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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Homochiral and racemic MicroED structures of a peptide repeat from the ice-nucleation protein InaZ

The ice-nucleation protein InaZ from Pseudomonas syringae contains a large number of degenerate repeats that span more than a quarter of its sequence and include the segment GSTSTA. Ab initio structures of this repeat segment, resolved to 1.1 Å by microfocus X-ray crystallography and to 0.9 Å by the cryo-EM method MicroED, were determined from both racemic and homochiral crystals. The benefits of racemic protein crystals for structure determination by MicroED were evaluated and it was confirmed that the phase restriction introduced by crystal centrosymmetry increases the number of successful trials during the ab initio phasing of the electron diffraction data. Both homochiral and racemic GSTSTA form amyloid-like protofibrils with labile, corrugated antiparallel β-sheets that mate face to back. The racemic GSTSTA protofibril represents a new class of amyloid assembly in which all-left-handed sheets mate with their all-right-handed counterparts. This determination of racemic amyloid assemblies by MicroED reveals complex amyloid architectures and illustrates the racemic advantage in macromolecular crystallography, now with submicrometre-sized crystals.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1991

Is interstellar detection of higher members of the linear radicals CnCH and CnN feasible?

Rotational constants and dipole moments for linear-chain radicals CnCH and CnN are estimated using a combinatiaon of ab initio molecular orbital calculations and observed data on the starting members of the series. CnCH with n = 0-5 have been observed by radioastronomy in carbon-rich interstellar clouds; higher members of the series have 2Pi ground states with large dipole moments and are strong candidates for observation. CN and C3N have also been observed by radioastronomy; higher members of the series, with the possible exception of C5N, have 2Pi ground states with near-zero dipole moments making their interstellar detection hopeless under present observational conditions. C5N can be a strong candidate only if it has a 2Sigma ground state, and best computations so far indicate that this is not the case.

Pauzat, F.↗
NASA NTRS2015

Excited Vibrational Level Rotational Constants for SiC2: A Sensitive Molecular Diagnostic for Astrophysical Conditions

Silacyclopropynylidene, SiC2, is a known and highly abundant circumstellar molecule. Its spectrum has been established as a major component of lines observed toward the carbon-rich star IRC +10216 (CW Leonis). It has been detected in its low-lying v(sub 3) = 1 and 2 vibrational states as well as in various isotopic compositions. Increasing sensitivity and spatial resolution will enable many more emission or absorption lines to be detected. In order to detect new molecular species, unassigned lines of known species must be identified. This work uses established ab initio quartic force fields to produce data necessary for this classification of lines related to SiC2. Agreement between the theoretical vibrational frequencies and known rotational and spectroscopic constants is quite good, as good as 5 cm(exp -1) and 3 MHz, respectively in some cases. Additionally, experimentally unknown vibrational frequencies and rotational constants are provided for the first overtones and combination bands in addition to 3(sub v3), the second overtone of the low-lying antisymmetric stretch/carbide rotation mode. Frequencies of v(sub 3) = 3 low-J rotational transitions of the main isotopic species are also estimated from published data for v(sub 3) ≤ 2. Further, we determine rotational and centrifugal distortion parameters for which in most cases vibrational effects due to the v(sub 3) mode were reduced to first, and in several cases also to second order. These values may approximate equilibrium values better than the ground state values. The data produced herein will aid in the experimental and observational characterization of this known astromolecule in order to identify some of the unassigned lines for a known entity.

Astrochemistry↗
DOE OSTI2022

Precision measurement of Compton scattering in silicon with a skipper CCD for dark matter detection

Experiments aiming to directly detect dark matter through particle recoils can achieve energy thresholds of $\mathcal{O}(1\,\mathrm{eV})$. In this regime, ionization signals from small-angle Compton scatters of environmental $\gamma$-rays constitute a significant background. Monte Carlo simulations used to build background models have not been experimentally validated at these low energies. We report a precision measurement of Compton scattering on silicon atomic shell electrons down to 23$\,$eV. A skipper charge-coupled device (CCD) with single-electron resolution, developed for the DAMIC-M experiment, was exposed to a $^{241}$Am $\gamma$-ray source over several months. Features associated with the silicon K, L$_{1}$, and L$_{2,3}$-shells are clearly identified, and scattering on valence electrons is detected for the first time below 100$\,$eV. We find that the relativistic impulse approximation for Compton scattering, which is implemented in Monte Carlo simulations commonly used by direct detection experiments, does not reproduce the measured spectrum below 0.5$\,$keV. The data are in better agreement with $ab$$initio$ calculations originally developed for X-ray absorption spectroscopy.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2019

Ab Initio Molecular Dynamics Simulation of Divalent Metal Cation Incorporation in Calcite: Implications for Interpreting X-ray Absorption Spectroscopy Data

Calcite (CaCO 3 ) is a ubiquitous mineral with the ability to accommodate a wide range of impurities. Determination of the coordination environment and incorporation modes of impurities in calcite has historically relied primarily on the interpretation of extended X-ray absorption fine structure (EXAFS) spectroscopy. However, lack of standards combined with the large number of degrees of freedom involved in shell-by-shell fits have made the interpretation of EXAFS spectra challenging. As such, in this work, ab initio molecular dynamics (AIMD) simulations were performed to investigate the incorporation of seven divalent metal cation impurities, namely, Ba 2+ , Pb 2+ , Sr 2+ , Cd 2+ , Mn 2+ , Co 2+ , and Zn 2+ , in calcite. These cations span a wide range of sizes: 30.7 to –22.8% change in ionic radius with respect to Ca 2+ . The atomic trajectories were then used to compute EXAFS spectra for direct comparison with published experimental spectra. The simulations confirmed that all seven metal cations incorporate in calcite via substitution in the calcium site. The AIMD–EXAFS approach allowed for overcoming limitations of the shell-by-shell fitting approach, such as the difficulties in resolving weak backscatterers beyond the first coordination shell. As a result, the AIMD–EXAFS approach was able to provide a detailed and comprehensive characterization of the structural relaxation around divalent metal cation impurities in calcite.

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

Ab Initio Limits of Atomic Nuclei

We predict the limits of existence of atomic nuclei, the proton and neutron drip lines, from the light through medium-mass regions. Starting from a chiral two- and three-nucleon interaction with good saturation properties, we use the valence-space in-medium similarity renormalization group to calculate ground-state and separation energies from helium to iron, nearly 700 isotopes in total. Here, we use the available experimental data to quantify the theoretical uncertainties for our ab initio calculations towards the drip lines. Where the drip lines are known experimentally, our predictions are consistent within the estimated uncertainty. For the neutron-rich sodium to chromium isotopes, we provide predictions to be tested at rare-isotope beam facilities.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2022

Ab initio quantum scattering calculations for the CO–O 2 system and a new CO–O 2 potential energy surface: O 2 and air broadening of the R(0) line in CO

We present ab initio calculations of the collisional broadening of the R(0) pure rotational line in CO (at 115 GHz) perturbed by O 2 . Our calculations are done in a fully quantum way by solving close-coupling quantum-scattering equations without any approximations. We also report a new, highly accurate CO–O 2 potential energy surface on which we did the quantum-scattering calculations. The calculated collisional broadening agrees with the available experimental data in a wide temperature range. The calculated collisional shift is negligible compared to the broadening, which is also consistent with the experimental data. We combine this result with our previous calculations for the same line in CO perturbed by N 2 [Józwiak et al., J. Chem. Phys. 154, 054314 (2021)]; the obtained air-perturbed broadening of the R(0) pure rotational line in CO and its temperature dependence perfectly agree with the HITRAN database. This result constitutes an important step toward developing a methodology for providing accurate ab initio reference data on spectroscopic collisional line-shape parameters for molecular systems relevant to the Earth’s atmosphere and for populating spectroscopic line-by-line databases.

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

Extracting the number of short-range correlated nucleon pairs from inclusive electron scattering data

The extraction of the relative abundances of short-range correlated (SRC) nucleon pairs from inclusive electron scattering is studied using the generalized contact formalism (GCF) with several nuclear interaction models. GCF calculations can reproduce the observed scaling of the cross-section ratios for nuclei relative to deuterium at high xB and large Q 2 , a 2 =(σ A /A)/(σ d /2). In the nonrelativistic instant-form formulation, the calculation is very sensitive to the model parameters and only reproduces the data using parameters that are inconsistent with ab initio many-body calculations. Using a light-cone GCF formulation significantly decreases this sensitivity and improves the agreement with ab initio calculations. The ratio of similar mass isotopes, such as 40 Ca and 48 Ca, should be sensitive to the nuclear asymmetry dependence of SRCs, but is found to also be sensitive to low-energy nuclear structure. Thus the empirical association of SRC pair abundances with the measured a2 values is only accurate to about 20%. Finally, improving this will require cross-section calculations that reproduce the data while properly accounting for both nuclear structure and relativistic effects.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

The MolSSI QCArchive project: An open-source platform to compute, organize, and share quantum chemistry data

The Molecular Sciences Software Institute's (MolSSI) Quantum Chemistry Archive (QCArchive) project is an umbrella name that covers both a central server hosted by MolSSI for community data and the Python-based software infrastructure that powers automated computation and storage of quantum chemistry (QC) results. The MolSSI-hosted central server provides the computational molecular sciences community a location to freely access tens of millions of QC computations for machine learning, methodology assessment, force-field fitting, and more through a Python interface. Facile, user-friendly mining of the centrally archived quantum chemical data also can be achieved through web applications found at the website. The software infrastructure can be used as a standalone platform to compute, structure, and distribute hundreds of millions of QC computations for individuals or groups of researchers at any scale. The QCArchiveInfrastructure is open-source (BSD-3C), code repositories can be found at github, and releases can be downloaded via PyPI and Conda. This article is categorized under: Electronic Structure Theory > Ab Initio Electronic Structure Methods Software > Quantum Chemistry Data Science > Computer Algorithms and Programming

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

Chemistry Informed Machine Learning-Based Heat Capacity Prediction of Solid Mixed Oxides

Knowing heat capacity is crucial for modeling temperature changes with the absorption and release of heat and for calculating the thermal energy storage capacity of oxide mixtures with energy applications. The current prediction methods (ab initio simulations, computational thermodynamics, and the Neumann–Kopp rule) are computationally expensive, not fully generalizable, or inaccurate. Machine learning has the potential of being fast, accurate, and generalizable, but it has been scarcely used to predict mixture properties, particularly for mixed oxides. Here, we demonstrate a method for the generalizable prediction of heat capacity of solid oxide pseudobinary mixtures using heat capacity data obtained from computational thermodynamics and descriptors from ab initio databases. Further, models trained through this workflow achieved an error (mean absolute error of 0.43 J mol –1 K –1 ) lower than the uncertainty in differential scanning calorimetry measurements, and the workflow can be extended to predict other properties derived from the Gibbs free energy and for higher-order oxide mixtures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Elucidating structural order and disorder phenomena in mullite-type Al{sub 4}B{sub 2}O{sub 9} by automated electron diffraction tomography

The crystal structure and disorder phenomena of Al{sub 4}B{sub 2}O{sub 9}, an aluminum borate from the mullite-type family, were studied using automated diffraction tomography (ADT), a recently established method for collection and analysis of electron diffraction data. Al{sub 4}B{sub 2}O{sub 9}, prepared by sol-gel approach, crystallizes in the monoclinic space group C2/m. The ab initio structure determination based on three-dimensional electron diffraction data from single ordered crystals reveals that edge-connected AlO{sub 6} octahedra expanding along the b axis constitute the backbone. The ordered structure (A) was confirmed by TEM and HAADF-STEM images. Furthermore, disordered crystals with diffuse scattering along the b axis are observed. Analysis of the modulation pattern implies a mean superstructure (AAB) with a threefold b axis, where B corresponds to an A layer shifted by ½a and ½c. Diffraction patterns simulated for the AAB sequence including additional stacking disorder are in good agreement with experimental electron diffraction patterns. - Graphical abstract: Crystal structure and disorder phenomena of B-rich Al{sub 4}B{sub 2}O{sub 9} studied by automated electron diffraction tomography (ADT) and described by diffraction simulation using DISCUS. - Highlights: • Ab-initio structure solution by electron diffraction from single nanocrystals. • Detected modulation corresponding mainly to three-fold superstructure. • Diffuse diffraction streaks caused by stacking faults in disordered crystals. • Observed streaks explained by simulated electron diffraction patterns.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Fast parametric relationships for the large-scale reservoir simulation of mixed CH 4 -CO 2 gas hydrate systems

A recent Department of Energy field test on the Alaska North Slope has increased interest in the ability to simulate systems of mixed CO 2 -CH 4 hydrates. However, the physically realistic simulation of mixed-hydrate simulation is not yet a fully solved problem. Limited quantitative laboratory data leads to the use of various ab initio, statistical mechanical, or other mathematic representations of mixed-hydrate phase behavior. Few of these methods are suitable for inclusion in reservoir simulations, particularly for systems with large number of grid elements, 3D systems, or systems with complex geometric configurations. In this paper, we present a set of fast parametric relationships describing the thermodynamic properties and phase behavior of a mixed methane-carbon dioxide hydrate system. We use well-known, off-the-shelf hydrate physical properties packages to generate a sufficiently large dataset, select the most convenient and efficient mathematical forms, and fit the data to those forms to create a physical properties package suitable for inclusion in the TOUGH+ family of codes. Finally, the mapping of the phase and thermodynamic space reveals the complexity of the mixed-hydrate system and allows understanding of the thermodynamics at a level beyond what much of the existing laboratory data and literature currently offer.

58 GEOSCIENCES↗
DOE OSTI2022

Fast and Accurate Predictions of Total Energy for Solid Solution Alloys with Graph Convolutional Neural Networks

We use graph convolutional neural networks (GCNNs) to produce fast and accurate predictions of the total energy of solid solution binary alloys. GCNNs allow us to abstract the lattice structure of a solid material as a graph, whereby atoms are modeled as nodes and metallic bonds as edges. This representation naturally incorporates information about the structure of the material, thereby eliminating the need for computationally expensive data pre-processing which would be required with standard neural network (NN) approaches. We train GCNNs on ab-initio density functional theory (DFT) for copper-gold (CuAu) and iron-platinum (FePt) data that has been generated by running the LSMS-3 code, which implements a locally self-consistent multiple scattering method, on OLCF supercomputers Titan and Summit. GCNN outperforms the ab-initio DFT simulation by orders of magnitude in terms of computational time to produce the estimate of the total energy for a given atomic configuration of the lattice structure. We compare the predictive performance of GCNN models against a standard NN such as dense feedforward multi-layer perceptron (MLP) by using the root-mean-squared errors to quantify the predictive quality of the deep learning (DL) models. We find that the attainable accuracy of GCNNs is at least an order of magnitude better than that of the MLP.

Lupo Pasini, Massimiliano↗
DOE OSTI2021

Ultra-large-scale ab initio quantum chemical computation of bio-molecular systems: The case of spike protein of SARS-CoV-2 virus

The COVID-19 pandemic poses a severe threat to human health with an unprecedented social and economic disruption. Spike (S) glycoprotein of the SARS-CoV-2 virus is pivotal in understanding the virus anatomy, since it initiates the first contact with the ACE2 receptor in the human cell. We report results of ab initio computation of the spike protein, the largest ab initio quantum chemical computation to date on any bio-molecular system, using a divide and conquer strategy by focusing on individual structural domains. In this approach we divided the S-protein into seven structural domains: N-terminal domain (NTD), receptor binding domain (RBD), subdomain 1 (SD1), subdomain 2 (SD2), fusion peptide (FP), heptad repeat 1 with central helix (HR1-CH) and connector domain (CD). The entire Chain A has 14,488 atoms including the hydrogen atoms but excluding the amino acids with missing coordinates based on the PDB data (ID: 6VSB). The results include structural refinement, ab initio calculation of intramolecular bonding mechanism, 3- dimensional non-local inter-amino acid interaction with implications for the inter-domain interaction. Details of the electronic structure, interatomic bonding, partial charge distribution and the role played by hydrogen bond network are discussed. In the interaction among structural domains, we present new insights for crucial hinge-like movement and fusion process. Extension of such calculation to the interface between the S-protein binding domain and ACE2 receptor can provide a pathway for computational understanding of mutations and the design of therapeutic drugs to combat the COVID-19 pandemic.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Halo effective field theory analysis of one-neutron knockout reactions of Be 11 and C 15

Background: One-nucleon knockout reactions provide insightful information on the single-particle structure of nuclei. When applied to one-neutron halo nuclei, they are purely peripheral, suggesting that they could be properly modeled by describing the projectile within a halo effective field theory (halo-EFT). Purpose: We reanalyze the one-neutron knockout measurements of 11 Be and 15 C —both one-neutron halo nuclei—on beryllium at about 60 MeV/nucleon. We consider halo-EFT descriptions of these nuclei which already provide excellent agreement with breakup and transfer data. Method: Here we include a halo-EFT description of the projectile within an eikonal-based model of the reaction and compare its outcome to existing data. Results: Excellent agreement with experiment is found for both nuclei. The asymptotic normalization coefficients inferred from this comparison confirm predictions from ab initio nuclear-structure calculations and values deduced from transfer data. Conclusions: Halo-EFT can be reliably used to analyze one-neutron knockout reactions measured for halo nuclei and test predictions from state-of-the-art nuclear structure models on these experimental data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Machine learning approach to pattern recognition in nuclear dynamics from the ab initio symmetry-adapted no-core shell model

A novel machine learning approach is used to provide further insight into atomic nuclei and to detect orderly patterns amid a vast data of large-scale calculations. The method utilizes a neural network that is trained on ab initio results from the symmetry-adapted no-core shell model (SA-NCSM) for light nuclei. We show that the SA-NCSM, which expands ab initio applications up to medium-mass nuclei by using dominant symmetries of nuclear dynamics, can reach heavier nuclei when coupled with the machine learning approach. In particular, we find that a neural network trained on probability amplitudes for s- and p-shell nuclear wave functions not only predicts dominant configurations for heavier nuclei but in addition, when tested for the 20 Ne ground state, accurately reproduces the probability distribution. The non-negligible configurations predicted by the network provide an important input to the SA-NCSM for reducing ultralarge model spaces to manageable sizes that can be, in turn, utilized in SA-NCSM calculations to obtain accurate observables. The neural network is capable of describing nuclear deformation and is used to track the shape evolution along the 20-42 Mg isotopic chain, suggesting a shape coexistence that is more pronounced toward the very neutron-rich isotopes. We provide first descriptions of the structure and deformation of 24 Si and 40 Mg of interest to x-ray burst nucleosynthesis, and even of the extremely heavy nuclei such as 166,168 Er and 236 U, that build on first-principles considerations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Exploring NaCl-PuCl 3 molten salts with machine learning interatomic potentials and graph theory

Actinide molten salts are the basis of the liquid fuels used in molten salt reactors. Due to the inherent difficulties associated with high temperature and hazardous conditions, experimental investigations of fundamental properties of these materials are usually challenging. In this work, we describe the structure and transport of NaCl-PuCl 3 mixtures using computational techniques. Three compositions were considered (16, 25, and 36 mol% PuCl 3 ) over a temperature range (730 – 1257K) using ab initio molecular dynamics, which provided the necessary data sets for training machine learned interatomic potentials. Further, molecular dynamics simulations based on these potentials were then used to determine structure and transport properties. A substantial change was noted in the structure factor when increasing the PuCl 3 content from 25 to 36 mol%. This change is linked to the aggregation of larger Pu 3+ clusters. In addition, the similarity of the atomic environments of metal cations in molten salt systems to their solid states counterparts was investigated using an unsupervised learning technique. Finally, graph theory was employed to explore the structure and size of actinide networks. Consistent with the structure factor, a dense Pu 3+ intermolecular structure is observed within the 36 mol% PuCl 3 mixture. The structure of cation-cation inter-junctions is also discussed. In all cases, the diffusion of Pu 3+ is significantly lower than that of Na + and Cl - .

36 MATERIALS SCIENCE↗
DOE OSTI2018

Analytic model of the γ -surface deviation and influence on the stacking fault width between partial dislocations

The stacking fault width (R$_{eq}$) between partial dislocations within an FCC crystalline lattice characterizes the onset of numerous plastic flow mechanisms, as well as the relationship between material strength and grain size. Continuum models traditionally consider a complete unit of dislocation slip ( b ) along the $\langle{110}$$\rangle$ direction distributed between two discrete partial dislocations, each with a fixed partial Burgers vector ( b p ), which bound a stacking fault. Across the stacking fault, the vectorial slip is assumed to be constant, yielding a constant intrinsic stacking fault energy density, $\gamma$$_{isf}$ Here, we demonstrate that the vectorial displacement path taken in accomplishing a complete unit of slip (b) deviates from the expected displacement path containing the local minima, $\gamma$$_{isf}$ leading to a correction in the nominally derived stacking fault width. The magnitude of the correction depends on both the net orientation of the dislocation within the lattice, and also the degree of relaxation of each partial Burgers vector along the $\langle{\bar{1}12}$$\rangle$ direction. We derive a simple analytic model for the corrected stacking fault width, explicitly accounting for the deviation, by introducing a variable ξ (0 < ξ < 1), which governs the magnitude of each partial dislocation component along the $\langle{\bar{1}12}$$\rangle$ direction. Significantly, our model predicts a correction to R$_{eq}$ of ~$\mathscr{O}$ (|b|) for the nominally screw dislocation, and has no noticeable influence on nominally edge dislocations. We apply our model towards computing the stacking fault width of several FCC metals, and demonstrate excellent agreement both with our own numerical data as well as that obtained from ab initio and Molecular Statics (MS) methods within the literature. Lastly, the results from this study demonstrate that, upon judicious application, discrete linear elastic models are successful in reproducing elastic interactions as computed from higher fidelity models on the spatial scale of metallic dislocation cores.

36 MATERIALS SCIENCE↗