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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 829 records · Page 46
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Probing lead acetate in solution using X-ray diffraction

Here, for the purpose of water purification involving toxic metal sensing and removal, high energy X-ray diffraction experiments have been performed on lead acetate Pb(Ac) 2 solutions, liquid and amorphous glutathione disulfide (GSSG), and their mixtures. The data have been interpreted using Empirical Potential Structure Refinement and pair distribution function analysis. At the highest concentration of 1 M Pb(Ac) 2 in water, the lead molecules are found to cluster and the second shell in the water structure becomes slightly more ordered as the water molecules become compressed. Liquid and amorphous GSSG are found to hydrogen bond primarily via OH-O interactions, while NH-O bonds are much more distorted. Aqueous solutions of Pb(Ac) 2 + GSSG show the closest Pb-O (carboxyl) and Pb-N (amine) bonds both at a distance of 2.5 ± 0.1 Å at a concentration of 1 M Pb(Ac) 2 in water. At 0.75 M Pb(Ac) 2 in water, strong Pb-S bonds are found at a distance of 2.8 ± 0.1 Å. The implications for lead removal using capacitive deionization are discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1984

The size of clusters in a neutrino-dominated universe

Quite soon after the first collapse of structure, almost half the matter in a neutrino-dominated universe is expected to reside in clusters. The masses and binding energies of these neutrino clusters are too large for them to be identified with observed galaxy clusters. Even if such objects were able to suppress all galaxy formation, their X-ray emission would, however, make them highly visible if more than 2.5 percent of their mass was in ordinary matter. Such a low baryon density leads to insuffient cooling for galaxies to form in pancakes. A neutrino-dominated universe appears to conflict with observation irrespective of the details of the processes which govern galaxy formation.

White, S. D. M.↗
NASA NTRS1991

Using Gaussian windows to explore a multivariate data set

In an earlier paper, I recounted an exploratory analysis, using Gaussian windows, of a data set derived from the Infrared Astronomical Satellite. Here, my goals are to develop strategies for finding structural features in a data set in a many-dimensional space, and to find ways to describe the shape of such a data set. After a brief review of Gaussian windows, I describe the current implementation of the method. I give some ways of describing features that we might find in the data, such as clusters and saddle points, and also extended structures such as a 'bar', which is an essentially one-dimensional concentration of data points. I then define a distance function, which I use to determine which data points are 'associated' with a feature. Data points not associated with any feature are called 'outliers'. I then explore the data set, giving the strategies that I used and quantitative descriptions of the features that I found, including clusters, bars, and a saddle point. I tried to use strategies and procedures that could, in principle, be used in any number of dimensions.

Jaeckel, Louis A.↗
DOE OSTI2021

Structural Manipulation of a Zirconocene-Based Porous Coordination Cage Using External and Host–Guest Stimuli

Porous coordination cages (PCCs) constructed from a zirconocene-based cluster have drawn great attention for their high stability and structural tunability. These features have enabled these cages to be utilized for a wide array of applications. Here this work demonstrates the structural flexibility and stimulus-responsive features of two interconvertible zirconocene-based PCCs. The subjects, PCC-20c (capsular) and PCC-20t (tetrahedral), are constructed from the same cluster and ligand but exhibit different shapes and properties. In the synthetic study of the cages, it is found that higher temperatures of synthesis yield PCC-20c in several different crystalline phases while lower temperatures of synthesis yield pure phase PCC-20t. Thermodynamic studies on the interconversion of the two cages show that the conversion from PCC-20t into PCC-20c is an entropically driven process and can be largely affected by the solvent environment. Additionally, the process of PCC-20t/c conversion can be mediated by the counter anions and light irradiation as evidenced by the change in equilibrium constants under these influences. The current studies are conducted to decipher how the PCC-20t/c phase can be controllably synthesized, interconverted, and their properties can be modified under the use of external stimuli: heat, light, and guest molecules.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A Many-Body Perspective of Nuclear Quantum Effects in Aqueous Clusters

Nuclear quantum effects play an important role in the structure and thermodynamics of aqueous systems. Here, by performing a many-body expansion with nuclear-electronic orbital (NEO) theory, we show that proton quantization can give rise to significant energetic contributions for many-body interactions spanning several molecules in single-point energy calculations of water clusters. Although zero-point motion produces a large increase in energy at the one-body level, nuclear quantum effects serve to stabilize higher-order molecular interactions. These results are significant because they demonstrate that nuclear quantum effects play a nontrivial role in many-body interactions of aqueous systems. Our approach also provides a pathway for incorporating nuclear quantum effects into water potential energy surfaces. The NEO approach is advantageous for many-body expansion analyses because it includes nuclear quantum effects directly in the energies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1980

Carbon Fibers Conductivity Studies

In an attempt to understand the process of electrical conduction in polyacrylonitrile (PAN)-based carbon fibers, calculations were carried out on cluster models of the fiber consisting of carbon, nitrogen, and hydrogen atoms using the modified intermediate neglect of differential overlap (MINDO) molecular orbital (MO) method. The models were developed based on the assumption that PAN carbon fibers obtained with heat treatment temperatures (HTT) below 1000 C retain nitrogen in a graphite-like lattice. For clusters modeling an edge nitrogen site, analysis of the occupied MO's indicated an electron distribution similar to that of graphite. A similar analysis for the somewhat less stable interior nitrogen site revealed a partially localized II electron distribution around the nitrogen atom. The differences in bonding trends and structural stability between edge and interior nitrogen clusters led to a two-step process proposed for nitrogen evolution with increasing HTT.

Yang, C. Y.↗
DOE OSTI2024

Towards quantifying the impact of triaxiality on optical signatures of galaxy clusters: weak lensing and galaxy distributions

ABSTRACT We present observational evidence of the impact of triaxiality on radial profiles that extend to 40 Mpc from galaxy cluster centres in optical measurements. We perform a stacked profile analysis from a sample of thousands of nearly relaxed galaxy clusters from public data releases of the Dark Energy Survey and the Dark Energy Camera Legacy Survey. Using the central galaxy elliptical orientation angle as a proxy for galaxy cluster orientation, we measure cluster weak lensing and excess galaxy density axis-aligned profiles, extracted along the central galaxy’s major or minor axes on the plane of the sky. Our measurements show a ≳ 2σ–3σ difference per radial bin between the normalized axis-aligned profiles. The profile difference between each axis-aligned profile and the azimuthally averaged profile ($\sim \pm 10\,\rm per\ cent-20~{{\ \rm per\ cent}}$ along major/minor axis) appears inside the clusters (∼0.4 Mpc) and extends to the large-scale structure regime (∼10–20 Mpc). The magnitude of the difference appears to be relatively insensitive to cluster richness and redshift, and extends further out in the weak lensing surface mass density than in the galaxy overdensity. Looking forward, this measurement can easily be applied to other observational or simulation data sets and can inform the systematics in cluster mass modelling related to triaxiality. We expect imminent upcoming wide-area deep surveys, such as the Vera C. Rubin Observatory’s Legacy Survey of Space and Time, to improve our quantification of optical signatures of cluster triaxiality.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

The SRG/eROSITA All-Sky Survey: Constraints on ultralight axion dark matter through galaxy cluster number counts

Ultralight axions are hypothetical scalar particles that influence the evolution of large-scale structures of the Universe. Depending on their mass, they can potentially be part of the dark matter component of the Universe as candidates commonly referred to as fuzzy dark matter. While strong constraints have been established for pure fuzzy dark matter models, the more general scenario where ultralight axions constitute only a fraction of the dark matter has been limited to only a few observational probes. In this work, we use the galaxy cluster number counts obtained from the first All-Sky Survey (eRASS1) of the SRG/eROSITA mission together with gravitational weak lensing data from the Dark Energy Survey, the Kilo-Degree Survey, and the Hyper Suprime-Cam to constrain the fraction of ultralight axions in the mass range 10 −32 eV to 10 −24 eV. We put upper bounds on the ultralight axion relic density Ω a in independent logarithmic axion mass bins by performing a full cosmological parameter inference. We find an exclusion region in the intermediate ultralight axion mass regime with the tightest bounds reported so far in the mass bins around m a = 10 −27 eV with Ω a < 0.0035 and m a = 10 −26 eV with Ω a < 0.0079; both are at a 95% confidence level. When combined with cosmic microwave background probes, these bounds are tightened to Ω a < 0.0030 in the m a = 10 −27 eV mass bin and Ω a < 0.0058 in the m a = 10 −26 eV mass bin, with both at a 95% confidence level. This is the first time that constraints on ultralight axions have been obtained using the growth of structure measured by galaxy cluster number counts. These results pave the way for large surveys, which can be utilized to obtain tight constraints on the mass and relic density of ultralight axions with better theoretical modeling of the abundance of halos.

cosmological parameters↗
DOE OSTI2023

High-entropy electrolytes for practical lithium metal batteries

Electrolyte engineering is crucial for improving battery performance, particularly for lithium metal batteries. Recent advances in electrolytes have greatly improved cyclability by enhancing electrochemical stability at the electrode interfaces, but concurrently achieving high ionic conductivity has remained challenging. Here we report an electrolyte design strategy for enhanced lithium metal batteries by increasing the molecular diversity in electrolytes, which essentially leads to high entropy electrolytes (HEEs). We find that in weakly solvating electrolytes, the entropy effect reduces ion clustering while preserving the characteristic anion-rich solvation structures, which is characterized by synchrotron-based X-ray scattering and molecular dynamics simulations. Electrolytes with smaller- sized clusters exhibit a 2-fold improvement in ionic conductivity compared to conventional weakly- solvating electrolytes, enabling stable cycling at high current densities up to 2C (6.2 mA cm -2 ) in anode- free LiNi 0.6 Mn 0.2 Co 0.2 (NMC622)||Cu pouch cells. In conclusion, the efficacy of the design strategy is verified by performance improvements in three disparate weakly solvating electrolyte systems.

25 ENERGY STORAGE↗
DOE OSTI2022

Flexibility of the factorized form of the unitary coupled cluster Ansatz

The factorized form of the unitary coupled cluster Ansatz is a popular state preparation Ansatz for electronic structure calculations of molecules on quantum computers. It is often viewed as an approximation (based on the Trotter product formula) for the conventional unitary coupled cluster operator. In this work, we show that the factorized form is quite flexible, allowing one to range from a conventional configuration interaction, to conventional unitary coupled cluster, to efficient approximations that lie in between these two. The variational minimization of the energy often allows simpler factorized unitary coupled cluster approximations to achieve high accuracy, even if they do not accurately approximate the Trotter product formula. This is similar to how quantum approximate optimization algorithms can achieve high accuracy with a small number of levels.

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

Direct observation of ultrafast cluster dynamics in supercritical carbon dioxide using X-ray Photon Correlation Spectroscopy

Supercritical fluids exhibit distinct thermodynamic and transport properties, making them of particular interest for a wide range of scientific and engineering applications. These anomalous properties emerge from structural heterogeneities due to the formation of molecular clusters at conditions above the critical point. While the static behavior of these clusters and their effects on the thermodynamic response functions have been recognized, the relation between the ultrafast cluster dynamics and transport properties remains elusive. By measuring the intermediate scattering function in carbon dioxide at conditions near the critical point with X-ray photon correlation spectroscopy, we directly capture the cross-over dynamics between 4 and 13 picoseconds, revealing the transition between ballistic and diffusive motion. Complementary analysis using large-scale molecular dynamics simulations reveals that this behavior arises from collisions between unbound molecules and clusters. This study provides direct evidence of the ultrafast momentum exchange between clusters, which has significant impact on transport properties, solvation processes, and reaction kinetics in supercritical fluids.

carbon capture and storage↗
DOE OSTI2023

Electronic structure theory on modeling short-range noncovalent interactions between amino acids

While short-range noncovalent interactions (NCIs) are proving to be of importance in many chemical and biological systems, these atypical bindings happen within the so-called van der Waals envelope and pose an enormous challenge for current computational methods. We introduce SNCIAA, a database of 723 benchmark interaction energies of short-range noncovalent interactions between neutral/charged amino acids originated from protein x-ray crystal structures at the “gold standard” coupled-cluster with singles, doubles, and perturbative triples/complete basis set [CCSD(T)/CBS] level of theory with a mean absolute binding uncertainty less than 0.1 kcal/mol. Subsequently, a systematic assessment of commonly used computational methods, such as the second-order Møller−Plesset theory (MP2), density functional theory (DFT), symmetry-adapted perturbation theory (SAPT), composite electronic-structure methods, semiempirical approaches, and the physical-based potentials with machine learning (IPML) on SNCIAA is carried out. It is shown that the inclusion of dispersion corrections is essential even though these dimers are dominated by electrostatics, such as hydrogen bondings and salt bridges. Overall, MP2, ωB97M-V, and B3LYP+D4 turned out to be the most reliable methods for the description of short-range NCIs even in strongly attractive/repulsive complexes. SAPT is also recommended in describing short-range NCIs only if the δMP2 correction has been included. The good performance of IPML for dimers at close-equilibrium and long-range conditions is not transferable to the short-range. We expect that SNCIAA will assist the development/improvement/validation of computational methods, such as DFT, force-fields, and ML models, in describing NCIs across entire potential energy surfaces (short-, intermediate-, and long-range NCIs) on the same footing.

Chemistry↗
DOE OSTI2024

Composition-Dependent Reconstructions of Titanium Oxide Clusters and Cu(111) Support via Cluster-Adatom Interactions

Mass-selected cluster deposition and scanning tunneling microscopy (STM) were used to investigate the surface structure and thermal stability of Ti 3 O y (y = 5, 6) clusters on a Cu(111) surface. STM imaging shows that the substoichiometric Ti 3 O 5 clusters aggregate into large dendritic assemblies at step edges, while the stoichiometric Ti 3 O 6 clusters are highly dispersed as single or small groupings of clusters. Cluster deposition also results in extensive reconstruction of the Cu(111) surface. The Ti 3 O 5 /Cu(111) surface exhibits one Cu-layer deep pits that are ringed by cluster assemblies that nucleate and grow at the perimeter step edges. By comparison, the Ti 3 O 6 /Cu(111) surface consists of irregular step edges and small one Cu-layer islands that are decorated with clusters. The restructuring of the Cu(111) surface is attributed to strong Cu-cluster interactions that release Cu adatoms from the step edges. This mechanism is supported by density functional theory (DFT) calculations, which predict that the Cu adatom attachment to the clusters is energetically favorable. Annealing the surfaces at elevated temperatures (400-700 K) results in higher densities of irregular steps, pits and isolated Cu islands as well as increased cluster aggregation. In conclusion, this work highlights adatom-cluster interactions as another manifestation of strong cluster-support interactions that can significantly alter the nature of the oxide-metal interface.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2021

Nerpa: A Tool for Discovering Biosynthetic Gene Clusters of Bacterial Nonribosomal Peptides

Microbial natural products are a major source of bioactive compounds for drug discovery. Among these molecules, nonribosomal peptides (NRPs) represent a diverse class of natural products that include antibiotics, immunosuppressants, and anticancer agents. Recent breakthroughs in natural product discovery have revealed the chemical structure of several thousand NRPs. However, biosynthetic gene clusters (BGCs) encoding them are known only for a few hundred compounds. Here, we developed Nerpa, a computational method for the high-throughput discovery of novel BGCs responsible for producing known NRPs. After searching 13,399 representative bacterial genomes from the RefSeq repository against 8368 known NRPs, Nerpa linked 117 BGCs to their products. We further experimentally validated the predicted BGC of ngercheumicin from Photobacterium galatheae via mass spectrometry. Nerpa supports searching new genomes against thousands of known NRP structures, and novel molecular structures against tens of thousands of bacterial genomes. The availability of these tools can enhance our understanding of NRP synthesis and the function of their biosynthetic enzymes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Predicting the chemical space of fungal polyketides by phylogeny-based bioinformatics analysis of polyketide synthase-nonribosomal peptide synthetase and its modification enzymes

Fungal polyketide synthase (PKS)–nonribosomal peptide synthetase (NRPS) hybrids are key enzymes for synthesizing structurally diverse hybrid natural products (NPs) with characteristic biological activities. Predicting their chemical space is of particular importance in the field of natural product chemistry. However, the unexplored programming rule of the PKS module has prevented prediction of its chemical structure based on amino acid sequences. Here, we conducted a phylogenetic analysis of 884 PKS–NRPS hybrids and a modification enzyme analysis of the corresponding biosynthetic gene cluster, revealing a hidden relationship between its genealogy and core structures. This unexpected result allowed us to predict 18 biosynthetic gene cluster (BGC) groups producing known carbon skeletons (number of BGCs; 489) and 11 uncharacterized BGC groups (171). The limited number of carbon skeletons suggests that fungi tend to select PK skeletons for survival during their evolution. The possible involvement of a horizontal gene transfer event leading to the diverse distribution of PKS–NRPS genes among fungal species is also proposed. This study provides insight into the chemical space of fungal PKs and the distribution of their biosynthetic gene clusters.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1985

Preparation and analysis of particulate metal deposits

Small particles and clusters of palladium were grown by deposition from the vapor phase under ultrahigh vacuum conditions. Amorphous and crystalline support films of Al2O3 and ultrathin amorphous carbon films were used as substrate materials. The growth of the metal deposit was monitored in situ by scanning transmission diffraction of energy-filtered 100 kV electrons and high resolution transmission electron microscopy (TEM) analysis was performed in a separate instrument. It was established by in situ TEM, however, that the transfer of specimens in this case did not unduly affect the size and distribution of deposit particles. It was found that the cleanness, stoichiometry, crystallinity and structural perfection of the support surface play an essential role in determining the crystalline perfection and structure of the particles. The smallest palladium clusters reproducibly prepared contained not more than six atoms but size determinations below 1 nm average particle diameter are very problematic with conventional TEM. Palladium particles grown on carbon supports feature an impurity-stabilized mosaic structure.

Poppa, H.↗
DOE OSTI2021

Activity of Cu-Al-oxo extra-framework clusters for selective methane oxidation on Cu exchanged zeolites

Cu-zeolites are able to directly convert methane to methanol via a 3-step process using O2 as oxidant. Among the different zeolite topologies, Cu-exchanged mordenite (MOR) shows the highest methanol yields, attributed to a preferential formation of active Cu-oxo species in its 8-MR pores. The presence of extra-framework or partially detached Al species entrained in the micropores of MOR leads to the formation of nearly homotopic redox active Cu-Al-oxo nanoclusters with the ability to activate CH4. Studies of the activity of these sites together with characterization by 27Al NMR and IR spectroscopy leads to the conclusion that the active species are located in the 8-MR side pockets of MOR and it consists of two Cu ions and one Al linked by O. This Cu-Al oxo cluster shows an activity per Cu in methane oxidation significantly higher than of any previ-ously reported active Cu-oxo species. In order to determine unambiguously the structure of the active Cu-Al-oxo cluster, we combine experimental XANES of Cu K- and L- edges, Cu K-edge HERFD-XANES and Cu K-edge EXAFS with TDDFT and AIMD-assisted simulations. Our results provide evidence of a [Cu2AlO3]2+ cluster exchanged on MOR Al pairs that is able to oxidize up to two methane molecules per cluster at ambient pressure.

Methane oxidation, Cu L3-edge XANES, HERFD, TDDFT,↗
DOE OSTI2025

SAXS Assistant: Automated SAXS analysis for structural discovery in biologics and polymeric nanoparticles

Small-angle x-ray scattering (SAXS) is a powerful technique for assessing macromolecular structure. High-throughput SAXS is limited by the time-consuming and, at times, subjective nature of SAXS data interpretation. Here, we present SAXS Assistant, a Python-based script that streamlines SAXS data analysis to extract features for machine learning (ML) and key structural parameters, including the Guinier radius of gyration (R g ), pair distance distribution function (PDDF)-derived R g , maximum particle dimension (D max ), and Kratky plots. The script builds upon BioXTAS RAW and validates reliability via Guinier/PDDF R g agreement, an important indicator of well-measured data sets. For assistance in D max estimation, a multilayer perceptron regressor was trained with 1940 data files from the Small Angle Scattering Biological Data Bank. The model achieved a test set performance R 2 = 0.90 and mean absolute error = 11.7 Å. Training exclusively with experimental data translates analyses from researchers, including experts in the field, to the ML model, which helps assess D max estimations from PDDF. Gaussian mixture model clustering was implemented to classify profiles into structural classes based on entries in the Small Angle Scattering Biological Data Bank. Users may therefore assess the similarity between experimental samples and known biomolecular shapes within the mapped repository entries. This probabilistic clustering aids in quantifying information from Kratky and generating shape-descriptive features. SAXS Assistant accelerates SAXS data analysis through enforced quality control, ML-ready outputs, and flags for low-confidence results. In addition to providing the ability to analyze large data sets at high throughput, this tool is versatile and may serve researchers in both biological and synthetic polymer research fields.

36 MATERIALS SCIENCE↗