Search NASA⌕ Search

SEARCH · Search NASA

Results for “functional theory”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Towards the ionizing radiation induced bond dissociation mechanism in oxygen, water, guanine and DNA fragmentation: a density functional theory simulation

The radiation-induced damages in bio-molecules are ubiquitous processes in radiotherapy and radio-biology, and critical to space projects. In this study, we present a precise quantification of the fragmentation mechanisms of deoxyribonucleic acid (DNA) and the molecules surrounding DNA such as oxygen and water under non-equilibrium conditions using the first-principle calculations based on density functional theory (DFT). Our results reveal the structural stability of DNA bases and backbone that withstand up to a combined threshold of charge and hydrogen abstraction owing to simultaneously direct and indirect ionization processes. We show the hydrogen contents of the molecules significantly control the stability in the presence of radiation. This study provides comprehensive information on the impact of the direct and indirect induced bond dissociations and DNA damage and introduces a systematic methodology for fine-tuning the input parameters necessary for the large-scale Monte Carlo simulations of radio-biological responses and mitigation of detrimental effects of ionizing radiation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Coarse-Grained Density Functional Theory Predictions via Deep Kernel Learning

Scalable electronic predictions are critical for soft materials design. Recently, the Electronic Coarse-Graining (ECG) method was introduced to renormalize all-atom quantum chemical (QC) predictions to coarse-grained (CG) resolutions using deep neural networks (DNNs). While DNNs can learn complex representations that prove challenging for kernel-based methods, they are susceptible to overfitting and the overconfidence of uncertainty estimations. Here, we develop ECG within a GPU-accelerated Deep Kernel Learning (DKL) framework to enable CG QC predictions using range-separated hybrid density functional theory (DFT), obtaining a 107 speedup relative to naive all-atom QC. By treating the predicted electronic properties as random Gaussian Processes, DKL incorporates CG mapping degeneracy by learning the distribution of electronic energies as a function of CG configuration. DKL-ECG accurately reproduces molecular orbital energies from range-separated DFT while facilitating efficient training via active learning using the uncertainties provided by DKL. Further, we show that while active learning algorithms enable efficient sampling of a more diverse configurational space relative to random sampling, all explored query methods exhibit comparable performance for the examined system. We attribute this result to the significant overlap of the feature space and output property distributions across multiple temperatures.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Integrating density functional theory into reductive dechlorination research

Abstract Chlorinated organics have been frequently detected in groundwaters, threatening the quality of drinking water supplies worldwide. A promising method for groundwater remediation involves reductive dechlorination (RD), in which chlorine atoms are sequentially removed and substituted by hydrogen, producing less harmful byproducts. In this paper, for the first time, RD research is reviewed in light of the growing incorporation of density functional theory (DFT) as a research tool. DFT has been used to uncover a variety of reaction properties for a range of relevant groundwater pollutants, including 1,2,3‐trichloropropane, hexachlorobenzene, and various dioxins. DFT models have revealed the role of surface interactions in driving the kinetics of catalytically driven RD. Mechanisms involved with biologically mediated RD have also been elucidated with insights gleaned from DFT. Issues and challenges for future research are also discussed.

Das Schober, Jaya↗
DOE OSTI2024

Hyperfine interactions for small systems including transition-metal elements using self-interaction corrected density-functional theory

The interactions between the electronic magnetic moment and the nuclear spin moment, i.e., magnetic hyperfine (HF) interactions, play an important role in understanding electronic properties of magnetic systems and in realizing platforms for quantum information science applications. We investigate the HF interactions for atomic systems and small molecules, including Ti or Mn, by using Fermi–Löwdin orbital (FLO) based self-interaction corrected (SIC) density-functional theory. We calculate the Fermi contact (FC) and spin-dipole terms for the systems within the local density approximation (LDA) in the FLO-SIC method and compare them with the corresponding values without SIC within the LDA and generalized-gradient approximation (GGA), as well as experimental data. For the moderately heavy atomic systems (atomic number Z ≤ 25), we find that the mean absolute error of the FLO-SIC FC term is about 27 MHz (percentage error is 6.4%), while that of the LDA and GGA results is almost double that. Therefore, in this case, the FLO-SIC results are in better agreement with the experimental data. For the non-transition-metal molecules, the FLO-SIC FC term has the mean absolute error of 68 MHz, which is comparable to both the LDA and GGA results without SIC. For the seven transition-metal-based molecules, the FLO-SIC mean absolute error is 59 MHz, whereas the corresponding LDA and GGA errors are 101 and 82 MHz, respectively. Therefore, for the transition-metal-based molecules, the FLO-SIC FC term agrees better with experiment than the LDA and GGA results. We observe that the FC term from the FLO-SIC calculation is not necessarily larger than that from the LDA or GGA for all the considered systems due to the core spin polarization, in contrast to the expectation that SIC would increase the spin density near atomic nuclei, leading to larger FC terms.

Chemistry↗
DOE OSTI2023

Time-dependent density-functional-theory calculations of the nonlocal electron stopping range for inertial confinement fusion applications

Nonlocal electron transport is important for understanding laser-target coupling for laser-direct-drive (LDD) inertial confinement fusion (ICF) simulations. Current models for the nonlocal electron mean free path in radiation-hydrodynamic codes are based on plasma-physics models developed decades ago; improvements are needed to accurately predict the electron conduction in LDD simulations of ICF target implosions. Here we utilized time-dependent density functional theory (TD-DFT) to calculate the electron stopping power (SP) in the so-called conduction-zone plasmas of polystyrene in a wide range of densities and temperatures relevant to LDD. Compared with the modified Lee-More model, the TD-DFT calculations indicated a lower SP and a higher stopping range for nonlocal electrons. We fit these electron SP calculations to obtain a global analytical model for the electron stopping range as a function of plasma conditions and the nonlocal electron kinetic energy. This model was implemented in the one-dimensional radiation-hydrodynamic code LILAC to perform simulations of LDD ICF implosions, which are further compared with simulations by the standard modified Lee-More model. In conclusion, results from these integrated simulations are discussed in terms of the implications of this TD-DFT-based mean-free-path model to ICF simulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Antimony stable isotope fractionation during adsorption onto birnessite: A molecular perspective from X-ray absorption spectroscopy and density functional theory

Sorption of antimony (Sb) onto birnessite significantly influences the fate of Sb in oceanic and terrestrial environments and fractionates Sb isotopes. Nevertheless, little is known about Sb isotopic fractionation during its adsorption on birnessite. Here, in this study, we show the value of Δ 123 Sb adsorbed-aqueous increases from −0.398 to −0.332 ‰ in 1 h and then decreases and stabilizes at −0.384 ‰ in 72 h. The enrichment of the light Sb isotope is predominantly due to the distortion of the octahedral symmetry. X-ray absorption spectroscopy results indicate Sb first forms a double-corner-sharing complex on birnessite and then transforms to a double-edge-sharing complex during adsorption. The optimized bond distances for double-corner-sharing (3.37 Å) and double-edge-sharing (2.90 Å) complexes calculated using density functional theory (DFT) fits well with the structure (3.41 and 3.00 Å) revealed by X-ray absorption spectroscopy, respectively. The fractionation derived from reduced partition function ratios calculated using DFT aligns well with the experimental results. Therefore, the variation in Sb isotopic fractionation during adsorption is attributed to the evolving structure of Sb complexes on birnessite. Our results demonstrate the isotopic fractionation of Sb during adsorption on birnessite and provide a molecular-scale understanding of Sb behavior, contributing to the correct reconstruction of the Sb isotope composition of ancient seawater using ferromanganese crusts and nodules, and efforts to trace Sb migration in epigenetic mining environments.

Adsorption↗
DOE OSTI2021

Density Functional Theory Investigation of the NiO@Graphene Composite as a Urea Oxidation Catalyst in the Alkaline Electrolyte

Developing efficient and low-cost urea oxidation reaction (UOR) catalysts is a promising but still challenging task for environment and energy conversion technologies such as wastewater remediation and urea electrolysis. In this work, NiO nanoparticles that incorporated graphene as the NiO@Graphene composite were constructed to study the UOR process in terms of density functional theory. The single-atom model, which differed from the previous heterojunction model, was employed for the adsorption/desorption of urea and CO 2 in the alkaline media. As demonstrated from the calculated results, NiO@Graphene prefers to adsorb the hydroxyl group than urea in the initial stage due to the stronger adsorption energy of the hydroxyl group. After NiOOH@Graphene was formed in the alkaline electrolyte, it presents excellent desorption energy of CO 2 in the rate-determining step. Electronic density difference and the d band center diagram further confirmed that the Ni(III) species is the most favorable site for urea oxidation while facilitating charge transfer between urea and NiO@Graphene. Moreover, graphene provides a large surface for the incorporation of NiO nanoparticles, enhancing the electron transfer between NiOOH and graphene and promoting the mass transport in the alkaline electrolyte. Notably, this work provides theoretical guidance for the electrochemical urea oxidation work.

25 ENERGY STORAGE↗
DOE OSTI2020

Re-examining the silicon self-interstitial charge states and defect levels: A density functional theory and bounds analysis study

The self-interstitial atom (SIA) is one of two fundamental point defects in bulk Si. Isolated Si SIAs are extremely difficult to observe experimentally. Even at very low temperatures, they anneal before typical experiments can be performed. Given the challenges associated with experimental characterization, accurate theoretical calculations provide valuable information necessary to elucidate the properties of these defects. Previous studies have applied Kohn–Sham density functional theory (DFT) to the Si SIA, using either the local density approximation or the generalized gradient approximation to the exchange-correlation (XC) energy. The consensus of these studies indicates that a Si SIA may exist in five charge states ranging from -2 to +2 with the defect structure being dependent on the charge state. This study aims to re-examine the existence of these charge states in light of recently derived “approximate bounds” on the defect levels obtained from finite-size supercell calculations and new DFT calculations using both semi-local and hybrid XC approximations. We conclude that only the neutral and +2 charge states are directly supported by DFT as localized charge states of the Si SIA. Within the current accuracy of DFT, our results indicate that the +1 charge state likely consists of an electron in a conduction-band-like state that is coulombically bound to a +2 SIA. Furthermore, the -1 and -2 charge states likely consist of a neutral SIA with one and two additional electrons in the conduction band, respectively.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Development of an ab initio learned model of electron deposition range in deuterium-tritium plasmas through time-dependent density functional theory calculations and machine learning

Accurate hydrodynamic modeling for laser-direct-drive (LDD) inertial-confinement-fusion (ICF) relies on precise calculations of the electron thermal conduction in all target materials. The nonlocal stopping range of electrons in ICF plasmas directly influences thermal conduction; yet, no first principles model exists for the electron mean free path in the conduction-zone regime. This work utilized time-dependent stochastic density-functional theory (TD-sDFT) to calculate the electron stopping power in deuterium-tritium (DT) plasmas at (ρ, T) conditions relevant to the conduction zone and the compressed shell in ICF. Using a combination of our TD-sDFT data and already established analytical models, we developed and trained an artificial neural network to create a global model for the nonlocal electron deposition range, λ E . We compared our machine-learning (ML) based model for λ E to the currently-used modified-Lee-More model in LDD radiation-hydrodynamic codes, such as lilac, and saw an overall decrease in the deposition range. To understand the effects of λ E on LDD ICF implosion dynamics, we implemented the ML-based model into lilac; specifically, we looked at designs consistent with a current experiment on the OMEGA laser and for a newly designed LDD-ICF target for the future OMEGA-Next facility. In both cases, we saw an overall drop in predicted ablation pressure, peak areal density, and neutron yield due to the reduced thermal conduction (smaller λ E ) in DT plasmas. Comparisons with the experiment on OMEGA are also made.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Structure of chalcogen overlayers on Au(111): Density functional theory and lattice-gas modeling

Ordering of different chalcogens, S, Se, and Te, on Au(111) exhibit broad similarities but also some distinct features, which must reflect subtle differences in relative values of the long-range pair and many-body lateral interactions between adatoms. We develop lattice-gas (LG) models within a cluster expansion framework, which includes about 50 interaction parameters. These LG models are developed based on density functional theory (DFT) analysis of the energetics of key adlayer configurations in combination with the Monte Carlo (MC) simulation of the LG models to identify statistically relevant adlayer motifs, i.e., model development is based entirely on theoretical considerations. The MC simulation guides additional DFT analysis and iterative model refinement. Given their complexity, development of optimal models is also aided by strategies from supervised machine learning. The model for S successfully captures ordering motifs over a broader range of coverage than achieved by previous models, and models for Se and Te capture the features of ordering, which are distinct from those for S. More specifically, the modeling for all three chalcogens successfully explains the linear adatom rows (also subtle differences between them) observed at low coverages of ~0.1 monolayer. The model for S also leads to a new possible explanation for the experimentally observed phase with a (5 × 5)-type low energy electron diffraction (LEED) pattern at 0.28 ML and to predictions for LEED patterns that would be observed with Se and Te at this coverage.

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

Density Functional Theory Guided Investigation of Ligand‐Induced Neptunyl‐Neptunyl Interactions

Abstract Actinyl‐actinyl interactions are particularly prevalent for the pentavalent neptunyl cation (Np(V)O 2 ) + where these interactions appear either as a T ‐ or D ‐shape (diamond‐shape). T ‐shaped interactions have been previously identified in high concentration Np(V) solutions containing simple anions (NO 3 − , ClO 4 − , Cl − ) whereas D ‐shaped have only been isolated in the solid‐state in the presence of carboxylate ligands. In this study, Density Functional Theory (DFT) calculations were paired with Raman spectroscopy to evaluate the formation of D ‐shaped interactions in the presence of aliphatic (R=H (formate), CH 3 (acetate), CH 2 CH 3 (propionate)) and aromatic (R=C 6 H 5 (benzoate), C 6 H 4 OH (4‐hydroxybenzoate), C 5 H 4 N (isonicotinate)) carboxylate ligands. DFT studies indicate that the Δ G to form hydrated T ‐ and D ‐shaped forms are not spontaneous but become so with the addition of the carboxylate ligands. Raman spectra of the Np(V) carboxylate solutions contained vibrational modes associated with the D ‐shaped interactions, but spectral changes observed over time indicate a dynamic system. Crystallization experiments from the Np(V) carboxylate systems confirmed the presence of D‐ shaped dimers for the aromatic carboxylates, suggesting that the choice of the anion in solution favors actinyl‐actinyl interactions even at low concentrations (≤20 mM) of Np(V).

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

Broken-Symmetry Density Functional Theory Analysis of the Ω Intermediate in Radical S -Adenosyl- l -methionine Enzymes: Evidence for a Near-Attack Conformer over an Organometallic Species

Radical S-adenosyl-L-methionine (SAM) enzymes are found in all domains of life and catalyze a wide range of biochemical reactions. Recently, an organometallic intermediate, Ω, has been experimentally implicated in the 5'-deoxyadenosyl radical generation mechanism of the radical SAM superfamily. In this work, we employ broken-symmetry density functional theory to evaluate several structural models of Ω. The results show that the calculated hyperfine coupling constants (HFCCs) for the proposed organometallic structure of Ω are inconsistent with the experiment. In contrast, a near-attack conformer of SAM bound to the catalytic [4Fe–4S] cluster, in which the distance between the unique iron and SAM sulfur is ~3 Å, yields HFCCs that are all within 1 MHz of the experimental values. Furthermore, these results clarify the structure of the ubiquitous Ω intermediate and suggest a paradigm shift reversal regarding the mechanism of SAM cleavage by members of the radical SAM superfamily.

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

Microscopic force driving the photoinduced ultrafast phase transition: Time-dependent density functional theory simulations of IrTe 2

Photoinduced phase transitions can have complex and intriguing behaviors more than material ground-state dynamics. Understanding the underlying mechanism can help us to design new ways to manipulate the materials. A variety of mechanisms has been proposed to explain the photoinduced phase transitions of IrTe 2 , but a consensus has yet to be reached. Here, we study the photo-induced phase transitions of IrTe 2 by performing the real-time time-dependent density functional theory (rt-TDDFT) simulations in combination with the occupation constrained DFT method. We reveal that the microscopic driving force for the photo-induced phase transitions arises from the tendency to lower the energy levels occupied by the excited carriers, through the increase or decrease of the associated atomic pair distances, depending on whether the newly occupied states are antibonding or bonding states, respectively. The geometric constraints between different bonds represented by the Poisson ratio can bring together different tendencies from different atomic pairs, thus forming a complex intriguing dynamic picture depending on the intensity of the excitation. Furthermore, we also find that phonons don't play a primary role, but can assist the phase transition. These findings imply that one can control the structural phase transitions by selectively exciting photocarriers into designated atomic states using appropriate photon sources.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Strain-Induced Shifts in Defective Graphite Phonon Modes Predicted by Density Functional Theory

Carbon fiber composites have gained attention as a structural material because of their high strength-to-weight ratio, and understanding the effect of defects on reactivity and mechanical properties is important for the longevity and safety of the composite. Although it is known that strain causes the underlying graphitic vibrational modes to redshift, it is not clear how strain may alter reactivity and defect-induced vibrational changes. To investigate the strain-induced phonon changes of defective carbon fiber composites, density functional theory calculations of graphite are used, including intercalated hydrogen and fluorine defects. By comparing changes in the bond lengths, formation energies, and phonon density of states for uniaxially and biaxially strained graphite, strain was found to generally make defect formation more favorable and the specific behavior changes are dependent on the strain direction and defect identity. Specifically, intercalated fluorine phonons are more sensitive to strain than hydrogen intercalation phonons, and strain applied along the zigzag direction alters the calculated properties more than strain along the armchair direction. Finally, these results highlight the importance of understanding the microstructural effect of deviations from the ideal material because small changes in strain or defect type can significantly alter the behavior of the carbon fiber composite core.

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

Coupling of Flavonoid Initiation Sites with Monolignols Studied by Density Functional Theory

Lignin recalcitrance presents a challenge for the development of a bioeconomy that employs lignocellulosic feedstocks. The efficiency of lignin deconstruction is improved by a reduction of molecular weight, and given the discovery that flavones serve as initiation sites in lignin biosynthesis, these molecular weight reductions could potentially be achieved with plant metabolic engineering to over-express flavonoids. Upon increasing the flavonoid content in lignin, the bond strengths and properties of flavonoid-monolignol linkages become increasingly important. To that end, the current work applies density functional theory calculations to elucidate the bond dissociation enthalpies (BDEs) of flavonoid-monolignol linkages, including dimers with oxidized monolignols. Specifically, the dimer bond strengths and monomer hydrogen abstraction energies for the flavonoids tricin, chrysoeriol, luteolin, apigenin, catechin, epicatechin, epigallocatechin, and epigallocatechin gallate are calculated, when coupled to seven natural and engineered monolignols. Results indicate that 4'-O-ß linkage strengths between flavonoids and monolignols are of comparable strength to inter-monolignol ß-O-4 linkages, with average flavonoid-monolignol BDEs of 70.7 kcal/mol relative to ~69.3 kcal/mol in analogous canonical monolignols. Epigallocatechin yielded the lowest 4'-O-ß bond strength of 52.3 kcal/mol when coupled to an oxidized monolignol, while the flavones overall produced lower average BDEs, relative to the flavanols. Substituents at the 3'-C and 5'-C positions on flavonoids affected the dimer linkage strengths to a greater extent than glycosylation or substituents further from the linkage. Erythro and threo stereochemistry across the flavonoid-monolignol linkage library exhibited only small energetic differences and no pronounced correlations. Taken together, the predictions from this work support the concept that higher concentrations of flavonoid initiation sites in lignin may afford linkage properties conducive to more facile lignin depolymerization.

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

Accelerating multiscale electronic stopping power predictions with time-dependent density functional theory and machine learning

Knowing the rate at which particle radiation releases energy in a material, the “stopping power,” is key to designing nuclear reactors, medical treatments, semiconductor and quantum materials, and many other technologies. While the nuclear contribution to stopping power, i.e., elastic scattering between atoms, is well understood in the literature, the route for gathering data on the electronic contribution has for decades remained costly and reliant on many simplifying assumptions, including that materials are isotropic. We establish a method that combines time-dependent density functional theory (TDDFT) and machine learning to reduce the time to assess new materials to hours on a supercomputer and provide valuable data on how atomic details influence electronic stopping. Our approach uses TDDFT to compute the electronic stopping from first principles in several directions and then machine learning to interpolate to other directions at a cost of 10 million times fewer core-hours. We demonstrate the combined approach in a study of proton irradiation in aluminum and employ it to predict how the depth of maximum energy deposition, the “Bragg Peak,” varies depending on the incident angle—a quantity otherwise inaccessible to modelers and far outside the scales of quantum mechanical simulations. The lack of any experimental information requirement makes our method applicable to most materials, and its speed makes it a prime candidate for enabling quantum-to-continuum models of radiation damage. The prospect of reusing valuable TDDFT data for training the model makes our approach appealing for applications in the age of materials data science.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Accurate frozen core approximation for all-electron density-functional theory

We implement and benchmark the frozen core approximation, a technique commonly adopted in electronic structure theory to reduce the computational cost by means of mathematically fixing the chemically inactive core electron states. The accuracy and efficiency of this approach are well controlled by a single parameter, the number of frozen orbitals. Explicit corrections for the frozen core orbitals and the unfrozen valence orbitals are introduced, safeguarding against seemingly minor numerical deviations from the assumed orthonormality conditions of the basis functions. A speedup of over twofold can be achieved for the diagonalization step in all-electron density-functional theory simulations containing heavy elements, without any accuracy degradation in terms of the electron density, total energy, and atomic forces. This is demonstrated in a benchmark study covering 103 materials across the Periodic Table and a large-scale simulation of CsPbBr3 with 2560 atoms. Our study provides a rigorous benchmark of the precision of the frozen core approximation (sub-meV per atom for frozen core orbitals below −200 eV) for a wide range of test cases and for chemical elements ranging from Li to Po. The algorithms discussed here are implemented in the open-source Electronic Structure Infrastructure software package.

Yu, Victor Wen-zhe↗
DOE OSTI2025

Accurate Force Field for Carbon Dioxide–Silica Interactions Based on Density Functional Theory

Fluid–silica interfaces are ubiquitous in chemistry, occurring in both natural geochemical environments and practical applications ranging from separations to catalysis. Simulations of these interfaces have been, and continue to be, a significant avenue for understanding their behavior. A constraining factor, however, is the availability of accurate force fields. Most simulations use traditional “mixing rules” to determine nonbonded dispersion interactions, an approach that has not been critically examined. Here, in this study, we present Lennard-Jones parameters for the interaction of carbon dioxide with silica interfaces that are optimized to reproduce density functional theory (DFT)-based binding energies. The modeling is based on the recently developed silica-DDEC force field, whose atomic charges are consistent with DFT calculations. Standard mixing rules are found to predict weaker CO 2 binding to silica than that obtained from DFT, an effect corrected by the optimized parameters given here. This behavior extends to other silica force fields (Clayff and Gulmen-Thompson), and the present Lennard-Jones parameters improve their performance as well. The effects of improved Lennard-Jones parameters on the structural and dynamical properties of condensed CO 2 in silica slit pores are also examined.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗