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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Predicting Partial Atomic Charges in Metal–Organic Frameworks: An Extension to Ionic MOFs

Molecular simulation is an invaluable tool to predict and understand the usage of metal–organic frameworks (MOFs) for gas storage and separation applications. Accurate partial atomic charges, commonly obtained from density functional theory (DFT) calculations, are often required to model the electrostatic interactions between the MOF and adsorbates, especially when the adsorbates have dipole or quadrupole moments, such as water and CO 2 . Machine learning (ML) models have been previously employed to predict partial charges and avoid the computational cost associated with DFT calculations. However, previous ML models suffer from small training data sets, which limit their scope of application. In this work, we introduce two novel machine learning models, PACMOF2-neutral and PACMOF2-ionic, aimed at predicting the density-derived electrostatic and chemical (DDEC6) partial atomic charges for both neutral and ionic MOFs. These models not only yield DFT-level accuracy at a fraction of the computational cost but also demonstrate a remarkable improvement in prediction of adsorption, as validated with grand canonical Monte Carlo simulations. Furthermore, the robustness and fast computational time of the PACMOF2 models, along with their transferability to other porous materials such as covalent organic frameworks and zeolites, underscores their potential in high-throughput screening of MOFs for diverse applications.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Localized Orbital Excitation Drives Bond Formation in Plasmonic Catalysis

Localized surface plasmons generated on metallic nanostructures can be used to accelerate molecular transformations; however, the efficiency is limited by the challenge to control the energy/charge transfer at the interfaces. Here, we combine density functional theory (DFT) calculations and experiments to reveal the mechanism of nitrophenol reduction on Au nanoparticles under visible-light irradiation and propose a strategy to further enhance the reaction rates. DFT calculations show a reduced activation barrier under electronic excitation on Au(111), thus explaining the measured higher rates under visible-light irradiation. Furthermore, we propose a heterostructure with Au nanoparticles covered by a thin film of hexagonal boron nitride; the latter is used to decouple the molecular orbitals from the metal to enable charge localization in the molecule. DFT calculations show that, by this electronic decoupling, the activation barrier can be lowered by a factor of five. Furthermore, this work thus provides a valuable strategy for optimizing catalytic efficiency.

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

Molecular Recognition at Mineral Interfaces: Implications for the Beneficiation of Rare Earth Ores

Ce-bastnäsite is the single largest mineral source for light rare-earth elements. In view of the growing industrial importance of rare-earth minerals, it is critical to develop more efficient methods for separating the valuable rare-earth-containing minerals from the surrounding gangue. In this work, we employ a combination of periodic density functional theory (DFT) and molecular mechanics (MM) calculations together with the de novo molecular design program HostDesigner to identify bis-phosphinate ligands that preferentially bind to the (100) Ce-bastnäsite surface rather than the (104) calcite surface. DFT calculations for a simple phosphinate ligand were employed to qualitatively understand key behaviors involved in ligand–metal, ligand–solvent, and solvent–metal interactions. These insights were then used to guide the search for flexible, rigid, and semirigid hydrocarbon linkers to identify candidate bis-phosphinate ligands with the potential to bind preferentially to Ce-bastnäsite. Among the five most promising bis-phosphinate ligands suggested by theoretical studies, three ligands were synthesized and their adsorption characteristics to bastnäsite (100) interfaces were characterized using vibrational sum-frequency (vSFG) spectroscopy, attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy, and isothermal titration calorimetry (ITC). The efficacy of the selective interfacial molecular binding was demonstrated by identifying a bis-phosphinate ligand capable of providing an overall higher surface coverage of alkyl groups relative to a monophosphinate ligand. The results highlight the interplay between adsorption binding strength and maximum surface coverage in determining ligand efficiency to render the mineral surface hydrophobic. DFT calculations further indicate that all tested ligands have higher affinity for Ce-bastnäsite than for calcite. Finally, this is consistent with the ITC data showing stronger adsorption enthalpy to bastnäsite than to calcite, making these ligands promising candidates for selective flotation of Ce-bastnäsite.

58 GEOSCIENCES↗
DOE OSTI2020

Ni Nanoparticles on CeO 2 (111): Energetics, Electron Transfer, and Structure by Ni Adsorption Calorimetry, Spectroscopies, and Density Functional Theory

The morphology, interfacial bonding energetics and charge transfer of Ni clusters and nanoparticles on slightly-reduced CeO 2-x (111) surfaces at 100 to 300 K have been studied using single crystal adsorption calorimetry (SCAC), low-energy ion scattering spectroscopy (LEIS), Xray photoelectron spectroscopy (XPS), low energy electron diffraction (LEED) and density functional theory (DFT). The initial heat of adsorption of Ni vapor decreased with the extent of pre-reduction (x) of the CeO 2-x (111), showing that stoichiometric ceria adsorbs Ni more strongly than oxygen vacancies. On CeO 1.95 (111) at 300 K, the heat dropped quickly with coverage in the first 0.1 ML, attributed to nucleation of Ni clusters on stoichiometric steps, followed by the Ni particles spreading onto less favorable terrace sites. At 100 K, the clusters nucleate on terraces due to slower diffusion. Adsorbed Ni monomers are in the +2 oxidation state, and they bind by ~45 kJ/mol more strongly to step sites than terraces. The measured heat of adsorption versus average particle size on terraces is favorably compared to DFT calculations. The Ce 3d XPS lineshape showed an increase in Ce 3+ /Ce 4+ ratio with Ni coverage, providing the number of electrons donated to the ceria per Ni atom. The charge transferred per Ni is initially large but strongly decreases with increasing cluster size for both experiments and DFT, and shows large differences between clusters at steps versus terraces. This charge is localized on the interfacial Ni and Ce atoms in their atomic layers closest to the interface. This knowledge is crucial to understanding the nature of the active sites on the surface of Ni-CeO 2 catalysts for which metal-oxide interactions play a very important role in the activation of O-H and C-H bonds. In conclusion, the changes in these interactions with Ni particle size (metal loading) and the extent of reduction of the ceria help to explain how previously reported catalytic activity and selectivity change with these same structural details.

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

Quantum Monte Carlo Approaches to Na Intercalation on Bilayer Graphene

We have performed Quantum Monte Carlo (QMC) simulations on Na-intercalated bilayer graphene to study the evolution of electronic and optical properties upon Na intercalation into hard carbon layers. The objective was to model the optimal configuration of Na intercalation into a hard carbon matrix containing graphene regions. Our study showed that Na intercalation can be energetically stabilized at large interlayer distances (over 6 Å) in both AA- and AB-stacked bilayer graphene. In the QMC results, we found a significant band gap opening at the equilibrium interlayer distance of Na-intercalated bilayer graphene, while corresponding density functional theory (DFT) results showed no gap. This difference between DFT and QMC results indicates that the gap opening induced by Na intercalation into a hard carbon is underestimated within the DFT framework. In addition, a zigzag configuration of Na atoms was found to be energetically stable at interlayer distances up to 10 Å, leading us to predict the existence of a local minimum of Na intercalation at large interlayer distance. These computation and modeling results can provide guidance on how to synthesize and optimize hard carbon with bilayer graphene regions that permit a zigzag intercalation configuration that will maximize and stabilize sodium hosting.

Binding energy↗
DOE OSTI2022

How the Bioinspired Fe 2 Mo 6 S 8 Chevrel Breaks Electrocatalytic Nitrogen Reduction Scaling Relations

The nitrogen reduction reaction (NRR) is a renewable alternative to the energy- and CO 2 -intensive Haber–Bosch NH 3 synthesis process but is severely limited by the low activity and selectivity of studied electrocatalysts. The Chevrel phase Fe 2 Mo 6 S 8 has a surface Fe–S–Mo coordination environment that mimics the nitrogenase FeMo-cofactor and was recently shown to provide state-of-the-art activity and selectivity for NRR. Here, we elucidate the previously unknown NRR mechanism on Fe 2 Mo 6 S 8 via grand-canonical density functional theory (GC-DFT) that realistically models solvated and biased surfaces. Fe sites of Fe 2 Mo 6 S 8 selectively stabilize the key *NNH intermediate via a narrow band of free-atom-like surface d-states that selectively hybridize with p-states of *NNH, which results in Fe sites breaking NRR scaling relationships. These sharp d-states arise from an Fe–S bond dissociation during N 2 adsorption that mimics the mechanism of the nitrogenase FeMo-cofactor. Furthermore, we developed a new GC-DFT-based approach for calculating transition states as a function of bias (GC-NEB) and applied it to produce a microkinetic model for NRR at Fe 2 Mo 6 S 8 that predicts high activity and selectivity, in close agreement with experiments. Furthermore, our results suggest new design principles that may identify effective NRR electrocatalysts that minimize the barriers for *N 2 protonation and *NH 3 desorption and that may be broadly applied to the rational discovery of stable, multinary electrocatalysts for other reactions where narrow bands of surface d-states can be tuned to selectively stabilize key reaction intermediates and guide selectivity toward a target product. Furthermore, our results highlight the importance of using GC-DFT and GC-NEB to accurately model electrocatalytic reactions.

10 SYNTHETIC FUELS↗
DOE OSTI2022

Ru-promoted perovskites as effective redox catalysts for CO2 splitting and methane partial oxidation in a cyclic redox scheme

The current study reports AxA’1-xByB’1-yO3- perovskite redox catalysts (RCs) for CO2-splitting and methane partial oxidation (POx) in a cyclic redox scheme. Strontium (Sr) and iron (Fe) were chosen as A and B site elements with A’ being lanthanum (La), samarium (Sm) or yttrium (Y), and B’ being manganese (Mn), or titanium (Ti) to tailor their equilibrium oxygen partial pressures (P_(O_2 ) s) for CO2-splitting and methane partial oxidation. DFT calculations were performed for predictive optimization of the oxide materials whereas experimental investigation confirmed the DFT predicted redox performance. The redox kinetics of the RCs improved significantly by 1 wt.% ruthenium (Ru) impregnation without affecting their redox thermodynamics. Ru impregnated LaFe0.375Mn0.625O3 (A=0, A’=La, B=Mn, and B’=0) was the most promising RC in terms of its superior redox performance (CH4/CO2 conversion >90% and CO selectivity~ 95%) at 800oC. Long-term redox testing over Ru impregnated LaFe0.375Mn0.625O3 indicated stable performance during the first 30 cycles following with a ~25% decrease in the activity during the last 70 cycles. Air treatment was effective to reactivate the redox catalyst. Detailed characterizations revealed the underlying mechanism for redox catalyst deactivation and reactivation. Furthermore, this study not only validated a DFT guided mixed oxide design strategy for CO2 utilization but also provides potentially effective approaches to enhance redox kinetics as well as long-term redox catalyst performance.

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

Revealing symmetry-broken superconducting configurations by density functional theory

A coherent theory for the superconductivity of both conventional and unconventional superconductors is currently lacking. Here we show that superconductivity arises from the formation of a symmetry-broken superconducting configuration (SCC) due to atomic perturbation of the normal conducting configuration (NCC). This electron–phonon interaction creates straight one-dimensional tunnels (SODTs) for charge density of electrons and/or holes as revealed by the calculations based on density functional theory (DFT). The SODTs act as resistance-free superhighways and are correlated to the Cooper pairs in the Bardeen–Cooper–Schrieffer (BCS) theory. The formation of SODTs implies that the electron–phonon interaction in the BCS theory can be represented by the difference in charge densities between SCC and NCC predicted by DFT. The present work highlights that in conventional superconductors, SODTs are embedded within the bulk materials and are easily destroyed by phonon vibrations, resulting in a low critical superconducting temperature (T C ). Conversely, in unconventional superconductors such as YBa 2 Cu 3 O 7 (YBCO 7 ), SODTs are protected by a layered pontoon structure with very weak bonding to the bulk materials, maintaining SODTs’ stability at higher temperatures and leading to a much higher T C . The present approach is validated for 14 conventional superconductors of 18 pure elements and MgB 2 examined in this work, including the presently predicted superconductivity in Cu, Ag, Au, Sb, Bi, and MgB 2 at 0 K and 0 GPa, and one unconventional superconductor of YBCO 7 . Our discovery indicates that DFT can be a practical tool for predicting superconductors, enabling a systematic search for new superconducting materials in the future.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Reflections on one million compounds in the open quantum materials database (OQMD)

Abstract Density functional theory (DFT) has been widely applied in modern materials discovery and many materials databases, including the open quantum materials database (OQMD), contain large collections of calculated DFT properties of experimentally known crystal structures and hypothetical predicted compounds. Since the beginning of the OQMD in late 2010, over one million compounds have now been calculated and stored in the database, which is constantly used by worldwide researchers in advancing materials studies. The growth of the OQMD depends on project-based high-throughput DFT calculations, including structure-based projects, property-based projects, and most recently, machine-learning-based projects. Another major goal of the OQMD is to ensure the openness of its materials data to the public and the OQMD developers are constantly working with other materials databases to reach a universal querying protocol in support of the FAIR data principles.

08 HYDROGEN↗
DOE OSTI2022

FINETUNA: fine-tuning accelerated molecular simulations

Abstract Progress towards the energy breakthroughs needed to combat climate change can be significantly accelerated through the efficient simulation of atomistic systems. However, simulation techniques based on first principles, such as density functional theory (DFT), are limited in their practical use due to their high computational expense. Machine learning approaches have the potential to approximate DFT in a computationally efficient manner, which could dramatically increase the impact of computational simulations on real-world problems. However, they are limited by their accuracy and the cost of generating labeled data. Here, we present an online active learning framework for accelerating the simulation of atomic systems efficiently and accurately by incorporating prior physical information learned by large-scale pre-trained graph neural network models from the Open Catalyst Project. Accelerating these simulations enables useful data to be generated more cheaply, allowing better models to be trained and more atomistic systems to be screened. We also present a method of comparing local optimization techniques on the basis of both their speed and accuracy. Experiments on 30 benchmark adsorbate-catalyst systems show that our method of transfer learning to incorporate prior information from pre-trained models accelerates simulations by reducing the number of DFT calculations by 91%, while meeting an accuracy threshold of 0.02 eV 93% of the time. Finally, we demonstrate a technique for leveraging the interactive functionality built in to Vienna ab initio Simulation Package (VASP) to efficiently compute single point calculations within our online active learning framework without the significant startup costs. This allows VASP to work in tandem with our framework while requiring 75% fewer self-consistent cycles than conventional single point calculations. The online active learning implementation, and examples using the VASP interactive code, are available in the open source FINETUNA package on Github.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Changes in polarization dictate necessary approximations for modeling electronic deexcitation intensity: Application to x-ray emission

Accurate simulation of electronic excitations and deexcitations are critical for complementing complex spectroscopic experiments and can provide validation to theoretical approaches. Here, using a generalized framework, we contrast the accuracy and validity of orbital-constrained and linear-response approaches that build upon Kohn-Sham density functional theory (DFT) to simulate emission spectra of electronic origin and propose an efficient approximation, named many-body x-ray emission spectroscopy or MBXES, for simulating such processes. We show analytically as well as with computed examples that for electronic (de)excitation leading to an appreciable change in polarization (i.e., density rearrangement), the adiabatic approximation in a response-based formalism will be inadequate for the calculation of oscillator strength. Thus, such a change (e.g., in the net electrostatic dipole moment of a finite system) can be used as a metric for evaluating the applicability of the adiabatic response-based approach and can be particularly valuable in x-ray emission spectroscopy. On the other hand, MBXES, the flexible method introduced in this paper, can compute oscillator strengths accurately at a much lower computational expense on the basis of two DFT-based self-consistent field calculations. Using illustrative examples of emission spectra, the efficacy of the MBXES method is demonstrated by comparison with its parent theory, orbital-optimized DFT, and with experiments.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2022

Capturing the ground state of uranium dioxide from first principles: Crystal distortion, magnetic structure, and phonons

Uranium dioxide (UO 2 ) remains a formidable challenge for first-principles approaches due to the complex interplay among spin-orbit coupling, Mott physics, magnetic ordering, and crystal distortions. Here we use DFT+U to explore UO 2 at zero temperature, incorporating all the aforementioned phenomena. The technical challenge is to navigate the many metastable electronic states produced by DFT+U, which is accomplished using f-orbital occupation matrix control to search for the ground state. We restrict our search to the high-symmetry ferromagnetic phase, including spin-orbit coupling, which produces a previously unreported occupation matrix. This newfound occupation matrix is then used as an initialization to explore the broken symmetry phases. We find the oxygen cage distortion of the 3k antiferromagnetic state to be in excellent agreement with experiments, and both the spin-orbit coupling and the Hubbard U are critical ingredients. Further, we demonstrate that only select phonon modes have a strong dependence on the Hubbard U, whereas magnetic ordering has only a small influence overall. We perform measurements of the phonon dispersion curves using inelastic neutron scattering, and our calculations show good agreement when using reasonable values of U. The quantitative success of DFT+U warrants exploration of thermal transport and other observables within this level of theory.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Electron and Electron-Nuclear Dynamics of Open Quantum Subsystems

Leveraging an open-subsystem formulation of Density Functional Theory (DFT) we aim at describing periodic and molecular systems alike, including their electronic and nuclear dynamics. Subsystem DFT enables first principles simulations to approach realistic time- and length-scales, and most importantly sheds light on the dynamical behavior of complex systems. Taking subsystem DFT to the time domain allows us to inspect the electron dynamics of condensed-phase systems in real time. In liquids and interfaces, we observe all the relevant regimes proper of non-Markovian open quantum system dynamics, such as electronic energy transfer, and screening. In addition, the ab-initio modeling of system-bath interactions brought us to observe and justify the holographic time-dependent electron density theorem. Contrary to interactions between molecular (finite) systems, when molecules interact with metal or semiconductor surfaces the electron dynamics is strongly non-Markovian with dramatic repercussions to the molecule’s response to external perturbations. Metals and semiconductors typically have large polarizabilities, and even in a regime of low coupling their effect on impinging molecular species is significant–line broadening, peak shift, and intensity borrowing are observed, characterized, and explained in terms of inter-subsystem dynamical interactions and a many-body decomposition of the system’s density-density response function in a way that transcends the canons of Fermi Golden Rule.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Radiation-Induced Oxidation Reactions of 2-Selenouracil in Aqueous Solutions: Comparison with Sulfur Analog of Uracil

One-electron oxidation of 2-selenouracil (2-SeU) by hydroxyl (●OH) and azide (●N3) radicals leads to various primary reactive intermediates. Their optical absorption spectra and kinetic characteristics were studied by pulse radiolysis with UV-vis spectrophotometric and conductivity detection and by the density functional theory (DFT) method. The transient absorption spectra recorded in the reactions of ●OH with 2-SeU are dominated by an absorption band with an λmax = 440 nm, the intensity of which depends on the concentration of 2-SeU and pH. Based on the combination of conductometric and DFT studies, the transient absorption band observed both at low and high concentrations of 2-SeU was assigned to the dimeric 2c-3e Se-Se-bonded radical in neutral form (2●). The dimeric radical (2●) is formed in the reaction of a selenyl-type radical (6●) with 2-SeU, and both radicals are in equilibrium with Keq = 1.3 × 104 M−1 at pH 4 (below the pKa of 2-SeU). Similar equilibrium with Keq = 4.4 × 103 M−1 was determined for pH 10 (above the pKa of 2-SeU), which admittedly involves the same radical (6●) but with a dimeric 2c-3e Se-Se bonded radical in anionic form (2●−). In turn, at the lowest concentration of 2-SeU (0.05 mM) and pH 10, the transient absorption spectrum is dominated by an absorption band with an λmax = 390 nm, which was assigned to the ●OH adduct to the double bond at C5 carbon atom (3●) based on DFT calculations. Similar spectral and kinetic features were also observed during the ●N3-induced oxidation of 2-SeU. In principle, our results mostly revealed similarities in one-electron oxidation pathways of 2-SeU and 2-thiouracil (2-TU). The major difference concerns the stability of dimeric radicals with a 2c-3e chalcogen-chalcogen bond in favor of 2-SeU.

2-selenouracil↗
DOE OSTI2024

Discovery of Stable Surfaces with Extreme Work Functions by High‐Throughput Density Functional Theory and Machine Learning

Abstract The work function is the key surface property that determines the energy required to extract an electron from the surface of a material. This property is crucial for thermionic energy conversion, band alignment in heterostructures, and electron emission devices. This work presents a high‐throughput workflow using density functional theory (DFT) to calculate the work function and cleavage energy of 33,631 slabs (58,332 work functions) that are created from 3,716 bulk materials. The number of calculated surface properties surpasses the previously largest database by a factor of ≈27. Several surfaces with an ultra‐low (<2 eV) and ultra‐high (>7 eV) work function are identified. Specifically, the (100)‐Ba‐O surface of BaMoO 3 and the (001)‐F surface of Ag 2 F have record‐low (1.25 eV) and record‐high (9.06 eV) steady‐state work functions. Based on this database a physics‐based approach to featurize surfaces is utilized to predict the work function. The random forest model achieves a test mean absolute error (MAE) of 0.09 eV, comparable to the accuracy of DFT. This surrogate model enables rapid predictions of the work function (≈ 10 5 faster than DFT) across a vast chemical space and facilitates the discovery of material surfaces with extreme work functions for energy conversion and electronic device applications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Accelerated Modeling of Lithium Diffusion in Solid State Electrolytes using Artificial Neural Networks

Abstract Previous efforts to understand structure‐function relationships in high ionic conductivity materials for solid state batteries have predominantly relied on density functional theory (DFT‐) based ab initio molecular dynamics (MD). Such simulations, however, are computationally demanding and cannot be reasonably applied to large systems containing more than a hundred atoms. Here, an artificial neural network (ANN) is trained to accelerate the calculation of high accuracy atomic forces and energies used during such MD simulations. After carefully training a robust ANN for four and five element systems, nearly identical lithium ion diffusivities are obtained for Li 10 GeP 2 S 12 (LGPS) when benchmarking the ANN‐MD results with DFT‐MD. Applying the ANN‐MD approach, the effect of chlorine doping on the lithium diffusivity is calculated in an LGPS‐like structure and it is found that a dopant concentration of 1.3% maximizes ionic conductivity. The optimal concentration balances the competing consequences of effective atomic radii and dielectric constants on lithium diffusion and agrees with the experimental composition. Performing simulations at the resolution necessary to model experimentally relevant and optimal concentrations would be infeasible with traditional DFT‐MD. Systems that require a large number of simulated atoms can be studied more efficiently while maintaining high accuracy with the proposed ANN‐MD framework.

Rao, Karun K.↗
DOE OSTI2023

Ultrafast Jahn‐Teller Photoswitching in Cobalt Single‐Ion Magnets

Abstract Single‐ion magnets (SIMs) constitute the ultimate size limit in the quest for miniaturizing magnetic materials. Several bottlenecks currently hindering breakthroughs in quantum information and communication technologies could be alleviated by new generations of SIMs displaying multifunctionality. Here, ultrafast optical absorption spectroscopy and X‐ray emission spectroscopy are employed to track the photoinduced spin‐state switching of the prototypical complex [Co(terpy) 2 ] 2+ (terpy = 2,2′:6′,2″‐terpyridine) in solution phase. The combined measurements and their analysis supported by density functional theory (DFT), time‐dependent‐DFT (TD‐DFT) and multireference quantum chemistry calculations reveal that the complex undergoes a spin‐state transition from a tetragonally elongated doublet state to a tetragonally compressed quartet state on the femtosecond timescale, i.e., it sustains ultrafast Jahn‐Teller (JT) photoswitching between two different spin multiplicities. Adding new Co‐based complexes as possible contenders in the search for JT photoswitching SIMs will greatly widen the possibilities for implementing magnetic multifunctionality and eventually controlling ultrafast magnetization with optical photons.

36 MATERIALS SCIENCE↗