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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 919 records · Page 51
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Tungsten-dioxo single-site heterogeneous catalyst on carbon: synthesis, structure, and catalysis

This study investigates the application of a novel third-row metal, tungsten, to carbon-supported single-site metal-oxo heterogeneous catalysis. Tungsten is a green and earth-abundant metal, but an unexplored candidate in this role. The carbon (AC = activated carbon)-supported tungsten dioxo complex, AC/WO 2 was prepared via grafting of (DME)WO 2 Cl 2 (DME = 1,2-dimethoxyethane) onto high-surface-area activated carbon. AC/WO 2 was fully characterized by ICP-OES, XPS, EXAFS, XANES, SMART-EM, and DFT. W 4d 7/2 XPS and W L III -Edge XANES assign the oxidation state as W(VI), while EXAFS reveals two W=O double and two W–O single bonds at distances of 1.73 and 1.92 Å, respectively. These data align well with DFT computational results, supporting the structure as Carbon(–μ-O–) 2 M(=O) 2 . SMART-EM verifies that single W(VI) catalytic sites are bonded in an out-of-plane manner. The catalytic performance of air- and water-stable AC/WO 2 is compared to that of AC/MoO 2 . AC/WO 2 is more active and selective than the molybdenum analog in mediating alcohol dehydration of various substrates, and is recyclable. Notably, AC/WO 2 is an effective and recyclable catalyst for primary aliphatic alcohol dehydration and forms no dehydrogenation side products in contrast to AC/MoO 2 . However, AC/WO 2 is less effective in epoxidation and PET depolymerization. Overall, this work demonstrates the potential of carbon-supported third row metals for future studies.

02 PETROLEUM↗
DOE OSTI2025

Libration of hydroxyl groups in layered aluminum (oxy)hydroxides and other material analogs: insights from inelastic neutron scattering and theory

We analyzed the hydroxyl librational signatures of five structurally related aluminum (oxy)hydroxides, using inelastic neutron scattering (INS) and plane-wave lattice dynamics simulations. A clear trend across these aluminum-containing phases illustrates the relationship between hydrogen bonding, local atomic structure, and the spectral location and profile of the librational bands. The INS spectra have been compared to previous optical spectroscopy and computational studies, highlighting the complementary nature of the INS technique. Taking into account other structurally or chemically related material analogs, we have identified a correlation between a blueshift (to higher energy) of the upper librational band edge and the geometry of the hydrogen bond interactions, mirroring (with opposite correlation) the well-known redshift in the intramolecular O–H stretching energy with increasing hydrogen bond strength. For hydroxyl groups that do not participate in hydrogen bonding effectively, the bending librations occur at lower energies and hybridize with metal–oxygen lattice modes. Standard density functional theory approximations, including dispersion corrections, struggle to correctly predict vibrational frequencies of motions dominated by H but perform well for metal–oxygen modes, allowing us to make detailed mode assignments in several cases, including a demonstration of how layer-to-layer disorder in boehmite hydrogen bond orientations is reflected in the sharp but minor low energy peaks (at ∼70–80 meV) of the INS spectrum.

Wang, Hsiu-Wen [Oak Ridge National Laboratory (ORN↗
DOE OSTI2024

Nontrivial fusion of Majorana zero modes in interacting quantum-dot arrays

Motivated by recent experimental reports of Majorana zero modes (MZMs) in quantum-dot systems at the “sweet spot,” where the electronic hopping t ℎ is equal to the superconducting coupling Δ, we study the time-dependent spectroscopy corresponding to the nontrivial fusion of MZMs. The term “nontrivial” refers to the fusion of Majoranas from different original pairs of MZMs, each with well-defined parities. We employ an experimentally accessible time-dependent real-space local density-of-states (LDOS) method to investigate the nontrivial MZM fusion outcomes in canonical chains and in a Y-shaped array of interacting electrons. In the case of quantum-dot chains where two pairs of MZMs are initially disconnected, after fusion we find equal-height peaks in the electron and hole components of the LDOS, signaling nontrivial fusion into both the vacuum I and fermion Ψ channels with equal weight. For π-junction quantum-dot chains, where the superconducting phase has opposite signs on the left and right portions of the chain, after the nontrivial fusion we observed the formation of an exotic two-site MZM near the center of the chain, coexisting with another single-site MZM. Furthermore, we also studied the fusion of three MZMs in the Y-shaped geometry. In this case, after the fusion we observed the novel formation of another exotic multisite MZM, with properties depending on the connection and geometry of the central region of the Y-shaped quantum-dot array.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

ESnet/JLab FPGA Accelerated Transport

To increase the science rate for high data rates/volumes, Thomas Jefferson National Accelerator Facility (JLab) has partnered with Energy Sciences Network (ESnet) to define an edge to data center traffic shaping / steering transport capability featuring data event aware network shaping and forwarding. The keystone of this ESnet+JLab FPGA Accelerated Transport (EJFAT) is the joint development of an AI/ML directed dynamic compute work Load Balancer (LB) of UDP streamed data. The LB is a suite consisting of a Field Programmable Gate Array (FPGA) executing the dynamically configurable, low fixed latency LB data plane featuring real-time packet redirection and high throughput, and a control plane running on the FPGA host computer that monitors network and compute farm telemetry in order to make dynamic AI/ML guided decisions for destination compute host redirection/load balancing and destination resource provisioning. The LB provides for three-tier horizontal scaling across LB suites, core compute hosts, and CPUs within a host. The LB effectively provides seamless integration of edge/core computing to support direct experimental data processing for immediate use by JLab science programs and others such as the EIC as well as data centers of the future requiring high throughput and low latency for both hot and cooled data for both running experiment data acquisition systems and data center use cases.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Experimental Investigation of Innovative Cooling Schemes on an Additively Manufactured Engine Scale Turbine Nozzle Guide Vane

This study includes the design, validation, and fabrication via direct metal laser sintering (DMLS) of a gas turbine nozzle guide vanes (NGV) that incorporates three innovative cooling schemes specifically enabled by additive manufacturing. The novel NGV design is the culmination of an extensive research and development effort over a period of 4 years that included low- and high-speed cascade testing coupled with unsteady computational fluid dynamics for numerous candidate innovative cooling architectures. The final vane design (SJ-vane) consists of sweeping jet (SJ) film cooling holes on the suction surface (SS), sweeping jet impingement holes at the leading edge and double-wall partial length triangular pin-fin with impinging jet at the trailing edge. For comparison purposes, a second DMLS enabled vane (777-vane) was designed and fabricated with prototypical cooling circuits to serve as a baseline. This vane consists of a shaped film cooling holes on the suction surface, circular impingement holes at the leading edge, and full-length cylindrical pin-fins at the trailing edge. Experiments with the two DMLS enabled vanes were performed at the Ohio State University Turbine Reacting Flow Rig (TuRFR) at engine-relevant temperature (1375 K) and Mach number conditions. Infrared (IR) thermography was utilized to measure the wall temperature of the pressure and suction surface at several coolant mass flowrates to estimate the overall cooling effectiveness (ϕ). Results showed improved cooling performance for the advanced cooling schemes (sweeping jet film cooling, impingement cooling, and triangular pin-fin cooling) compared with the baseline cooling schemes.

Engineering↗
DOE OSTI2016

C1-continuous Virtual Element Method for Poisson-Kirchhoff plate problem

We present a family of C1-continuous high-order Virtual Element Methods for Poisson-Kirchho plate bending problem. The convergence of the methods is tested on a variety of meshes including rectangular, quadrilateral, and meshes obtained by edge removal (i.e. highly irregular meshes). The convergence rates are presented for all of these tests.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Industrial Internet-of-Things & Data Analytics for Nuclear Power & Safeguards

Data analytics applied to nuclear power operations and nuclear safeguards is in a nascent state, yet some significant initial efforts are being undertaken by industry and academia. This report highlights our findings as to the current state-of-the-art of such efforts, in particular considering the Industrial Internet-of-Things aspect of this work, as well as an investigation into the utility of machine learning tools being developed for other industries. Blockchain applications were also studied. A consideration was undertaken into how to apply data analytics and machine learning to nuclear power and safeguards within the realm of Probabilistic Risk Assessments (PRAs), predictive maintenance & edge analytics, and proprietary data sharing.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2018

Basic Research Needs for Microelectronics

Since the invention of the integrated circuit in 1958, advances in microelectronics have followed Moore’s law and other scaling laws. These have led to over a billion-fold increase in the number of transistors on a chip. The Department of Energy’s Office of Science (DOE-SC) programs have always been at the cutting edge of microelectronics, making major contributions to the scientific understanding, materials, and advanced instrumentation that enabled innovations to promote scaling. This has driven transformative advances in microelectronics for the challenging demands of DOE’s high performance computing and science facilities. Now, strong evidence exists that scaling is approaching its physical and economic limits, and yet, the growth of data-centric computing and sensor networks is redefining computing workloads and microelectronics needs. In addition, greatly improved microelectronics are needed for the nation’s electricity grid if it is to be energy-efficient, resilient to natural phenomena and intentional attack, and agile in adapting to fluctuations in demand and power generation. Sustained and rapid progress in microelectronics science and technology from millivolt to megavolt scales is thus essential if we are to continue pushing the boundaries of science within DOE, and more significantly, to continue to lead the global information and power technology revolution. In October 2018, DOE-SC convened a workshop to address Basic Research Needs for Microelectronics by a “co-design” approach. Participants focused on scientific issues associated with advanced microelectronics technologies for applications relevant to the DOE mission, including computing, power grid management, and science facility workloads. (Topics of direct relevance to quantum information science and quantum computing were outside the scope of this workshop.) The workshop was organized around microelectronics needs for three areas: 1) future DOE-SC facilities, 2) high performance computing beyond exascale (a billion billion calculations per second), and 3) power control, conversion, and detection for a modernized electrical grid and related high power applications. Panels were formed around each of these areas, with a fourth panel formed to address Crosscutting Research. Workshop participants were asked to focus on a co-design innovation ecosystem in which materials, chemistries, devices, systems, architectures, algorithms, and software are researched and developed in a closely integrated fashion, with feedback and interdisciplinary collaboration at each interface in this microelectronics technology hierarchy. The panels identified the five Priority Research Directions on the following page.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Application of Advanced Metering Infrastructure Data to Advanced Utility System Operations: Cooperative Research and Development, CRADA Number CRD-17-00712 (Final Report)

The primary objective of the proposed project is to evaluate the capabilities of Advanced Metering Infrastructure (AMI) based controls for grid operations. This includes monitoring and control at the secondary transformer level using existing AMI infrastructure. In addition, some of the challenges of using a model-less control will also be identified. The lessons learned will be disseminated to other utilities around the country through peer-reviewed publications with the consent of SDG&E. The scope of the work includes using data from SDG&E's existing AMI infrastructure and working with third party vendors selected by SDG&E. The grid edge monitoring systems and controls provided by the selected vendors will perform grid operations using AMI data. The National Renewable Energy Laboratory (NREL) will perform a software and controller-based evaluation of the grid edge controller, intelligent devices and sensors, at the Energy System Integration Facility (ESIF) laboratory.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2017

Scalable polylithic on-package integratable apparatus and method

Described is an apparatus which comprises: a first die including: a processing core; a crossbar switch coupled to the processing core; and a first edge interface coupled to the crossbar switch; and a second die including: a first edge interface positioned at a periphery of the second die and coupled to the first edge interface of the first die, wherein the first edge interface of the first die and the first edge interface of the second die are positioned across each other; a clock synchronization circuit coupled to the second edge interface; and a memory interface coupled to the clock synchronization circuit.

42 ENGINEERING↗
DOE OSTI2021

Explaining Missing Data in Graphs: A Constraint-based Approach

Abstract: This paper introduces a constraint-based approach to clarify missing values in graphs. Our method capitalizes on a set S of graph data constraints. An explanation is a sequence of operational enforcement of S towards the recovery of interested yet missing data (e.g., attribute values, edges). We show that constraint-based approach helps us to understand not only why a value is missing, but also how to recover the missing value. We study S-explanation problem, which is to compute the optimal explanations with guarantees on the informativeness and conciseness. We show the problem is in ?P^2 for established graph data constraints such as graph keys and graph association rules. We develop an efficient bidirectional algorithm to compute optimal explanations, without enforcing S on the entire graph. We also show our algorithm can be easily extended to support graph refinement within limited time, and to explain missing answers. Using real-world graphs, we experimentally verify the effectiveness and efficiency of our algorithms.

Data Analytics↗
DOE OSTI2022

Situational Awareness of Grid Anomalies (SAGA)

The modern power industry becomes more vulnerable to cyber events due to the growing interconnectivity, interdependence, and complexity of the electric power grid. High-fidelity modeling and simulation tools that support the preventative risk analysis on potential cyber-relevant events is essential for ensuring the situational awareness of the system operator as it provides an inexpensive and risk-free environment to test the system responses under various cyber-relevant events and hereby can support research on cyber anomaly detection, optimal protective resource allocation, and mitigation measures. In this webinar, we will share NREL's cybersecurity research capabilities by highlighting the development of a scalable cyber-physical event test bed and demonstration with real hardware in the loop. The developed cyber-physical event test bed is backboned by an integrated transmission, distribution, and communication dynamic co-simulation framework and a plug-and-play cyber event generation module. It is designed to be modular and compatible with parallel computing, and thereby supports large-scale system simulations at an affordable computation cost. The test bed can capture millisecond-to-minutes dynamic frequency and voltage responses under cyber events from the bulk transmission system to the active distribution systems and distributed energy resources at the grid edge.

co-simulation↗
DOE OSTI2016

An asynchronous traversal engine for graph-based rich metadata management

Rich metadata in high-performance computing (HPC) systems contains extended information about users, jobs, data files, and their relationships. Property graphs are a promising data model to represent heterogeneous rich metadata flexibly. Specifically, a property graph can use vertices to represent different entities and edges to record the relationships between vertices with unique annotations. The high-volume HPC use case, with millions of entities and relationships, naturally requires an out-of-core distributed property graph database, which must support live updates (to ingest production information in real time), low-latency point queries (for frequent metadata operations such as permission checking), and large-scale traversals (for provenance data mining). Among these needs, large-scale property graph traversals are particularly challenging for distributed graph storage systems. Most existing graph systems implement a "level synchronous" breadth-first search algorithm that relies on global synchronization in each traversal step. This performs well in many problem domains; but a rich metadata management system is characterized by imbalanced graphs, long traversal lengths, and concurrent workloads, each of which has the potential to introduce or exacerbate stragglers (i.e., abnormally slow steps or servers in a graph traversal) that lead to low overall throughput for synchronous traversal algorithms. Previous research indicated that the straggler problem can be mitigated by using asynchronous traversal algorithms, and many graph-processing frameworks have successfully demonstrated this approach. Such systems require the graph to be loaded into a separate batch-processing framework instead of being iteratively accessed, however. In this work, we investigate a general asynchronous graph traversal engine that can operate atop a rich metadata graph in its native format. We outline a traversal-aware query language and key optimizations (traversal-affiliate caching and execution merging) necessary for efficient performance. We further explore the effect of different graph partitioning strategies on the traversal performance for both synchronous and asynchronous traversal engines. Our experiments show that the asynchronous graph traversal engine is more efficient than its synchronous counterpart in the case of HPC rich metadata processing, where more servers are involved and larger traversals are needed. Furthermore, the asynchronous traversal engine is more adaptive to different graph partitioning strategies.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2021

A Kinetic Monte Carlo Approach for Simulating Cascading Transmission Line Failure

In this work, cascading transmission line failures are studied through a dynamical model of the power system operating under fixed conditions. The power grid is modeled as a stochastic dynamical system where first-principles electromechanical dynamics are excited by small Gaussian disturbances in demand and generation around a specified operating point. In this context, a single line failure is interpreted in a large deviation context as a first escape event across a surface in phase space defined by line security constraints. The resulting system of stochastic differential equations admits a transverse decomposition of the drift, which leads to considerable simplification in evaluating the quasipotential (rate function) and, consequently, computation of exit rates. Tractable expressions for the rate of transmission line failure in a restricted network are derived from large deviation theory arguments and validated against numerical simulations. Extensions to realistic settings are considered, and individual line failure models are aggregated into a Markov model of cascading failure inspired by chemical kinetics. Cascades are generated by traversing a graph composed of weighted edges representing transitions to degraded network topologies. Numerical results indicate that the Markov model can produce cascades with qualitative power-law properties similar to those observed in empirical cascades.

Kinetic Monte Carlo, rare events, Cascading Failur↗
DOE OSTI2017

Uncovering the Atomistic Mechanism for Calcite Step Growth

Abstract Determining a complete atomic‐level picture of how minerals grow from aqueous solution remains a challenge as macroscopic rates can be a convolution of many reactions. For the case of calcite (CaCO 3 ) in water, computer simulations have been used to map the complex thermodynamic landscape leading to growth of the two distinct steps, acute and obtuse, on the basal surface. The carbonate ion is found to preferentially adsorb at the upper edge of acute steps while Ca 2+ only adsorbs after CO 3 2− . In contrast to the conventional picture, ion pairs prefer to bind at the upper edge of the step with only one ion, at most, coordinated to the step and lower terrace. Migration of the first carbonate ion to a growth site is found to be rate‐limiting for kink nucleation, with this process having a lower activation energy on the obtuse step.

De La Pierre, Marco↗
DOE OSTI2024

Improved Statistics for F-theory Standard Models

Much of the analysis of F-theory-based Standard Models boils down to computing cohomologies of line bundles on matter curves. By varying parameters one can degenerate such matter curves to singular ones, typically with many nodes, where the computation is combinatorial and straightforward. The question remains to relate the (a priori possibly smaller) value on the original curve to the singular one. In this work, we introduce some elementary techniques (pruning trees and removing interior edges) for simplifying the resulting nodal curves to a small collection of terminal ones that can be handled directly. When applied to the QSMs, these techniques yield optimal results in the sense that obtaining more precise answers would require currently unavailable information about the QSM geometries. This provides us with an opportunity to enhance the statistical bounds established in earlier research regarding the absence of vector-like exotics on the quark-doublet curve.

Bies, Martin↗
DOE OSTI2021

Charged Particle Tracking via Edge-Classifying Interaction Networks

Recent work has demonstrated that geometric deep learning methods such as graph neural networks (GNNs) are well suited to address a variety of reconstruction problems in high-energy particle physics. In particular, particle tracking data are naturally represented as a graph by identifying silicon tracker hits as nodes and particle trajectories as edges, given a set of hypothesized edges, edge-classifying GNNs identify those corresponding to real particle trajectories. In this work, we adapt the physics-motivated interaction network (IN) GNN toward the problem of particle tracking in pileup conditions similar to those expected at the high-luminosity Large Hadron Collider. Assuming idealized hit filtering at various particle momenta thresholds, we demonstrate the IN’s excellent edge-classification accuracy and tracking efficiency through a suite of measurements at each stage of GNN-based tracking: graph construction, edge classification, and track building. The proposed IN architecture is substantially smaller than previously studied GNN tracking architectures; this is particularly promising as a reduction in size is critical for enabling GNN-based tracking in constrained computing environments. Furthermore, the IN may be represented as either a set of explicit matrix operations or a message passing GNN. Efforts are underway to accelerate each representation via heterogeneous computing resources towards both high-level and low-latency triggering applications.

accelerator physics↗