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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 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Cosmological constraints from the Planck cluster catalogue with DES shear profiles and Chandra observations

We present cosmological constraints from the Planck PSZ2 cosmological cluster sample, using weak-lensing shear profiles from Dark Energy Survey (DES) data and X-ray observations from the Chandra telescope for the mass calibration. We compute hydrostatic mass estimates for all clusters in the PSZ2 sample with a scaling relation between their Sunyaev-Zeldovich signal and X-ray derived hydrostatic mass, calibrated with the Chandra data. We introduce a method to correct these masses with a hydrostatic mass bias using shear profiles from wide-field galaxy surveys. We simultaneously fit the number counts of the PSZ2 sample and the mass calibration with the DES data, finding $Ω_\text{m}=0.312^{+0.018}_{-0.024}$, $σ_8=0.777\pm 0.024$, $S_8\equiv σ_8 \sqrt{Ω_\text{m} / 0.3}=0.791^{+0.023}_{-0.021}$, and $(1-b)=0.844^{+0.055}_{-0.062}$ for our baseline analysis when combined with BAO data. When considering a hydrostatic mass bias evolving with mass, we find $Ω_\text{m}=0.353^{+0.025}_{-0.031}$, $σ_8=0.751\pm 0.023$, and $S_8=0.814^{+0.019}_{-0.020}$. We verify the robustness of our results by exploring a variety of analysis settings, with a particular focus on the definition of the halo centre used for the extraction of shear profiles. We compare our results with a number of other analyses, in particular two recent analyses of cluster samples obtained from SPT and eROSITA data that share the same mass calibration data set. We find that our results are in overall agreement with most late-time probes, in very mild tension with CMB results (1.6$σ$), and in significant tension with results from eROSITA clusters (2.9$σ$). We confirm that our mass calibration is consistent with the eROSITA analysis by comparing masses for clusters present in both Planck and eROSITA samples, eliminating it as a potential cause of tension.

Aymerich, G. [Orsay, IAS; AIM, Saclay] (ORCID:0009↗
DOE OSTI2015

Examining the Critical Roles of Protons in Facilitating Oxidation of Chloride Ions by Permanganates: A Cluster Model Study

The oxidation power of permanganates (MnO4–) is known to be strongly dependent on pH values, and is greatly enhanced in acidic solutions, in which, for example, MnO4– can even oxidize Cl– ions to produce Cl2 molecules. Although such dependence has been ascribed due to the different reduced states of Mn affordable in different pH media, a molecular level understanding and characterization of initial redox pair complexes available in different pH solutions is very limited. Herein, we report a comparative study of [MnO4]– and [MnO4•Sol]– (Sol = H2O, KCl, and HCl) anion clusters by negative ion photoelectron spectroscopy (NIPES) and theoretical computations to probe chemical bonding and electronic structures of [MnO4•Sol]– clusters, aimed to obtain a microscopic understanding of how MnO4– interacts with surrounding molecules. Our study shows that H2O behaves as a solvent molecule, KCl is a spectator bound by pure electrostatic interactions, both of which do not influence the MnO4– identity in their respective clusters. In contrast, in [MnO4•HCl]–, the proton is found to interact with both MnO4– and Cl– with appreciable covalent characters, and the frontier MOs of the cluster are comprised of contributions from both MnO4– and Cl– moieties. Therefore the proton serves as a chemical bridge, bringing two negatively charged redox species together to form an intimate redox pair. By adding more H+ to MnO4–, the oxygen atom can be taken away in the form of a water molecule, leaving MnO4– as an electron deficient MnO3+ species, which can subsequently oxidize Cl– ions.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2018

Water Oxidation Catalysis via Size-Selected Iridium Clusters

Here, the detailed mechanism and efficacy of four electron electrochemical water oxidation depend critically upon the detailed atomic structure of each catalytic site, which are numerous and diverse in most metal oxides anodes. In order to limit the diversity of sites, arrays of discrete iridium clusters with identical metal atom number (Ir 2 , Ir 4 , or Ir 8 ) were deposited in submonolayer coverage on conductive oxide supports, and the electrochemical properties and activity of each was evaluated. Exceptional electroactivity for the oxygen evolving reaction (OER) was observed for all cluster samples in acidic electrolyte. Reproducible cluster-size-dependent trends in redox behavior were also resolved. First-principles computational models of the individual discrete-size clusters allow correlation of catalytic-site structure and multiplicity with redox behavior.

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

A Reference Architecture For Emulytics TM Clusters

In this document we describe a reference architecture developed for Emulytics TM clusters at Sandia National Laboratories. Taking into consideration the constraints of our Emulytics software and the requirements for integration with the larger computing facilities at Sandia, we developed a cluster platform suitable for use by Sandia's several Emulytics toolsets and also useful for more general large-scale computing tasks.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

An improved fast multipole method for electrostatic potential calculations in a class of coarse-grained molecular simulations

This paper presents a novel algorithm to approximate the long-range electrostatic potential field in the Cartesian coordinates applicable to 3D coarse-grained simulations of biopolymers. In such models, coarse-grained clusters are formed via treating groups of atoms as rigid and/or flexible bodies connected together via kinematic joints. Therefore, multibody dynamic techniques are used to form and solve the equations of motion of such coarse-grained systems. In this article, the approximations for the potential fields due to the interaction between a highly negatively/positively charged pseudo-atom and charged particles, as well as the interaction between clusters of charged particles, are presented. These approximations are expressed in terms of physical and geometrical properties of the bodies such as the entire charge, the location of the center of charge, and the pseudo-inertia tensor about the center of charge of the clusters. Further, a novel substructuring scheme is introduced to implement the presented far-field potential evaluations in a binary tree framework as opposed to the existing quadtree and octree strategies of implementing fast multipole method. Using the presented Lagrangian grids, the electrostatic potential is recursively calculated via sweeping two passes: assembly and disassembly. In the assembly pass, adjacent charged bodies are combined together to form new clusters. Then, the potential field of each cluster due to its interaction with faraway resulting clusters is recursively calculated in the disassembly pass. The method is highly compatible with multibody dynamic schemes to model coarse-grained biopolymers. Since the proposed method takes advantage of constant physical and geometrical properties of rigid clusters, improvement in the overall computational cost is observed comparing to the tradition application of fast multipole method.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

Detecting Extreme Events in Gridded Climate Data

Detecting and tracking extreme events in gridded climatological data is a challenging problem on several fronts: algorithms, scalability, and I/O. Successful detection of these events will give climate scientists an alternate view of the behavior of different climatological variables, leading to enhanced scientific understanding of the impacts of events such as heat and cold waves, and on a larger scale, the El Nin o Southern Oscillation. Recent advances in computing power and research in data sciences enabled us to look at this problem with a different perspective from what was previously possible. In this paper we present our computationally efficient algorithms for anomalous cluster detection on climate change big data. We provide results on detection and tracking of surface temperature and geopotential height anomalies, a trend analysis, and a study of relationships between the variables. We also identify the limitations of our approaches, future directions for research and alternate approaches.

climate extremes temperature anomalies reanalysis↗
DOE OSTI2023

Impact of Disorder and Defects on Bond Energies in Highly Fluorinated Graphene

Fluorinated graphite materials are of interest for an assortment of applications and can be synthesized under a variety of synthetic conditions from many different types of carbon. Due to such variations, structural disorders in the form of defects and polymorphism are often present. Here, we investigate the impact of local structural variations on the C–F bond dissociation energies (BDEs) in carbon-based fluoride materials using density functional theory (DFT) computational methods. Employing fluorographene (FG) cluster models, we determine the impact of different C–F bonding configurations in the core of each platelet on the equilibrium BDEs for each C–F bond. The introduction of structural disorder decreases the first C–F BDE by approximately 1 eV compared to the canonical arrangement of axial C–F bonds ordered as in a network of cyclohexane “chairs”. Variability of calculated BDEs among the different polymorphs decreases upon subsequent F removal. Common structural tendencies of the adiabatic defluorination pathways for each polymorph are identified. In conclusion, our analysis suggests that at F/C ratios near 1.0, disorder in the local structure can play a significant role in the energetics of the initial carbon fluoride defluorination and that the influence of this configurational disorder diminishes with decreasing F/C ratios.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Scattering of NH{sub 3} and ND{sub 3} with rare gas atoms at low collision energy

We present a theoretical study of elastic and rotationally inelastic collisions of NH{sub 3} and ND{sub 3} with rare gas atoms (He, Ne, Ar, Kr, Xe) at low energy. Quantum close-coupling calculations have been performed for energies between 0.001 and 300 cm{sup −1}. We focus on collisions in which NH{sub 3} is initially in the upper state of the inversion doublet with j = 1, k = 1, which is the most relevant in an experimental context as it can be trapped electrostatically and Stark-decelerated. We discuss the presence of resonances in the elastic and inelastic cross sections, as well as the trends in the inelastic cross sections along the rare gas series and the differences between NH{sub 3} and ND{sub 3} as a colliding partner. We also demonstrate the importance of explicitly taking into account the umbrella (inversion) motion of NH{sub 3} in order to obtain accurate scattering cross sections at low collision energy. Finally, we investigate the possibility of sympathetic cooling of ammonia using cold or ultracold rare gas atoms. We show that some systems exhibit a large ratio of elastic to inelastic cross sections in the cold regime, which is promising for sympathetic cooling experiments. The close-coupling calculations are based on previously reported ab initio potential energy surfaces for NH{sub 3}–He and NH{sub 3}–Ar, as well as on new, four-dimensional, potential energy surfaces for the interaction of ammonia with Ne, Kr, and Xe, which were computed using the coupled-cluster method and large basis sets. We compare the properties of the potential energy surfaces corresponding to the interaction of ammonia with the various rare gas atoms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

An integral-factorized implementation of the driven similarity renormalization group second-order multireference perturbation theory

We report an efficient implementation of a second-order multireference perturbation theory based on the driven similarity renormalization group (DSRG-MRPT2) [C. Li and F. A. Evangelista, J. Chem. Theory Comput. 11, 2097 (2015)]. Our implementation employs factorized two-electron integrals to avoid storage of large four-index intermediates. It also exploits the block structure of the reference density matrices to reduce the computational cost to that of second-order Møller–Plesset perturbation theory. Our new DSRG-MRPT2 implementation is benchmarked on ten naphthyne isomers using basis sets up to quintuple-ζ quality. We find that the singlet-triplet splittings (Δ{sub ST}) of the naphthyne isomers strongly depend on the equilibrium structures. For a consistent set of geometries, the Δ{sub ST} values predicted by the DSRG-MRPT2 are in good agreements with those computed by the reduced multireference coupled cluster theory with singles, doubles, and perturbative triples.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Fermi–Löwdin orbital self-interaction correction of adsorption energies on transition metal ions

Density functional theory (DFT)-based descriptions of the adsorption of small molecules on transition metal ions are prone to self-interaction errors. Here, we show that such errors lead to a large over-estimation of adsorption energies of small molecules on Cu + , Zn + , Zn 2+ , and Mn + in local spin density approximation (LSDA) and Perdew, Burke, Ernzerhof (PBE) generalized gradient approximation calculations compared to reference values computed using the coupled-cluster with single, doubles, and perturbative triple excitations method. These errors are significantly reduced by removing self-interaction using the Perdew–Zunger self-interaction correction (PZ-SIC) in the Fermi–Löwdin Orbital (FLO) SIC framework. In the case of FLO-PBE, typical errors are reduced to less than 0.1 eV. Furthermore, analysis of the results using DFT energies evaluated on self-interaction-corrected densities [DFT(@FLO)] indicates that the density-driven contributions to the FLO-DFT adsorption energy corrections are roughly the same size in DFT = LSDA and PBE, but the total corrections due to removing self-interaction are larger in LSDA.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Infrared extrapolations for atomic nuclei

Harmonic oscillator model-space truncations introduce systematic errors to the calculation of binding energies and other observables. We identify the relevant infrared (IR) scaling variable and give values for this nucleus-dependent quantity. We consider isotopes of oxygen computed with the coupled-cluster method from chiral nucleon–nucleon interactions at next-to-next-to-leading order and show that the IR component of the error is sufficiently understood to permit controlled extrapolations. By employing oscillator spaces with relatively large frequencies, that are well above the energy minimum, the ultraviolet corrections can be suppressed while IR extrapolations over tens of MeVs are accurate for ground-state energies. However, robust uncertainty quantification for extrapolated quantities that fully accounts for systematic errors is not yet developed.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Ab initio coupled-cluster calculations of ground and dipole excited states in He 8

We perform coupled-cluster calculations of ground- and dipole excited-state properties of the 8 He halo nucleus with nucleon-nucleon and three-nucleon interactions from chiral effective field theory, both with and without explicit delta degrees of freedom. By increasing the precision in our coupled-cluster calculations via the inclusion of leading-order three-particle three-hole excitations in the cluster operator, we obtain a ground-state energy and a charge radius that are consistent with experiment, albeit with a slight underbinding. We also investigate the excited states induced by the electric dipole operator and present a discussion on the Thomas-Reiche-Kuhn and cluster sum rules. Lastly, we compute the electric dipole polarizability, providing a theoretical benchmark for future experimental determinations that will study this exotic nucleus.

6 ≤ A ≤ 19↗
DOE OSTI2017

rvGAHP: push-based job submission using reverse SSH connections. In: WORKS '17 Proceedings of the 12th Workshop on Workflows in Support of Large-Scale Science, Article No. 3

Computational science researchers running large-scale scientific workflow applications often want to run their workflows on the largest available compute systems to improve time to solution. Workflow tools used in distributed, heterogeneous, high performance computing environments typically rely on either a push-based or a pull-based approach for resource provisioning from these compute systems. However, many large clusters have moved to two-factor authentication for job submission, making traditional automated push-based job submission impossible. On the other hand, pull-based approaches such as pilot jobs may lead to increased complexity and a reduction in node-hour efficiency. In this paper, we describe a new, efficient approach based on HTCondor-G called reverse GAHP (rvGAHP) that allows us to push jobs using reverse SSH submissions with better efficiency than pull-based methods. We successfully used this approach to perform a large probabilistic seismic hazard analysis study using SCEC's CyberShake workflow in March 2017 on the Titan Cray XK7 hybrid system at Oak Ridge National Laboratory.

Callaghan, Scott↗
DOE OSTI2018

berkeleylab/reproducible

The software is a research tool for improving the reproducibility of simulations. It does this by keeping a log file of the input file and the input parameters; it also helps with running the same simulations on different computers such as desktops and clusters. It's should be useful for anyone who runs many simulations with input files that are kept in a git repository.

Persaud, Arun↗
DOE OSTI2015

Translating Non-Trivial Algorithms from the Circuit Model to the Measurement

We provide a set of prescriptions for implementing a circuit model algorithm as measurement based quantum computing via a large discrete cluster state constructed sequentially, from qubits implemented as single photons. We describe a large optical discrete graph state capable of searching logical 4 and 8 element lists as an example. To do so we have developed several prescriptions based on analytic evaluation of the evolution of discrete cluster states and graph state equations. We describe the cluster state as a sequence of repeated entanglement and measurement steps using a small number of single photons for each step. These prescriptions can be generalized to implement any logical circuit model operation with appropriate single photon measurements and feed forward error corrections. Such a cluster state is not guaranteed to be optimal (i.e. minimum number of photons, measurements, run time).

Smith, IV, Amos M↗
DOE OSTI2017

The FabrIc for Frontier Experiments Project at Fermilab: Computing for Experiments

The FabrIc for Frontier Experiments (FIFE) project is a major initiative within the Fermilab Scientific Computing Division designed to steer the computing model for non-LHC experiments at Fermilab. The FIFE project enables close collaboration between experimenters and computing professionals to serve high-energy physics experiments of differing scope and physics area of study. The project also tracks and provides feedback on the development of common tools for job submission, identity management, software and data distribution, job monitoring, and databases for project tracking. The computing needs of the experiments under the FIFE umbrella continue to increase, and present a complex list of requirements to their service providers. To meet these requirements, recent advances in the FIFE toolset include a new identity management infrastructure, significantly upgraded job monitoring tools, and a workflow management system. We have also upgraded existing tools to access remote computing resources such as GPU clusters and sites outside the United States. We will present these recent advances, highlight the nature of collaboration between the diverse set of experimenters and service providers, and discuss the project's future directions.

43 PARTICLE ACCELERATORS↗
DOE OSTI2017

ML-GA

ML-GA is a software that can be used to expedite design optimization process combining machine learning and genetic algorithm approaches. It employs a machine learning (ML) model (any ML algorithm can be incorporated) to predict the quality (merit) of a design from the input parameters. Then, a stochastic global optimization genetic algorithm (GA) is used, with the machine learning model as the objective function, to optimize the input parameters based on the merit function. ML-GA is scalable to higher computational platforms like supercomputers and clusters enabling optimization to be performed in significantly short time frames (e.g., in a day).

PAL, PINAKI↗