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DOE OSTI2020

Achieving balanced execution through runtime detection of performance variation

Systems, apparatuses, and methods for achieving balanced execution in a multi-node cluster through runtime detection of performance variation are described. During a training phase, performance counters and an amount of time spent waiting for synchronization is monitored for a plurality of tasks for each node of the multi-node cluster. These values are utilized to generate a model which correlates the values of the performance counters to the amount of time spent waiting for synchronization. Once the model is built, the values of the performance counters are monitored for a period of time at the start of each task, and these values are input into the model. The model generates a prediction of whether a given node is on the critical path. If the given node is predicted to be on the critical path, the power allocation of the given node is increased.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2026

SPT-3G D1: Compton-$y$ maps using data from the SPT-3G and Planck surveys

We present thermal Sunyaev-Zel'dovich (tSZ) Compton-$y$ parameter maps constructed from two years (2019-2020) of observations with the South Pole Telescope (SPT) third-generation camera, SPT-3G, combined with data from the Planck satellite. Using a linear combination (LC) pipeline, we obtain a suite of reconstructions that explore different trade-offs between statistical sensitivity and suppression of astrophysical contaminants, including minimum-variance, CMB-deprojected, and CIB-deprojected $y$-maps. We validate these maps through different statistical techniques such as auto- and cross-power spectra with large-scale structure tracers as well as stacking on cluster locations. These tests are used to understand the balance between noise and astrophysical foreground residuals (such as the CIB) in combination with the recovery of the tSZ signal for different maps. For example, results from stacking at the location of clusters confirm the robustness of the recovered tSZ signal over the $\sim 1500\: {\rm deg}^2$ SPT-3G survey field used in this analysis. The high-resolution and low-noise maps produced here provide an important cosmological tool for future studies, including measurements of the Compton-$y$ map power spectrum, cross-correlations with other tracers of the large-scale structure, detailed modeling of cluster pressure profiles, and study of the thermodynamic state of the baryons in the Universe.

Maniyar, A. S. [Harvard-Smithsonian Ctr. Astrophys↗

DOE OSTI2020

Supramolecular Assembly of U(IV) Clusters and Superatoms with Unconventional Countercations

Superatoms are nanometer-sized molecules or particles that form ordered lattices, mimicking their atomic counterparts. Hierarchical assembly of superatoms gives rise to emergent properties in lattices of quantum dots, p-block clusters, and fullerenes. In this report, we introduce a family of uranium-oxysulfate cluster anions whose hierarchical assembly in water is controlled by two parameters: acidity and the lanthanide or transition-metal countercation. In acid, larger Ln III (Ln = La–Ho) link hexamer (U 6 ) oxoclusters into body-centered cubic frameworks, while smaller Ln III (Ln = Er–Lu and Y) promote linking of 14 U 6 clusters into hollow superclusters (U 84 superatoms). U 84 assembles into superlattices including cubic-closest packed, body-centered cubic, and interpenetrating networks, bridged by interstitial countercations and U 6 clusters. Divalent transition metals (TM = Mn II and Zn II ) charge-balance and promote the fusion of 10 U 6 and 10 U monomers into a wheel-shaped cluster (U 70 ). Dissolution of U 70 in organic media shows (by small-angle X-ray scattering) that differing supramolecular assemblies are accessed, controlled by TM II -linking of U 70 clusters. Magnetic measurements of these assemblies reveal Curie–Weiss behavior at high temperatures, without pairing of the 5f 2 -electrons down to 2 K.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Metastable Clusters and Competitive Solvation Tune Ion Pairing at Liquid Interfaces

The balance of hydrophobic and hydrophilic interactions underlies emergent phenomena in complex multicomponent chemical systems. Here, we show that a supposedly ‘non–interacting’ nonpolar phase can be used to competitively solvate amphiphilic molecules at an oil/aqueous interface. This solvation, as probed by surface specific nonlinear spectroscopy and simulations, results in a molecularly thin corrugated phase boundary featuring metastable assemblies that alter the hydrogen bonding networks of water and the apparent ‘hard/soft’ descriptors used to describe ionic interactions. We show that competitive solvation enhances amphiphile mobility, opening up otherwise energetically inaccessible complexes that transiently interact with aqueous phase ions. These transient species impact ensemble binding affinities and may represent the molecular agents responsible for aspects of ionic transport and function. In conclusion, the result of this work highlights how seemingly unrelated nonpolar interactions feedback onto aqueous phase chemical phenomena, providing a pathway to tune phase separation and self-assembly to access new reaction pathways using interfaces for a range of chemical and biological systems.

Anions↗

DOE OSTI2023

Magic Numbers and Stabilities of Photoionized Water Clusters: Computational and Experimental Characterization of the Nanosolvated Hydronium Ion

The stability and distributions of small water clusters generated in a supersonic beam expansion are interrogated by tunable vacuum ultraviolet (VUV) radiation generated at a synchrotron. Time-of-flight mass spectrometry reveals enhanced population of various protonated water clusters (H + (H 2 O) $n$ ) based upon ionization energy and photoionization distance from source, suggesting there are "magic" numbers below the traditional $n$ = 21 that predominates in the literature. These intensity distributions suggest that VUV threshold photoionization (11.0-11.5 eV) of neutral water clusters close to the nozzle exit leads to a different nonequilibrium state compared to a skimmed molecular beam. This results in the appearance of a new magic number at 14. Metadynamics conformer searches coupled with modern density functional calculations are used to identify the global minimum energy structures of protonated water clusters between $n$ = 2 and 21, as well as the manifold of low-lying metastable minima. New lowest energy structures are reported for the cases of $n$ = 5, 6, 11, 12, 16, and 18, and special stability is identified by several measures. These theoretical results are in agreement with the experiments performed in this work in that $n$ = 14 is shown to exhibit additional stability, based on the computed second-order stabilization energy relative to most cluster sizes, though not to the extent of the well-known $n$ = 21 cluster. Other cluster sizes that show some additional energetic stability are $n$ = 7, 9, 12, 17, and 19. To gain insight into the balance between ion-water and water-water interactions as a function of the cluster size, an analysis of the effective two-body interactions (which sum exactly to the total interaction energy) was performed. In conclusion, this analysis reveals a crossover as a function of cluster size between a water-hydronium-dominated regime for small clusters and a water-water-dominated regime for larger clusters around $n$ = 17.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Internal Conversion between Bright (1 1 B $^+_u$) and Dark (21 A $^-_g$) States in s- trans -Butadiene and s- trans -Hexatriene

Internal conversion (IC) between the two lowest singlet excited states, 1 1 B$_u^+$ and 2 1 A$_g^–$, of s-trans-butadiene and s-trans-hexatriene is investigated using a series of single- and multi- reference wave function and density functional theory (DFT) methodologies. Three independent types of the equation-of-motion coupled-cluster (EOMCC) theory capable of providing an accurate and balanced description of one- as well as two-electron transitions, abbreviated as δ-CR-EOMCC(2,3), DIP-EOMCC(4h2p){N o }, and DEA-EOMCC(4p2h){N u } or DEA-EOMCC(3p1h,4p2h){N u }, consistently predict that the 1 1 B$_u^+$/2 1 A$_g^–$ crossing in both molecules occurs along the bond length alternation coordinate. However, the analogous 1 1 B$_u^+$ and 2 1 A$_g^–$ potentials obtained with some multireference approaches, such as CASSCF and MRCIS(D), as well as with the linear-response formulation of time-dependent DFT (TDDFT), do not cross. Hence, caution needs to be exercised when studying the low-lying singlet excited states of polyenes with conventional multiconfigurational methods and TDDFT. The multistate many-body perturbation theory methods, such as XMCQDPT 2 , do correctly reproduce the curve crossing. Among the simplest and least expensive computational methodologies, the DFT approaches that incorporate the contributions of doubly excited configurations, abbreviated as MRSF (mixed reference spin-flip) TDDFT and SSR( 4,4 ), accurately reproduce our best EOMCC results. This is highly promising for nonadiabatic molecular dynamics simulations in larger systems.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Computational Estimation by Scientific Data Mining with Classical Methods to Automate Learning Strategies of Scientists

Experimental results are often plotted as 2-dimensional graphical plots (aka graphs) in scientific domains depicting dependent versus independent variables to aid visual analysis of processes. Repeatedly performing laboratory experiments consumes significant time and resources, motivating the need for computational estimation. The goals are to estimate the graph obtained in an experiment given its input conditions, and to estimate the conditions that would lead to a desired graph. Existing estimation approaches often do not meet accuracy and efficiency needs of targeted applications. We develop a computational estimation approach called AutoDomainMine that integrates clustering and classification over complex scientific data in a framework so as to automate classical learning methods of scientists. Knowledge discovered thereby from a database of existing experiments serves as the basis for estimation. Challenges include preserving domain semantics in clustering, finding matching strategies in classification, striking a good balance between elaboration and conciseness while displaying estimation results based on needs of targeted users, and deriving objective measures to capture subjective user interests. These and other challenges are addressed in this work. The AutoDomainMine approach is used to build a computational estimation system, rigorously evaluated with real data in Materials Science. Our evaluation confirms that AutoDomainMine provides desired accuracy and efficiency in computational estimation. It is extendable to other science and engineering domains as proved by adaptation of its sub-processes within fields such as Bioinformatics and Nanotechnology.

Computer Science↗

DOE OSTI2020

Molecular Specificity and Proton Transfer Mechanisms in Aerosol Prenucleation Clusters Relevant to New Particle Formation

Atmospheric aerosol particles influence Earth’s radiative energy balance and cloud properties either directly through interacting with the solar radiation or indirectly through acting as cloud condensation nuclei (CCN), thus impacting Earth’s climate change, air quality, and human health. Regarding both the important scientific and overarching practical implications of aerosols, the past two decades have seen an extensive research effort, with emphasis on the chemical compositions and underlying mechanisms of aerosol formation. New particle formation (NPF) has been recognized as an important pathway, contributing up to 50% of atmospheric aerosols. Nowadays, the general consensus in NPF is that it proceeds via two distinct stages—the nucleation from gaseous precursors to form critical nuclei of sub-1–2 nanometer size, and the subsequent growth into large particles. However, a fundamental understanding of both the NPF process and the molecular-level characterization of the critical size aerosol clusters is still largely missing, hampering the development of reliable and predictive aerosol nucleation and climate models.

Hou, Gao-Lei↗

DOE OSTI2023

OCTOKV: An Agile Network-Based Key-Value Storage System with Robust Load Orchestration

In this paper, we propose OctoKV, an innovative network-based key-value storage system. OctoKV addresses the repetitive address translation overhead associated with traditional key-value stores running on file systems on the client side. To mitigate this overhead, we implemented the key-value store on the server side using NVMe-oF and a user-level NVMe driver. In particular, we employed fine-grained resource monitoring and load balancing based on heuristics to optimize I/O performance. OctoKV is deployed on a Linux cluster with Intel SPDK. The extensive evaluation shows that OctoKV achieves lower I/O response times in comparison to traditional approaches where key-value stores run on the client side. Also, the proposed load balancing strategies efficiently enhance I/O response times by equally distributing the workload from overloaded cores to other cores.

Khan, Awais↗

DOE OSTI2020

Roles of Alkali Metals and Ionic Networks in Directing the Formation of Anionic Metal–Organic Frameworks

Integrating different types of fundamental chemical interactions to direct the self-assembly processes and to control the dimension of the network formed by each type of interactions is a promising strategy to develop advanced functional materials. Here, the ionic interaction of alkali metals (Na, K, Cs) towards multi-functional 2,2’-disulfo-4,4’-oxydibenzoic acid is utilized in two solvent systems, aqueous-amide and uro-amide, to synthesize six novel anionic framework materials with dramatically different features and dimensionalities: (Na 3 [Zn 4 O(L 4- ) 3 (e-murea)(H 2 O) 3 ](H 2 N(CH 3 ) 2 +) 3 (CPM-s1), [Zn 4 O(L 4- ) 3 (DMF)]((NH 2 (CH 3 ) 2 +) 6 ) (CPM-s2), Na 6 [(Zn 2 OH 2 ) 3 (L 3- ) 6 ](H 2 O) 3 (CPM-s3), K 3 [Zn 2 (L 4- ) 2 ](H 2 N(CH 3 ) 2 +)(e-murea) 2 (H 2 O) 3 (CPM-s4), K 4 [Zn(L 3- ) 2 ](H 2 O) 2 (CPM-s5), and Cs 6 [Zn(L 4- ) 2 ](H 2 O) 2 (CPM-s6), L 4- = 2,2’-disulfo-4,4’-oxydibenzoate, DMF = N,N-dimethylformamide, e-murea = 1,3-dimethyl-1-2-imidazolidinone). In CPM-s1 to CPM-s6, the alkali-sulfonate ionic bonding networks transformed from 0D clusters with Na + to 1D chains and 2D sheets with K + , and 3D network with Cs + . These vastly differing ionic domains influenced the coordination modes and spatial arrangements of the metal-carboxylate linkers, which consequently, directed the dimensionality of the coordination networks from 3D with Na + to 1D with Cs + . CPM-s1 and CPM-s2, made from tetrameric Zn 4 O clusters are rare examples of anionic MOF-5-type structures. CPM-s3 features an unprecedented hexameric Zn 6 cluster. Even though a large portion of the charge-balancing cations in these materials would hamper hydrogen bonding networks, some of them still exhibit very high ionic conductivity (e.g. 1.25 x 10 -3 S cm -1 in CPM-s3), suggesting the potential of these materials as solid-state electrolytes.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Summer Proceedings 2019

The Computer Science Research Institute (CSRI) brings university faculty and students to Sandia for focused collaborative research on Department of Energy (DOE) computer and computational science problems. The institute provides an opportunity for university researchers to learn about problems in computer and computational science at DOE laboratories. Participants conduct leading-edge research, interact with scientists and engineers at the laboratories, and help transfer results of their research to programs at the labs. Some specific CSRI research interest areas are: scalable solvers, optimization, adaptivity and mesh refinement, graph-based, discrete, and combinatorial algorithms, uncertainty estimation, mesh generation, dynamic load-balancing, virus and other malicious-code defense, visualization, scalable cluster computers and heterogeneous computers, data-intensive computing, environments for scalable computing, parallel input/output, advanced architectures, and theoretical computer science. The CSRI Summer Program includes the organization of a weekly seminar series and the publication of this summer proceedings.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

CSRI Summer Proceedings 2020

The Computer Science Research Institute (CSRI) brings university faculty and students to Sandia for focused collaborative research on Department of Energy (DOE) computer and computational science problems. The institute provides an opportunity for university researchers to learn about problems in computer and computational science at DOE laboratories. Participants conduct leading-edge research, interact with scientists and engineers at the laboratories, and help transfer results of their research to programs at the labs. Some specific CSRI research interest areas are: scalable solvers, optimization, adaptivity and mesh refinement, graph-based, discrete, and combinatorial algorithms, uncertainty estimation, mesh generation, dynamic load-balancing, virus and other malicious-code defense, visualization, scalable cluster computers, data-intensive computing, environments for scalable computing, parallel input/output, advanced architectures, and theoretical computer science. The CSRI Summer Program is organized by CSRI and typically includes the organization of a weekly seminar series and the publication of a summer proceedings. In 2020, the CSRI summer program was executed completely virtually; all student interns worked from home, due to the COVID-19 pandemic.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Power Sector Cybersecurity Building Blocks

The Power Sector Cybersecurity Building Blocks, developed through the USAID-NREL Partnership and the Resilient Energy Platform, are designed to help a variety of stakeholders improve security for the electrical grid. This effort grows out of USAID and NREL's discussions with utilities around the world, as well as past cybersecurity assessments performed by NREL on dozens of utilities and government agencies, with a focus on the cybersecurity challenges faced by small and under-resourced utilities. This document outlines eleven building blocks for power sector cyber security. It functions as a guide to help organizations develop a robust, balanced cybersecurity defense program. Individually, each building block represents a cluster of related activities within cybersecurity on which an organization should focus. Using the building blocks, organizations can effectively prioritize their cybersecurity efforts to best thwart a wide range of potential cyberattacks.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

CSRI Summer Proceedings 2021

The Computer Science Research Institute (CSRI) brings university faculty and students to Sandia National Laboratories for focused collaborative research on Department of Energy (DOE) computer and computational science problems. The institute provides an opportunity for university researches to learn about problems in computer and computational science at DOE laboratories, and help transfer results of their research to programs at the labs. Some specific CSRI research interest areas are: scalable solvers, optimization, algebraic preconditioners, graph-based, discrete, and combinatorial algorithms, uncertainty estimation, validation and verification methods, mesh generation, dynamic load-balancing, virus and other malicious-code defense, visualization, scalable cluster computers, beyond Moore’s Law computing, exascale computing tools and application design, reduced order and multiscale modeling, parallel input/output, and theoretical computer science. The CSRI Summer Program is organized by CSRI and includes a weekly seminar series and the publication of a summer proceedings.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

CSRI Summer Proceedings 2021

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Resilient Energy Platform. Fact Sheet: Power Sector Cybersecurity Building Blocks

building blocks↗

DOE OSTI2021

Influence of Al location on formation of silver clusters in mordenite

Formation of zeolite supported Ag 0 clusters depends on a combination of thermodynamically stable atomic configurations, charge balance considerations, and mobility of species on the surface and within pores. Periodic density functional theory (DFT) calculations were performed to evaluate how the location of Al in the mordenite (MOR) framework and humidity control Ag 0 nanocluster formation. Four Al framework sites were studied (T1-T4) and the Al positions in the framework were identified by the shifts in the differential Al…Al pair distribution function (PDF). Furthermore, structural information about the Ag 0 nanoclusters, such as dangling bonds, can be identified by Ag…Ag PDF data. For Ag 0 formation in vacuum MOR structures with a Si:Al ratio of 5:1 with Al in the T1 position resulted in the most framework flexibility and the lowest Ag 0 nanocluster charge, indicating the best result for formation of charge neutral nanoclusters. When water is present, Al in the T3 and T4 positions results in the formation of the smallest average Ag 0 nanoclusters plus greater expansion of the O-T-O bond angle than in vacuum, indicating easier diffusion of the Ag 0 nanoclusters to the surface. Here, the presence of Al in 4-membered rings and in pairs indicates favorable MOR structures for formation of single Ag atoms, despite the existence of synthesis challenges. Therefore, Al in the T2 position is the least favorable for Ag 0 nanocluster formation in both vacuum and in the presence of water. Al in the T1, T3, and T4 positions provides beneficial effects through framework flexibility and changes in nanocluster size or charge that can be leveraged for design of zeolites for formation of metallic nanoclusters.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Clustering Effects on the Structure of Ionomer Solutions: A Combined SANS and Simulations Study

Ionic assemblies, or clusters, determine the structure and dynamics of ionizable polymers and enable their many applications. Fundamental to attaining well-defined materials is controlling the balance between van der Waals interactions that govern the backbone behavior and the forces that drive the formation of ionic clusters. Here, using small angle neutron scattering and fully atomistic molecular dynamics simulations, the structure of a model ionomer, sulfonated polystyrene in toluene solutions, was investigated as the cluster cohesion was tweaked by the addition of ethanol. The static structure factor was measured by both techniques and correlated with the size of the ionic clusters as the polymer concentration was varied. The conjunction of SANS results and molecular insight from MD simulations enabled the determination of the structure in these inhomogeneous networks on multiple length scales. Additionally, we find that across the entire concentration range studied, a network driven by the formation of ionic clusters was formed, where the size of the clusters drives the inhomogeneity of these systems. Tweaking the ionic clusters through the addition of ethanol impacts the packing of the sulfonated groups, their shape, and their size distribution, which in turn, affects the structure of these networks.

36 MATERIALS SCIENCE↗