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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 1,117 records · Page 62
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Symbol alphabets from plabic graphs

Symbol alphabets of n-particle amplitudes in N = 4 super-Yang-Mills theory are known to contain certain cluster variables of Gr(4, n) as well as certain algebraic functions of cluster variables. In this paper we suggest an algorithm for computing these symbol alphabets from plabic graphs by solving matrix equations of the form C ∙ Z = 0 to associate functions on Gr(m, n) to parameterizations of certain cells of Gr(k, n) indexed by plabic graphs. For m = 4 and n = 8 we show that this association precisely reproduces the 18 algebraic symbol letters of the two-loop NMHV eight-particle amplitude from four plabic graphs.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

The amorphization of 3C-SiC irradiated at moderately elevated temperatures as revealed by X-ray diffraction

Mechanisms of radiation damage buildup in 3C-SiC remain poorly understood. Here, we use X-ray diffraction in combination with numerical simulations to study depth profiles of radiation-produced strain and lattice damage in 3C-SiC bombarded in the temperature range of 25–200 °C with 500 keV Ar ions. Results reveal increased defect recombination with increasing temperature, with a critical amorphization fluence increasing from 0.17 to 0.44 displacements per atom. The amorphization process is found to be correlated with the evolution of lattice strain. We find that, at fluences corresponding to the onset of amorphization, lattice strain is ~2% and is independent of temperature. With continuing bombardment above the onset of amorphization, the strain in the crystal bulk increases and reaches a saturation value that decreases from 7% to 5% with increasing temperature. Based on strain profiles, we compute depth profiles of the effective concentration of point defect clusters in the crystalline phase. Bombardment at higher temperatures results in lower maximum defect concentrations pointing to enhanced defect mobility.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Evaluation of kriging based surrogate models constructed from mesoscale computations of shock interaction with particles

Macro-scale computations of shocked particulate flows require closure laws that model the exchange of momentum/energy between the fluid and particle phases. Closure laws are constructed in this work in the form of surrogate models derived from highly resolved mesoscale computations of shock-particle interactions. The mesoscale computations are performed to calculate the drag force on a cluster of particles for different values of Mach Number and particle volume fraction. Two Kriging-based methods, viz. the Dynamic Kriging Method (DKG) and the Modified Bayesian Kriging Method (MBKG) are evaluated for their ability to construct surrogate models with sparse data; i.e. using the least number of mesoscale simulations. It is shown that if the input data is noise-free, the DKG method converges monotonically; convergence is less robust in the presence of noise. The MBKG method converges monotonically even with noisy input data and is therefore more suitable for surrogate model construction from numerical experiments. This work is the first step towards a full multiscale modeling of interaction of shocked particle laden flows.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Unsupervised learning for identifying events in active target experiments

This article presents novel applications of unsupervised machine learning methods to the problem of event separation in an active target detector, the Active-Target Time Projection Chamber (AT-TPC). The overarching goal is to group similar events in the early stages of the data analysis, thereby improving efficiency by limiting the computationally expensive processing of unnecessary events. The application of unsupervised clustering algorithms to the analysis of two-dimensional projections of particle tracks from a resonant proton scattering experiment on 46 Ar is introduced. We explore the performance of autoencoder neural networks and a pre-trained VGG16 Simonyan and Zisserman (2015) convolutional neural network. We study clustering performance on both data from a simulated 46 Ar experiment, and real events from the AT-TPC detector. We find that a -means algorithm applied to simulated data in the VGG16 latent space forms almost perfect clusters. Additionally, the VGG16+-means approach finds high purity clusters of proton events for real experimental data. Here, we also explore the application of clustering the latent space of autoencoder neural networks for event separation. While these networks show strong performance, they suffer from high variability in their results.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Open-Shell Tensor Hypercontraction

The extension of least-squares tensor hypercontracted second- and third-order Møller–Plesset perturbation theory (LS-THC-MP2 and LS-THC-MP3) to open-shell systems is an important development due to the scaling reduction afforded by THC and the ubiquity of molecular ions, radicals, and other open-shell reactive species. The complexity of wavefunction-based quantum-chemical methods such as Møller–Plesset and coupled cluster theory is reflected in the steep scaling of the computational costs with the molecular size. The least-squares tensor hypercontraction (LS-THC) method is an efficient, single-step factorization for the two-electron integral tensor but can also be used to factorize the double excitation amplitudes, leading to significant scaling reduction. Herein we extend this promising method to open-shell variants of LS-THC-MP2 and -MP3 by using diagrammatic techniques and explicit spin summation. The accuracy of the resulting methods for open-shell species is benchmarked on standard test systems such as regular alkanes as well as realistic systems involving bond breaking, radical stabilization, and other effects. We find that open-shell LS-THC-MPn methods exhibit errors highly comparable to those produced by closed-shell LS-THC-MPn and are highly insensitive to particular chemical interactions, geometries, or even moderate spin contamination.

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

Reaction Energetics and 13 C Fractionation of Alanine Transamination in the Aqueous and Gas Phases

The alanine transaminase enzyme catalyzes the transfer of an amino group from alanine to α-ketoglutarate to produce pyruvate and glutamate. Isotope fractionation factors (IFFs) for the reaction +H 3 NCH(CH 3 )COO – + – OOCCH 2 CH 2 C(O)COO – ↔ CH 3 C(O)COO – + + H 3 NCH(CH 2 CH 2 COO – )COO – (zwitterionic neutral alanine + doubly deprotonated α-ketoglutarate ↔ pyruvate + zwitterionic glutamate anion) were calculated from the partition functions of explicitly and implicitly solvated molecules at 298 K. Calculations were done for alanine (noncharge separated, zwitterion, deprotonated), pyruvic acid (neutral, deprotonated), glutamic acid (noncharge separated, zwitterion, deprotonated, doubly deprotonated), and α-ketoglutaric acid (neutral, deprotonated, doubly deprotonated). The computational results, calculated from gas phase- and aqueous-optimized clusters with explicit H 2 O molecules at the MP2/aug-cc-pVDZ and MP2/aug-cc-pVDZ/COSMO levels, respectively, predict that substitution of 13 C at the C2 position of alanine and pyruvic acid and their various forms leads to the C2 position of pyruvic acid/pyruvate being enriched in 13 C/ 12 C ratio by 9‰. Simpler approaches that estimate the IFFs based solely on changes in the zero-point energies (ZPEs) are consistent with the higher-level model. ZPE-based IFFs calculated for simple analogues formaldehyde and methylamine (analogous to the C2 positions of pyruvate and alanine, respectively) predict a 13 C enrichment in formaldehyde of 7–8‰ at the MP2/aug-cc-pVDZ and aug-cc-pVTZ levels. A simple predictive model using canonical functional group frequencies and reduced masses for 13 C exchange between R 2 C=O and R 2 CH–NH 2 predicted enrichment in R 2 C=O that is too large by a factor of two but is qualitatively accurate compared with the more sophisticated models. Our models are all in agreement with the expectation that pyruvate and formaldehyde will be preferentially enriched in 13 C because of the strength of their >C=O bond relative to that of ≡C–NH 2 in alanine and methylamine. 13 C/ 12 C substitution is also modeled at the methyl and carboxylic acid sites of alanine and pyruvic acid, respectively.

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

Cryogenic “Iodide-Tagging” Photoelectron Spectroscopy: A Sensitive Probe for Specific Binding Sites of Amino Acids

This work showcases cryogenic and temperature-dependent “iodide-tagging” photoelectron spectroscopy to probe specific binding sites of amino acids using the glycine-iodide complex (Gly?I-) as a case study. Multiple Gly?I- isomers were generated from ambient electrospray ionization and kinetically isolated in a cryogenic ion trap. These structures were characterized with temperature-dependent “iodide-tagging” negative ion photoelectron spectroscopy (NIPES) where iodide was used as the “messenger” to interpret electronic energetics and structural information of various Gly?I- isomers. Accompanied by theoretical computations and Franck-Condon simulations, a total of five cluster structures have been identified along with their various binding motifs. This work demonstrates that “iodide-tagging” NIPES is a powerful general means for probing specific binding interactions in biological molecules of interest.

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

Correlated Anion Disorder in Heteroanionic Cubic TiOF 2

Resolving anion configurations in heteroanionic materials is crucial for understanding and controlling their properties. For anion-disordered oxyfluorides, conventional Bragg diffraction cannot fully resolve the anionic structure, necessitating alternative structure determination methods. We have investigated the anionic structure of anion-disordered cubic (ReO 3 -type) TiOF 2 using X-ray pair distribution function (PDF), 19 F MAS NMR analysis, density functional theory (DFT), cluster expansion modeling, and genetic-algorithm structure prediction. Our computational data predict short-range anion ordering in TiOF 2 , characterized by predominant cis-[O 2 F 4 ] titanium coordination, resulting in correlated anion disorder at longer ranges. To validate our predictions, we generated partially disordered supercells using genetic-algorithm structure prediction and computed simulated X-ray PDF data and 19 F MAS NMR spectra, which we compared directly to experimental data. To construct our simulated 19 F NMR spectra, we derived new transformation functions for mapping calculated magnetic shieldings to predicted magnetic chemical shifts in titanium (oxy)fluorides, obtained by fitting DFT-calculated magnetic shieldings to previously published experimental chemical shift data for TiF 4 . We find good agreement between our simulated and experimental data, which supports our computationally predicted structural model and demonstrates the effectiveness of complementary experimental and computational techniques in resolving anionic structure in anion-disordered oxyfluorides. From additional DFT calculations, we predict that increasing anion disorder makes lithium intercalation more favorable by, on average, up to 2 eV, highlighting the significant effect of variations in short-range order on the intercalation properties of anion-disordered materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Electronic and chemical state of aluminum from the single- (K) and double-electron excitation (KL II&III , KL I ) x-ray absorption near-edge spectra of α-alumina, sodium aluminate, aqueous Al³⁺•(H₂O)₆, and aqueous Al(OH)₄⁻

We probe, at high energy resolution, the double electron excitation (KL II&II ) x-ray absorption region that lies approximately 115 eV above the main Al K-edge (1566 eV) of α-alumina and sodium aluminate. The two solid standards, α-alumina (octahedral) and sodium aluminate (tetrahedral) are compared to aqueous species that have the same Al coordination symmetries, Al³⁺•6H₂O (octahedral) and Al(OH)₄⁻ (tetrahedral). For the octahedral species, the edge height of the KL II&III -edge is approximately 10% of the main K-edge however the edge height is much weaker (3% of K-edge height) for Al species with tetrahedral symmetry. For the α-alumina and aqueous Al³⁺•6H₂O the KL II&III spectra contain white line features and extended absorption fine structure (EXAFS) that mimics the K-edge spectra. The KL II&III -edge feature interferes with an important region of the extended-XAFS region of the spectra for the K-edge of the crystalline and aqueous standards. The K-edge spectra and K-edge positions are predicted using time-dependent density functional theory (TDDFT). The TDDFT calculations for the K-edge XANES spectra reproduce the observed transitions in the experimental spectra of the four Al species. The KL II&III and KL I onsets and their corresponding chemical shifts for the four standards are estimated using the delta self-consistent field (ΔSCF) method. Research by JLF, NG, EJB, AV, TDS was supported by U.S. Department of Energy’s (DOE), Office of Science, Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences, and Biosciences. NG thanks Amity Andersen for help with the α-Al₂O₃ and tetrahedral sodium aluminate (NaAlO₂) clusters. All the calculations were performed using the Molecular Science Computing Capability at EMSL, a national scientific user facility sponsored by the U.S. Department of Energy’s Office of Biological and Environmental Research and located at Pacific Northwest National Laboratory (PNNL). PNNL is a multi-program national laboratory operated for DOE by Battelle under Contract # AC05-76RL01830.

aluminum↗
DOE OSTI2015

A comparison of neutral and charged species of one- and two-dimensional models of graphene nanoribbons using multireference theory

This study examines the dependence of the polyradical character of charged quasi-linear n-acenes and two-dimensional periacenes used as models for graphene nanoribbons in comparison to the corresponding neutral compounds. For this purpose, high-level ab initio calculations have been performed using the multireference averaged quadratic coupled cluster theory. Vertical ionization energies and electron affinities have been computed. Systematic tests show that the dependence on chain length of these quantities can be obtained from a consideration of the π system only and that remaining contributions coming from the σ orbitals or extended basis sets remain fairly constant. Using best estimate values, the experimental values for the ionization energy of the acene series can be reproduced within 0.1 eV and the experimental electron affinities within 0.4 V. The analysis of the natural orbital occupations and related unpaired electron densities shows that the ionic species exhibit a significant decrease in polyradical character and thus an increased chemical stability as compared to the neutral state.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Application of vibrational correlation formalism to internal conversion rate: Case study of Cu{sub n} (n = 3, 6, and 9) and H{sub 2}/Cu{sub 3}

This work reports non-radiative internal conversion (IC) rate constants obtained for Cu{sub n} with n = 3, 6, and 9 and H{sub 2} on Cu{sub 3}. The Time-Dependent Density Functional Theory (TDDFT) method was employed with three different functionals in order to investigate the electronic structures and the absorption spectra. The performance of the generalized gradient approximation of Perdew, Burke and Ernzerhof (PBE) and the hybrid B3LYP and PBE0 exchange correlation functionals in combination with the SVP and the def2-TZVP basis sets was examined. TDDFT results were used as input data to compute internal conversion rate constants. For this purpose, we have developed a program package. A description of the theoretical background used in our numerical implementation and the program input file is presented. In view of future applications of this program package in photoinduced catalysis, we present the analysis of the IC rate processes for the photodissociation of H{sub 2} on Cu{sub 3}. These results showed the applicability of the method and the computational program to identify the vibrational modes in transition metal clusters giving rise to the largest IC rate constant due to their interactions with the excited electronic states occurring in the hot-electron induced dissociation phenomena.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2020

Coupled Cluster Green's function formulations based on the effective Hamiltonians

In this work, we demonstrate that the effective Hamiltonians obtained with the downfolding procedure based on double unitary coupled cluster (DUCC) ansatz can be used in the context of Green’s function coupled cluster (GFCC) formalism to calculate spectral functions of molecular systems. This combined approach (DUCC-GFCC) provides a significant reduction of numerical effort and good agreement with the corresponding all-orbital GFCC methods in energy windows that are consistent with the choice of active space. These features are demonstrated on the example of two benchmark systems: H 2 O and N 2 , where DUCC-GFCC calculations were performed for active spaces of various sizes.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2024

Generalized representative structures for atomistic systems

A new method is presented to generate atomic structures that reproduce the essential characteristics of arbitrary material systems, phases, or ensembles. Previous methods allow one to reproduce the essential characteristics (e.g. the chemical disorder) of a large random alloy within a small crystal structure. The ability to generate small representations of random alloys, along with the restriction to crystal systems, results from using the fixed-lattice cluster correlations to describe structural characteristics. A more general description of the structural characteristics of atomic systems is obtained using complete sets of atomic environment descriptors. These are used within for generating representative atomic structures without restriction to fixed lattices. A general data-driven approach is provided here utilizing the atomic cluster expansion (ACE) basis. The N-body ACE descriptors are a complete set of atomic environment descriptors that span both chemical and spatial degrees of freedom and are used within for describing atomic structures. The generalized representative structure (GRS) method presented within generates small atomic structures that reproduce ACE descriptor distributions corresponding to arbitrary structural and chemical complexity. It is shown that systematically improvable representations of crystalline systems on fixed parent lattices, amorphous materials, liquids, and ensembles of atomic structures may be produced efficiently through optimization algorithms. With the GRS method, we highlight reduced representations of atomistic machine-learning training datasets that contain similar amounts of information and small 40–72 atom representations of liquid phases. The ability to use GRS methodology as a driver for informed novel structure generation is also demonstrated. The advantages over other data-driven methods and state-of-the-art methods restricted to high-symmetry systems are highlighted.

atomic cluster expansion↗
DOE OSTI2016

Comparison of weak lensing by NFW and Einasto halos and systematic errors

Recent N-body simulations have shown that Einasto radial profiles provide the most accurate description of dark matter halos. Predictions based on the traditional NFW functional form may fail to describe the structural properties of cosmic objects at the percent level required by precision cosmology. We computed the systematic errors expected for weak lensing analyses of clusters of galaxies if one wrongly models the lens density profile. Even though the NFW fits of observed tangential shear profiles can be excellent, viral masses and concentrations of very massive halos (∼> 10{sup 15}M{sub ⊙}/h) can be over- and underestimated by 0∼ 1 per cent, respectively. Misfitting effects also steepen the observed mass-concentration relation, as observed in multi-wavelength observations of galaxy groups and clusters. Based on shear analyses, Einasto and NFW halos can be set apart either with deep observations of exceptionally massive structures (∼> 2×10{sup 15}M{sub ⊙}/h) or by stacking the shear profiles of thousands of group-sized lenses (∼> 10{sup 14}M{sub ⊙}/h)

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Large-scale 16S gene assembly using metagenomics shotgun sequences

Combining a 16S rRNA (16S) gene database with metagenomic shotgun sequences allows unbiased identification of known and novel microbes.To attain this, we herein report reference-based ribosome assembly (RAMBL), a computational pipeline, which integrates taxonomic tree search and Dirichlet process clustering to reconstruct full-length 16S gene sequences from metagenomic sequencing data with high accuracy. By benchmarking against the synthetic and real shotgun sequences, we demonstrated that full-length 16S gene assemblies of RAMBL were a good proxy for known and putative microbes, including Candidate Phyla Radiation. Here, we found that 30-40% of bacteria genera in the terrestrial and intestinal biomes have no closely related genome sequences. We also observed that RAMBL was able to generate a more accurate determination of environmental microbial diversity and yield better disease classification, suggesting that full-length 16S gene assemblies are a powerful alternative to marker gene set and 16S short reads. RAMBL first realizes the access to full-length 16S gene sequences in the near-terabase-scale metagenomic shotgun sequences, which markedly improve metagenomic data analysis and interpretation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Partitioning of Large-Scale Power Electronics-Based Power Systems for Small-Signal Stability Analysis

The nodal admittance matrix (NAM)-based approach is suitable for analyzing the small-signal stability of large-scale power electronics-based power systems (PEPSs) as it preserves the system structure by utilizing the admittance matrix. Previously, NAM-based area partition has been proposed, which divides the system into various subareas and interconnections for easier analysis of the low-dimension matrix compared to the entire system-based high-dimension matrix. However, no partition algorithm has been presented for the NAM-based area partition method. This paper focuses on implementing the spectral partitioning algorithm for partitioning large-scale PEPSs into a low-dimension matrix to reduce the computation complexity of the analysis. These spectral components facilitate data transformation into a new space, enabling the application of traditional clustering methods like k-means. To evaluate the performance of the partitioning method, the subareas and interconnections obtained from the spectral clustering algorithm are incorporated into the NAM-based area partition method for a large system with 140 buses. The computational times of the original method, where the NAM-based criterion is directly applied to the entire system, are compared with those of the NAM-based partition method in MATLAB. PSCAD simulations of the whole system and the obtained subareas are conducted to validate the effectiveness of the proposed algorithm.

Nupur, Nupur↗
DOE OSTI2020

Designing Catalysts for Dehydrogenation of Methane for Reducing Greenhouse Gas during Natural Gas Extraction

Catalytic conversion of methane (CH 4 ) into useful products is critical for maximizing the utility of natural gas output and for reducing green house gas release associated with flaring (burning off CH 4 at natural gas extraction sites). One particular useful technique is methane dry reforming (DRM), which involves the chemical reaction of CH 4 with carbon dioxide (CO 2 ) to generate carbon monoxide (CO), hydrogen gas (H 2 ), and subsequently other useful products. New and improved catalysts are required to facilitate efficient dry methane reforming. In this report, we apply the Density Functional Theory (DFT) computational technique to investigate a catalyst consisting of small nickel clusters (Ni n , n < 10) on ceria (Ce0 2 (111) surfaces) support. One main thrust of this project is to study the initial CH 4 and CO 2 reactions with the catalyst. We find that CH 4 exhibits barrierless reactive adsorption on to the catalyst. In order words, this step is likely not the rate-determining step. A second thrust is to perform detailed studies of the catalyst itself and examine the role of oxygen vacancies. Using a specific DFT method and a hypothesis about the absence of the Ce(III) redox state, we obtain predictions about oxygen vacancies in good agreement with experimental observations.

03 NATURAL GAS↗
DOE OSTI2022

Nuclear Theory from First Principles to Forefront Experiments (Final Report for DE-SC0018638)

The Lee research group is a part of the Nuclear Lattice Effective Field Theory Collaboration, which has developed and performed ab initio lattice simulations of nuclear structure, scattering, reactions, and many-body systems. The other senior members of the collaboration include Ulf-G. Meißner at Bonn/Julich, Evgeny Epelbaum and Hermann Krebs at Bochum, Timo Lahde and Thomas Luu at Julich, and Gautam Rupak at Mississippi State. Our letter “Ab initio alpha-alpha scattering” was featured in a Nature News and Views article. Another letter “Nuclear binding near a quantum phase transition” was highlighted in a Viewpoint article in the online APS journal Physics as well as a news article in the IOP publication Physics World (September 21, 2016). Our letter “Eigenvector continuation with subspace learning” was also highlighted a Synopsis article in Physics. There are many promising ab initio approaches being used to calculate the properties of few-and many-nucleon systems. This includes the no-core shell model, symmetry-adapted no-core shell model quantum Monte Carlo, auxiliary-field diffusion Monte Carlo, self-consistent Green’s functions, many-body perturbation theory, in-medium similarity renormalization group, and coupled cluster methods. Lattice effective field theory is another ab initio approach which combines the framework of effective field theory with lattice Monte Carlo methods to allow favorable scaling from few- to many-body systems. Perhaps the most important aspect of lattice effective field theory is that its strengths and weaknesses are orthogonal to that of other ab initio methods. For example, lattice effective field theory has little difficulty in probing cluster structures and collectivity, while such features are much more difficult using other methods. Furthermore it can be used to compute superfluid condensate fractions as well as the phase diagram of strongly matter and the density and temperature dependence of clustering. Lattice effective field theory was first used in simulations of infinite nuclear matter and infinite neutron matter with pions and without pions. In addition to the efforts by our collaboration, there have been recent efforts by other groups as well.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗