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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 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Time-Resolved Radioluminescence of the Polynuclear Copper(I) Phosphor Cu4I6²–. Different Temporal responses to Photo, X-Ray, β-Ray and α-Particle Excitation

Described for the first time are the time-resolved radioluminescence (TRRL) properties of the highly luminescent copper(I) cluster Cu4I62– using X-ray, b-ray and a-particle excitation. The copper(I) phosphors are two crystalline salts of this anion, [Na2(18-crown-6)2(H2O)3][Cu4I6] (I) and [Li(benzo-15-crown-5)2(H2O)]2[Cu4I6] (II), that had been shown to display strong photoluminescence (PL) when excited with ultraviolet light. The integrated radioluminescence (RL) spectra observed when pulsed X-rays were used as the excitation source are virtually the same as the PL spectra under comparable conditions. These temporal RL spectra are invariant at all observation times indicating that the observed scintillation occurs from a common excited state (or set of excited states). When the TRRL is collected from excitation with a pulsed X-ray source, b-ray decay from 90Sr or a-decay from 244Cm, the longer components (>2 μs) of the TRRL displayed (in each case) lifetimes comparable to those of the strictly exponential PL decays recorded under pulsed laser UV excitation. However, at shorter observation times (< 500 ns), the RL decay deviated from the exponential model, indicating a markedly different temporal luminescence behavior when these materials were excited with pulsed high energy radiation. Furthermore, this effect was the most pronounced for the a-particle excitation. These results suggest that the absorption of a very high energy X-ray photon, b-ray or a-particle at a site within the crystalline solid leads to a high local density of electronic excited states and that coupling between these states provides an alternative channel for excited state decay. Given that the patterns observed

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2026

Combining ToF‐SIMS and Multivariate Analysis to Resolve Active Sites on Ni‐Based HER Catalysts

Unambiguous identification of active sites in heterogeneous catalysis remains a major challenge, particularly for materials with ultrathin, chemically mixed surface layers. Here, we demonstrate a generalizable approach that combines time-of-flight secondary ion mass spectrometry (ToF-SIMS) with multivariate statistical analysis (principal component analysis [PCA] and multivariate curve resolution [MCR]) to resolve catalytically relevant motifs at the nanoscale. Using Ni electrodes as a model system, PCA distinguished hydroxide-enriched domains from oxide- and metal-rich regions, while MCR decomposed depth profiles and 3D images into hydroxide, oxide, and metallic layers with nanometer resolution. A unique secondary-ion fragment, NiO 3 H 3 − (m/z 108.94), emerged as a marker of hydroxide-rich environments and correlated with hydrogen evolution reaction (HER) activity across a series of Ni electrodes. Complementary density functional theory (DFT) calculations revealed that Ni(OH) 2 clusters adjacent to metallic Ni offer the most favorable water dissociation energetics, establishing the structural origin of the marker. While illustrated here for Ni-based HER, this workflow provides a broadly applicable framework to isolate and rank near-surface patterns that govern catalytic activity, thereby extending ToF-SIMS from a qualitative probe to a predictive tool for active site identification.

HER active sites↗
DOE OSTI2025

Quenching of the octupole rotational band in 71 Ge

The main goal of this study was to enhance the knowledge of the properties of the known octupole rotational band in 71 Ge, including transition rates, and to investigate whether the band persists to higher spin. An experiment at Florida State University using the 62 Ni ( 14 C, 𝛼⁢𝑛) reaction at 50 MeV was used to produce 71 Ge at high spin. An array of ten Compton-suppressed Ge detectors, consisting of three Clover detectors and seven single-crystal detectors, was used to measure the 𝛾 decays in coincidence. An analysis of the resulting coincidence spectra resulted in the placement of 13 additional transitions in the 71 Ge level scheme, one of which (1092 keV) extends the octupole band to a (35/2 − ) state at 8206 keV. However, calculations of the kinematic moment of inertia show that the 1092-keV transition disrupts the rigid rotational pattern and is likely associated with a band crossing, potentially quenching the octupole deformation. Transition strengths inferred from lifetime measurements in the octupole band are not well reproduced by either shell-model calculations using the JUN45 interaction or a semimicroscopic cluster model, while those for the 𝜈⁢𝑔 9/2 band are in good agreement with the corresponding shell-model predictions. Comparisons between the octupole band in 71 Ge and negative-parity bands based on 3 − octupole states in some neighboring even-even nuclei show both similarities and differences. Systematic trends within the 𝜈⁢𝑔 9/2 bands among odd-𝐴 Ge isotopes point to increased collectivity near 𝑁 = 40.

59 ≤ A ≤ 89↗
NASA NTRS1985

Detailed X-ray observations of M83

X-ray observation of M83 with the Einstein Observatory indicates an extent and shape for this emission that are comparable to those in the blue band, although the inner 2-arcmin region shows a relative X-ray excess that may be accounted for by a clustering of bulge-type X-ray sources in the inner region of the plane of the galaxy. A lack of correlation in high resolution X-ray observations is noted between X-ray emission and the spiral arm pattern, suggesting that most of the X-ray emission from the plane of M83 is due to unresolved sources, belonging to the 'smooth' disk population, whose ages are in the 100 million-1 billion year range. Attention is given to six bright sources in the plane and nuclear region of M83, whose high X-ray luminosities suggest that they are close accreting binaries.

Trinchieri, G.↗
DOE OSTI2019

Phasor Measurement Units Optimal Placement and Performance Limits for Fault Localization

Here, the performance limits of faults localization are investigated using synchrophasor data. The focus is on a non-trivial operating regime where the number of Phasor Measurement Unit (PMU) sensors available is insufficient to have full observability of the grid state. Proposed analysis uses the Kullback Leibler (KL) divergence between the distributions corresponding to different fault location hypotheses associated with the observation model. This analysis shows that the most likely locations are concentrated in clusters of buses more tightly connected to the actual fault site akin to graph communities. Consequently, a PMU placement strategy is derived that achieves a near-optimal resolution for localizing faults for a given number of sensors. The problem is also analyzed from the perspective of sampling a graph signal, and how the placement of the PMUs i.e. the spatial sampling pattern and the topological characteristic of the grid affect the ability to successfully localize faults. To highlight the superior performance of presented fault localization and placement algorithms, the proposed strategy is applied to a modified IEEE 34, IEEE-123 bus test cases and to data from a real distribution grid. Additionally, the detection of cyber-physical attacks is also examined where PMU data and relevant Supervisory Control and Data Acquisition (SCADA) network traffic information are compared to determine if a network breach has affected the integrity of the system information and/or operations.

42 ENGINEERING↗
DOE OSTI2022

Covert MOF-Based Photoluminescent Tags via Tunable Linker Energetics

We report that the optical anticounterfeiting tags utilize the photoluminescent properties of materials to encode unique patterns, enabling identification and validation of important items and assets. These tags must combine optical complexity with ease of production and authentication to both prevent counterfeiting and to remain practical for widespread use. Metal–organic frameworks (MOFs) based on polynuclear, rare earth clusters are ideal materials platforms for this purpose, combining fine control over structure and composition, with tunable, complex energy transfer mechanisms via both linker and metal components. Here we report the design and synthesis of a set of heterometallic MOFs based on combinations of Eu, Nd, and Yb with the tetratopic linker 1,3,6,8-tetrakis(4-carboxyphenyl)pyrene. The energetics of this linker facilitate the intentional concealment of the visible emissions from Eu while retaining the infrared emissions of Nd and Yb, creating an optical tag with multiple covert elements. Unique to the materials system reported herein, we document the occurrence of a previously not observed 11-metal cluster correlated with the presence of Yb in the MOFs, coexisting with a commonly encountered 9-metal cluster. We demonstrate the utility of these materials as intricate optical tags with both rapid and in-depth screening techniques, utilizing orthogonal identifiers across composition, emission spectra, and emission decay dynamics. This work highlights the important effect of linker selection in controlling the resulting photoluminescent properties in MOFs and opens an avenue for the targeted design of highly complex, multifunctional optical tags.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

A transmission electron microscopy and X-ray photoelectron spectroscopy study of annealing induced γ-phase nucleation, clustering, and interfacial dynamics in reactively sputtered amorphous alumina thin films

Pure α-Al{sub 2}O{sub 3} exhibits a very high degree of thermodynamical stability among all metal oxides and forms an inert oxide scale in a range of structural alloys at high temperatures. We report that amorphous Al{sub 2}O{sub 3} thin films sputter deposited over crystalline Si instead show a surprisingly active interface. On annealing, crystallization begins with nuclei of a phase closely resembling γ-Alumina forming almost randomly in an amorphous matrix, and with increasing frequency near the substrate/film interface. This nucleation is marked by the signature appearance of sharp (400) and (440) reflections and the formation of a diffuse diffraction halo with an outer maximal radius of ≈0.23 nm enveloping the direct beam. The microstructure then evolves by a cluster-coalescence growth mechanism suggestive of swift nucleation and sluggish diffusional kinetics, while locally the Al ions redistribute slowly from chemisorbed and tetrahedral sites to higher anion coordinated sites. Chemical state plots constructed from XPS data and simple calculations of the diffraction patterns from hypothetically distorted lattices suggest that the true origins of the diffuse diffraction halo are probably related to a complex change in the electronic structure spurred by the a-γ transformation rather than pure structural disorder. Concurrent to crystallization within the film, a substantially thick interfacial reaction zone also builds up at the film/substrate interface with the excess Al acting as a cationic source.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Entropy production fluctuations encode collective behavior in active matter

We derive a general lower bound on distributions of entropy production in interacting active matter systems. The bound is tight in the limit that interparticle correlations are small and short-ranged, which we explore in four canonical active matter models. In all models studied, the bound is weak where collective fluctuations result in long-ranged correlations, which subsequently links the locations of phase transitions to enhanced entropy production fluctuations. We develop a theory for the onset of enhanced fluctuations and relate it to specific phase transitions in active Brownian particles. Furthermore, we also derive optimal control forces that realize the dynamics necessary to tune dissipation and manipulate the system between phases. In so doing, we uncover a general relationship between entropy production and pattern formation in active matter, as well as ways of controlling it.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Power Profile Monitoring and Tracking Evolution of System-Wide HPC Workloads

The power & energy demands of HPC machines have grown significantly. Modern exascale HPC systems require tens of megawatts of combined power for computing resources and cooling facilities at full capacity. The current energy trend is not sustainable for future HPC systems, and there is a need to work toward the energy efficiency aspect of HPC performance. Energy awareness of the HPC applications at the job level is essential for running an efficient HPC system. This work aims to develop a pipeline to provide a production-level system-wide overview of the HPC workloads' power profile while handling evolving workloads exhibiting new power trends. We developed an open-set classification model for HPC jobs based on the properties of power profiles to continuously provide a system-wide holistic view of recently completed jobs. The pipeline helps continuously monitor the job-level power usage pattern of HPC and enables us to capture the new trends in applications' power behavior. We employed a comprehensive set of techniques to generate job-level data, custom-designed feature extraction methods to extract critical features from jobs' power profiles, clustering techniques powered by generative modeling, and open-set classification for identifying job profiles into known classes or an unknown set. With extensive evaluations, we demonstrate the effectiveness of each component in our pipeline. We provide an analysis of the resulting clusters that characterize the power profile landscape of the Summit supercomputer from more than 60K jobs executed in a year. The open-set classification classifies the known data sets into known classes with high accuracy and identifies unknown data noints with over 85% accuracy.

Karimi, Ahmad Maroof↗
DOE OSTI2020

ENSIGN

ENSIGN is a data analytics software package offering a modern unsupervised machine learning solution for scalable discovery in Big Data. The analytics in ENSIGN are based on an advanced mathematical tool called tensor decomposition and they are optimized to run efficiently on a range of computing platforms (from small multicore Desktop platforms to large Supercomputing clusters and novel high-end memory-driven computing platforms such as HPE Superdome Flex). ENSIGN enables the user to extract deep insights from the entirety of massive-scale (100s of Gigabytes or Terabytes scale) multidimensional data. ENSIGN uncovers latent patterns in data without the user having to specify or describe what the patterns are; the user, in the first place, may not even know such patterns existed and that they have to look for such patterns. The insights gained from ENSIGN could be trailheads that can be used as starting points for deeper forensic investigation.

Baskaran, Muthu↗
DOE OSTI2022

ENSIGN

ENSIGN is a data analytics software package offering a modern unsupervised machine learning solution for scalable discovery in Big Data. The analytics in ENSIGN are based on an advanced mathematical tool called tensor decomposition and they are optimized to run efficiently on a range of computing platforms (from small multicore Desktop platforms to large Supercomputing clusters and novel high-end memory-driven computing platforms such as HPE Superdome Flex). ENSIGN enables the user to extract deep insights from the entirety of massive-scale (100s of Gigabytes or Terabytes scale) multidimensional data. ENSIGN uncovers latent patterns in data without the user having to specify or describe what the patterns are; the user, in the first place, may not even know such patterns existed and that they have to look for such patterns. The insights gained from ENSIGN could be trailheads that can be used as starting points for deeper forensic investigation.

Baskaran, Muthu↗
DOE OSTI2018

Mobilizing the anti-duck brigade: technology and market pathways for load-shifting demand response in California

With rapidly increasing renewable power generation, the California electricity system is experiencing the impacts of the so-called “duck curve,” with occasional over-generation in the middle of the day, followed by rapid ramping of net demand producing a sharp evening peak. Mitigating this pattern will require novel demand-side management approaches to shifting demand away from high net demand periods and toward high renewables generation periods. In this paper, drawing from more than 200,000 individual residential, commercial, and industrial customers’ hourly smart meter data, we disaggregate load shapes for certain key end-uses and then average the results across a highly granular set of customer segments by sector, building type, demand profile and geographic region, to yield a library of characteristic daily load profiles (“clusters”) for different end-uses and seasons. By categorizing the library into particularly desirable or undesirable load shapes in the context of mitigating the duck curve, we can gain insight into specific technologies, seasonal effects, or site-level attributes that may serve as helpful levers to use in developing future load-shifting programs. Based on these insights, we develop recommendations on technologies and new market structures and incentives that can create a future demand curve that more closely matches renewable generation patterns.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

A Guide to Conquer the Biological Network Era Using Graph Theory

Networks are one of the most common ways to represent biological systems as complex sets of binary interactions or relations between different bioentities. In this article, we discuss the basic graph theory concepts and the various graph types, as well as the available data structures for storing and reading graphs. In addition, we describe several network properties and we highlight some of the widely used network topological features. We briefly mention the network patterns, motifs and models, and we further comment on the types of biological and biomedical networks along with their corresponding computer- and human-readable file formats. Finally, we discuss a variety of algorithms and metrics for network analyses regarding graph drawing, clustering, visualization, link prediction, perturbation, and network alignment as well as the current state-of-the-art tools. We expect this review to reach a very broad spectrum of readers varying from experts to beginners while encouraging them to enhance the field further.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Single Cell RNA-Seq and Machine Learning Reveal Novel Subpopulations in Low-Grade Inflammatory Monocytes With Unique Regulatory Circuits

Subclinical doses of LPS (SD-LPS) are known to cause low-grade inflammatory activation of monocytes, which could lead to inflammatory diseases including atherosclerosis and metabolic syndrome. Sodium 4-phenylbutyrate is a potential therapeutic compound which can reduce the inflammation caused by SD-LPS. To understand the gene regulatory networks of these processes, we have generated scRNA-seq data from mouse monocytes treated with these compounds and identified 11 novel cell clusters. We have developed a machine learning method to integrate scRNA-seq, ATAC-seq, and binding motifs to characterize gene regulatory networks underlying these cell clusters. Using guided regularized random forest and feature selection, our method achieved high performance and outperformed a traditional enrichment-based method in selecting candidate regulatory genes. Our method is particularly efficient in selecting a few candidate genes to explain observed expression pattern. In particular, among 531 candidate TFs, our method achieves an auROC of 0.961 with only 10 motifs. Finally, we found two novel subpopulations of monocyte cells in response to SD-LPS and we confirmed our analysis using independent flow cytometry experiments. Our results suggest that our new machine learning method can select candidate regulatory genes as potential targets for developing new therapeutics against low grade inflammation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Unsupervised Power System Event Detection and Classification Using Unlabeled PMU Data

This paper proposes a novel data-driven power system event detection and classification method based on 5TB of actual PMU measurements collected from the US western interconnect. Firstly, a set of comprehensive power quality rules are proposed to pre-filter the raw data and extract the regions of interest (ROI). Six distinct event categories are defined and corresponding patterns are chosen as references. Meanwhile, detailed characteristics of patterns are summarized to enhance our understanding of the actual events. Then, the time-independent feature vectors are generated by extracting the statistical, temporal, and spectral features from the raw time-series data. Furthermore, an ensemble model is proposed to cluster the events by combining multiple K-means clustering models using a voting strategy. Besides, both system-level and PMU-level clustering models are developed. The accuracy and robustness of the event detection method are further improved through interactive evaluation of the two-level clustering results. This paper summarizes the actual characteristics of each event category and provides a reliable basis for accurate label generation. The experiments demonstrate the effectiveness of the proposed event detection and classification method.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Unsupervised Power System Event Detection and Classification Using Unlabeled PMU Data

This paper proposes a novel data-driven power system event detection and classification method based on 5TB of actual PMU measurements collected from the US western interconnect. Firstly, a set of comprehensive power quality rules are proposed to pre-filter the raw data and extract the regions of interest (ROI). Six distinct event categories are defined and corresponding patterns are chosen as references. Meanwhile, detailed characteristics of patterns are summarized to enhance our understanding of the actual events. Then, the time-independent feature vectors are generated by extracting the statistical, temporal, and spectral features from the raw time-series data. Furthermore, an ensemble model is proposed to cluster the events by combining multiple K-means clustering models using a voting strategy. Besides, both system-level and PMU-level clustering models are developed. The accuracy and robustness of the event detection method are further improved through interactive evaluation of the two-level clustering results. This paper summarizes the actual characteristics of each event category and provides a reliable basis for accurate label generation. The experiments demonstrate the effectiveness of the proposed event detection and classification method.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Constraining the Galactic bar using the M92 stellar stream

Stellar streams are excellent probes of the gravitational potential in which they evolve. In the Milky Way (MW), globular cluster (GC) streams are routinely used to infer properties about time-dependent perturbations of the underlying potential. This implies that streams with Galactocentric radii small enough to be perturbed by the MW bar should offer constraints on it, such as its pattern speed, which currently has a wide range of values reported in the literature and is important when studying stellar kinematics. The GC M92 has a small pericentre and should be affected by the bar. It has a diffuse stellar stream, but confirming stream members has previously been hindered by a lack of spectroscopic data. In this paper, we use Dark Energy Spectroscopic Instrument (DESI) observations together with photometric and astrometric data to obtain spectroscopic members of the M92 stream for the first time. We identify a clear spatial distribution and gradients in distance moduli, proper motions, and radial velocities that confirm the stream's existence. We compare the observed stream to mock streams generated in different barred potentials and estimate the MW bar's pattern speed $Ω= 29.1^{+0.7}_{-0.4}$ km s$^{-1}$ kpc$^{-1}$ and $\dot Ω= 0.7^{+3.5}_{-2.3}$ km s$^{-1}$ kpc$^{-1}$ Gyr$^{-1}$. This is the first time a stellar stream is used to probabilistically infer these bar properties, and it opens up an exciting realm of inner Galactic potential characterisation using stellar streams.

Byström, Amanda [Edinburgh U., Inst. Astron.] (ORC↗
DOE OSTI2017

Induction of α6 and β1 integrins by acupuncture stimulation in rats

Acupuncture therapy is performed by applying the needle insertion at discrete cutaneous locations and used for the treatments of diverse symptoms and disorders. In order to elucidate mechanistic basis on how acupuncture stimulation (AS) produces therapeutic effects, it is primarily important to understand tissue responses locally at the acupuncture site (acupoint). Here, we investigated integrin protein as molecular target responding to and integrating AS. Signals of α6 and β1 integrins were clearly induced at zusanli acupoint 24 h after AS in areas of nuclear clusters around the needle track. Induction levels of integrin were largely reduced by needle insertion at non-acupuncture point or without needle rotation. Phospho-Erk1/2 was initially decreased below the basal level after AS but increased 24 h later. Induction pattern of phospho-Erk1/2 was as similar as that of α6 integrin in its selectivity to needling procedure and tissue distribution. We further found that mRNA expression of P2X3 purinergic receptor was upregulated in the dorsal root ganglion (DRG) after AS, but decreased by the inhibition of Erk1/2 activity at the acupuncture area. Moreover, AS-mediated integrin activation was required for Erk1/2 activation at the acupuncture site and regulation of pain sensitivity in the hind paw. The present results provide a new evidence on acupuncture-specific tissue response in terms of integrin induction, and further suggest that integrin activation may be involved in transmitting mechanosensory signals from the acupoint to afferent nerve fiber. - Highlights: • We investigated local tissue responses after acupuncture stimulation (AS) in rats. • AS strongly induced α6 and β1 integrins and activated Erk1/2. • Integrin Induction was primarily specific to acupuncture site and needle rotation.

60 APPLIED LIFE SCIENCES↗