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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Joint Estimation of Topology and Injection Statistics in Distribution Grids with Missing Nodes

Optimal operation of distribution grid resources relies on accurate estimation of its state and topology. Practical estimation of such quantities is complicated by the limited presence of real-time meters. This article discusses a theoretical framework to jointly estimate the operational topology and statistics of injections in radial distribution grids under limited availability of nodal voltage measurements. In particular, we show that our proposed algorithms are able to provably learn the exact grid topology and injection statistics at all unobserved nodes as long as they are not adjacent. The algorithm design is based on novel ordered trends in voltage magnitude fluctuations at node groups, that are independently of interest for radial physical flow networks. The complexity of the designed algorithms is theoretically analyzed and their performance is validated using both linearized and nonlinear ac power flow samples in test distribution grids.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Metal–Organic Frameworks with Zero and Low‐Valent Metal Nodes Connected by Tetratopic Phosphine Ligands

Abstract Metal–organic frameworks (MOFs) constructed with M 0 nodes are attractive targets due to the reactivity of these low‐valent metals, but examples of these MOFs remain exceedingly rare. The rational design of three‐dimensional MOFs with Pd 0 and Pt 0 nodes using tetratopic phosphine ligands is reported. Five new MOFs have been synthesized by systematic variation of the phosphine ligands and metal precursors employed, and these represent the first examples of MOFs constructed using phosphine–metal bonds as the sole structural component. The MOFs display solid‐state luminescence, with emission maxima that are significantly red‐shifted compared to Pd(PPh 3 ) 4 . In addition, a Rh I low‐valent coordination solid based on the same linker design is reported, which displays solid‐state luminescence that is not observed for the molecular analogue.

Sikma, R. Eric↗
DOE OSTI2022

Metal–Organic Frameworks with Zero and Low–Valent Metal Nodes Connected by Tetratopic Phosphine Ligands

Metal–organic frameworks (MOFs) constructed with M 0 nodes are attractive targets due to the reactivity of these low-valent metals, but examples of these MOFs remain exceedingly rare. The rational design of three-dimensional MOFs with Pd 0 and Pt 0 nodes using tetratopic phosphine ligands is reported. Five new MOFs have been synthesized by systematic variation of the phosphine ligands and metal precursors employed, and these represent the first examples of MOFs constructed using phosphine–metal bonds as the sole structural component. Furthermore, the MOFs display solid-state luminescence, with emission maxima that are significantly red-shifted compared to Pd(PPh 3 ) 4 . In addition, a Rh I low-valent coordination solid based on the same linker design is reported, which displays solid-state luminescence that is not observed for the molecular analogue.

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

Unveiling User Behavior on Summit Login Nodes as a User

We observe and analyze usage of the login nodes of the leadership class Summit supercomputer from the perspective of an ordinary user—not a system administrator—by periodically sampling user activities (job queues, running processes, etc.) for two full years (2020–2021). Our findings unveil key usage patterns that evidence misuse of the system, including gaming the policies, impairing I/O performance, and using login nodes as a sole computing resource. Our analysis highlights observed patterns for the execution of complex computations (workflows), which are key for processing large-scale applications.

Wilkinson, Sean↗
DOE OSTI2023

Multiscale spatial analysis of fracture nodes in two dimensions

Spatial arrangement of fractures as a function of scale is an important component of fracture quantification for inferential and predictive modeling. Available methods that analyze fracture spatial arrangement are based on one-dimensional spacing data; therefore, they are limited to semi-parallel fractures. Such methods cannot be applied to fracture networks in higher dimensions, particularly when fractures have different orientations. Here to characterize fracture arrangements in two dimensions, we propose using Ripley’s K-function, as a method of point pattern analysis, to quantify spatial arrangement of fracture nodes. Fracture nodes, such as barycenters, intersection points, and tips, are point-based representations of fracture locations and connectivity within the fracture network. We introduce formulations for isotropic as well as directional analyses of spatial arrangement. In addition, we derive formulations for edge correction in circular and rectangular study domains. Finally, we demonstrate applications of Ripley’s K-function on two natural fracture datasets. Our proposed method supports quantification and characterization of fracture spatial arrangements that allow practitioners to build representative models of fractures in the subsurface.

02 PETROLEUM↗
DOE OSTI2024

Beyond Single-Reference Fixed-Node Approximation in Ab Initio Diffusion Monte Carlo Using Antisymmetrized Geminal Power Applied to Systems with Hundreds of Electrons

Diffusion Monte Carlo (DMC) is an exact technique to project out the ground state (GS) of a Hamiltonian. Since the GS is always bosonic, in Fermionic systems, the projection needs to be carried out while imposing antisymmetric constraints, which is a nondeterministic polynomial hard problem. In practice, therefore, the application of DMC on electronic structure problems is made by employing the fixed-node (FN) approximation, consisting of performing DMC with the constraint of having a fixed, predefined nodal surface. How do we get the nodal surface? The typical approach, applied in systems having up to hundreds or even thousands of electrons, is to obtain the nodal surface from a preliminary mean-field approach (typically, a density functional theory calculation) used to obtain a single Slater determinant. This is known as single reference. In this paper, we propose a new approach, applicable to systems as large as the C 60 fullerene, which improves the nodes by going beyond the single reference. In practice, we employ an implicitly multireference ansatz (antisymmetrized geminal power wave function constraint with molecular orbitals), initialized on the preliminary mean-field approach, which is relaxed by optimizing a few parameters of the wave function determining the nodal surface by minimizing the FN-DMC energy. We highlight the improvements of the proposed approach over the standard single-reference method on several examples and, where feasible, the computational gain over the standard multireference ansatz, which makes the methods applicable to large systems. We also show that physical properties relying on relative energies, such as binding energies, are affordable and reliable within the proposed scheme.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Exploring the Computational Aspects of Propylene Oligomerization Catalysis Using M′ 2 M Type Trimetallic MOF Nodes

Metal-organic frameworks have emerged as promising materials in the field of catalysis. They offer an optimal ground for screening catalysts and tailoring their catalytic properties. Here, in this work, via density functional theory (DFT) calculations, we investigated the catalytic activity of the trimetallic MOF nodes, M' 2 M for propylene oligomerization, by varying the active metal M from Sc to Cu with M' being Fe, aiming to grasp the impact of altering the active atoms on the catalyst's activity. Additionally, we examined how substituting the spectator atom, M', with other transition metals, i.e., from Sc to Cu, affects these energy barriers, keeping Ni as the active metal. We proposed several cases with lower or comparable energy barriers to the experimentally reported Fe 2 Ni trimetallic MOF node. In addition, we found a correlative relationship between spin-density from natural population analysis and energy barriers in the realm of C-C bond formation, whereby an elevation in spin-density is found to be inversely proportional to the magnitude of the energy barriers. Moreover, we calculated the energy barriers for C-C coupling and beta-hydride elimination using multireference NEVPT2 calculations on top of the CASSCF wave function to validate the rate-determining step that is predicted by DFT.

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

Zr 6 O 8 Node-Catalyzed Butene Hydrogenation and Isomerization in the Metal–Organic Framework NU-1000

Zirconium-based metal–organic frameworks (Zr-MOFs) have been increasingly studied over the past two decades as heterogeneous catalysts due to their synthetic tunability, well-defined nature, and chemical stability. In contrast to traditional zirconia-based heterogeneous catalysts, the community has assumed that Zr-MOFs are inert catalyst supports that do not participate directly in hydrocarbon transformations, such as olefin hydrogenation and isomerization. Here, we report that the Zr-MOF NU-1000 is capable of catalyzing olefin hydrogenation and isomerization, without any postsynthetic modifications, under a hydrogen atmosphere. We probe H 2 activation over the nodes of NU-1000 via spectroscopic and computational techniques revealing that H 2 dissociation can occur heterolytically across coordinatively unsaturated Zr sites and proximal hydroxide and μ3-oxo ligands. These results, along with catalytic experiments, suggest that H 2 activation results in node-supported zirconium hydrides capable of the hydrogenation and isomerization of 1-butene. When examining rate dependence on the partial pressure of H 2 , we observe first-order dependence for hydrogenation and half-order dependence for isomerization. Half-order H 2 rate dependence is consistent with a mechanism where both fragments of cleaved H 2 are active for 1-butene isomerization, suggesting that heterolytic cleavage generates acidic protons resulting in parallel, acid-, and hydride-catalyzed isomerization pathways. In conclusion, this work shows that Zr-MOFs have more diverse reactivity than the current literature may suggest and opens possibilities for ways in which Zr-MOFs can be used as heterogeneous catalysts and supports.

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

Subnetwork representation learning for discovering network biomarkers in predicting lymph node metastasis in early oral cancer

Cervical lymph node metastasis is the leading cause of poor prognosis in oral tongue squamous cell carcinoma and also occurs in the early stages. The current clinical diagnosis depends on a physical examination that is not enough to determine whether micrometastasis remains. The transcriptome profiling technique has shown great potential for predicting micrometastasis by capturing the dynamic activation state of genes. However, there are several technical challenges in using transcriptome data to model patient conditions: (1) An Insufficient number of samples compared to the number of genes, (2) Complex dependence between genes that govern the cancer phenotype, and (3) Heterogeneity between patients between cohorts that differ geographically and racially. We developed a computational framework to learn the subnetwork representation of the transcriptome to discover network biomarkers and determine the potential of metastasis in early oral tongue squamous cell carcinoma. Our method achieved high accuracy in predicting the potential of metastasis in two geographically and racially different groups of patients. The robustness of the model and the reproducibility of the discovered network biomarkers show great potential as a tool to diagnose lymph node metastasis in early oral cancer.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Heavy chalcogenide-transition metal clusters as coordination polymer nodes

While metal–oxygen clusters are widely used as secondary building units in the construction of coordination polymers or metal–organic frameworks, multimetallic nodes with heavier chalcogenide atoms (S, Se, and Te) are comparatively untapped. The lower electronegativity of heavy chalcogenides means that transition metal clusters of these elements generally exhibit enhanced coupling, delocalization, and redox-flexibility. Leveraging these features in coordination polymers provides these materials with extraordinary properties in catalysis, conductivity, magnetism, and photoactivity. In this perspective, we summarize common transition metal heavy chalcogenide building blocks including polynuclear metal nodes with organothiolate/selenolate or anionic heavy chalcogenide atoms. Based on recent discoveries, we also outline potential challenges and opportunities for applications in this field.

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

Altering the solubility of metal–organic polyhedra via pendant functionalization of Cp 3 Zr 3 O(OH) 3 nodes

Here, the chemistry of zirconium-based metal-organic polyhedra (ZrMOPs) is often limited by their poor solubilities. Despite their attractive features—including high yielding and facile syntheses, predictable topologies, high stability, and tunability—problematic solubilities have caused ZrMOPs to be under-studied and under-applied. Although these cages have been synthesized with a wide variety of carboxylate-based bridging ligands, we explored a new method for ZrMOP functionalization via node-modification, which we hypothesized could influence solubility. Herein, we report ZrMOPs with benzyl-, vinylbenzyl-, and trifluoromethylbenzyl-pendant groups decorating cyclopentadienyl moieties. The series was characterized by 1 H/ 19 F NMR, high-resolution mass spectrometry, infrared spectroscopy, and single-crystal X-ray diffraction. The effects of node functionalities on ZrMOP solubility were quantified using inductively coupled plasma mass spectrometry. Substitution caused a decrease in water solubility, but for certain organic solvents, e.g. DMF, solubility could be enhanced by ~20×, from 16 μM for the unfunctionalized cage to 310 μM for the vinylbenzyl- and trifluoromethylbenzyl-cages.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Reproducibility of fixed-node diffusion Monte Carlo across diverse community codes: The case of water–methane dimer

Fixed-node diffusion quantum Monte Carlo (FN-DMC) is a widely trusted many-body method for solving the Schrödinger equation, known for its reliable predictions of material and molecular properties. Furthermore, its excellent scalability with system complexity and near-perfect utilization of computational power make FN-DMC ideally positioned to leverage new advances in computing to address increasingly complex scientific problems. Even though the method is widely used as a computational gold standard, reproducibility across the numerous FN-DMC code implementations has yet to be demonstrated. This difficulty stems from the diverse array of DMC algorithms and trial wave functions, compounded by the method’s inherent stochastic nature. Here, this study represents a community-wide effort to assess the reproducibility of the method, affirming that yes, FN-DMC is reproducible (when handled with care). Using the water–methane dimer as the canonical test case, we compare results from eleven different FN-DMC codes and show that the approximations to treat the non-locality of pseudopotentials are the primary source of the discrepancies between them. In particular, we demonstrate that, for the same choice of determinantal component in the trial wave function, reliable and reproducible predictions can be achieved by employing the T-move, the determinant locality approximation, or the determinant T-move schemes, while the older locality approximation leads to considerable variability in results. These findings demonstrate that, with appropriate choices of algorithmic details, fixed-node DMC is reproducible across diverse community codes—highlighting the maturity and robustness of the method as a tool for open and reliable computational science.

Della Pia, Flaviano [Univ. of Cambridge (United Ki↗
DOE OSTI2021

Oxygen magnetic polarization, nodes in spin density, and zigzag spin order in oxides

Recent studies on Ba 2 CoO 4 (BCO) and SrRuO 3 (SRO) have unveiled a variety of intriguing phenomena, such as magnetic polarization on oxygens, unexpected nodes in the spin density profile along bonds, and unusual zigzag spin patterns in triangular lattices. Here, using simple model calculations supplemented by density functional theory we explain the presence of nodes based on the antibonding character of the dominant singly occupied molecular orbitals along the transition metal (TM) to oxygen bonds. Our simple model also allows us to explain the net polarization on oxygen as originated from the hybridization between atoms and mobility of the electrons with spins opposite to those of the closest TM atoms. Overall, our results are not limited to BCO and SRO, but they are generic and qualitatively predict the net polarization expected on any ligands, according to the spin order of the closest TM atoms and the number of intermediate ligand atoms. Finally, we propose that a robust easy-axis anisotropy would suppress the competing 120° antiferromagnetic order to stabilize the zigzag pattern order as ground state in a triangular lattice. Our generic predictions should be applicable to any other compound with characteristics similar to those of BCO and SRO.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Efficient Contingency Analysis in Power Systems via Network Trigger Nodes

Modeling failure dynamics within a power system is a complex and challenging process due to multiple inter-dependencies and convoluted inter-domain relationships. Subject matter experts (SMEs) are interested in understanding these failure dynamics for reducing the impact from future disasters (i.e., losses or failures of power system components, such as transmission lines). Contingency analysis (CA) tools enable such ’what-if’ scenario analyses to evaluate the impacts on the power system. Analyzing all possible contingencies among N system components can be computationally expensive. An important step for performing CA is identifying a set of k ‘trigger’ components, which when failed initially can significantly impact the overall system by causing multiple failures. Currently SMEs focus on identifying these trigger components by running expensive simulations on all possible subsets, which quickly becomes infeasible. Hence finding a relevant set of trigger components (contingencies) rapidly to enable efficient and useful CA is crucial.In a collaboration between computer scientists and power system experts, we propose an efficient method for performing CA by exploiting network inter-dependencies in power system components. First, we construct a network with multiple electric grid infrastructure components and dependencies as connections among them. We reformulate the problem of finding a set of trigger components as a problem of identifying critical nodes in the network, which can cascade power failures through connected nodes and cause significant damage to the network. To guide the practical CA tools, we develop a network-based model with a probabilistic edge-weights setup using intricate domain rules. Then we conduct an empirical study on real power system data in the US for both regional and national levels. Firstly, we use power system datasets for the US to create a national-scale domain-driven model. Secondly, we demonstrate that network-based model outperforms the outputs from a real CA tool and show on average 25 × improved selection of contingencies, thereby showcasing practical benefits to the power experts.

Tabassum, Anika↗
DOE OSTI2020

Thermal Management for FPGA Nodes in HPC Systems

The integration of FPGAs into large-scale computing systems is gaining attention. In these systems, real-time data handling for networking, tasks for scientific computing, and machine learning can be executed with customized datapaths on reconfigurable fabric within heterogeneous compute nodes. At the same time, thermal management, particularly battling the cooling cost and guaranteeing the reliability, is a continuing concern. The introduction of new heterogeneous components into HPC nodes only adds further complexities to thermal modeling and management. The thermal behavior of multi-FPGA systems deployed within large compute clusters is less explored. Here, we first show that the thermal behaviors of different FPGAs of the same generation can vary due to their physical locations in a rack and process variation, even though they are running the same tasks. We present a machine learning–based model to capture the thermal behavior of each individual FPGA in the cluster. We then propose two thermal management strategies guided by our thermal model. First, we mitigate thermal variation and hotspots across the cluster by proactive thermal-aware task placement. Under the tested system and benchmarks, we achieve up to 26.4° C and on average 13.3° C system temperature reduction with no performance penalty. Second, we utilize this thermal model to guide HLS parameter tuning at the task design stage to achieve improved thermal response after deployment.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

node-red-contrib-ocpp2

Open source Node-Red "nodes" to support the Open Charge Point Protocol (OCPP) 2.0.1 protocol.

Nystrom, Bryan↗
DOE OSTI2026

Fine-Grained Power and Energy Attribution on AMD GPU/APU-Based Exascale Nodes

Modern exascale GPU- and APU-based systems provide multiple power and energy sensors, but differences in scope, update rate, timing, and filtering complicate the attribution of short-lived accelerator activity. This paper presents a methodology to characterize and correct these effects on Cray EX systems with AMD Instinct MI250X GPUs (Frontier) and MI300A APUs (Portage). Using controlled square-wave workloads, we quantify update intervals, delay, aliasing, and variability across up to 512 GPUs and 480 APUs with on-chip (rocm-smi/amd-smi) and off-chip Cray Power Management sensors. We reconstruct power from cumulative energy counters to achieve faster response times, validate it against on-chip, off-chip, and node-level sensors, and integrate the resulting streams into a Score-P/PAPI-based tool for time-aligned, phase-level attribution. Applied to rocHPL, rocHPL-MxP, and HPG-MxP, the method separates energy savings due to reduced runtime from changes in power. Mixed precision reduces node energy on Frontier by 79% for rocHPL-MxP and 31% for HPG-MxP, with similar trends on Portage. These results provide portable guidance for sensor validation and power-aware optimization on current and future exascale systems.

Mcdaniel, Adam [ORNL] (ORCID:000000016926028X)↗
DOE OSTI2022

Node Monitoring as a Fault Detection Countermeasure against Information Leakage within a RISC-V Microprocessor

Advanced, superscalar microprocessors (μP) are highly susceptible to wear-out failures because of their highly complex, densely packed circuit structure and extreme operational frequencies. Although many types of fault detection and mitigation strategies have been proposed, none have addressed the specific problem of detecting faults that lead to information leakage events on I/O channels of the μP. Information leakage can be defined very generally as any type of output that the executing program did not intend to produce. In this work, we restrict this definition to output that represents a security concern, and in particular, to the leakage of plaintext or encryption keys, and propose a counter-based countermeasure to detect faults that cause this type of leakage event. Fault injection (FI) experiments are carried out on two RISC-V microprocessors emulated as soft cores on a Xilinx multi-processor System-on-chip (MPSoC) FPGA. The μP designs are instrumented with a set of counters that records the number of transitions that occur on internal nodes. The transition counts are collected from all internal nodes under both fault-free and faulty conditions, and are analyzed to determine which counters provide the highest fault coverage and lowest latency for detecting leakage faults. We show that complete coverage of all leakage faults is possible using only a single counter strategically placed within the branch compare logic of the μPs.

42 ENGINEERING↗