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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 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
NASA NTRS1978

A simple formula for estimating Stark widths of neutral lines

A simple formula for the prediction of Stark widths of neutral lines similar to the semiempirical method of Griem (1968) for ion lines is presented. This formula is a simplification of the quantum-mechanical classical path impact theory and can be used for complicated atoms for which detailed calculations are not readily available, provided that the effective position of the closest interacting level is known. The expression does not require the use of a computer. The formula has been applied to a limited number of neutral lines of interest, and the width obtained is compared with the much more complete calculations of Bennett and Griem (1971). The agreement generally is well within 50% of the published value for the lines investigated. Comparisons with other formulas are also made. In addition, a simple estimate for the ion-broadening parameter is given.

Freudenstein, S. A.↗
NASA NTRS1980

A study of the cleft region using synoptic ionospheric plasma data obtained by the polar orbiting satellites Aeros-B and Isis-2

The concentrations of O(+) and NO(+) in the dayside high-latitude cleft region of the ionosphere are investigated based on synoptic particle and plasma measurements obtained by the polar orbiting Aeros-B and Isis-2 satellites. At a time when the orbital planes of the satellites are almost at right angles to each other, three maxima in ion temperature are observed, with two of them accompanied by an increased electron temperature and electron density irregularities, and the density of the molecular ions NO(+) and O2(+) is found to increase at the expense of O(+) density. Results are discussed in terms of a theory relating perpendicular electric fields to oxygen atom reaction rates. Systematic analysis of the Aeros data base reveals 14 additional instances of O(+) to NO(+) conversion, with a large variety of forms and structures reflecting the complex structure and dynamics of the high-latitude dayside ionosphere.

Kist, R.↗
NASA NTRS1992

Investigations on atomic-vapor-filter high-spectral-resolution lidar for temperature measurements

The temperature measurement by the analysis of Rayleigh scattered laser radiation with atomic vapor filters is investigated in both theory and laboratory experiments. Synthetic air is irradiated with a cw dye laser at 283 nano-meters, and the backscattered spectrum is analyzed with two lead vapor cells in one oven. Temperature measurements are carried out, and the effect of different parameters on the accuracy is investigated. Important aspects for the realization of a lidar are given.

Voss, E.↗
NASA NTRS1992

The sodium and potassium atmosphere of the moon and its interaction with the surface

Results are presented from Apollo satellite observations (from May 1988 to July 1991) of sodium and potassium in the lunar atmosphere. The observations of Na and K show a wide range of scale heights, single-component temperatures, and surface number densities, while the column abundances remain within a factor of 3. The observed trends can be explained using a model of competing release mechanisms with different dependences on solar zenith angle and resulting two-component atmospheres. The theory is applied to the budget of atomic oxygen.

Sprague, A. L.↗
NASA NTRS1995

A Comparison of the Accuracy of Different Functionals

The errors in the computed geometries, zero-point energies, and atomization energies of molecules containing only first and second row atoms are compared for several levels of theory, including Hartree-Fock, second-order Moller-Plesset perturbation theory (MP2), and density functional theory (DFT) using five different functionals, including two hybrid functionals. The 6-31G* and 6-311+G(3df,2p) basis set are used. Overall, the B3LYP hybrid functional yields the best results.

Bauschlicher, Charles W., Jr.↗
NASA NTRS2018

Aladyn - Adaptive Neural Network Molecular Dynamics Simulation Code: Computational Materials Mini-Application

This report provides an overview and commands description of the Computational Materials mini-application, Aladyn. Aladyn is a simple molecular dynamics code written in FORTRAN 2008, which is designed to demonstrate the use of adaptive neural networks (ANNs) in atomistic simulations. The role of ANNs is to reproduce the very complex energy landscape resulting from the atomic interactions in materials with the accuracy of quantum mechanics-based energy calculations. The ANN is trained on a large set of atomic structures calculated using the density functional theory (DFT) method. The Aladyn code is being released to serve as a training testbed for students and professors in academia to explore possible optimization algorithms for parallel computing on multicore central processing unit (CPU) computers or computers utilizing many core architectures based on graphic processing units (GPUs). The effort is related to the High Performance Computing Incubator (HPCI) project at NASA Langley Research Center.

Yamakov, Vesselin I.↗
NASA NTRS2022

Evaluating Mineral Lattices as Evolutionary Proxies for Metalloprotein Evolution

Protein coordinated iron-sulfur clusters drive electron flow within metabolic pathways for organisms throughout the tree of life. It is not known how iron-sulfur clusters were first incorporated into proteins. Structural analogies to iron-sulfde minerals present on early Earth, suggest a connection in the evolution of both proteins and minerals. The availability of large protein and mineral crystallographic structure data sets, provides an opportunity to explore co-evolution of proteins and minerals on a large-scale using informatics approaches. However, quantitative comparisons are confounded by the infnite, repeating nature of the mineral lattice, in contrast to metal clusters in proteins, which are fnite in size. We address this problem using the Niggli reduction to transform a mineral lattice to a fnite, unique structure that when translated reproduces the crystal lattice. Protein and reduced mineral structures were represented as quotient graphs with the edges and nodes corresponding to bonds and atoms, respectively. We developed a graph theory-based method to calculate the maximum common connected edge subgraph (MCCES) between mineral and protein quotient graphs. MCCES can accommodate differences in structural volumes and easily allows additional chemical criteria to be considered when calculating similarity. To account for graph size differences, we use the Tversky similarity index. Using consistent criteria, we found little similarity between putative ancient iron-sulfur protein clusters and iron-sulfur mineral lattices, suggesting these metal sites are not as evolutionarily connected as once thought. We discuss possible evolutionary implications of these findings in addition to suggesting an alternative proxy, mineral surfaces, for better understanding the coevolution of the geosphere and biosphere

Kenneth N. McGuinness↗
DOE OSTI2020

Facile and quantitative estimation of strain in nanobubbles with arbitrary symmetry in 2D semiconductors verified using hyperspectral nano-optical imaging

When layers of van der Waals materials are deposited via exfoliation or viscoelastic stamping, nanobubbles are sometimes created from aggregated trapped fluids. Though they can be considered a nuisance, nanobubbles have attracted scientific interest in their own right owing to their ability to generate large in-plane strain gradients that lead to rich optoelectronic phenomena, especially in the semiconducting transition metal dichalcogenides. Determination of the strain within the nanobubbles, which is crucial to understanding these effects, can be approximated using elasticity theory. However, the Föppl–von Kármán equations that describe strain in a distorted thin plate are highly nonlinear and often necessitate assuming circular symmetry to achieve an analytical solution. Here, we present an easily implemented numerical method to solve for strain tensors of nanobubbles with arbitrary symmetry in 2D crystals. The method only requires topographic information from atomic force microscopy and the Poisson ratio of the 2D material. We verify that this method reproduces the strain for circularly symmetric nanobubbles that have known analytical solutions. Finally, we use the method to reproduce the Grüneisen parameter of the E' mode for 1L-WS2 nanobubbles on template-stripped Au by comparing the derived strain with measured Raman shifts from tip-enhanced Raman spectroscopy, demonstrating the utility of our method for estimating localized strain in 2D crystals.

2D materials↗
DOE OSTI2025

Competition between Hydrogen and Chalcogen Bonding in Homodimers of Chalcogen Hydrides (H 2 X) 2 , X = O, S, Se, Te

The structural and chemical bonding motifs manifested by the competition between hydrogen and chalcogen bonding in the homodimers of chalcogen hydrides (H 2 X) 2 , where X = O, S, Se, Te have been characterized using high-level electronic structure calculations and analysis of the electron density based on Quasi-atomic orbital (QUAO) and the Symmetry-adapted perturbation theory (SAPT) methods. The QUAO analysis clearly identifies a three-center interaction responsible for either hydrogen or chalcogen bonds: in the former, the σ-bond connecting the donor and hydrogen atom participating in the hydrogen bond interacts with the lone pair on the nucleophile acceptor via the hydrogen atom, while in the latter this same σ-bond interacts with the nucleophile lone pair via the donor chalcogen. The number of minimum energy structures increase dramatically from one for (H 2 O) 2 , three for (H 2 S) 2 , four for (H 2 Se) 2 , and finally six for (H 2 Te) 2 . Furthermore, the emergence of the chalcogen-bonded arrangements appears for (H 2 S) 2 with their subsequent energetic stabilization over the hydrogen-bonded minima manifesting in (H 2 Se) 2 and (H 2 Te) 2 . In particular, one of the (H 2 S) 2 , two of the (H 2 Se) 2 , and three of the (H 2 Te) 2 dimers are chalcogen bonded. Induction plays a small but important role in stabilizing hydrogen over chalcogen-bonded structures, while dispersion is more important for chalcogen bonds.

Chemical structure↗
DOE OSTI2021

Atomic-Scale Investigation of Oxidation at the Black Phosphorus Surface

Black phosphorus (BP) exhibits extraordinary electronic properties that are desirable for a wide variety of electronic and optoelectronic applications. However, applications of BP are hindered by its rapid degradation in ambient conditions. Despite significant advances that have been made in understanding the degradation mechanism, no consensus has yet been reached on how BP oxidation occurs at the atomic scale as experimental studies have been mostly restricted to averaged effects of degradation over a micron- to millimeter-sized region. Here, BP oxidation is investigated using scanning tunneling microscopy/spectroscopy (STM/S). Introducing O 2 gas to the BP surface in ultrahigh vacuum at a pressure of 10 –5 mbar for 1 min creates two new types of defects on the surface. We identify these defects as dangling atomic oxygen and phosphorus multivacancies using density functional theory simulations. In addition to the structural changes to the surface, the electronic structure is also drastically altered by the introduction of oxygen. The 300 meV band gap of BP is lifted due to dosing. This change in the electronic structure is reversible through STM tip manipulation. As a result, these are the first experimental results showing the atomic-scale oxidation of BP, an important step toward understanding the degradation process

2D materials↗
DOE OSTI2023

Tailoring the Near-Surface Environment of Rh Single-Atom Catalysts for Selective CO 2 Hydrogenation

For this study, we used a combination of experimental spectroscopies, density functional theory calculations, and CO 2 hydrogenation studies to investigate the effects of modifying single-atom Rh 1 /TiO 2 catalysts with functionalized phosphonic acid monolayers. We found that the deposition of specific amine-functionalized ligands resulted in an ~8× increase in site-specific CO 2 reduction turnover frequency at 150 °C and a ~2× increase at 250 °C. On-stream stability also improved following ligand deposition. The effect of the modifier on reactivity was highly sensitive to the proximity of the amine functional group to the surface, which was controlled by adjusting the length of the phosphonic acid tail. Furthermore, deposition of alkyl phosphonic acids without an amine functional group resulted in blocked CO 2 adsorption and a near-complete loss of catalytic activity. Infrared spectroscopy studies suggested that the amine group provided binding sites for CO 2 that enabled hydrogenation when the amine was positioned near a Rh1 site. Phosphonic acid-modified catalysts also exhibited high selectivity to CO over the series product methane; the selectivity effect was traced to modification of the Rh1 sites to favor CO desorption. Phosphonic acid deposition resulted in 80–90% loss of accessible Rh1 sites, likely due to blocking by tail groups. However, even with the loss of sites, under low-temperature reaction conditions, the rates of CO 2 hydrogenation were improved with the coatings, indicating that the remaining sites are highly efficient. Organic functionalization of the supports for atomically dispersed catalysts offers the opportunity to precisely control the positioning of functional groups in the vicinity of a well-defined active site, potentially enabling an additional level of control over active site design.

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

Incorporating Electronic Information into Machine Learning Potential Energy Surfaces via Approaching the Ground-State Electronic Energy as a Function of Atom-Based Electronic Populations

Machine learning (ML) approximations to density functional theory (DFT) potential energy surfaces (PESs) are showing great promise for reducing the computational cost of accurate molecular simulations, but at present, they are not applicable to varying electronic states, and in particular, they are not well suited for molecular systems in which the local electronic structure is sensitive to the medium to long-range electronic environment. With this issue as the focal point, we present a new machine learning approach called "BpopNN" for obtaining efficient approximations to DFT PESs. Conceptually, the methodology is based on approaching the true DFT energy as a function of electron populations on atoms; in practice, this is realized with available density functionals and constrained DFT (CDFT). Additionally, the new approach creates approximations to this function with neural networks. These approximations thereby incorporate electronic information naturally into a ML approach, and optimizing the model energy with respect to populations allows the electronic terms to self-consistently adapt to the environment, as in DFT. We confirm the effectiveness of this approach with a variety of calculations on LinHn clusters.

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

Retrieval of the molecular orientation distribution from atom-pair angular distributions

Imaging laser-induced rotational dynamics is an important and active field due to its applications in capturing reactions in the molecular frame and in molecular imaging. Experimental measurement of the molecular orientation distribution, as a function of the Euler angles, has only been demonstrated for special cases when the detectable signal is generated along the molecular symmetry axis. Here we developed the general theory that maps the probability density distribution of the molecular orientation to the atom-pair angular distributions for nonlinear molecules. With the theory, the molecular orientation distribution can be retrieved from the measured atom-pair angular distribution, which we demonstrate experimentally using ultrafast electron diffractive imaging of impulsively aligned trifluoro-iodomethane molecules. Here, the retrieved molecular orientation distribution is in good agreement with direct numerical simulations of the time-dependent Schrodinger equation using the experimental conditions. Unlike the existing retrieval methods, the retrieval method does not require solving Schrodinger equation, works for any alignment method, and is in principle applicable to asymmetric top molecules.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2025

Ca X ML: Chemistry‐informed machine learning explains mutual changes between protein conformations and calcium ions in calcium‐binding proteins using structural and topological features

Proteins' flexibility is a feature in communicating changes in cell signaling instigated by binding with secondary messengers, such as calcium ions, associated with the coordination of muscle contraction, neurotransmitter release, and gene expression. When binding with the disordered parts of a protein, calcium ions must balance their charge states with the shape of calcium-binding proteins and their versatile pool of partners depending on the circumstances they transmit. Accurately determining the ionic charges of those ions is essential for understanding their role in such processes. However, it is unclear whether the limited experimental data available can be effectively used to train models to accurately predict the charges of calcium-binding protein variants. Here, we developed a chemistry-informed, machine-learning algorithm that implements a game theoretic approach to explain the output of a machine-learning model without the prerequisite of an excessively large database for high-performance prediction of atomic charges. We used the ab initio electronic structure data representing calcium ions and the structures of the disordered segments of calcium-binding peptides with surrounding water molecules to train several explainable models. Network theory was used to extract the topological features of atomic interactions in the structurally complex data dictated by the coordination chemistry of a calcium ion, a potent indicator of its charge state in protein. Our design created a computational tool of Ca X ML, which provided a framework of explainable machine learning model to annotate ionic charges of calcium ions in calcium-binding proteins in response to the chemical changes in an environment. Our framework will provide new insights into protein design for engineering functionality based on the limited size of scientific data in a genome space.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Theoretical Calculation Guided Design of Single-Atom Catalysts toward Fast Kinetic and Long-Life Li–S Batteries

Lithium–sulfur (Li–S) batteries are enticing next-generation energy storage technologies due to their high theoretical energy density, environmental friendliness, and low cost. Yet, low conductivity of sulfur species, dissolution of polysulfides, poor conversion from sulfur reduction, and lithium sulfide (Li 2 S) oxidation reactions during discharge–charge processes hinder their practical applications. Herein, under the guidance of density functional theory calculations, we have successfully synthesized large-scale single atom vanadium catalysts seeded on graphene to achieve high sulfur content (80 wt % sulfur), fast kinetic (a capacity of 645 mAh g –1 at 3 C rate), and long-life Li–S batteries. Both forward (sulfur reduction) and reverse reactions (Li 2 S oxidation) are significantly improved by the single atom catalysts. This finding is confirmed by experimental results and consistent with theoretical calculations. The ability of single metal atoms to effectively trap the dissolved lithium polysulfides (LiPSs) and catalytically convert the LiPSs/Li 2 S during cycling significantly improved sulfur utilization, rate capability, and cycling life. Our work demonstrates an efficient design pathway for single atom catalysts and offers solutions for the development of high energy/power density Li–S batteries.

25 ENERGY STORAGE↗
DOE OSTI2024

Effects of carbon concentration on the local atomic structure of amorphous GST

Ge-Sb-Te (GST) alloys are leading phase-change materials for data storage due to the fast phase transition between amorphous and crystalline states. Ongoing research aims at improving the stability of the amorphous phase to improve retention. This can be accomplished by the introduction of carbon as a dopant to Ge 2 Sb 2 Te 5 , which is known to alter the short- and mid-range structure of the amorphous phase and form covalently bonded C clusters, both of which hinder crystallization. The relative importance of these processes as a function of C concentration is not known. Here we used molecular dynamics simulation based on density functional theory to study how carbon doping affects the atomic structure of GST-C. Carbon doping results in an increase in tetrahedral coordination, especially of Ge atoms, and this is known to stabilize the amorphous phase. We observe an unexpected, non-monotonous trend in the number of tetrahedral bonded Ge with the amount of carbon doping. Our simulations show an increase in the number of tetrahedral bonded Ge up to 5 at.% C, after which the number saturates and begins to decrease above 14 at.% C. The carbon atoms aggregate into clusters, mostly in the form of chains and graphene flakes, leaving less carbon to disrupt the GST matrix at higher carbon concentrations. Different degrees of carbon clustering can explain divergent experimental results for recrystallization temperature for carbon doped GST.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗