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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Multiprobe cosmology from the abundance of SPT clusters and DES galaxy clustering and weak lensing

Cosmic shear, galaxy clustering, and the abundance of massive halos each probe the large-scale structure of the Universe in complementary ways. We present cosmological constraints from the joint analysis of the three probes, building on the latest analyses of the lensing-informed abundance of clusters identified by the South Pole Telescope (SPT) and of the auto- and cross-correlation of galaxy position and weak lensing measurements (3 × 2 ⁢pt) in the Dark Energy Survey (DES). We consider the cosmological correlation between the different tracers and we account for the systematic uncertainties that are shared between the large-scale lensing correlation functions and the small-scale lensing-based cluster mass calibration. Marginalized over the remaining Λ cold dark matter (Λ ⁢CDM) parameters (including the sum of neutrino masses) and 52 astrophysical modeling parameters, we measure Ω m = 0.300 ± 0.017 and 𝜎 8 = 0.797 ± 0.026. Compared to constraints from Planck primary cosmic microwave background (CMB) anisotropies, our constraints are only 15% wider with a probability to exceed of 0.22 (1.2⁢𝜎) for the two-parameter difference. We further obtain 𝑆 8 ≡𝜎 8 ⁢(Ω m /0.3) 0.5 = 0.796 ± 0.013 which is lower than the Planck measurement at the 1.6⁢𝜎 level. The combined SPT cluster, DES 3 ×2 ⁢pt, and Planck datasets mildly prefer a nonzero positive neutrino mass, with a 95% upper limit ∑ 𝑚 𝜈 < 0.25 eV on the sum of neutrino masses. Assuming a 𝑤⁢CDM model, we constrain the dark energy equation of state parameter 𝑤 = −1.1⁢5$^{+0.23}_{−0.17}$ and when combining with Planck primary CMB anisotropies, we recover 𝑤 = −1.2⁢0$^{+0.15}_{−0.09}$, a 1.7⁢𝜎 difference with a cosmological constant. The precision of our results highlights the benefits of multiwavelength multiprobe cosmology and our analysis paves the way for upcoming joint analyses of next-generation datasets.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Massively scalable workflows for quantum chemistry: BigChem and ChemCloud

Electronic structure theory, i.e., quantum chemistry, is the fundamental building block for many problems in computational chemistry. Here we present a new distributed computing framework (BigChem), which allows for an efficient solution of many quantum chemistry problems in parallel. BigChem is designed to be easily composable and leverages industry-standard middleware (e.g., Celery, RabbitMQ, and Redis) for distributed approaches to large scale problems. BigChem can harness any collection of worker nodes, including ones on cloud providers (such as AWS or Azure), local clusters, or supercomputer centers (and any mixture of these). BigChem builds upon MolSSI packages, such as QCEngine to standardize the operation of numerous computational chemistry programs, demonstrated here with Psi4, xtb, geomeTRIC, and TeraChem. BigChem delivers full utilization of compute resources at scale, offers a programable canvas for designing sophisticated quantum chemistry workflows, and is fault tolerant to node failures and network disruptions. We demonstrate linear scalability of BigChem running computational chemistry workloads on up to 125 GPUs. Finally, we present ChemCloud, a web API to BigChem and successor to TeraChem Cloud. ChemCloud delivers scalable and secure access to BigChem over the Internet.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Programming Function via Soft Materials (PFvSM) (Final Report)

The PFvSM cluster at the University of Illinois greatly deepened the science of soft materials and expanded the means for embedding within them unprecedented functionalities. We pioneered a mesoscopic approach to materials design that combined leading competencies in fundamental experimental and theoretical soft matter science and fabrication that powerfully establishes equilibrium and nonequilibrium assembly of novel and complex building blocks as a preeminent contributor to progress in materials chemistry. Our cluster’s vision was an integrated program of work centered on soft matter science with the ultimate goal of impacting important energy technologies. As elementary units we employed function-encoded colloids, nanoparticles, large mesh fibrillar gels, deterministically fabricated networks and hybrid objects. These materials were employed as building blocks for diverse model systems that allowed fundamental soft matter principles of wide relevance to be established. Their assembly into materials with useful functional behavior provided new approaches to challenging problems in basic energy science including energy harvesting, transport and storage. To achieve these goals the cluster brought together a team of recognized world-leaders in materials synthesis and processing, in-situ characterization, theory and modeling, and materials design, integration and fabrication

36 MATERIALS SCIENCE↗
DOE OSTI2020

Untangling the Galaxy. II. Structure within 3 kpc

We present the results of the hierarchical clustering analysis of the Gaia DR2 data to search for clusters, comoving groups, and other stellar structures. The current paper builds on the sample from the previous work, extending it in distance from 1 to 3 kpc and increasing the number of identified structures up to 8292. To aid in the analysis of the population properties, we developed a neural network called Auriga to robustly estimate the age, extinction, and distance of a stellar group based on the input photometry and parallaxes of the individual members. We apply Auriga to derive the properties of not only the structures found in this paper, but also previously identified open clusters. Through this work, we examine the temporal structure of the spiral arms. Specifically, we find that the Sagittarius Arm has moved by >500 pc in the last 100 Myr and the Perseus Arm has been experiencing a relative lull in star formation activity over the last 25 Myr. We confirm the findings of the previous paper on the transient nature of the spiral arms, with the timescale of transition of a few 100 Myr. Finally, we find a peculiar ~1 Gyr old stream of stars that appears to be heliocentric. Its origin is unclear.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2016

Using Docker Containers to Extend Reproducibility Architecture for the NASA Earth Exchange (NEX)

NASA Earth Exchange (NEX) is a data, supercomputing and knowledge collaboratory that houses NASA satellite, climate and ancillary data where a focused community can come together to address large-scale challenges in Earth sciences. As NEX has been growing into a petabyte-size platform for analysis, experiments and data production, it has been increasingly important to enable users to easily retrace their steps, identify what datasets were produced by which process chains, and give them ability to readily reproduce their results. This can be a tedious and difficult task even for a small project, but is almost impossible on large processing pipelines. We have developed an initial reproducibility and knowledge capture solution for the NEX, however, if users want to move the code to another system, whether it is their home institution cluster, laptop or the cloud, they have to find, build and install all the required dependencies that would run their code. This can be a very tedious and tricky process and is a big impediment to moving code to data and reproducibility outside the original system. The NEX team has tried to assist users who wanted to move their code into OpenNEX on Amazon cloud by creating custom virtual machines with all the software and dependencies installed, but this, while solving some of the issues, creates a new bottleneck that requires the NEX team to be involved with any new request, updates to virtual machines and general maintenance support. In this presentation, we will describe a solution that integrates NEX and Docker to bridge the gap in code-to-data migration. The core of the solution is saemi-automatic conversion of science codes, tools and services that are already tracked and described in the NEX provenance system, to Docker - an open-source Linux container software. Docker is available on most computer platforms, easy to install and capable of seamlessly creating and/or executing any application packaged in the appropriate format. We believe this is an important step towards seamless process deployment in heterogeneous environments that will enhance community access to NASA data and tools in a scalable way, promote software reuse, and improve reproducibility of scientific results.

earth exchange↗
DOE OSTI2020

Theoretical insight into thermodynamics of particle-based crystallization

Crystallization process often does not follow the monomer-by-monomer addition pathway, as described by classical nucleation theory. Instead, initial step may involve the formation of larger building blocks, such as crystalline or amorphous nanoparticles, droplets, clusters, complexes or oligomers, which subsequently undergo assembly into a crystal. These multistep crystallization processes are ubiquitous in mineral formation and biomineralization. In materials synthesis utilizing non-classical crystallization pathways is particularly attractive as the restriction on which crystalline faces can grow is lifted in a multistep crystallization process adding to the versatility of materials architectures that can be obtained. Predicting the outcomes of non-classical crystallization through the understanding of the control parameters influencing crystallization pathways is an important and challenging task essential for utilizing the full potential of non-classical crystallization in the design of functional materials. Here, the current status of the development of a predictive theoretical framework for modeling non-classical crystallization is reviewed.

Sushko, Maria L.↗
DOE OSTI2022

A Microporous Metal–Organic Framework Incorporating Both Primary and Secondary Building Units for Splitting Alkane Isomers

We demonstrate the assembly of a mononuclear metal center, a hexanuclear cluster, and a V-shaped, trapezoidal tetracarboxylate linker into a microporous MOF featuring an unprecedented 3-nodal (4,4,8)-c lyu topology. Here, the compound, HIAM-302, represents the first example that incorporates both primary building unit (PBU) and hexanuclear secondary building unit (SBU) in one structure, which should be attributed to the desymmetrized geometry of the organic linker. HIAM-302 possesses optimal pore dimensions and can separate mono-branched and di-branched alkanes through selective molecular sieving, which is of significant value in petrochemical industry.

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

Can assembly bias explain the lensing amplitude of the BOSS CMASS sample in a Planck cosmology?

ABSTRACT In this paper, we investigate whether galaxy assembly bias can reconcile the 20–40 ${{\ \rm per\ cent}}$ disagreement between the observed galaxy projected clustering signal and the galaxy–galaxy lensing signal in the Baryon Oscillation Spectroscopic Survey CMASS galaxy sample. We use the suite of abacuscosmos lambda cold dark matter simulations at Planck best-fitting cosmology and two flexible implementations of extended halo occupation distribution (HOD) models that incorporate galaxy assembly bias to build forward models and produce joint fits of the observed galaxy clustering signal and the galaxy–galaxy lensing signal. We find that our models using the standard HODs without any assembly bias generalizations continue to show a 20–40 ${{\ \rm per\ cent}}$ overprediction of the observed galaxy–galaxy lensing signal. We find that our implementations of galaxy assembly bias do not reconcile the two measurements at Planck best-fitting cosmology. In fact, despite incorporating galaxy assembly bias, the satellite distribution parameter, and the satellite velocity bias parameter into our extended HOD model, our fits still strongly suggest a $\sim \! 34{{\ \rm per\ cent}}$ discrepancy between the observed projected clustering and galaxy–galaxy lensing measurements. It remains to be seen whether a combination of other galaxy assembly bias models, alternative cosmological parameters, or baryonic effects can explain the amplitude difference between the two signals.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Equation-of-Motion Coupled-Cluster Cumulant Green’s Function for Excited States and X-ray Spectra

Green’s function methods within many-body perturbation theory provide a general framework for treating electronic correlations in excited states and spectra. Conventional methods using the Dyson equation or the cumulant expansion are typically based on the GW self-energy approximation. In order to extend this approximation in molecular systems, a non-perturbative real-time coupled-cluster cumulant Green’s function approach has been introduced, where the cumulant is obtained as the solution to a set of coupled first order, non-linear differential equations. This approach naturally includes non-linear corrections to conventional cumulant Green’s function techniques where the cumulant is linear in the GW self-energy. The method yields the spectral function associated with the core Green’s function, which is directly related to the x-ray photoemission spectra (XPS) of molecular systems. The approach also yields very good results for binding energies and satellite excitations. The x-ray absorption spectrum (XAS) is then obtained as a convolution of the core spectral function and an effective one-body absorption spectrum. Here this approach is extended to include the full coupled-cluster-singles (CCS) core Green’s function by including the complete form of the non-linear contributions to the cumulant as well as all single, double, and triple cluster excitations in the CC amplitude equations. This approach naturally builds in orthogonality and shake-up effects analogous to those in the Mahan-Noizeres-de Dominicis edge singularity corrections that enhance the XAS near the edge. Themethod is illustrated for the XPS and XAS of NH 3 .

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

An Automatic Learning Framework for Smart Residential Communities

Predictability has been foundational to matching supply and demand in the day-to-day operation of the electric power system. Demand predictability is eroding because of the increased use of renewable energy resources and more sophisticated loads, such as electric vehicles and smart appliances. In this paper, an automatic software framework is described which can be used for load forecasting in smart communities. A time-varying clustering-based Markov chain approach is used to predict the energy consumption of residential buildings in a smart community. The training data is based on 1-minute meter data of occupied homes over one month. The data points are first clustered based on the energy consumption and the time of the day. Then, the original data is converted using the Centroids of the clusters. A time-varying Markov chain is subsequently trained to model the energy consumption behavior of residents for each home using the transformed data. The trained model is shown to successfully predict load in 5-minute intervals over a 24 hours period.

Zandi, Helia↗
DOE OSTI2019

Stabilization of an Unprecedented Hexanuclear Secondary Building Unit in a Thorium-Based Metal–Organic Framework

The crystal structures of thorium clusters are important for understanding the formation and transformation mechanisms of actinide species in solution, which can in turns benefit nuclear waste processing and management. However, stabilizing thorium clusters in aqueous solution is quite challenging because of their fast olation and oxolation reactions. Here, we report a thorium-based meta-organic framework, NU-905, with the formula [Th 6 (μ 3 -O) 2 (HCOO) 4 (H 2 O) 6 ] [TCPP = tetrakis(4-carboxyphenyl)porphyrin], synthesized by a solvothermal reaction in N,N-dimethylformamide and water at 120 °C. NU-905 contains a hexanuclear secondary building unit (SBU), [Th 6 (μ 3 -O) 2 (HCOO) 4 (H 2 O) 6 ], which has never been reported previously. The SBUs are capped and bridged by the tetratopic linker TCPP to form a three-dimensional network with scu topology. The activated NU-905 exhibits permanent porosity and shows high catalytic activity for the selective photooxidation of a mustard gas simulant.

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

Light Exposure Promotes Degradation of Intermediates and Growth of Phosphine-Ligated Gold Clusters

Subnanometer clusters exhibit unique properties not observed at the bulk or nanometer scale. Many applications, however, require clusters to be monodisperse in size and composition.While substantial progress has been made empirically on producing specific-sized gold clusters using different ligands, the mechanisms of cluster formation remain insufficiently understood. Using high mass-resolution electrospray ionization mass spectrometry (ESI-MS), we characterized the formation of cationic triphenylphosphine-ligated gold clusters [Aux(PPh3)y z+] in solution. Our data provides evidence that small hydrogen-containing intermediate “building blocks” (i.e., Au2(PPh3)2H+, Au4(PPh3)4H+, and Au7(PPh3)7H5 2+) are responsible for the growth of larger gold clusters (i.e., Au6(PPh3)6 2+ and Au8(PPh3)7 2+) over several hours. In addition, intermediate degradation and cluster growth are shown to be dependent on irradiation of the reacting solution with light. Specifically, the rate of growth of large clusters is demonstrated to scale with the intensity of light exposure. Complementary theoretical calculations were also performed that provide molecular-level insight into the nature of the bonding between the hydrogens and gold atoms in the intermediate Au-phosphine clusters. Collectively, our joint experimental and theoretical findings advance the understanding of the factors at play in the size-selective synthesis of ligated gold clusters in solution.

Hewitt, Michael A.↗
DOE OSTI2019

Inhomogeneous Distribution of Cationic Surfactants around Anionic Molecular Clusters

An interesting phenomenon is reported when uranyl peroxide nanoclusters U 60 (Li 48+ m K 12 (OH) m [UO 2 (O 2 )(OH)] 60 (H 2 O) n , m ≈20 and n ≈310) interact with a small number of cationic surfactant molecules. Cationic surfactant molecules do not distribute evenly around the U 60 clusters during the interaction as expected. Instead, a small fraction of U 60 clusters attract almost all the surfactant molecules, leading to the self-assembly into supramolecular structures by using surfactant–U 60 complexes as building locks, and later further aggregate and precipitate based on hydrophobic interaction, whereas the rest of the clusters remained unbounded soluble macroions in bulk dispersion. This phenomenon nicely demonstrates a unique feature of macroion solutions. Furthermore, considering that Debye–Hückel approximation is no longer valid in such solutions, the competition between the local electrostatic interaction and hydrophobic interaction becomes important to regulate the solution behaviors of macroions.

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

A family of ionic supersalts with covalent-like directionality and unconventional multiferroicity

Ionic crystals composed of elemental ions such as NaCl are non-polar due to directionless ionic bonding interactions. Here, we show that these can develop polarity by changing their building blocks from elemental ions to superalkali and superhalogen cluster-ions, which mimic the chemistry of alkali and halogen atoms, respectively. Due to the non-spherical geometries of these cluster ions, corresponding supersalts form anisotropic polar structures with ionic bonding, yet covalent-like directionality, akin to sp 3 hybridized systems. Using density functional theory and extensive structure searches, we predict a series of stable ferroelectric/ferroelastic supersalts, PnH 4 MX 4 (Pn = N, P; M = B, Al, Fe; X = Cl, Br) composed of superalkali PnH 4 and superhalogen MX 4 ions. Unlike traditional ferroelectric/ferroelastic materials, the cluster-ion based supersalts possess ultra-low switching barrier and can endure large ion displacements and reversible strain. In particular, PH 4 FeBr 4 exhibits triferroic coupling of ferroelectricity, ferroelasticity, and antiferromagnetism with controllable spin directions via either ferroelastic or 90-degree ferroelectric switching.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Automated characterization of spatial and dynamical heterogeneity in supercooled liquids via implementation of machine learning

Abstract A computational approach by an implementation of the principle component analysis (PCA) with K -means and Gaussian mixture (GM) clustering methods from machine learning algorithms to identify structural and dynamical heterogeneities of supercooled liquids is developed. In this method, a collection of the average weighted coordination numbers ( W C N s ‾ ) of particles calculated from particles’ positions are used as an order parameter to build a low-dimensional representation of feature (structural) space for K -means clustering to sort the particles in the system into few meso-states using PCA. Nano-domains or aggregated clusters are also formed in configurational (real) space from a direct mapping using associated meso-states’ particle identities with some misclassified interfacial particles. These classification uncertainties can be improved by a co-learning strategy which utilizes the probabilistic GM clustering and the information transfer between the structural space and configurational space iteratively until convergence. A final classification of meso-states in structural space and domains in configurational space are stable over long times and measured to have dynamical heterogeneities. Armed with such a classification protocol, various studies over the thermodynamic and dynamical properties of these domains indicate that the observed heterogeneity is the result of liquid–liquid phase separation after quenching to a supercooled state.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Porting Fragmentation Methods to Graphical Processing Units Using an OpenMP Application Programming Interface: Offloading the Fock Build for Low Angular Momentum Functions

Here, a framework to offload four-index two-electron repulsion integrals to graphical processing units (GPUs) using OpenMP is discussed. The method has been applied to the Fock build for low angular momentum s and p functions in both the restricted Hartree–Fock (RHF) and in the effective fragment molecular orbital (EFMO) framework. Benchmark calculations for the GPU code for the pure RHF method show an increasing speedup relative to the existing OpenMP CPU code in GAMESS from 1.04 to 52× for clusters of 70–569 water molecules. The parallel efficiency on 24 NVIDIA V100 GPU boards also increases when increasing the system size: from 75 to 94% for water clusters that contain 303–1120 molecules. In the EFMO framework, the GPU Fock build shows a high linear scalability up to 4608 V100s with a parallel efficiency of 96% for calculations on a solvated mesoporous silica nanoparticle system with ~67,000 basis functions.

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

Robust clustering of the local Milky Way stellar kinematic substructures with Gaia eDR3

Understanding local stellar kinematic substructures in the solar neighbourhood helps build a complete picture of the formation of the Milky Way, as well as an empirical phase space distribution of dark matter that would inform detection experiments. We apply the clustering algorithm HDBSCAN on the Gaia early third data release to identify a list of stable clusters in velocity space and action-angle space by taking into account the measurement uncertainties and studying the stability of the clustering results. We find 1405 (497) stars in 23 (6) robust clusters in velocity space (action-angle space) that are consistently not associated with noise. We discuss the kinematic properties of these structures and study whether many of the small clusters belong to a similar larger cluster based on their chemical abundances. They are attributed to the known structures: the Gaia Sausage-Enceladus, the Helmi Stream, and globular cluster NGC 3201 are found in both spaces, while NGC 104 and the thick disc (Sequoia) are identified in velocity space (action-angle space). Although we do not identify any new structures, we find that the HDBSCAN member selection of already known structures is unstable to input kinematics of the stars when resampled within their uncertainties. We therefore present the stable subset of local kinematic structures, which are consistently identified by the clustering algorithm, and emphasize the need to take into account error propagation during both the manual and automated identification of stellar structures, both for existing ones as well as future discoveries.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Short-term apartment-level load forecasting using a modified neural network with selected auto-regressive features

Residential electricity load profiles and their diversity have become increasingly important to realize the benefits of Smart or Transactive Energy Networks (TENs). An important element of TENs will be practical, accurate, and implementable residential load forecasting techniques. While there have been many approaches to short-term load forecasting, few have included forecasting for individual households, partly because the high volatility and idiosyncrasies present in individual household load data can pose significant challenges. In this study, we develop a Convolutional Long Short-Term Memory-based neural network with Selected Autoregressive Features (termed a CLSAF model) to improve short-term household electricity load forecasting accuracy by employing three strategies: autoregressive features selection, exogenous features selection, and a “default” state to avoid overfitting at times of high load volatility. We include aggregations of apartments to floor and building level, because utilities may favor transactive approaches that rely on aggregator models, e.g., a cluster of consumers as opposed to an individual. We demonstrate that the CLSAF model, by virtue of its enhanced feature representation and modest computational resources, can accomplish load forecasting in a multi-family residential building across three spatial granularities (individual apartment/household, floor, and building levels), with an accuracy improvement of up to 25% compared to a persistence model. We propose a data screening technique to characterize time-series electricity-load data. This technique is suitable for integration into a TEN ecosystem and allows one to estimate confidence levels of the load forecasts to optimize computational resources and the risks associated with uncertain forecasts.

24 POWER TRANSMISSION AND DISTRIBUTION↗