesis and growth in general.

Momeni, Kasra↗
DOE OSTI2022

Computational investigation of hydrogen-induced phonon changes in carbon fiber

Optical vibrational spectroscopy has shown promise as a noninvasive means of monitoring the mechanical properties of carbon fiber (CF), which is increasingly used for industrial and consumer purposes. However, interpretation of optical vibrational spectra for solid materials is inferential, particularly when defects are present. Because inelastic neutron scattering (INS) spectroscopy is not subject to selection rules, the full vibrational spectra can be measured. And, identifying correlations between INS features and tensile properties can assist in the interpretation of spectra from more commonly used optical vibrational spectroscopic techniques, such as Raman and infrared (IR) spectroscopy. Recent INS experiments on high-performance commercial carbon fibers showed features near 900 and 1100 cm –1 in addition to a broad feature near 3000 cm –1 that increased in intensity with decreasing tensile strength. These features were assigned to hydrogen defects. Here, we use density functional theory to simulate the INS spectra of several hydrogen defect geometries in graphite as a model for carbon fiber structure units, confirming the experimental assignment of these peaks to hydrogen modes and providing insights into the structure and lattice dynamics of the defects.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Demonstration of an x-ray Raman spectroscopy setup to study warm dense carbon at the high energy density instrument of European XFEL

We present a proof-of-principle study demonstrating x-ray Raman Spectroscopy (XRS) from carbon samples at ambient conditions in conjunction with other common diagnostics to study warm dense matter, performed at the high energy density scientific instrument of the European x-ray Free Electron Laser (European XFEL). We obtain sufficient spectral resolution to identify the local structure and chemical bonding of diamond and graphite samples, using highly annealed pyrolytic graphite spectrometers. Due to the high crystal reflectivity and XFEL brightness, we obtain signal strengths that will enable accurate XRS measurements in upcoming pump–probe experiments with a high repetition-rate, where the samples will be pumped with high-power lasers. Molecular dynamics simulations based on density functional theory together with XRS simulations demonstrate the potential of this technique and show predictions for high-energy-density conditions. Our setup allows simultaneous implementation of several different diagnostic methods to reduce ambiguities in the analysis of the experimental results, which, for warm dense matter, often relies on simplifying model assumptions. The promising capabilities demonstrated here provide unprecedented insights into chemical and structural dynamics in warm dense matter states of light elements, including conditions similar to the interiors of planets, low-mass stars, and other celestial bodies.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Fast Emulation of Expensive Simulations using Approximate Gaussian Processes [Slides]

Nuclear Computational Low-Energy Initiative (NUCLEI) collaboration uses Density Functional Theory (DFT) simulations to predict the structure and binding energies of nuclei over a wide range of proton (Z) and neutron (N) numbers. The DFT simulations utilize a particular parameterization of a Skyrme energy density functional called UNEDF1 which depends on 12 free parameters that must be fit to data (M Kortelainen et al 2014). Fitting involves comparing (e.g.) predicted binding energies of nuclei to experimentally measured values. We use only binding energies as observables, but DFT with UNEDF1 will predict structure (shape) observables as well. In this work, assessing the capability of approximate GP emulators to balance emulator accuracy with computational speed to facilitate improved UNEDF1 calibration. Sparse GPs are straightforward to train and accurate. Calibration is not straightforward with MCMC (using MH or HMC/NUTS). We produced reusable software for continuing and building on this work as well as accessing and using Darwin cluster compute resources

97 MATHEMATICS AND COMPUTING↗