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Results for “density functional theory development”

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 1,135 records · Page 63
All sourcesNASA NTRSDOE OSTI
NASA NTRS1979

Physical models of Comet Halley based upon qualitative data from the 1910 apparition

A semi-empirical theory was developed, tying the hydrogen production rate of a comet to its visual light curve. Two unknown constants, which are essentially the efficiencies of these two processes, are derived from the comets for which quantitative data exist. This theory has been applied to P/Halley, using the light curve of Yeomans, which was derived from the original 1910 observations, with aperture corrections applied. Given the hydrogen production rate, it is assumed that N(H20) = 0.5 N(H) and that there is 0.2 N(H20) of other species. From several converging lines of evidence the mass of dust is taken as half the mass of gas. The Sekanina-Miller distribution function of particle size is used. Particle velocities are calculated using Delsemmes version of the Probstein theory. From these, near nucleus dust density, flux, etc. are calculated. Dust envelope sizes are calculated from the old mechanical theory of tails. Extreme models are calculated from the old mechanical theory of tails. Extreme models are also furnished based upon a "sum-of-negative-tolerance" approach.

Newburn, R. L.↗
DOE OSTI2024

Computational Advances in Ionic Liquid Applications for Green Chemistry: A Critical Review of Lignin Processing and Machine Learning Approaches

The valorization and dissolution of lignin using ionic liquids (ILs) is critical for developing sustainable biorefineries and a circular bioeconomy. This review aims to critically assess the current state of computational and machine learning methods for understanding and optimizing IL-based lignin dissolution and valorization processes reported since 2022. The paper examines various computational approaches, from quantum chemistry to machine learning, highlighting their strengths, limitations, and recent advances in predicting and optimizing lignin-IL interactions. Key themes include the challenges in accurately modeling lignin’s complex structure, the development of efficient screening methodologies for ionic liquids to enhance lignin dissolution and valorization processes, and the integration of machine learning with quantum calculations. These computational advances will drive progress in IL-based lignin valorization by providing deeper molecular-level insights and facilitating the rapid screening of novel IL-lignin systems.

09 BIOMASS FUELS↗
DOE OSTI2021

Increasing Ionic Conductivity of Poly(ethylene oxide) by Reaction with Metallic Li

Poly(ethylene oxide) (PEO) was the first lithium-ion conducting polymer developed 50 years ago and is still the most popular electrolyte matrix for solid-state lithium metal batteries. While many studies focus on increasing PEO ionic conductivity through doping with Li salts, little work has addressed using PEO and Li directly to generate Li + -conducting species in situ. Reaction between PEO and Li leads to ionic conductivity largely from Li + , in contrast to the case of added salts where the anion contribution dominates. Herein, electrochemical impedance spectroscopy shows the ionic conductivity of PEO thin films increases up to three orders of magnitude (from 10 –7 to 10 –4 S cm –1 ) when contacted with Li at elevated temperature. This is due to the reduction of ether bonds, which produces lithium alkoxides that are responsible for Li + transport. Density functional theory analysis confirms this mechanism as thermodynamically favorable. X-ray photoelectron spectroscopy also shows the presence of organolithium species and Li 2 O, which are responsible for propagating reactions with PEO and forming an electronically insulating layer at the PEO–Li interface that halts further reaction, respectively. The underlying mechanisms of Li–polymer electrolyte reactions is clarified and new pathways for in situ Li + doping of polymer electrolytes is presented.

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

First Principles Nonadiabatic Excited-State Molecular Dynamics in NWChem

Computational simulation of non-adiabatic molecular dynamics is an indispensable tool for understanding complex photoinduced processes such as internal conversion, energy transfer, charge separation, and spatial localization of excitons, to name a few. Here, we report an implementation of the fewest-switches surface hopping algorithm in the NWChem computational chemistry program. Here the surface hopping method is combined with linear-response time-dependent density functional theory calculations of adiabatic excited state potential energy surfaces. To treat quantum transitions between arbitrary electronic Born{Oppenheimer states, we have implemented both numerical and analytical differentiation schemes for derivative non-adiabatic couplings. A numerical approach for the time-derivative non-adiabatic couplings together with an analytical method for calculating non-adiabatic coupling vectors is an efficient combination for surface hopping approaches. Additionally, electronic decoherence schemes and a state reassigned unavoided crossings algorithm are also implemented to improve the accuracy of the simulated dynamics and to handle trivial unavoided crossings. We apply our code to study the ultrafast decay of photoexcited benzene, including a detailed analysis of the potential energy surface, population decay time scales, and vibrational coordinates coupled to the excitation dynamics. The development presented in this work is a baseline for future implementations of more sophisticated frameworks for simulating of non-adiabatic molecular dynamics in NWChem.

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

Stability Analysis of Substituted Cobaltocenium [Bis(cyclopentadienyl)cobalt(III)] Employing Chemistry-Informed Neural Networks

Cobaltocenium derivatives are promising components of the anion exchange membranes due to their excellent thermal and alkaline stability under the operating conditions of a fuel cell. Here we present an efficient modeling approach of assessing the chemical stability of substituted cobaltocenium CoCp 2 + based on the computed electronic structure enhanced by machine learning techniques. Within the aqueous environment, the positive charge of the metal cation is balanced by the hydroxide anion through formation of the CoCp 2 + OH¯ complexes, whose dissociation is studied within the implicit solvent employing density functional theory. The data set of about 118 species based on 42 substituent groups characterized by a range of electron- donating (ED) and electron-withdrawing (EW) properties is constructed and analyzed. Given 12 carefully chosen chemistry-informed descriptors of the complexes and relevant fragments, the stability of the complexes is found to strongly correlate with the energies of the highest occupied and lowest unoccupied molecular orbitals, modulated by a switching function of the Hirshfeld charge. The latter is used as a measure of the electron withdrawing-donating character of the substituents. Based on this observation from the conventional regression analysis, two fully connected, feed-forward neural network (FNN) models with different unit structures, called the chemistry-informed (CINN) and the quadratic (QNN) neural networks, are developed. Both models predict the bond dissociation energies of the cobaltocenium complexes with mean relative errors less than 5.40% and average absolute errors less than 0.94 kcal/mol. The results show the potential of QNN to efficiently capture more complex relationships. Here, the concept of incorporating the domain (chemical) knowledge/insight into the neural network structure paves the way to applications of machine learning techniques with small data sets, ultimately leading to better predictive models compared to the conventional regression analysis.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Real-Time Time-Dependent Density Functional Theory for Simulating Nonequilibrium Electron Dynamics

The explicit real-time propagation approach for time-dependent density functional theory (RT-TDDFT) has increasingly become a popular first-principles computational method for modeling various time-dependent electronic properties of complex chemical systems. Here, in this Perspective, we provide a nontechnical discussion of how this first-principles simulation approach has been used to gain novel physical insights into nonequilibrium electron dynamics phenomena in recent years. Following a concise overview of the RT-TDDFT methodology from a practical standpoint, we discuss our recent studies on the electronic stopping of DNA in water and the Floquet topological phase as examples. Our discussion focuses on how RT-TDDFT simulations played a unique role in deriving new scientific understandings. We then discuss existing challenges and some new advances at the frontier of RT-TDDFT method development for studying increasingly complex dynamic phenomena and systems.

Hamiltonians↗
DOE OSTI2022

Training and projecting: A reduced basis method emulator for many-body physics

Here, we present the reduced basis method as a tool for developing emulators for equations with tun able parameters within the context of the nuclear many-body problem. The method uses a basis expansion informed by a set of solutions for a few values of the model parameters and then projects the equations over a well-chosen low-dimensional subspace. We connect some of the results in the eigenvector continuation literature to the formalism of reduced basis methods and show how these methods can be applied to a broad set of problems. As we illustrate, the possible success of the formalism on such problems can be diagnosed beforehand by a principal component analysis. We apply the reduced basis method to the one-dimensional Gross-Pitaevskii equation with a harmonic trap ping potential and to nuclear density functional theory for 48 Ca, achieving speed-ups of more than x150 and x250, respectively, when compared to traditional solvers. The outstanding performance of the approach, together with its straightforward implementation, show promise for its application to the emulation of computationally demanding calculations, including uncertainty quantification.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1983

A mathematical characterization of vegetation effect on microwave remote sensing from the Earth

In passive microwave remote sensing of the earth, a theoretical model that utilizes the radiative transfer equations was developed to account for the volume scattering effects of the vegetation canopy. Vegetation canopies such as alfalfa, sorghum, and corn are simulated by a layer of ellipsoidal scatterers and cylindrical structures. The ellipsoidal scatterers represent the leaves of vegetation and are randomly positioned and oriented. The orientation of ellipsoids is characterized by a probability density function of Eulerian angles of rotation. The cylindrical structures represent the stalks of vegetation and their radii are assumed to be much smaller than their lengths. The underlying soil is represented by a half-space medium with a homogeneous permittivity and uniform temperature profile. The radiative transfer quations are solved by a numerical method using a Gaussian quadrature formula to compute both the vertical and horizontal polarized brightness temperature as a function of observation angle. The theory was applied to the interpretation of experimental data obtained from sorghum covered fields near College Station, Texas.

Choe, Y.↗
DOE OSTI2021

Sparse expansions of multicomponent oxide configuration energy using coherency and redundancy

We report that compressed sensing has become a widely accepted paradigm to construct high dimensional cluster expansion models used for statistical mechanical studies of atomic configuration in complex multicomponent crystalline materials. However, strict sampling requirements necessary to obtain minimal coherence measurements for compressed sensing to guarantee accurate estimation of model parameters are difficult and in some cases impossible to satisfy due to the inability of physical systems to access certain configurations. Nevertheless, the dependence of energy on atomic configuration can still be adequately learned without these strict requirements by using compressed sensing by way of coherent measurements using redundant function sets known as frames. We develop a particular frame constructed from the union of all occupancy-based cluster expansion basis sets. We illustrate how using this highly redundant frame yields sparse expansions of the configuration energy of complex oxide materials that are competitive and often surpass the prediction accuracy and sparsity of models obtained from standard cluster expansions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Molecular dynamics simulation of Fe-Si alloys using a neural network machine learning potential

Interatomic potential development using machine learning (ML) approaches has attracted a lot of attention in recent years because these potentials can effectively describe the structural and dynamical properties of complex materials at the atomistic level. Here, in this work, we present the development of a neural network (NN) deep ML interatomic potential for Fe-Si alloys, and we demonstrate the effectiveness of the NN-ML potential in predicting the structures and energies of liquid and crystalline phases of Fe-Si alloys in comparison with the results from ab initio molecular dynamics simulations or experimental data. The developed NN-ML potential is also used to perform molecular dynamics simulations to study the structures of Fe-Si alloys with various compositions under rapid solidification conditions. The short-ranged orders in the rapidly solidified Fe-Si alloys are also analyzed by a cluster alignment method.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Chelating Rare-Earth Metals (Ln 3+ ) and 225 Ac 3+ with the Dual-Size-Selective Macrocyclic Ligand Py 2 -Macrodipa

Radioisotopes of metallic elements, or radiometals, are widely employed in both therapeutic and diagnostic nuclear medicine. For this application, chelators that efficiently bind the radiometal of interest and form a stable metal–ligand complex with it are required. Toward the development of new chelators for nuclear medicine, we recently reported a novel class of 18-membered macrocyclic chelators that is characterized by their ability to form stable complexes with both large and small rare-earth metals (Ln 3+ ), a property referred to as dual size selectivity. A specific chelator in this class called py-macrodipa, which contains one pyridyl group within its macrocyclic core, was established as a promising candidate for 135 La 3+ , 213 Bi 3+ , and 44 Sc 3+ chelation. Building upon this prior work, here we report the synthesis and characterization of a new chelator called py 2 -macrodipa with two pyridyl units fused into the macrocyclic backbone. Its coordination chemistry with the Ln 3+ series was investigated by NMR spectroscopy, X-ray crystallography, density functional theory (DFT) calculations, analytical titrations, and transchelation assays. These studies reveal that py 2 -macrodipa retains the expected dual size selectivity and possesses an enhanced thermodynamic affinity for all Ln 3+ compared to py-macrodipa. By contrast, the kinetic stability of Ln 3+ complexes with py 2 -macrodipa is only improved for the light, large Ln 3+ ions. Based upon these observations, we further assessed the suitability of py 2 -macrodipa for use with 225 Ac 3+ , a large radiometal with valuable properties for targeted α therapy. Radiolabeling and stability studies revealed py 2 -macrodipa to efficiently incorporate 225 Ac 3+ and to form a complex that is inert in human serum over 3 weeks. Although py 2 -macrodipa does not surpass the state-of-the-art chelator macropa for 225 Ac 3+ chelation, it does provide another effective 225 Ac 3+ chelator. Furthermore, these studies shed light on the fundamental coordination chemistry of the Ln 3+ series and may inspire future chelator design efforts.

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

Atomic Three-Dimensional Investigations of Pd Nanocatalysts for Acetylene Semi-hydrogenation

Deciphering the three-dimensional (3D) insight into nanocatalyst surfaces at the atomic level is crucial to understanding catalytic reaction mechanisms and developing high-performance catalysts. Nevertheless, better understanding the inherent insufficiency of a long-range ordered lattice in nanocatalysts is a big challenge. Here, in this work, we report the local structure of Pd nanocatalysts, which is beneficial for demonstrating the shape-structure-adsorption relationship in acetylene hydrogenation. The 5.27 nm spherical Pd catalyst (Pd sph ) shows an ethylene selectivity of 88% at complete acetylene conversion, which is much higher than those of the Pd octahedron and Pd cube and superior to other reported monometallic Pd nanocatalysts so far. By virtue of the local structure revelation combined with the atomic pair distribution function (PDF) and reverse Monte Carlo (RMC) simulation, the atomic surface distribution of the unique compressed strain of Pd-Pd pairs in Pd sph was revealed. Density functional theory calculations verified the obvious weakening of the ethylene adsorption energy on account of the surface strain of Pd sph . It is the main factor to avoid the over-hydrogenation of acetylene. The present work, entailing shape-induced surface strain manipulation and atomic 3D insight, opens a new path to understand and optimize chemical activity and selectivity in the heterogeneous catalysis process.

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

A Novel NASICON‐Type Na 4 MnCr(PO 4 ) 3 Demonstrating the Energy Density Record of Phosphate Cathodes for Sodium‐Ion Batteries

Abstract Sodium‐ion batteries (SIBs) have attracted incremental attention as a promising candidate for grid‐scale energy‐storage applications. To meet practical requirements, searching for new cathode materials with high energy density is of great importance. Herein, a novel Na superionic conductor (NASICON)‐type Na 4 MnCr(PO 4 ) 3 is developed as a high‐energy cathode for SIBs. The Na 4 MnCr(PO 4 ) 3 nanoparticles homogeneously embedded in a carbon matrix can present an extraordinary reversible capacity of 160.5 mA h g −1 with three‐electron reaction at ≈3.53 V during the Na + extraction/insertion process, realizing an unprecedentedly high energy density of 566.5 Wh kg −1 in the phosphate cathodes for SIBs. It is intriguing to reveal the underlying mechanism of the unique Mn 2+ /Mn 3+ , Mn 3+ /Mn 4+ , and Cr 3+ /Cr 4+ redox couples via X‐ray absorption near‐edge structure spectroscopy. The whole electrochemical reaction undergoes highly reversible single‐phase and biphasic transitions with a moderate volume change of 7.7% through in situ X‐ray diffraction and ex situ high‐energy synchrotron X‐ray diffraction. Combining density functional theory (DFT) calculations with the galvanostatic intermittent titration technique, the superior performance is ascribed to the low ionic‐migration energy barrier and desirable Na‐ion diffusion kinetics. The present work can offer a new insight into the design of multielectron‐reaction cathode materials for SIBs.

Zhang, Jian↗
DOE OSTI2023

Type-I CdS/ZnS Core/Shell Quantum Dot-Gold Heterostructural Nanocrystals for Enhanced Photocatalytic Hydrogen Generation

Developing Type-I core/shell quantum dots is of great importance toward fabricating stable and sustainable photocatalysts. However, the application of Type-I systems has been limited due to the strongly confined photogenerated charges by the energy barrier originating from the wide-bandgap shell material. In this project, we found that through the decoration of Au satellite-type domains on the surface of Type-I CdS/ZnS core/shell quantum dots, such an energy barrier can be effectively overcome and an over 400-fold enhancement of photocatalytic H(2) evolution rate was achieved compared to bare CdS/ZnS quantum dots. Transient absorption spectroscopic studies indicated that the charges can be effectively extracted and subsequently transferred to surrounding molecular substrates in a subpicosecond time scale in such hybrid nanocrystals. Based on density functional theory calculations, the ultrafast charge separation rates were ascribed to the formation of intermediate Au2S layer at the semiconductor-metal interface, which can successfully offset the energy confinement introduced by the ZnS shell. In conclusion, our findings not only provide insightful understandings on charge carrier dynamics in semiconductor-metal heterostructural materials but also pave the way for the future design of quantum dot-based hybrid photocatalytic systems.

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

Nuclear–electronic orbital approach to quantization of protons in periodic electronic structure calculations

The nuclear–electronic orbital (NEO) method is a well-established approach for treating nuclei quantum mechanically in molecular systems beyond the usual Born–Oppenheimer approximation. In this work, we present a strategy to implement the NEO method for periodic electronic structure calculations, particularly focused on multicomponent density functional theory (DFT). The NEO-DFT method is implemented in an all-electron electronic structure code, FHI-aims, using a combination of analytical and numerical integration techniques as well as a resolution of the identity scheme to enhance computational efficiency. After validating this implementation, proof-of-concept applications are presented to illustrate the effects of quantized protons on the physical properties of extended systems, such as two-dimensional materials and liquid–semiconductor interfaces. Specifically, periodic NEO-DFT calculations are performed for a trans-polyacetylene chain, a hydrogen boride sheet, and a titanium oxide–water interface. The zero-point energy effects of the protons as well as electron–proton correlation are shown to noticeably impact the density of states and band structures for these systems. These developments provide a foundation for the application of multicomponent DFT to a wide range of other extended condensed matter systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Role of Pr-Vacancies and O-Interstitials on the Activity and Stability of (Pr 1−x Ln x ) 2 NiO 4 (Ln = La, Nd, Pm, Sm, Gd, Tb, Dy, and Ho) towards Oxygen Reduction Reactions: A DFT Study

Praseodymium nickelate, Pr 2 NiO 4 (PNO), is a promising electrode to promote oxygen reduction reaction (ORR) in a solid oxide fuel cell, but it exhibits phase transformation during electrochemical operation. The origin of the simultaneous phase transformation and high electrochemical performance remains obscure. We carried out a systematic density functional theory study to elucidate the mechanism for this conjugated phenomenon. Charge, electronic structure, and normal-mode analysis suggest the presence of peroxide. Our study shows that the formation of peroxide (O 2 2– ) is attributed to both oxygen interstitials and Pr vacancies. The peroxide species limits the oxygen ion migration due to the additional energy required to break its O–O bond, which leads to a decrease in ORR activity. Subsequently, we investigate the diffusion paths of Pr-ions while comparing them with those of other Ln 3+ ions (La, Nd, Pm, Sm, Gd, Tb, Dy, and Ho) in PNO. The formation energies for various Ln 3+ cation occupancies are calculated, as well as segregation energies in CeO 2 (111) surfaces. Lastly, criteria for effective Ln 3+ dopants are developed. La, Nd, and Pm are proposed as potential substituents in PNO to obtain a stable structure.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1977

Room-temperature-operation visible-emission semiconductor diode lasers

There were two main approaches taken to develop shorter wavelength lasers. (1) Based on (AlGa)As and liquid-phase epitaxy, significant new results were obtained: Properties of these laser diodes (power output, spectra, and beam patterns), materials considerations, laser theory, and growth problems are discussed. The design of (AlGa)As layers is discussed from the vertical point of view, and various design curves are given. Horizontal structural requirements are also discussed. Experimental results from measurements done as a function of hydrostatic pressure are correlated with other results. (2) The first heterojunction laser structures using GaAs sub l-x P sub x and In sub y Ga sub l-y P at compositions, where the lattice constants are matched, were grown using vapor-phase growth technology and are described in detail, including experimental device results. Threshold current densities from 3,000 to 5,000 A per sq cm. and emission wavelengths from 6,520 A to 6,640 A were obtained at 77 K. The limiting factor in these devices is nonradiative recombination at the heterojunctions. Life tests on facet-coated (AlGa)As CW diodes are reported.

Ladany, I.↗
DOE OSTI2023

Probing Oxidation-Driven Amorphized Surfaces in a Ta(110) Film for Superconducting Qubit

Recent advances in superconducting qubit technology have led to significant progress in quantum computing, but the challenge of achieving a long coherence time remains. Despite the excellent lifetime performance that tantalum (Ta) based qubits have demonstrated to date, the majority of superconducting qubit systems, including Ta-based qubits, are generally believed to have uncontrolled surface oxidation as the primary source of the two-level system loss in two-dimensional transmon qubits. Therefore, atomic-scale insight into the surface oxidation process is needed to make progress toward a practical quantum processor. Here, in this study, the surface oxidation mechanism of native Ta films and its potential impact on the lifetime of superconducting qubits were investigated using advanced scanning transmission electron microscopy (STEM) techniques combined with density functional theory calculations. The results suggest an atomistic model of the oxidized Ta(110) surface, showing that oxygen atoms tend to penetrate the Ta surface and accumulate between the two outermost Ta atomic planes; oxygen accumulation at the level exceeding a 1:1 O/Ta ratio drives disordering and, eventually, the formation of an amorphous Ta 2 O 5 phase. In addition, we discuss how the formation of a noninsulating ordered TaO 1–δ (δ < 0.1) suboxide layer could further contribute to the losses of superconducting qubits. Subsurface oxidation leads to charge redistribution and electric polarization, potentially causing quasiparticle loss and decreased current-carrying capacity, thus affecting superconducting qubit coherence. The findings enhance the comprehension of the realistic factors that might influence the performance of superconducting qubits, thus providing valuable guidance for the development of future quantum computing hardware.

36 MATERIALS SCIENCE↗