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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Local Embedding and Effective Downfolding in the Auxiliary-Field Quantum Monte Carlo Method

A local embedding and effective downfolding scheme has been developed and implemented in the auxiliary-field quantum Monte Carlo (AFQMC) method. A local cluster in which electrons are fully correlated is defined, and the frozen orbital method is used on the remainder of the system to construct an effective Hamiltonian, which operates within the local cluster. Local embedding, which involves only the occupied sector, has previously been employed in the context of Co/graphene. Here, the methodology is extended in order to allow for effective downfolding of the virtual sector, thus allowing for significant reduction in the computational effort required for AFQMC calculations. The system size, which can be feasibly treated with AFQMC, is therefore greatly extended as only a single local cluster is explicitly correlated at the AFQMC level of theory. The approximation is controlled by the separate choice of the spatial size of the active occupied region (Ro) and of the active virtual region (Rv). In conclusion, the systematic dependence of the AFQMC energy on Ro and Rv is investigated, and it is found that relative AFQMC energies of physical and chemical interest converge rapidly to the full AFQMC treatment (i.e., using no embedding or downfolding).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Assessment of DFT functionals for a minimal nitrogenase [Fe(SH) 4 H]- model employing state-of-the-art ab initio methods

We have designed a [Fe(SH)4H]- model with the fifth proton binding either to Fe or S. We show that the energy difference between these two isomers (ΔE) is hard to estimate with quantum-mechanical (QM) methods. For example, different density functional theory (DFT) methods give ΔE estimates that vary by almost 140 kJ/mol, mainly depending on the amount of exact Hartree–Fock included (0%–54%). The model is so small that it can be treated by many high-level QM methods, including coupled-cluster (CC) and multiconfigurational perturbation theory approaches. With extrapolated CC series (up to fully connected coupled-cluster calculations with singles, doubles, and triples) and semistochastic heat-bath configuration interaction methods, we obtain results that seem to be converged to full configuration interaction results within 5 kJ/mol. Our best result for ΔE is 101 kJ/mol. With this reference, we show that M06 and B3LYP-D3 give the best results among 35 DFT methods tested for this system. Brueckner doubles coupled cluster with perturbaitve triples seems to be the most accurate coupled-cluster approach with approximate triples. CCSD(T) with Kohn–Sham orbitals gives results within 4–11 kJ/mol of the extrapolated CC results, depending on the DFT method. Single-reference CC calculations seem to be reasonably accurate (giving an error of ~5 kJ/mol compared to multireference methods), even if the D1 diagnostic is quite high (0.25) for one of the two isomers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Unsupervised Clustering-Based Short-Term Solar Forecasting

Solar forecasting accuracy is highly affected by weather conditions, therefore, weather awareness forecasting models are expected to improve the forecasting performance. However, it may not be available or reliable to classify different forecasting tasks by only using predefined meteorological weather categorization. In this paper, an unsupervised clustering-based (UC-based) solar forecasting method is developed for short-term (1-h-ahead) global horizontal irradiance (GHI) forecasting. This UC-based method consists of three parts: GHI time series unsupervised clustering, pattern recognition, and UC-based forecasting. The daily GHI time series is first clustered by an Optimized Cross-validated ClUsteRing (OCCUR) method, which determines the optimal number of clusters and best clustering results. Then, support vector machine pattern recognition is adopted to recognize the category of a certain day using the first four hours' data in the forecasting stage. GHI forecasts are generated by the most suitable models in different clusters, which are built by a two-layer machine learning based multi-model (M3) forecasting framework. The developed UC-M3 method is validated by using 1-year of data with 13 solar features from three information sources. Numerical results show that 1) UC-based models outperform non-UC (all-in-one) models with the same M3 architecture by approximately 20%; and 2) M3-based models also outperform the single-algorithm machine learning models by approximately 20%.

14 SOLAR ENERGY↗
DOE OSTI2023

Vertical detachment energies of ammonia cluster anions using self-interaction-corrected methods

Systems with weakly bound extra electrons impose great challenges to semilocal density functional approximations (DFAs), which suffer from self-interaction errors. Small ammonia clusters are one such example of weakly bound anions where the extra electron is weakly bound. We applied two self-interaction correction (SIC) schemes, viz., the well-known Perdew–Zunger and the recently developed locally scaled SIC (LSIC) with the local spin density approximation (LSDA), Perdew–Burke–Ernzerhof (PBE) generalized gradient approximation (GGA), and the SCAN meta-GGA functionals to calculate the vertical detachment energies (VDEs) of small ammonia cluster anions (NH3)n–. Our results show that the LSIC significantly reduces the errors in calculations of VDE with LSDA and PBE-GGA functionals leading to better agreement with the reference values calculated with coupled cluster singles and doubles with perturbative triples [CCSD(T)]. Accurate prediction of VDE as an absolute of the highest occupied molecular orbital (HOMO) is challenging for DFAs. Our results show that VDEs estimated from the negative of HOMO eigenvalues with the LSIC-LSDA and Perdew–Zunger SIC-PBE are within 11 meV of the reference CCSD(T) results. Here, the LSIC method performs consistently well for the VDE estimates, from both the total energy differences and the absolute HOMO eigenvalues.

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

Interpreting the Operando XANES of Surface-Supported Subnanometer Clusters: When Fluxionality, Oxidation State, and Size Effect Fight.

X-ray absorption near edge structure (XANES) spectroscopy is widely used for operando catalyst characterization. We show that, for highly fluxional supported nanoclusters, the customary extraction of the oxidation state of the metal from the XANES data by fitting to the bulk standards is highly questionable. The XANES signatures as well as the apparent oxidation state for such clusters arise from a complex combination of many factors, and not only from the chemical composition in reaction conditions (e.g., oxygen content in oxidizing atmosphere). The thermally accessible isomerization and population of several structurally distinct cluster forms, cluster-support interaction, and intrinsic size effects all impact the metal oxidation state and XANES signal. We demonstrate this on copper oxide clusters with different compositions, Cu4Ox(x = 2-5) and Cu5Oy (y = 3, 5), deposited on amorphous alumina and ultrananocrystalline diamond, for which we computed the XANES spectra and compare the results to the experiment. We show in addition that fitting the experimental spectrum to calculated spectra of supported clusters can, in contrast, provide good agreement and insight into the spectrum-composition-structure relation. Experimental XANES interpreted using the proposed fitting scheme shows the partial reduction of Cu oxide clusters at rising temperatures, and pinpoints the specific stoichiometries that dominate in the ensemble of cluster states as the temperature changes.

Zandkarimi, Borna↗
DOE OSTI2019

Revisiting surface core-level shifts for ionic compounds

The shifts of core-level binding energies can provide powerful information about the electronic structure of a material. Understanding the physical origin of these shifts for catalytically relevant oxides may provide important insight into their properties. This requires reliable theoretical methods which are able to relate the binding energy shifts to the electronic structure. In order to establish such a methodology, the CaO(100) surface to bulk core-level binding energy shifts have been studied with Hartree-Fock and density-functional theory methods using both cluster and periodic slab models. The shifts obtained from the different theoretical methods are compared with each other and with data from synchrotron-based x-ray photoelectron spectroscopy (XPS) measurements. With a common approximation for the slab model treatment of XPS, the predicted binding energy shifts are seriously in error. In this work, the origin of the error is identified as arising from a flawed treatment of the surface atom binding energies, and a method for correcting the failure is presented.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS1997

Sulfur in Cometary Dust

The computer-intensive project consisted of the analysis and synthesis of existing data on composition of comet Halley dust particles. The main objective was to obtain a complete inventory of sulfur containing compounds in the comet Halley dust by building upon the existing classification of organic and inorganic compounds and applying a variety of statistical techniques for cluster and cross-correlational analyses. A student hired for this project wrote and tested the software to perform cluster analysis. The following tasks were carried out: (1) selecting the data from existing database for the proposed project; (2) finding access to a standard library of statistical routines for cluster analysis; (3) reformatting the data as necessary for input into the library routines; (4) performing cluster analysis and constructing hierarchical cluster trees using three methods to define the proximity of clusters; (5) presenting the output results in different formats to facilitate the interpretation of the obtained cluster trees; (6) selecting groups of data points common for all three trees as stable clusters. We have also considered the chemistry of sulfur in inorganic compounds.

Fomenkova, M. N.↗
NASA NTRS2010

Device and method to enhance availability of cluster-based processing systems

An electronic computing device including at least one processing unit that implements a specific fault signal upon experiencing an associated fault, a control unit that generates a specific recovery signal upon receiving the fault signal from the at least one processing unit, and at least one input memory unit. The recovery signal initiates specific recovery processes in the at least one processing unit. The input memory buffers input data signals input to the at least one processing unit that experienced the fault during the recovery period.

Lupia, David J.↗
DOE OSTI2024

Superhydrophobic Array Devices for the Enhanced Formation of 3D Cancer Models

During the metastatic cascade, cancer cells travel through the bloodstream as circulating tumor cells (CTCs) to a secondary site. Clustered CTCs have greater shear stress and treatment resistance, yet their biology remains poorly understood. We therefore engineered a tunable superhydrophobic array device (SHArD). The SHArD-C was applied to culture a clinically relevant model of CTC clusters. Using our device, we cultured a model of cancer cell aggregates of various sizes with immortalized cancer cell lines. These exhibited higher E-cadherin expression and are significantly more capable of surviving high fluid shear stress-related forces compared to single cells and model clusters grown using the control method, helping to explain why clustering may provide a metastatic advantage. Additionally, the SHArD-S, when compared with the AggreWell 800 method, provides a more consistent spheroid-forming device culturing reproducible sizes of spheroids for multiple cancer cell lines. Overall, we designed, fabricated, and validated an easily tunable engineered device which grows physiologically relevant three-dimensional (3D) cancer models containing tens to thousands of cells.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Proton reconstruction with the TOTEM Roman pot detectors for high- β * LHC data

The TOTEM Roman pot detectors are used to reconstruct the transverse momentum of scattered protons and to estimate the transverse location of the primary interaction. This paper presents new methods of track reconstruction, measurements of strip-level detection efficiencies, cross-checks of the LHC beam optics, and detector alignment techniques, along with their application in the selection of signal collision events. The track reconstruction is performed by exploiting hit cluster information through a novel method using a common polygonal area in the intercept-slope plane. The technique is applied in the relative alignment of detector layers with μm precision. A tag-and-probe method is used to extract strip-level detection efficiencies. The alignment of the Roman pot system is performed through time-dependent adjustments, resulting in a position accuracy of 3 μm in the horizontal and 60 μm in the vertical directions. The goal is to provide an optimal reconstruction tool for central exclusive physics analyses based on the high-β* data-taking period at $\sqrt({s})$ = 13 TeV in 2018.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1994

A measurement of the Hubble constant from the X-ray properties and the Sunyaev-Zel'dovich effect of Abell 2218

The distance of the cluster of galaxies Abell 2218, and hence the value of the Hubble constant, has been measured by comparing the X-ray properties and the Sunyaev-Zel'dovich effect of the cluster. The result for the Hubble constant is H(sub zero) = 65 +/- 25 km/s/MPC, where the error includes the random and systematic errors, combined in quadrature, and the largest contributions to the overall error come from systematic errors in the Sunyaev-Zel'dovich effect data and in the X-ray spectrum of the cluster. The X-ray and Sunyaev-Zel'dovich effect data are consistent with the same model for the intergalactic medium in Abell 2218 (an isothermal Beta-model with Beta is about 0.65 and cluster core radius about 1.0 min). A prevous report of a smaller Hubble constant, found by applying the same method on the same cluster, is shown to be based on a model for the cluster gas that is inconsistent with the Einstein IPC data. The present result for the Hubble constant is consistent with the value found earlier for the cluster Abell 665: by combining the results of the method for both clusters we conclude that the value of the Hubble constant is H(sub zero) = 55 +/- 17 km/s/MPC.

Birkinshaw, M.↗
DOE OSTI2019

Atom Probe Tomography Interlaboratory Study on Clustering Analysis in Experimental Data Using the Maximum Separation Distance Approach

We summarize the findings from an interlaboratory study conducted between ten international research groups and investigate the use of the commonly used maximum separation distance and local concentration thresholding methods for solute clustering quantification. The study objectives are: to bring clarity to the range of applicability of the methods; identify existing and/or needed modifications; and interpretation of past published data. Participants collected experimental data from a proton-irradiated 304 stainless steel and analyzed Cu-rich and Ni–Si rich clusters. The datasets were also analyzed by one researcher to clarify variability originating from different operators. The Cu distribution fulfills the ideal requirements of the maximum separation method (MSM), namely a dilute matrix Cu concentration and concentrated Cu clusters. This enabled a relatively tight distribution of the cluster number density among the participants. By contrast, the group analysis of the Ni–Si rich clusters by the MSM was complicated by a high Ni matrix concentration and by the presence of Si-decorated dislocations, leading to larger variability among researchers. While local concentration filtering could, in principle, tighten the results, the cluster identification step inevitably maintained a high scatter. Recommendations regarding reporting, selection of analysis method, and expected variability when interpreting published data are discussed.

APT, Round Robin Studies, atom probe tomography, c↗
NASA NTRS1991

Geography of cretaceous extinctions: Data base development

Data bases built from the source literature are plagued by problems of data quality. Unless the data acquisition is done by experts, working slowly, the data base may contain so much garbage that true signals and patterns cannot be detected. On the other hand, high quality data bases develop so slowly that satisfactory statistical analysis may never be possible due to the small sample sizes. Results of a test are presented of the opposite strategy: rapid data acquisition by non-experts with minimal control on data quality. A published list of 186 species and genera of fossil invertibrates of the latest Cretaceous Age (Maestrichtian) were located through a random search of the paleobiological and geological literature. The geographic location for each faunal list was then transformed electronically to Maestrichtian latitude and longitude and the lists were further digested to identify the genera occurring in each ten-degree, latitude-longitude block. The geographical lists were clustered using the Otsuka similarity coefficient and a standard unweight-pair-group method. The resulting clusters are remarkably consistent geographically, indicating that a strong biogeographic signal is visible despite low-quality data. A further test evaluated the geographic pattern of end-Cretaceaous extinctions. All genera in the data base were compared with Sepkoski's compendium of time ranges of genera to determine which of the reported genera survived the Cretaceous mass extinction. In turn, extinction rates for the ten-degree, latitude-longitude blocks were mapped. The resulting distribution is readily interpretable as a robust pattern of the geography of the mass extinction. The study demonstrates that a low-quality data base, built rapidly, can provide a basis for meaningful analysis of past biotic events.

Raup, D. M.↗
NASA NTRS1993

X-ray substructure in A1656 and A2256

We report the confirmation of X-ray substructure in two rich clusters of galaxies, A1656 (Coma) and A2256. Using data from the Einstein Observatory imaging proportional counter, we present a technique of fitting the cluster profile and searching for contributions to the X-ray emission from small regions within the cluster. Using this method we find substructure in both A1656 and A2256 while simultaneously fitting the cluster profile. We obtain the ellipticity and position angle of both clusters as a function of radius and find that both have ellipticity and position angles which vary with radius. We interpret the existence of substructure along with the variable ellipticity and position angle as evidence for a recent merger in both of these clusters.

Davis, David S.↗
NASA NTRS1992

Arcminute fluctuations in the microwave background from clusters of galaxies

A method for computing arcmin microwave fluctuations produced by Compton scattering of the cosmic background photons by hot electrons in clusters of galaxies is described. Microwave images of the sky for a range of Omega and primordial fluctuation spectral index n are generated which are then 'observed' to determine Delta T/T in precisely the same manner as actual observations to determine if the cluster-induced fluctuations are consistent with the measured upper limit. The geometry used by Uson and Wilkinson (1984) in the NRAO experiment and Readhead et al. (1989) in the OVRO experiment are applied to the simulated images. The 95 percent confidence lower limit for Omega is found to be about 1/10 for n = -1 (which approximates the CDM mass spectrum for clusters), while for n = 0 it is 1/7; for n = +1 the limit is 1/5 if the gas density profile extends to five core radii.

Markevitch, M.↗