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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 OSTI2025

Edge at the Pier: EPCAPE Software-Defined Sensing Field Campaign Report

The Eastern Pacific Cloud Aerosol Precipitation Experiment (EPCAPE) was aimed to enhance the understanding of cloud and aerosol properties in the region surrounding La Jolla, California. To address challenges in data collection and processing from various instruments, an edge computing device known as Waggle Sage Node (WSN) was deployed at the Ellen Browning Scripps Memorial Pier. WSN is a distributed-sensing platform designed to collect and analyze environmental data at the edge. Sage is a multi-agency-supported project that designs and builds a new kind of national-scale reusable cyberinfrastructure to enable artificial intelligence (AI) at the edge based on the Waggle platform. Sponsors include the U.S. Department of Energy (DOE) Advanced Scientific Computing Research (ASCR), DOE National Nuclear Security Administration (NNSA), DOE Biological and Environmental Research (BER) through DOE Artificial Intelligence for Earth System Predictability (AI4ESP), Argonne Laboratory-Directed Research and Development (LDRD). Sage (https://sagecontinuum.org/) is funded as a National Science Foundation Mid-Scale Research Infrastructure (MSRI) project (https://www.nsf.gov/awardsearch/showAward?AWD_ID=1935984). This robust, multi-architecture edge computing platform facilitated environmental monitoring during the campaign. This report details the scientific objectives, deployment process, and key results of integrating Waggle into the EPCAPE field campaign.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

ARMing the Edge: Designing Edge Computing–Capable Machine Learning Algorithms to Target ARM Doppler Lidar Processing

Abstract There is a need for long-term observations of cloud and precipitation fall speeds in validating and improving rainfall forecasts from climate models. To this end, the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility Southern Great Plains (SGP) site at Lamont, Oklahoma, hosts five ARM Doppler lidars that can measure cloud and aerosol properties. In particular, the ARM Doppler lidars record Doppler spectra that contain information about the fall speeds of cloud and precipitation particles. However, due to bandwidth and storage constraints, the Doppler spectra are not routinely stored. This calls for the automation of cloud and rain detection in ARM Doppler lidar data so that the spectral data in clouds can be selectively saved and further analyzed. During the ARMing the Edge field experiment, a Waggle node capable of performing machine learning applications in situ was deployed at the ARM SGP site for this purpose. In this paper, we develop and test four algorithms for the Waggle node to automatically classify ARM Doppler lidar data. We demonstrate that supervised learning using a ResNet50-based classifier will classify 97.6% of the clear-air images and 94.7% of cloudy images correctly, outperforming traditional peak detection methods. We also show that a convolutional autoencoder paired with k -means clustering identifies 10 clusters in the ARM Doppler lidar data. Three clusters correspond to mostly clear conditions with scattered high clouds, and seven others correspond to cloudy conditions with varying cloud-base heights.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Distributed approximate minimal Steiner trees with millions of seed vertices on billion-edge graphs

In this report, we present a parallel 2-approximation Steiner minimal tree algorithm and its MPI-based distributed implementation. In place of expensive distance computations between all pairs of seed vertices, the solution we employ exploits a cheaper Voronoi cell computation. Our design leverages asynchronous processing and message prioritization to accelerate convergence of distance computations, and harnesses vertex and edge centric processing to offer fast time-to-solution. We demonstrate scalability and performance using real-world graphs with up to 128 billion edges and 512 compute nodes, and show the ability to find Steiner trees with up to one million seed vertices. Using 12 data instances, we present comparison with the state-of-the-art exact solver, SCIP-Jack, and two sequential 2-approximate algorithms. We empirically show that, on average, the total distance of the Steiner tree identified by our solution is 1.1290 times greater than the Steiner minimal tree – well within the theoretical approximation bound of 2.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

On the formation of swelling and related flaws in laser powder bed fusion

Process monitoring in laser powder bed fusion additive manufacturing can provide insights into stochastic anomalies, melt pool and plume dynamics, and part quality. Swelling, a build anomaly where overbuilt material protrudes through the powder layer after recoating, is readily detectable in post-recoat visible light images of the powder bed. Here, this work identifies several of the underlying mechanisms driving swelling formation by analyzing the influence of processing parameters, laser scan paths, and build plate locations on the presence of swelling detected in situ. Swelling near the edge of the part and swelling in the internal region of the part are shown to correlate with different process conditions. Edge and internal swelling may be driven by different phenomena, with edge swelling predominately occurring on the edge of a part facing the laser module and correlated to clusters of near-surface voids (detected with X-ray computed tomography). A larger spot size, higher laser power, and lower scan velocity also increased the presence of edge swelling. Laser spot size and scan path influenced internal swelling, which occurred preferentially with a larger spot size and in regions with large melt pools, caused by localized heat accumulation due to non-optimal processing parameters or scan path strategies. For coupons processed with a slicer-defined maximum scan vector length, swelling seldom occurred at internal vector-stripe boundaries. These results provide a mechanistic understanding of how swelling can be linked to material flaws, insight into how some instances of swelling can be avoided, and evidence supporting the use of swelling as an in situ indicator for quality assurance and part qualification.

Anomaly↗
DOE OSTI2021

Investigation of Rocket Effect in BRC 18 using Gaia EDR3

ABSTRACT Bright-rimmed clouds (BRCs) are ideal candidates to study radiation-driven implosion mode of star formation as they are potential sites of triggered star formation, located at the edges of Hii regions, showing evidence of ongoing star formation processes. BRC 18 is located towards the eastern edge of relatively closer (∼400 pc) H ii region excited by λ Ori. We made R-band polarimetric observations of 17 candidate young stellar objects (YSOs) located towards BRC 18 to investigate any preferred orientation of the discs with respect to the ambient magnetic field and the direction of energetic photons from λ Ori. We found that the discs are oriented randomly with respect to the projected magnetic field. Using distances and proper motions from the Gaia EDR3 of the candidate YSOs, we investigated the possible acceleration of BRC 18, away from λ Ori due to the well-known ‘Rocket Effect’, by assuming that both the candidate YSOs and BRC 18 are kinematically coupled. The relative proper motions of the candidate YSOs are found to show a trend of moving away from λ Ori. We computed the offset between the angle of the direction of the ionization front and the relative proper motion of the candidate YSOs and found it to lie close to being parallel to each other. Additionally, we found 12 sources that are co-moving with the known candidate YSOs towards BRC 18. These co-moving sources are most likely to be young and are missed in previous surveys conducted to identify potential YSOs of the region.

Saha, Piyali (ORCID:0000000200281354)↗
DOE OSTI2025

Imaging Bragg Edge Analysis TooLs for Engineering Structures (iBeatles)

The Spallation Neutron Source (SNS) at Oak Ridge National Laboratory (ORNL) provides pulsed neutrons with energies varying from epithermal to cold. In preparation for VENUS, the neutron imaging beamline to be located at beam port 10, we have performed a series of experiments focused on wavelength-dependent radiography and computed tomography for a broad range of applications, from materials science to biological tissues.One of the time-of-flight (TOF) techniques that is of interest to the scientific community is the 2-dimensional mapping of phases and average crystalline plane orientation in samples both ex-situ and during applied stresses such as tensile loading and heating. This technique is known as Bragg edgeimaging and relies on the identification of changes of transmission values, fitting of the edge to measure its displacement, and thus identify the shift in lattice parameter due to stresses. One of the challenges of TOF imaging measurements is the amount of data and the inability to observe Bragg edge shifts in real time during an experiment. Thus, we have been focusing on creating a Python-based interface that allows fast data processing and instantaneous mapping and fitting of the Bragg edges, and their evolution through time. Python libraries and Jupyter notebooks have been implemented to facilitate decision making during an experiment. The advantage of the notebooks is the possibility to guide an experiment as they can quickly process and display Bragg edge data. These notebooks can be used independently, or can be combined in a Python Graphical User Interface (GUI) tool called iBeatles. This interface permits visualization and fitting of the Bragg edges, and ultimately back-projects the fitting results onto the radiographs to display a strain map. Assuming data collection has sufficient statistics, the strain mapping analysis can be performed on a pixel-by-pixel basis. This development is a step forward toward a better user experience at the future VENUS beamline in terms of live feedback and productivity. Analysis that used to take days of switching between different applications can now be done in minutes within the

Bilheux, JeanChristophe [Oak Ridge National Labora↗
DOE OSTI2023

Long-pulse high-performance H-mode plasmas achieved on EAST

A record duration of a 310 s H-mode plasma (H 98y2 ~ 1.3, n e /n GW ~ 0.7, f BS > 50%) has been recently achieved on experimental advanced superconducting tokamak (EAST) with metal walls, exploiting the device's improved long-pulse capabilities. The experiment demonstrates good control of tungsten concentration, core/edge MHD stability, and particle and heat exhaust with an ITER-like tungsten divertor and zero injected torque, establishing a milestone on the path to steady-state long-pulse high-performance scenarios in support of ITER and CFETR. Important synergistic effects are leveraged toward this result, which relies purely on radio frequency (RF) powers for heating and current drive (H&CD). On-axis electron cyclotron heating enhances the H&CD efficiency from lower hybrid wave injection, increasing confinement quality and enabling fully non-inductive operation at high density (n e /n GW ~ 70%) and high poloidal beta (β P ~ 2.5). A small-amplitude grassy edge localized mode regime facilitates the RF power coupling to the H-mode edge and reduces divertor sputtering/erosion. The high energy confinement quality (H 98y2 ~ 1.3) is achieved with the experimental and simulated results pointing to the strong effect of Shafranov shift on turbulence. Transport analysis suggests that trapped electron modes dominate in the core region during the record discharge. The detailed physics processes (RF synergy, core-edge integration, confinement properties, etc.) of the steady-state operation will be illustrated in the content. In the future, EAST will aim at accessing more relevant dimensionless parameters to develop long-pulse high-performance plasma toward ITER and CFETR steady-state advanced operation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Enhanced Oxide Reduction by Hydrogen at Cuprous Oxide–Copper Interfaces near Ascending Step Edges

We report that understanding the dynamic processes involved in the interaction of hydrogen with oxides is of fundamental importance in catalysis. This paper probes the reduction of Cu 2 O-‘29’ surfaces by hydrogen at room temperature combining in situ ambient pressure scanning tunneling microscopy (STM), X-ray photoelectron spectroscopy (XPS), and density functional theory (DFT) calculations. Reduction of the atomic layer thin Cu 2 O film is observed to be preferentially initiated2 at step edges and terrace defects, where perfect Cu 2 O(111) terraces are found to be stable towards hydrogenation under the same conditions. After a long induction period, regions of partially reduced Cu 2 O-‘29’ and metallic Cu co-exist before the surface is fully reduced to Cu(111). The reduction rate strongly depends on the nature of nearby Cu step edges. We propose a mechanism for the reduction of Cu 2 O-‘29’ by hydrogen where free copper atoms from ascending metallic step edges facilitate the formation of active ensembles for H 2 dissociation and transfer H to the edges of Cu2O regions

08 HYDROGEN↗
DOE OSTI2022

Shape Evolution of C75 Large-Grain Niobium Half-Cells During Cavity Fabrication

The largely anisotropic deformation of large-grain Nb discs during deep drawing into half-cells poses a challenge for achieving a desired shape accuracy. Two 5-cell cavities for the C75 CEBAF cryomodule rework program have been fabricated at Jefferson Lab from large-grain Nb discs directly sliced from an ingot. The shape of the inner surface of eight half-cells has been inspected using a FARO Edge laser scanner during the fabrication process and compared to the reference shape. On average, approximately 63% of the half-cell inner surface was found to be within 0.1 mm of the reference shape and ~90% to be within 0.2 mm, after the final equator machining. Several 5-cell C75 cavities have also been fabricated at Research Instruments, Germany, and measurements of the shape accuracy using a Zeiss 3D coordinate measuring machine gave similar results. One half-cell was measured both at Research Instruments and Jefferson Lab for comparison.

Ciovati, G.↗
DOE OSTI2020

Sandblasting the r -process: Spallation of Ejecta from Neutron Star Mergers

Neutron star mergers (NSMs) are rapid neutron-capture (r-process) nucleosynthesis sites that expel matter at high velocities, from 0.1c to as high as 0.6c. Nuclei ejected at these speeds are sufficiently energetic to initiate spallation nuclear reactions with interstellar medium (ISM) particles. We adopt a thick-target model for the propagation of high-speed heavy nuclei in the ISM, similar to the transport of cosmic rays. We find that spallation may create observable perturbations to NSM isotopic abundances, particularly around the low-mass edges of the r-process peaks where neighboring nuclei have very different abundances. The extent to which spallation modifies the final NSM isotopic yields depends on: (1) the ejected abundances, which are determined by the NSM astrophysical conditions and the properties of nuclei far from stability, (2) the ejecta velocity distribution and propagation in interstellar matter, and (3) the spallation cross sections. Observed solar and stellar r-process yields could thus constrain the velocity distribution of ejected neutron star matter, assuming NSMs are the dominant r-process source. We suggest avenues for future work, including measurement of relevant cross sections.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Analyzing Data Privacy for Edge Systems

Internet-of-Things (IoT)-based streaming applications are all around us. Currently, we are transitioning from IoT processing being performed on the cloud to the edge. While moving to the edge provides significant networking efficiency benefits, IoT edge computing creates significant data privacy concerns. We propose a methodology that can successfully privacy protect the continual data streams generated by sensors on the edge device. We implement local differential privacy on streaming data and incorporate Bayesian inference and Gaussian process to evaluate the privacy policy. We demonstrate our methodology on a real-world smart meter testbed and identify the optimal privacy protection settings.

Kotevska, Olivera↗
DOE OSTI2020

Detailed Characterization of an Annealed Reduced Graphene Oxide Catalyst for Selective Peroxide Formation Activity

Recently, electrochemical hydrogen peroxide (H 2 O 2 ) generation from oxygen molecules has been extensively studied. Thus far, the best peroxide activity under alkaline conditions has been reported at the surface of a mild reduced graphene oxide annealed at 600 °C (mrGO-600). However, the detailed material information, such as chemical functionality and structural morphology, is unknown, which results in ambiguous debates on its catalytic active sites. Therefore, to solve this problem, we intensively characterize the structure of mrGO-600 to clarify the origin of its catalytic activity. Various characterizations, including X-ray photoelectron spectroscopy, Raman spectroscopy, infrared spectroscopy, near-edge X-ray absorption fine spectroscopy, and high-resolution transmittance electron microscopy coupled with in situ infrared spectroelecrochemistry, reveal that the annealing process generates not only various hole edge defects that are related to the ring ether group but also numerous point defects that result in a small-sized disconnected graphitic carbon region. These defects are believed to form a unique atomic level configuration in mrGO-600, which enables it to facilitate high peroxide-generated activity from oxygen molecules in an alkaline electrolyte.

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

Scalable edge clustering of dynamic graphs via weighted line graphs

Timestamped relational datasets consisting of records (or connections) between pairs of entities are ubiquitous in network science. For applications like peer-to-peer communication, email, various social network interactions, and computer network security, it is useful to organize these records into groups based on how and when they are occurring. Weighted line graphs offer a natural way to model how records are related in such datasets but for large real-world graph topologies, building and utilizing the line graph is prohibitively expensive. Here, we present the framework to cluster the edges of a dynamic graph via the associated line graph that contains two major contributions. The first is a method to work with the line graph implicitly and the second is a distributed scale implementation of an agglomerative hierarchical graph clustering algorithm. We outline a novel hierarchical dynamic graph edge clustering approach that efficiently breaks massive relational datasets into small sets of edges containing events at various timescales. This is in stark contrast to traditional graph clustering algorithms that prioritize highly connected (clique-like) community structures. Our approach relies on constructing a sufficient subgraph of a weighted line graph and applying a hierarchical agglomerative clustering. This approach is related to scalable techniques from spatial clustering, nonlinear-dimension reduction, topological data analysis, and draws particular inspiration from HDBSCAN. As an edge clustering, this method yields an overlapping node clustering. Our algorithm is parallelizable and we demonstrate efficient clustering of a billion-scale, real-world dynamic graph into small edge sets that correlate in topology and time. The entire clustering process for a graph with tens of billions of edges takes just a few minutes of run time on 256 nodes of a distributed compute environment. We argue how the output of the edge clustering is useful for a multitude of data visualization and powerful machine learning tasks, both involving the original massive dynamic graph data and metadata associated with the nodes and edges. Finally, we describe how this approach can be extended to dynamic hypergraphs and dynamic graphs/hypergraphs with unstructured data living on vertices and edges.

Data Analysis↗
DOE OSTI2025

In Situ Electrochemistry of Buried Interfaces in Metal Halide Perovskites: Probing Energy Bands, Halide Redox Activity, and Kinetics

Control over charge injection and extraction processes across buried interfaces is fundamental for all (opto)electronic multilayer device platforms, necessitating detailed understanding of local structural and chemical differences that promote defect formation, distort energetic band-edge alignments, and alter charge transport processes. Herein, the implementation of a low-cost electroanalytical methodologies’ tool suite is described to quantitatively characterize buried interfaces and redox reactions in printable, mixed electrical–ionic, and redox-active metal halide perovskites and a prototypical hole-transporting nickel oxide (NiO x ) thin film. The objective is to demonstrate the power of electrochemical methodologies to improve the nanoscale understanding of complex interfaces within optoelectronic devices by providing case studies on how to: i) differentiate between electronic and chemical properties in NiO x contacts; ii) measure changes in reversibility of halide redox reactions via NiO x surface states; iii) assess energy alignment and charge transport across (modified) buried interfaces; and iv) quantify defects at buried interfaces that change with modifiers and differences in perovskite processing, including increasing defect concentrations when films are slot-die-coated versus spin-cast. The collective approach addresses major challenges in understanding the precise energy landscape and interface reactivity under relevant electric fields that mimic operando conditions (away from equilibrium) and across length scales in thin film device formats.

(spectro)electrochemistry↗
DOE OSTI2023

Lewis Acid Supported Nickel Nitrenoids

Metalation of the polynucleating ligand F,tbs LH 6 (1,3,5-C 6 H 9 (NC 6 H 3 −4-F−2-NSiMe 2 t Bu) 3 ) with two equivalents of Zn(N(SiMe 3 ) 2 ) 2 affords the dinuclear product ( F,tbs LH 2 )Zn 2 (1), which can be further deprotonated to yield ( F,tbs L)Zn 2 Li 2 (OEt 2 ) 4 (2). Transmetalation of 2 with NiCl 2 (py) 2 yields the heterometallic, trinuclear cluster ( F,tbs L)Zn 2 Ni(py) (3). Reduction of 3 with KC 8 affords [KC 222 ][( F,tbs L)Zn 2 Ni] (4) which features a monovalent Ni centre. Addition of 1-adamantyl azide to 4 generates the bridging μ 3 -nitrenoid adduct [K(THF) 3 ][( F,tbs L)Zn 2 Ni(μ 3 -NAd)] (5). EPR spectroscopy reveals that the anionic cluster possesses a doublet ground state (S = 1/2). Cyclic voltammetry of 5 reveals two fully reversible redox events. The dianionic nitrenoid [K 2 (THF) 9 ][( F,tbs L)Zn 2 Ni(μ 3 -NAd)] (6) was isolated and characterized while the neutral redox isomer was observed to undergo both intra- and intermolecular H-atom abstraction processes. Here, Ni K-edge XAS studies suggest a divalent oxidation state for the Ni centres in both the monoanionic and dianionic [Zn 2 Ni] nitrenoid complexes. However, DFT analysis suggests Ni-borne oxidation for 5.

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

A short account of thermoelectric film characterization techniques

Thermoelectric films and periodic structures have particularly intriguing electrical and thermal transport features due to their low dimensionality. As a result, they have piqued the attention of researchers from across the spectrum of disciplines. Their applications span from cooling fast CPUs to providing energy for wearable devices. The progress in the techniques for synthesizing TE materials and fabricating thin films has facilitated the emergence of a flourishing research domain in the field of electrical and thermal transport at the nanoscale. Further, a significant proportion of contemporary electronic, opto-electronic, and solar energy components are composed of materials featuring numerous interfaces and nanoscale contacts. Consequently, it is imperative to explore the thermal energy transfer and charge carrier transport across the films with thickness dimensions in the nanometer range. The development of cutting-edge approaches for grasping complicated processes at the nanoscale is critical. This review provides a concise overview of the prevalent methodologies developed over the last two decades and employed for the characterization of the Seebeck coefficient and electrical and thermal conductivity of thermoelectric films.

36 MATERIALS SCIENCE↗
DOE OSTI2025

The Effect of Core-Hole Shape on Attosecond Valence Electron Dynamics

Rapid X-ray ionization of a core electron is known to induce the attosecond motion of valence electrons; however, the effect of core-hole shape on the triggered dynamics remains relatively unknown. In this work, the sub-four fs response of prototypical functionalized/heterocyclic/polycyclic molecules was simulated using real-time time-dependent density functional theory (RT-TDDFT), a sudden approximation core-hole, and phenomenologically Auger–Meitner (AM) decay. These molecules included fluorobenzene, chlorobenzene, bromobenzene, phenol, thiophenol, pyridine, phosphorus, and azulene. It is observed that the valence electron dynamics are essentially independent of the core-hole created, provided that it is ionized from an inner-shell orbital and not an inner-valence orbital. This has broad implications for free-electron laser studies of X-ray pumped attosecond processes since the flexibility in edge allows for a wide range of experimental modalities, core-holes with longer AM lifetimes, and molecular targets.

aromatic compounds↗
DOE OSTI2025

Low-Cost, Scalable Sorbents with Balanced Capacity-Kinetics-Thermodynamics for H2 Storage

The goal of this project is to utilize cutting-edge materials science, chemistry, and process engineering to demonstrate the feasibility of a new class of scalable sorbents with unprecedented balance of capacity-kinetics-thermodynamics for H 2 storage in fossil fuel power plants . The core fabrication leverages the unique exotic properties (e.g., high H 2 affinity, ultrahigh surface area, and exceptional thermal, mechanical and chemical stability) of the emerging 2D materials i.e. hexagonal boron nitride (hBN) followed by strategic coupling with alkali metals (Li, Na) dopants and optimal interlayer distance to deliver a stable, long-term energy storage for the grid. Figure 1 shows how this technology works.

08 HYDROGEN↗