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At least 1,747 records · Page 97
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Origin of matter and space-time in the big bang

We review the case for and against a bulk cosmic motion resulting from the quantum entanglement of our universe with the multiverse beyond our horizon. Within the current theory for the selection of the initial state of the universe from the landscape multiverse there is a generic prediction that pre-inflation quantum entanglement with other universes should give rise to a cosmic bulk flow with a correlation length of order horizon size and a velocity field relative to the expansion frame of the universe. Indeed, the parameters of this motion are are tightly constrained. A robust prediction can be deduced indicating that there should be an overall motion of of about 800 km/s relative to the background space time as defined by the cosmic microwave background (CMB). This talk will summarize the underlying theoretical motivation for this hypothesis. Of course our motion relative to the background space time (CMB dipole) has been known for decades and is generally attributed to the gravitational pull of the local super cluster. However, this cosmic peculiar velocity field has been recently deduced out to very large distances well beyond that of the local super cluster by using X-ray galaxy clusters as tracers of matter motion. This is achieved via the kinematic component of the Sunyaev-Zeldovich (KSZ) effect produced by Compton scattering of cosmic microwave background photons from the local hot intracluster gas. As such, this method measures peculiar velocity directly in the frame of the cluster. Similar attempts by our group and others have attempted to independently assess this bulk flow via Type la supernova redshifts. In this talk we will review the observation case for and against the existence of this bulk flow based upon the observations and predictions of the theory. If this interpretation is correct it has profound implications in that we may be observing for the first time both the physics that occurred before the big bang and the existence of the multiverse beyond our horizon.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1997

Formation and Combustion of Unconfined Drop Clusters in Microgravity

Single-drop and droplet array studies have become common methods to isolate and investigate the effects of any of the complexities that enter into the drop combustion process. Microgravity environments are required to allow larger drops to be studied while minimizing or eliminating the confounding effects of buoyancy. Based on the results from current isolated drop, drop array, and spray studies funded through the Microgravity Science and Applications Division, it has become clear that even with the effects of buoyancy removed, the extrapolation of results from droplet array studies to spray flames is difficult. The problem occurs because even the simplest spray systems introduce complexities of multi-disperse drop sizes and drop-drop interactions, coupled with more complicated fluid dynamics. Not only do these features make the interpretation of experimental data difficult, they also make the problem very difficult to analyze computationally. Group combustion models, in which the interaction between droplets is treated on a statistical manner, have become a popular method to investigate the behavior of large numbers of interacting droplets, particularly through the work of Ryan et al. and Bellan and co-workers. While these models idealize the actual spray systems to a point where they can be treated computationally, the experimental analogy to these models is difficult to achieve because it requires the formation and Combustion of drop clusters without the effects of buoyancy. Therefore, even though these models have provided useful and insightful information, the verification of the results by direct comparison with experimental data is still lacking.

Liu, S.↗
DOE OSTI2013

TANGENTIAL VELOCITY OF THE DARK MATTER IN THE BULLET CLUSTER FROM PRECISE LENSED IMAGE REDSHIFTS

We show that the fast-moving component of the ''Bullet Cluster'' (1E0657-56) can induce potentially resolvable redshift differences between multiply lensed images of background galaxies. This moving cluster effect, due to the tangential peculiar velocity of the lens, can be expressed as the scalar product of the lensing deflection angle with the tangential velocity of the mass components; the effect is maximal for clusters colliding in the plane of the sky with velocities boosted by their mutual gravity. The Bullet Cluster is likely to be the best candidate for the first measurement of this effect due to the large collision velocity and because the lensing deflection and the cluster fields can be calculated in advance. We derive the deflection field using multiply lensed background galaxies detected with the Hubble Space Telescope. The velocity field is modeled using self-consistent N-body/hydrodynamical simulations constrained by the observed X-ray and gravitational lensing features of this system. We predict that the triply lensed images of systems ''G'' and ''H'' straddling the critical curve of the bullet component will show the largest frequency shifts up to {approx}0.5 km s{sup -1}. These shifts are within the range of the Atacama Large Millimeter/Submillimeter Array for molecular emission, and are near the resolution limit of the new generation high-throughput optical-IR spectrographs. The detection of this effect measures the tangential motion of the subclusters directly, thereby clarifying the tension with {Lambda}CDM, which is inferred from the gas motion less directly. This method may be extended to smaller redshift differences using the Ly{alpha} forest toward QSOs lensed by more typical clusters of galaxies. More generally, the tangential component of the peculiar velocities of clusters derived by our method complements the radial component determined by the kinematic Sunyaev-Zel'dovich effect, providing a full three-dimensional description of velocities.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

Complex absorbing potentials within EOM-CC family of methods: Theory, implementation, and benchmarks

A production-level implementation of equation-of-motion coupled-cluster singles and doubles (EOM-CCSD) for electron attachment and excitation energies augmented by a complex absorbing potential (CAP) is presented. The new method enables the treatment of metastable states within the EOM-CC formalism in a similar manner as bound states. The numeric performance of the method and the sensitivity of resonance positions and lifetimes to the CAP parameters and the choice of one-electron basis set are investigated. A protocol for studying molecular shape resonances based on the use of standard basis sets and a universal criterion for choosing the CAP parameters are presented. Our results for a variety of π{sup *} shape resonances of small to medium-size molecules demonstrate that CAP-augmented EOM-CCSD is competitive relative to other theoretical approaches for the treatment of resonances and is often able to reproduce experimental results.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Large-scale atomistic calculations of clusters in intense x-ray pulses

Here, we present the methodology of our recently developed Monte-Carlo/ Molecular-Dynamics method for studying the fundamental ultrafast dynamics induced by high-fluence, high-intensity x-ray free electron laser (XFEL) pulses in clusters. The quantum nature of the initiating ionization process is accounted for by a Monte Carlo method to calculate probabilities of electronic transitions, including photo absorption, inner-shell relaxation, photon scattering, electron collision and recombination dynamics, and thus track the transient electronic configurations explicitly. The freed electrons and ions are followed by classical particle trajectories using a molecular dynamics algorithm. These calculations reveal the surprising role of electron-ion recombination processes that lead to the development of nonuniform spatial charge density profiles in x-ray excited clusters over femtosecond timescales. In the high-intensity limit, it is important to include the recombination dynamics in the calculated scattering response even for a 2- fs pulse. We also demonstrate that our numerical codes and algorithms can make e!cient use of the computational power of massively parallel supercomputers to investigate the intense-field dynamics in systems with increasing complexity and size at the ultrafast timescale and in non-linear x-ray interaction regimes. In particular, picosecond trajectories of XFEL clusters with attosecond time resolution containing millions of particles can be e!ciently computed on upwards of 262,144 processes.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2025

Enhancing Cluster Identification in Atom Probe Tomography Data Using Transfer Learning

Atom Probe Tomography (APT) is a powerful technique for visualizing the atomic-scale distribution of solutes in materials, but quantitative cluster analysis of APT datasets remains a challenge due to the need for subjective parameter selection in clustering algorithms. While distance-based and density-based methods such as HDBSCAN are widely used, their performance is highly sensitive to user-defined parameters, which undermines reproducibility and accuracy. This study proposes an image-based, deep learning-aided workflow for automating parameter selection and cluster detection in APT data analysis. By projecting 3D APT point clouds onto 2D planes, we leverage pretrained convolutional neural networks (ConvNeXt-Tiny and ResNet-50) through transfer learning to predict the number of clusters present in synthetic datasets. The output is used to guide K-means clustering and estimate HDBSCAN parameters, specifically minimum cluster size and minimum sample points. This approach reduces reliance on manual parameter tuning, improving consistency and scalability. The methodology demonstrates the feasibility of using image-based deep learning for interpreting complex spatial patterns in APT data, enabling faster and more objective analysis. The complete workflow and code are made publicly available to support reproducibility and future research.

Density-based clustering↗
NASA NTRS2003

Constraints on the Energy Content of the Universe from a Combination of Galaxy Cluster Observables

We demonstrate that constraints on cosmological parameters from the distribution of clusters as a function of redshift (dN/dz) are complementary to accurate angular diameter distance (D(sub A)) measurements to clusters, and their combination significantly tightens constraints on the energy density content of the Universe. The number counts can be obtained from X-ray and/or SZ (Sunyaev-Ze'dovich effect) surveys, and the angular diameter distances can be determined from deep observations of the intra-cluster gas using their thermal bremsstrahlung X-ray emission and the SZ effect. We combine constraints from simulated cluster number counts expected from a 12 deg(sup 2) SZ cluster survey and constraints from simulated angular diameter distance measurements based on the X-ray/SZ method assuming a statistical accuracy of 10% in the angular diameter distance determination of 100 clusters with redshifts less than 1.5. We find that Omega(sub m), can be determined within about 25%, Omega(sub lambda) within 20% and w within 16%. We show that combined dN/dz+(sub lambda) constraints can be used to constrain the different energy densities in the Universe even in the presence of a few percent redshift dependent systematic error in D(sub lambda). We also address the question of how best to select clusters of galaxies for accurate diameter distance determinations. We show that the joint dN/dz+ D(lambda) constraints on cosmological parameters for a fixed target accuracy in the energy density parameters are optimized by selecting clusters with redshift upper cut-offs in the range 0.55 approx. less than 1. Subject headings: cosmological parameters - cosmology: theory - galaxies:clusters: general

Molnar, Sandor M.↗
DOE OSTI2020

Low Energy Implantation into Transition-Metal Dichalcogenide Monolayers to Form Janus Structures

Atomically-thin two-dimensional (2D) materials face significant energy barriers for synthesis and processing into functional metastable phases such as Janus structures. Here, in this study, the controllable implantation of hyperthermal species from pulsed laser deposition (PLD) plasmas is introduced as a top-down method to compositionally engineer 2D monolayers. The kinetic energies of Se clusters impinging on suspended monolayer WS 2 crystals were controlled in the <10 eV/atom range with in situ plasma diagnostics to determine the thresholds for selective top layer replacement of sulfur by selenium for the formation of high quality WSSe Janus monolayers at low (300 °C) temperatures, and bottom layer replacement for complete conversion to WSe 2 . Atomic-resolution electron microscopy and spectroscopy in tilted geometry confirm the WSSe Janus monolayer. Molecular dynamics simulations reveal that Se clusters implant to form disordered metastable alloy regions, which then recrystallize to form highly ordered structures, opening the door for low-energy implantation by PLD as a novel method to explore the synthesis of 2D Janus layers and alloys of variable composition.

2D materials↗
DOE OSTI2018

Unsupervised phase mapping of X-ray diffraction data by nonnegative matrix factorization integrated with custom clustering

Abstract Analyzing large X-ray diffraction (XRD) datasets is a key step in high-throughput mapping of the compositional phase diagrams of combinatorial materials libraries. Optimizing and automating this task can help accelerate the process of discovery of materials with novel and desirable properties. Here, we report a new method for pattern analysis and phase extraction of XRD datasets. The method expands the Nonnegative Matrix Factorization method, which has been used previously to analyze such datasets, by combining it with custom clustering and cross-correlation algorithms. This new method is capable of robust determination of the number of basis patterns present in the data which, in turn, enables straightforward identification of any possible peak-shifted patterns. Peak-shifting arises due to continuous change in the lattice constants as a function of composition and is ubiquitous in XRD datasets from composition spread libraries. Successful identification of the peak-shifted patterns allows proper quantification and classification of the basis XRD patterns, which is necessary in order to decipher the contribution of each unique single-phase structure to the multi-phase regions. The process can be utilized to determine accurately the compositional phase diagram of a system under study. The presented method is applied to one synthetic and one experimental dataset and demonstrates robust accuracy and identification abilities.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Direct Observation of Ultrafast Dissociation Dynamics of (R–I){sub n}-Type Iodide Clusters as a Result of UV Excitation below the Ionization Threshold

The dynamics of dissociation of (IF{sub 2}CCOF){sub n}, (CF{sub 3}I){sub n}, and (CH{sub 3}I){sub n} clusters induced by femtosecond UV radiation (λ = 266 nm) is investigated. The method of UV excitation and photoionization probing (λ = 400 nm) combined with the time-of-flight mass spectrometry is applied. It is found that clusters excited to Rydberg states lying below the ionization threshold are decomposed, as a result of subsequent relaxation processes, giving rise to free neutral molecules. A mechanism of electronic–vibrational relaxation process is proposed, and data on the characteristic times of different stages of this process are obtained.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

Recursive Soft Drop

We introduce a new jet substructure technique called Recursive Soft Drop, which generalizes the Soft Drop algorithm to have multiple grooming layers. Like the original Soft Drop method, this new recursive variant traverses a jet clustering tree to remove soft wide-angle contamination. By enforcing the Soft Drop condition N times, Recursive Soft Drop improves the jet mass resolution for boosted hadronic objects like W bosons, top quarks, and Higgs bosons. We further show that this improvement in mass resolution persists when including the effects of pileup, up to large pileup multiplicities. In the limit that N goes to infinity, the resulting groomed jets formally have zero catchment area. As an alternative approach, we present a bottom-up version of Recursive Soft Drop which, in its local form, is similar to Recursive Soft Drop and which, in its global form, can be used to perform event-wide grooming.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Evolution of microstructures in radiation fields using a coupled binary-collision Monte Carlo phase field approach

The simulation of radiation effects in materials broadly falls into two categories. At short time and length scales lies the modeling of primary radiation damage, such as point defect creation, energy deposition, and ballistic mixing. This is followed by the modeling at longer time scales of thermally activated microstructure evolution and defect reactions, such as recombination, clustering, and coarsening. The binary collision Monte Carlo method is an established, numerically efficient method for the computation of primary radiation damage. Conversely, the phase field method is a state of the art method for microstructure evolution on longer time and length scales. Here we present a concurrent coupling of these two methods, overcoming the difference between the discrete object Monte Carlo paradigm for primary radiation damage and the continuum field variable approach for microstructure evolution. The coupling is bidirectional, in which the microstructure evolution in the MOOSE finite element frame- work provides the spatial scattering data set for the charged particle trans- port and receives point defect, mass transport, and heat source terms from the simulated collision cascades that contribute to the field variable evolution. The concurrent coupling scheme is implemented in the code Magpie and demonstrated by investigating patterning for a model irradiated immiscible binary alloy. The results from the coupled binary collision Monte Carlo/phase field simulations reproduce the results of analytical models for phase separation, phase mixing, and patterning, supporting the approach and indicating its utility for modeling real materials systems.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Taxonomy of USA east coast fishing communities in terms of social vulnerability and resilience

Increased concern with the impacts that changing coastal environments can have on coastal fishing communities led to a recent effort by NOAA Fisheries social scientists to develop a set of indicators of social vulnerability and resilience for the U.S. Southeast and Northeast coastal communities. A goal of the NOAA Fisheries social vulnerability and resilience indicator program is to support time and cost effective use of readily available data in furtherance of both social impact assessments of proposed changes to fishery management regulations and climate change adaptation planning. The use of the indicators to predict the response to change in coastal communities would be enhanced if community level analyses could be grouped effectively. This study examines the usefulness of combining 1130 communities into 35 relevant subgroups by comparing results of a numerical taxonomy with data collected by interview methods, a process herein referred to as “ground-truthing.” The validation of the taxonomic method by the method of ground-truthing indicates that the clusters are adequate to be used to select communities for in-depth research. - Highlights: • We develop a taxonomy of fishing communities based on vulnerability indicators. • We validate the community clusters through the use of surveys (“ground-truthing”). • Clusters differ along important aspects of fishing community vulnerability. • Clustering communities allows for accurate and timely social impact assessments.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Web-based wide-area monitoring platform for ringdown and clustering analytics in power systems

This paper introduces an open-source research platform for monitoring the Mexican interconnected power grid, allowing real-time processing and information extraction of the grid’s dynamic condition. Moreover, the platform is a Python-based development that embeds different ringdown and clustering analytics tools. In the case of ringdown analysis, the modal information can be extracted using some of the most known algorithms, i.e., Prony analysis, eigensystem realization algorithm (ERA), and matrix pencil (MP). For clustering analysis, the coherent behaviour of generator and non-generator buses is provided by applying recent state-of-the-art techniques such as affinity propagation, K-means, hierarchical agglomerative clustering, and typicality data analysis. The results of up to 93 PMUs show that this open-source platform suits researchers’ and engineers’ power system dynamic analysis requirements.

Clustering↗
DOE OSTI2021

Correlative STEM-APT characterization of radiation-induced segregation and precipitation of in-service BWR 304 stainless steel

In this study, radiation induced segregation and precipitation phenomena in an in-service boiling water reactor 304 stainless steel component were investigated using directly correlated 3D-atom probe tomography and scanning transmission electron microscopy. Significant quantitative differences in measured segregation at grain boundaries were found between the atom probe and energy dispersive spectroscopy measurements of the exact same locations. In particular, a much stronger Si segregation (~10 atomic% via atom probe versus ~4 atomic% via electron microscopy) and different Cr profile shapes were detected that are critical to models of radiation induced segregation and stress corrosion cracking behavior. These quantitative differences highlight the need for comparative microscopy and critical evaluation of limitations in each analytical method. Elemental segregation to dislocations and conjoined-clusters were also highlighted by atom probe; confirming and expanding upon what has been observed in test reactor neutron and accelerator-based ion irradiations.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Lithium doping on covalent organic framework-320 for enhancing hydrogen storage at ambient temperature

Density Functional Theory (DFT) combines with grand canonical Monte Carlo (GCMC) simulations are performed to explore the effect of Li doping on the hydrogen storage capability of COF-320. The results show that the interaction energy between the H{sub 2} and the Li-doped COF-320 is about three times higher than that of pristine COF-320. GCMC simulations are employed to study the hydrogen uptake of Li-doped COF-320 at ambient temperature, further confirm that the lithium doping can improve the hydrogen uptake at ambient temperature. Our results demonstrate that Li-doped COFs have good potential in the field of hydrogen storage. - Graphical abstract: Fig. 1. The optimized cluster model used here to represent the COF-320 and possible adsorption sites (A, B, C) for adsorption of metals in the COF-320. The dangling bonds are terminated by H atoms. C, H, and N atoms are shown as gray, white, and blue colors, respectively. Fig. 2. The adsorption isotherm of H{sub 2} in the pristine and Li-doped COF-320 at 298 K. - Highlights: • The binding sites of single and two lithium atoms in COF-320 were studied. • The interaction energy between the H{sub 2} and the Li-doped COF-320 is about three times higher than that of pristine COF-320. • H{sub 2} uptakes on the Li-doped COFs obtain significant improvement at ambient temperature. • Lithium-doping is a successful strategy for improving hydrogen uptake.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Bi-cross validation of spectral clustering hyperparameters

One challenge impeding the analysis of terabyte scale X-ray scattering data from the Linac Coherent Light Source (LCLS) is determining the number of clusters required for the execution of traditional clustering algorithms. Here, we demonstrate that the previous work using bi-cross validation to determine the number of singular vectors directly maps to the spectral clustering problem of estimating both the number of clusters and hyperparameter values. Here by applying this method to LCLS X-ray scattering data enables the identification of dropped shots without manually setting boundaries on detector fluence and provides a path toward identifying rare and anomalous events.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

The Effect of Geometry, Spin, and Orbital Optimization in Achieving Accurate, Correlated Results for Iron–Sulfur Cubanes

Iron–sulfur clusters comprise an important functional motif in the catalytic centers of biological systems, capable of enabling important chemical transformations at ambient conditions. This remarkable capability derives from a notoriously complex electronic structure that is characterized by a high density of states that is sensitive to geometric changes. The spectral sensitivity to subtle geometric changes has received little attention from correlated, large active space calculations, owing partly to the exceptional computational complexity for treating these large and correlated systems accurately. Here, to provide insight into this aspect, we report the first Complete Active Space Self Consistent Field (CASSCF) calculations for different geometries of the [Fe(II/III) 4 S 4 (SMe) 4 ] -2 clusters using two complementary, correlated solvers: spin-pure Adaptive Sampling Configuration Interaction (ASCI) and Density Matrix Renormalization Group (DMRG). We find that the previously established picture of a double-exchange driven magnetic structure, with minute energy gaps (<1 mHa) between consecutive spin states, has a weak dependence on the underlying geometry. However, the spin gap between the singlet and the spin state 2S + 1 = 19, corresponding to a maximal number of Fe-d electrons being unpaired and of parallel spin, is strongly geometry dependent, changing by a factor of 3 upon slight deformations that are still within biologically relevant parameters. The CASSCF orbital optimization procedure, using active spaces as large as 86 electrons in 52 orbitals, was found to reduce this gap compared to typical mean-field orbital approaches. Our results show the need for performing large active space calculations to unveil the challenging electronic structure of these complex catalytic centers and should serve as accurate starting points for fully correlated treatments upon inclusion of dynamical correlation outside the active space.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗