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At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Oxygen Generation via Water Splitting by a Novel Biogenic Metal Ion-Binding Compound

The discovery that MB will couple the oxidation of H 2 O to metal ion reduction and the release of O 2 suggests that methanotrophs expressing MB may be able to maintain their activity under hypoxic/anoxic conditions through the “self-generation” of dioxygen required for the initial oxidation of methane to methanol. Such an ability may be an important factor in enabling methanotrophs to not only colonize the oxic-anoxic interface where methane concentrations are highest but also tolerate significant temporal fluctuations of this interface.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1991

The application of experimental data to blade wake interaction noise prediction

Blade wake interaction noise (BWI) has been defined as the broadband noise generated by the ingestion of turbulent trailing tip vortices by helicopter rotors. This has been shown to be the dominant contributor to the subjectively important part of the acoustic spectrum for the approach stage of a helicopter flyover. A prediction method for BWI noise based on the calculated trailing vortex trajectories has been developed and estimates of the vortex turbulence have been made. These measurements were made on a trailing vortex from a split wing arrangement and did not give the spectrum of the velocity fluctuations. A recent experiment carried out to measure the turbulence associated with a trailing vortex and the application of the results to BWI noise prediction is described.

Glegg, Stewart A. L.↗
DOE OSTI2023

Realization of flat bands by lattice intercalation in kagome metals

Recently there has been intense interest in kagome metals, which are expected to host flat bands (FBs). However, the observed “FBs” are not flat over the whole two-dimensional Brillouin zone and overlap strongly with other bands. In fact, the FB does not truly exist in a default d-orbital kagome lattice, and the conditions for its existence in kagome metals are unknown. Here, based on tight-binding model analyses of the interplay between orbital and lattice symmetry, we establish such conditions. Additionally, we show that for a single d-orbital kagome lattice assuming large crystal field splitting (CFS), only the d z 2 orbital gives rise to a FB, while d xy , d x 2 -y 2 , d x⁢z , and d yz orbitals can only produce a FB with a rotated d-orbital basis so that they conform with the underlying kagome lattice symmetry. Most importantly, we demonstrate that both conditions of d-orbital rotation and large CFS can be ideally satisfied by intercalating the kagome lattice with a hexagonal sublattice without disrupting the destructive interference of FB wave function. Furthermore, we propose layered metalorganic frameworks as promising candidate kagome metals to realize FBs.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Quantum Dynamics of Attractive and Repulsive Polarons in a Doped MoSe 2 Monolayer

When mobile impurities are introduced and coupled to a Fermi sea, new quasiparticles known as Fermi polarons are formed. There are two interesting, yet drastically different regimes of the Fermi polaron problem: (i) the attractive polaron (AP) branch connected to pairing phenomena spanning the crossover from BCS superfluidity to the Bose-Einstein condensation of molecules and (ii) the repulsive branch (RP), which underlies the physics responsible for Stoner’s itinerant ferromagnetism. Here, we study Fermi polarons in two-dimensional systems, where many questions and debates regarding their nature persist. The model system we investigate is a doped MoSe2 monolayer. We find the observed AP-RP energy splitting and the quantum dynamics of attractive polarons agree with the predictions of polaron theory. As the doping density increases, the quantum dephasing of the attractive polarons remains constant, indicative of stable quasiparticles, while the repulsive polaron dephasing rate increases nearly quadratically. The dynamics of Fermi polarons are of critical importance for understanding the pairing and magnetic instabilities that lead to the formation of rich quantum phases found in a wide range of physical systems including nuclei, cold atomic gases, and solids.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Solar Thermochemical Ammonia Production (STAP) (Final Report)

Ammonia (NH 3 ) is an energy-dense chemical and a vital component of fertilizer. In addition, it is a carbon-neutral liquid fuel and a potential candidate for thermochemical energy storage for high-temperature concentrating solar power (CSP). Currently, NH 3 synthesis occurs via the Haber-Bosch process, which requires high pressures (15-25 MPa) and medium to high temperatures (400-500 °C). N 2 and H 2 are essential feedstocks for this NH 3 production process. H 2 is generally derived from methane via steam reforming; N 2 is sourced from air, after oxygen removal via combustion of hydrocarbons. Both processes consume hydrocarbons, resulting in the release of CO 2 . In addition, hydrocarbon fuels are burned to produce the heat and mechanical energy required to perform the NH 3 reaction, further increasing CO 2 emissions. Overall, the production of ammonia via the Haber-Bosch (H-B) process is responsible for up to 1.4% of the world’s carbon emissions. The development of a renewable pathway to NH 3 synthesis, which utilizes concentrated solar irradiation as a process heat instead of fossil fuels and operates under low or ambient pressure, will result in a decrease (or elimination) of greenhouse gas emissions as well as avoid the cost, complexity, and safety issues inherent in high-pressure processes. Most current efforts to “green” ammonia production involve either electrolysis or simply replacing the energy source for H-B with renewable electricity, but otherwise leaving the process intact. The effort proposed here would create a new paradigm for the synthesis of NH 3 utilizing solar-thermal heat, water, and air as feedstocks, providing a truly green method of production. The overall objective of the STAP (Solar Thermal Ammonia Production) project was to develop a solar thermochemical looping technology to produce and store nitrogen (N 2 ) from air for the subsequent production of ammonia (NH 3 ) via an advanced two-stage process. The goal is a cost-effective and energy efficient technology for the renewable N 2 production and synthesis of NH 3 from H 2 (produced from H 2 O) and air using solar-thermal energy from concentrating sunlight, under pressures an order of magnitude lower than H-B NH 3 production. Our process involves two looping cycles, which do not require catalysts and can be recycled. Over the course of the STAP project, we (1) developed and deeply characterized oxide materials for N 2 separation; (2) developed a method for the synthesis of metal nitrides, producing a series of quaternary compounds that have been heretofore unreported; (3) modeled, designed, and fabricated bench-scale tube and on-sun reactors for the N 2 production step and demonstrated the ability to separate N 2 over multiple cycles in the tube reactor; (4) designed and fabricated a bench-scale Ammonia Synthesis Reactor (ASR) and demonstrated the proof of concept of NH 3 synthesis via a novel looping process using metal nitrides over multiple cycles; and (5) completed a systems- and technoeconomic analysis showing the feasibility of ammonia production on a larger scale via the STAP process. The development of renewable, low-cost NH 3 will be of great interest to the chemicals industry, particularly agricultural sectors. The CSP industry should be both an important customer and potential end-user of this technology, as it affords the capability of synthesizing a promising thermochemical storage material on-site. Since the NH 3 synthesis step also requires H 2 , there will exist a symbiotic relationship between this technology and solar-thermochemical water-splitting applications. Green ammonia synthesis will result in the decarbonization of a hydrocarbon-intensive industry, helping to meet the Administration goal of industrial decarbonization by 2050. The resulting decrease in CO 2 and related pollutants will improve health and well-being of society, particularly for those living in the vicinity of commercial production plants.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2003

New Experiment to Measure the Electron Electric Dipole Moment

An electron can possess an electric dipole moment (edm) only if time reversal symmetry (T) is violated. No edm of any particle has yet been discovered. CP-violation, equivalent to T-violation by the CPT theorem, does occur in Kaon decays and can be accounted for by the standard model. However, this mechanism leads to an electron edm d(sub e) of the order of 10(exp -38) e cm, whereas the current experimental bound on d(sub e) is about 10(exp -27) e cm. However, well-motivated extensions of the standard model such as supersymmetric theories do predict that de could be as large as the current bound. In addition, CP violation in the early universe is required to explain the preponderance of matter over anti-matter, but the exact mechanism of this CP violation is unclear. For these reasons, we are undertaking a new experimental program to determine de to an improved accuracy of 10(exp -29) e cm. Our experiment will use laser-cooled, trapped Cesium atoms to measure the atomic edm d(sub Cs) that occurs if d(sub e) is not zero. In order to do this, we will measure the energy splitting between the atoms spin states in parallel electric and magnetic fields. The signature of an edm would be a linear dependence of the splitting on the electric field E due to the interaction - d(sub Cs) dot E. Our measurement will be much more sensitive than previous measurements because atoms can be stored in the trap for tens of seconds, allowing for much narrower Zeeman resonance linewidths. Also, our method eliminates the most important systematic errors, proportional to atomic velocity, which have limited previous experiments. In this presentation, we will describe the design of our new apparatus, which is presently under construction. An important feature of our experimental apparatus is that magnetic field noise will be suppressed to a very low value of the order of 1 fT/(Hz)1/2. This requires careful attention to the Johnson noise currents in the chamber, which have not been important in previous experiments. In addition we will present estimates of the limits of the various errors that we expect for our experiment.

Kittle, Melanie↗
DOE OSTI2020

High-throughput characterization of Ag–V–O nanostructured thin-film materials libraries for photoelectrochemical solar water splitting

Ag–V–O thin-film materials libraries, with both composition (Ag 22-77 V 23-78 O x ) and thickness (123–714 nm) gradients were fabricated using combinatorial reactive magnetron co-sputtering aiming on establishing relations between composition, structure, and functional properties. As-deposited libraries were annealed in air at 300 °C for 10 h. High-throughput characterization methods of composition, structure and functional properties were used to identify photoelectrochemically active regions. The phases AgV 6 O 15 , Ag 2 V 4 O 11 , AgVO 3 , and Ag 4 V 2 O 7 were observed throughout the composition gradient. The photoelectrochemical properties of Ag–V–O films are dependent on composition and morphology. An enhanced photocurrent density (~300–554 μA/cm 2 ) was obtained at 30 to 45 at.% Ag along the thickness gradient. Thin films of these compositions show a nanowire morphology, which is an important factor for the enhancement of photoelectrochemical performance. The photoelectrochemically active regions were further investigated by high-throughput synchrotron-X-ray diffraction and transmission electron microscopy (Ag 32 V 68 O x ) which confirmed the presence of Ag 2 V 4 O 11 as the dominating phase along with the minor phases AgV 6 O 15 and AgVO 3 . This enhanced photoactive region shows bandgap values of ~2.30 eV for the direct and ~1.87 eV for the indirect bandgap energies. Finally, the porous nanostructured films improve charge transport and are hence of interest for photoelectrochemical water splitting.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Photoinduced anomalous Hall effect in two-dimensional transition metal dichalcogenides

A circularly polarized ac pump field illuminated near resonance on two-dimensional transition metal dichalcogenides (TMDs) produces an anomalous Hall effect in response to a dc bias field. In this work, we develop a theory for this photoinduced anomalous Hall effect in undoped TMDs irradiated by a strong coherent laser field. The strong field renormalizes the equilibrium bands and opens up a dynamical energy gap where single-photon resonance occurs. The resulting photon dressed states, or Floquet states, are treated within the rotating-wave approximation. A quantum kinetic equation approach is developed to study the nonequilibrium density matrix and time-averaged transport currents under the simultaneous influence of the strong ac pump field and the weak dc probe field. Dissipative effects are taken into account in the kinetic equation that captures relaxation and dephasing. The photoinduced longitudinal and Hall conductivities display notable resonant signatures when the pump field frequency reaches the spin-split interband transition energies. Rather than valley polarization, we find that the anomalous Hall current is mainly driven by the intraband response of photon-dressed electron populations near the dynamical gap at both valleys, accompanied by a smaller contribution due to the interband response. In conclusion, these findings highlight the importance of photon-dressed bands and nonequilibrium distribution functions in achieving a proper understanding of the photoinduced anomalous Hall effect in a strong pump field.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS2010

On Variable Geometric Factor Systems for Top-Hat Electrostatic Space Plasma Analyzers

Even in the relatively small region of space that is the Earth's magnetosphere, ion and electron fluxes can vary by several orders of magnitude. Top-hat electrostatic analyzers currently do not possess the dynamic range required to sample plasma under all conditions. The purpose of this study was to compare, through computer simulation, three new electrostatic methods that would allow the sensitivity of a sensor to be varied through control of its geometric factor (GF) (much like an aperture on a camera). The methods studied were inner filter plates, split hemispherical analyzer (SHA) and top-cap electrode. This is the first discussion of the filter plate concept and also the first study where all three systems are studied within a common analyzer design, so that their relative merits could be fairly compared. Filter plates were found to have the important advantage that they facilitate the reduction in instrument sensitivity whilst keeping all other instrument parameters constant. However, it was discovered that filter plates have numerous disadvantages that make such a system impracticable for a top-hat electrostatic analyzer. It was found that both the top-cap electrode and SHA are promising variable geometric factor system (VGFS) concepts for implementation into a top-hat electrostatic analyzer, each with distinct advantages over the other.

Kataria, Dhiren O.↗
NASA NTRS2012

Security Data Warehouse Application

The Security Data Warehouse (SDW) is used to aggregate and correlate all JSC IT security data. This includes IT asset inventory such as operating systems and patch levels, users, user logins, remote access dial-in and VPN, and vulnerability tracking and reporting. The correlation of this data allows for an integrated understanding of current security issues and systems by providing this data in a format that associates it to an individual host. The cornerstone of the SDW is its unique host-mapping algorithm that has undergone extensive field tests, and provides a high degree of accuracy. The algorithm comprises two parts. The first part employs fuzzy logic to derive a best-guess host assignment using incomplete sensor data. The second part is logic to identify and correct errors in the database, based on subsequent, more complete data. Host records are automatically split or merged, as appropriate. The process had to be refined and thoroughly tested before the SDW deployment was feasible. Complexity was increased by adding the dimension of time. The SDW correlates all data with its relationship to time. This lends support to forensic investigations, audits, and overall situational awareness. Another important feature of the SDW architecture is that all of the underlying complexities of the data model and host-mapping algorithm are encapsulated in an easy-to-use and understandable Perl language Application Programming Interface (API). This allows the SDW to be quickly augmented with additional sensors using minimal coding and testing. It also supports rapid generation of ad hoc reports and integration with other information systems.

Vernon, Lynn R.↗
DOE OSTI2020

Robustness of Optical Response for Self-Assembled Plasmonic Metamaterials with Morphological Disorder and Surface Roughness

Bottom-up fabrication of metallized biotemplated nanostructures to form specific plasmonic nanoresonators holds promise as a means of achieving large-scale optical metamaterials. However, in contrast to top-down methods, the stochastic growth of self-assembled nanoresonators is prone to significant disorder and surface roughness, which naturally raise an important question about the robustness of their resonant properties in terms of structural imperfections. An aggregated-random-sphere model is developed to mimic the nucleated growth of metallized DNA origami assembly, leading to meta-atoms with realistic, experimentally observed morphological disorder and surface roughness. Using the well-known split-ring-resonator (SRR) motif as an example, the resonant properties of meta-atoms under different levels of roughness are investigated and a strong tolerance of optical response against morphological disorder is revealed. It is found that in SRRs, even with dramatic roughness introduced, the expected resonances are still observed, despite broadening line shapes compared to ideal smooth structure. Only for extreme disorder, which causes drastic segmentation of SRRs, does the resonant response disappear. Finally, the demonstrations are very encouraging for the prospects of bottom-up fabrication toward versatile functional metamaterials and metadevices.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Ne 21 energy levels approaching the α -particle threshold

Nuclei around Ne 20 exhibit an interplay of different excitations caused by different aspects of nuclear structure, including single-particle and multiparticle configurations and collective rotations. One-nucleon transfer reactions selectively probe single-particle structures in these nuclei. These nuclei are also important to astrophysics, with a number of important reactions proceeding through this mass region. Energy levels approaching the α -particle threshold in Ne 21 are of importance to nuclear structure. The Ne 20 ( d , p ) Ne 21 reaction was measured and the corresponding spectroscopic nuclear information was extracted. States in Ne 21 were populated using the Ne 20 ( d , p ) Ne 21 reaction in forward kinematics. Protons were identified in the Triangle Universities Nuclear Laboratory (TUNL) Enge split-pole spectrograph and angular distributions were extracted. Spin-party assignments were made and neutron partial widths were determined based on distorted-wave Born approximation (DWBA) analysis. Several new energy levels were observed at energies of 7176, 7235, 7250, and 7337 keV, and spin-parities are reported which generally agree with previous results where literature was available. Spin and parity assignments are reported for several energy levels along with estimated neutron widths for those states above the neutron threshold ( S n = 6761 keV ). Results from this study are placed in context with a review of the available literature on all known states in this energy region of Ne 21 . Published by the American Physical Society 2024

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Mountain Basin Controls on the Snow-to-Streamflow Signal: An AIC-Weighted Multiple Linear Regression Framework

A regression-based analysis quantifies how basin characteristics modulate the snow-to-streamflow signal. First, we use the ERA5-Land reanalysis gridded product (European Centre for Medium Range Weather Forecasts reanalysis 5 -Land component) for 4,655 hydrologic unit code - 10 (HUC10) mountain basins across the western United States (US) for water years 1987–2024. Linear regressions are performed for peak snow water equivalent (SWE) and annual streamflow for each mountain basin. Models use ordinary least squares in Python’s statsmodels package. After which, an Akaike Information Criterion (AIC)–weighted ensemble multiple linear regression (MLR) framework with 47 watershed traits is used to predict the linear regression coefficient of determination (r-squared) defining the ability of peak SWE to predict annual streamflow across all mountain basin. Predictor sets are constrained to avoid multicollinearity by excluding models with variance inflation factors (VIF) greater than 5. Mountain basin traits included in the MLR include seasonal climate, topography, vegetation type and structure, and bedrock geology. Accepted models are considered if their AIC is within 2.0 of the model with the minimum AIC, or best model. To compare predictor influence across acceptable models, we computed standardized regression coefficients. To evaluate structural redundancy among models, we constructed binary inclusion vectors for each acceptable model, denoting whether a predictor was present (1) or absent (0). Core predictor variables are defined as occurring in at least 67% of the acceptable models. For this regional analysis, only one model was found acceptable, with higher snow-to-streamflow translation (higher r-squared) occurring in colder mountain basins with higher relative winter precipitation, more snow accumulation and a lower fraction of annual precipitation that falls in the spring and summer. The second component of the data package uses previously published, high-resolution output from an integrated hydrological model of the East River watershed using the U.S. Geological Survey Groundwater and Surface water Flow model (GSFLOW, doi:10.15485/1998576). East River MLR expands upon the approach described above to explore the response of five streamflow metrics—annual streamflow, runoff efficiency, 7-day minimum flow, low-flow duration, and non-perennial stream fraction to snow system indicators including peak SWE, snow-covered area, snow disappearance date, and the fraction of basin area characterized by low-to-no snow, as well as seasonal precipitation and temperature, and annual hydrologic variables representing soil moisture, evapotranspiration (ET), the partitioning of incoming precipitation to evapotranspiration (ET/P), groundwater storage, and groundwater inflow to streams. MLR was done on all water years (P0: 1987-2024) and for each period as determined in the split analysis using pooled regression techniques (P1: 1987-2011 and P2: 2012-2024) to evaluate shifting predictor variable emphasis on streamflow generation. Results indicate that since 2012, peak SWE has lost statistical strength in its prediction of annual streamflow and runoff efficiency, and the indirect influence of spring temperature has emerged as critically important. Low-flow metrics remain largely influenced by soil moisture, vegetation water use and groundwater inflows with summer precipitation becoming a direct influence on minimum summer flow. Together, these data and Python-based analysis tools provide a framework for identifying the key watershed characteristics that control how streamflow responds to snow from year to year. The package also helps quantify uncertainty in statistical models and assess how snow–streamflow relationships vary across regions and over time. This dataset contains comma-separated values files (.csv), text files (.txt), python code files (.py), figure files (.png), and shapefiles (.cpg, .dbf, .prj, .sbn, .sbx, .shp, .xml). Further details on file contents and MLR execution can be found in the readme file and the FLMD files. Work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRSDate not supplied

Classifying Agnostic Biosignatures using Raman, VNIR, and Elemental Data

How can we use our current wealth of terrestrial data, encompassing biogenic and abiogenic systems, to determine the distinguishing properties of life? SCOBI (Statistical Classification of Biosignature Information) uses machine learning techniques to algorithmically identify combinations of measurements that are “indicative of life”. A set of ~1000 observations, comprising elemental abundance, isotopic fractionation, VNIR reflectance, and (in progress) Raman spectra, have been assembled from existing literature and databases. The observations cover systems classified as “indicative alive” (e.g., cells, vegetation), “indicative non-alive” (e.g., fossils, teeth), “mixed indicative” (e.g., soil, pond water), or “non-indicative” (e.g., rocks, meteorites). VNIR data was preprocessed by linear interpolation from 400-2100 nm and smoothed with a Savitzky-Golay filter. To limit the amount of Earth-biochemistry-specific (non-agnostic) information included, the first five spectral features extracted were number of peaks, number of troughs, mean reflectance, mean peak width, and broadest peak width. To help further emphasize agnostic biosignatures, Earth-specific features such as chlorophylls have been manually flagged so that feature importance with and without them can be compared. Classifiers including k-nearest neighbors (KNN), Gaussian Naïve Bayes (GNB), logistic regression (LR), random forest (RF), and support vector machine (SVM) were implemented, as was a combination voting classifier. Performance metrics included false positive rates, false negative rates, and AUC with 50-50 test/train splits (Monte Carlo simulations). Key takeaways from this stage, prior to the inclusion of Raman spectra, are (1) the overall success rate of 0.933 AUC was most heavily influenced by the elemental abundance data; and (2) VNIR reflectance had the lowest classification performance with 0.52 AUC (58% of objects correctly classified). The next steps are to complete integration of Raman spectral data and to improve the approach to pre-processing and feature extraction for both types of spectral data, such as automated baseline removal, whole spectrum matching, and dimensionality reduction.

Biosignatures↗
NASA NTRS1993

On the Shape of Liquid Metal Droplets in Electromagnetic Levitation Experiments

We present calculations and measurements on the shape of liquid metal droplets in electromagnetic levitation experiments. A normal stress balance model was developed to predict the shapes of liquid metal droplets that will be obtained in a microgravity experiment to measure the viscosity and surface tension of undercooled metals. This model was tested by calculating the droplet shapes in containerless experiments conducted to determine the surface tension of liquid metals. Inconsistencies associated with the results of a previous paper are elucidated. The computational results of the mathematical model are compared with the results of ground-based experiments for two different metals. The importance of the ratio of electromagnetic skin depth-to-droplet radius to the accuracy of the mathematical model is discussed. A planned alternate approach to modeling the shape by consideration of the entire droplet rather than only the surface is presented. As an example of an application. the influence of the shape on the splitting of the surface oscillation modes of levitated liquid metal droplets is discussed.

Schwartz, E.↗
NASA NTRS2003

A Fast Implementation of the ISOCLUS Algorithm

Unsupervised clustering is a fundamental tool in numerous image processing and remote sensing applications. For example, unsupervised clustering is often used to obtain vegetation maps of an area of interest. This approach is useful when reliable training data are either scarce or expensive, and when relatively little a priori information about the data is available. Unsupervised clustering methods play a significant role in the pursuit of unsupervised classification. One of the most popular and widely used clustering schemes for remote sensing applications is the ISOCLUS algorithm, which is based on the ISODATA method. The algorithm is given a set of n data points (or samples) in d-dimensional space, an integer k indicating the initial number of clusters, and a number of additional parameters. The general goal is to compute a set of cluster centers in d-space. Although there is no specific optimization criterion, the algorithm is similar in spirit to the well known k-means clustering method in which the objective is to minimize the average squared distance of each point to its nearest center, called the average distortion. One significant feature of ISOCLUS over k-means is that clusters may be merged or split, and so the final number of clusters may be different from the number k supplied as part of the input. This algorithm will be described in later in this paper. The ISOCLUS algorithm can run very slowly, particularly on large data sets. Given its wide use in remote sensing, its efficient computation is an important goal. We have developed a fast implementation of the ISOCLUS algorithm. Our improvement is based on a recent acceleration to the k-means algorithm, the filtering algorithm, by Kanungo et al.. They showed that, by storing the data in a kd-tree, it was possible to significantly reduce the running time of k-means. We have adapted this method for the ISOCLUS algorithm. For technical reasons, which are explained later, it is necessary to make a minor modification to the ISOCLUS specification. We provide empirical evidence, on both synthetic and Landsat image data sets, that our algorithm's performance is essentially the same as that of ISOCLUS, but with significantly lower running times. We show that our algorithm runs from 3 to 30 times faster than a straightforward implementation of ISOCLUS. Our adaptation of the filtering algorithm involves the efficient computation of a number of cluster statistics that are needed for ISOCLUS, but not for k-means.

Memarsadeghi, Nargess↗
NASA NTRS2011

K-Ca and Rb-Sr Dating of Lunar Granite 14321 Revisited

K-Ca and Rb-Sr age determinations were made for a bulk feldspar-rich portion of an Apollo rock fragment of the pristine lunar granite clast (14321,1062), an acid-leached split of the sample, and the leachate. K-Ca and Rb-Sr data were also obtained for a whole rock sample of Apollo ferroan anorthosite (FAN, 15415). The recent detection [1] of widespread intermediate composition plagioclase indicates that the generation of a diversity of evolved lunar magmas maybe more common and therefore more important to our understanding of crust formation than previously believed. Our new data strengthen the K-Ca and Rb-Sr internal isochrons of the well-studied Apollo sample 14321 [2], which along with a renewed effort to study evolved lunar magmas will provide an improved understanding of the petrogenetic history of evolved rocks on the Moon.

Simon, Justin I.↗
DOE OSTI2022

A new generation of effective core potentials from correlated and spin–orbit calculations: Selected heavy elements

We introduce new correlation consistent effective core potentials (ccECPs) for the elements I, Te, Bi, Ag, Au, Pd, Ir, Mo, and W with 4d, 5d, 6s, and 6p valence spaces. These ccECPs are given as a sum of spin-orbit averaged relativistic effective potential (AREP) and effective spin–orbit (SO) terms. The construction involves several steps with increasing refinements from more simple to fully correlated methods. The optimizations are carried out with objective functions that include weighted many-body atomic spectra, norm-conservation criteria, and SO splittings. Transferability tests involve molecular binding curves of corresponding hydride and oxide dimers. The constructed ccECPs are systematically better and in a few cases on par with previous effective core potential (ECP) tables on all tested criteria and provide a significant increase in accuracy for valence-only calculations with these elements. Our study confirms the importance of the AREP part in determining the overall quality of the ECP even in the presence of sizable spin–orbit effects. The subsequent quantum Monte Carlo calculations point out the importance of accurate trial wave functions that, in some cases (mid-series transition elements), require treatment well beyond a single-reference.

Wang, Guangming (ORCID:0000000231327925)↗