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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

η{sup 7}Li Scattering in the αt-Cluster Model

The cross sections for elastic and inelastic η-meson scattering on {sup 7}Li nuclei are obtained on the basis of the αt-cluster representation of the target nucleus. The experimentally known values of the parameters of elastic ηα and αt scattering are used in exactly solving three-body Faddeev equations with separable two-body potentials. The η{sup 7}Li elastic-scattering scattering length found from respective calculations is a{sub η7}Li = −0.310 − i0.198 fm.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Gaussian mixture model clustering algorithms for the analysis of high-precision mass measurements

The development of the phase-imaging ion-cyclotron resonance (PI-ICR) technique for use in Penning trap mass spectrometry (PTMS) increased the speed and precision with which PTMS experiments can be carried out. In PI-ICR, data sets of the locations of individual ion hits on a detector are created showing how ions cluster together into spots according to their cyclotron frequency. Ideal data sets would consist of a single, 2D-spherical spot with no other noise, but in practice data sets typically contain multiple spots, non-spherical spots, or significant noise, all of which can make determining the locations of spot centers non-trivial. A method for assigning groups of ions to their respective spots and determining the spot centers is therefore essential for further improving precision and confidence in PI-ICR experiments. Here, we present the class of Gaussian mixture model (GMM) clustering algorithms as an optimal solution. We show that on simulated PI-ICR data, several types of GMM clustering algorithms perform better than other clustering algorithms over a variety of typical scenarios encountered in PI-ICR. The mass spectra of 163Gd, 163 mGd, 162 Tb, and 162 mTb measured using PI-ICR at the Canadian Penning trap mass spectrometer were checked using GMMs, producing results that were in close agreement with the previously published values.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2019

Formulation of Multicomponent Lattice Gas Model Cluster Expansions Parameterized on Ab Initio Data: An Introduction to the Ab Initio Mean-Field Augmented Lattice Gas Modeling Code

A formalism is presented for the construction of multicomponent lattice gas models parameterized with ab initio (typically density functional theory) data. The leave-multiple-out and the leave-one-out cross validation score are showcased, and practical algorithms are developed and implemented in a new code called the Ab initio Mean-field Augmented Lattice Gas Modeling (AMALGM) code. Here, the functionality of these algorithms is demonstrated with a fully worked out example using the O/Fe(100) system. AMALGM and the formalism on which it is based are envisioned as a surface-oriented lattice gas alternative to other cluster expansion codes that are typically geared toward bulk systems whose lateral interactions between components are parameterized using an Ising model. While the formalism is created within the context of surfaces, it is equally applicable to bulk materials.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1992

On the luminosity of black hole cluster model of active galactic nuclei

The luminosity of a nuclear cluster of accreting black holes and other objects is discussed in terms of two accretion regimes: external supply of gas from outside the cluster and internal supply resulting from tidal disruption and capture of stars within the cluster. The external supply regime results in radiation being emitted from the innermost parts of the cluster while internal supply can efficiently feed the holes in the outer parts of the cluster as long as it is not too compact cluster and is embedded in a distribution of stars with a density larger than 10 exp 7 solar masses/cu pc.

Stoeger, W. R.↗
DOE OSTI2023

Robust design of semi-automated clustering models for 4D-STEM datasets

Materials discovery and design require characterizing material structures at the nanometer and sub-nanometer scale. Four-Dimensional Scanning Transmission Electron Microscopy (4D-STEM) resolves the crystal structure of materials, but many 4D-STEM data analysis pipelines are not suited for the identification of anomalous and unexpected structures. This work introduces improvements to the iterative Non-Negative Matrix Factorization (NMF) method by implementing consensus clustering for ensemble learning. We evaluate the performance of models during parameter tuning and find that consensus clustering improves performance in all cases and is able to recover specific grains missed by the best performing model in the ensemble. The methods introduced in this work can be applied broadly to materials characterization datasets to aid in the design of new materials.

Bruefach, Alexandra (ORCID:0000000209323477)↗
NASA NTRS1984

A proposal for the proper use of pseudopotentials in molecular orbital cluster model studies of chemisorption

The interaction of CO with Cu5, Ni5, and Al4 are treated as model systems for molecular adsorption on metal surfaces. The effect of the use of pseudopotentials for the metal atoms is studied by considering three types of clusters. In the first case, all of the metal electrons are explicitly included in the wave function; an all electron (AE) treatment. In the second case, the metal atom which directly interacts with the CO is described by AE but the remaining metal atoms include a pseudopotential for their core electrons. Finally, in the third case, all of the metal atoms in the cluster have a pseudopotential treatment for the core electrons. The AE cluster results are taken as reference values for the two pseudopotential treatments. The mixed cluster results are in excellent agreement with those of the all AE clusters; however, the results for the all pseudopotential cluster of Ni5CO or of Cu5CO are qualitatively different. The pseudopotential treatment for all of the metal atoms often leads to results that contain serious errors and it is not a reliable approach.

Bagus, P. S.↗
DOE OSTI2021

Inclusive breakup cross sections in reactions induced by the nuclides 6 He and 6,7 Li in the two-body cluster model

Calculations of inclusive α particle production are performed to interpret reaction experimental data induced by the two-neutron halo 6He and the isotopes 6,7 Li on different target nuclei. In this work, we have implemented the zero-range post-form DWBA to compute the elastic and nonelastic breakup cross sections. Integrated cross sections, angular distributions and spectra are presented. Projectiles are approximated as two-body clusters, namely 6 He as α+dineutron and 6 Li ( 7 Li) are interpreted as α+deuteron(triton). The São Paulo optical potential is employed in the calculation of the distorted wave functions for the incident channels, while standard phenomenological interactions are taken for the fragment-target interactions. Calculations for 6 Li and 7 Li furnish a good description of the data, while the reaction involving 6 He is found to be more complicated, where interpretation of the data must still be considered incomplete. The present analysis identifies an overall large contribution from inclusive breakup emission for all the cases studied.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Structure analysis of supported disordered molybdenum oxides using pair distribution function analysis and automated cluster modelling

Molybdenum oxides and sulfides on various low-cost high-surface-area supports are excellent catalysts for several industrially relevant reactions. The surface layer structure of these materials is, however, difficult to characterize due to small and disordered MoO x domains. Here, it is shown how X-ray total scattering can be applied to gain insights into the structure through differential pair distribution function (d-PDF) analysis, where the scattering signal from the support material is subtracted to obtain structural information on the supported structure. MoO x catalysts supported on alumina nanoparticles and on zeolites are investigated, and it is shown that the structure of the hydrated molybdenum oxide layer is closely related to that of disordered and polydisperse polyoxometalates. By analysing the PDFs with a large number of automatically generated cluster structures, which are constructed in an iterative manner from known polyoxometalate clusters, information is derived on the structural motifs in supported MoO x .

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

Development of molecular cluster models to probe pyrite surface reactivity

Abstract The recent discovery that anaerobic methanogens can reductively dissolve pyrite and utilize dissolution products as a source of iron and sulfur to meet their biosynthetic demands for these elements prompted the development of atomic‐scale nanoparticle models, as maquettes of reactive surface sites, for describing the fundamental redox steps that take place at the mineral surface during reduction. The given report describes our computational approach for modeling n (FeS 2 ) nanoparticles originated from mineral bulk structure. These maquettes contain a comprehensive set of coordinatively unsaturated Fe (II) sites that are connected via a range of persulfide (S 2 2− ) ligation. In addition to the specific maquettes with n = 8, 18, and 32 FeS 2 units, we established guidelines for obtaining low‐energy structures by considering the pattern of ionic, covalent, and magnetic interactions among the metal and ligand sites. The developed models serve as computational nano‐reactors that can be used to describe the reductive dissolution mechanism of pyrite to better understand the reactive sites on the mineral, where microbial extracellular electron‐transfer reactions can occur.

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

Pursuing sources of heterogeneity in modeling clustered population

Abstract Researchers often have to deal with heterogeneous population with mixed regression relationships, increasingly so in the era of data explosion. In such problems, when there are many candidate predictors, it is not only of interest to identify the predictors that are associated with the outcome, but also to distinguish the true sources of heterogeneity , that is, to identify the predictors that have different effects among the clusters and thus are the true contributors to the formation of the clusters. We clarify the concepts of the source of heterogeneity that account for potential scale differences of the clusters and propose a regularized finite mixture effects regression to achieve heterogeneity pursuit and feature selection simultaneously. We develop an efficient algorithm and show that our approach can achieve both estimation and selection consistency. Simulation studies further demonstrate the effectiveness of our method under various practical scenarios. Three applications are presented, namely, an imaging genetics study for linking genetic factors and brain neuroimaging traits in Alzheimer's disease, a public health study for exploring the association between suicide risk among adolescents and their school district characteristics, and a sport analytics study for understanding how the salary levels of baseball players are associated with their performance and contractual status.

Li, Yan↗