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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Minijet clustering algorithm using transverse-momentum seeds in high-energy nuclear collisions

We propose an algorithm to detect mini-jet clusters in high-energy nuclear collisions, by selecting a high-transverse-momentum (pT) particle as a seed and assigning a clustering radius (R) in the pseudorapidity and azimuthal-angle space. Our PYTHIA simulations for p+p collisions show that a scheme with a seeding p T of around 0.5 GeV/c and R of approximately 0.6 satisfactorily identifies mini-jet clusters. The correlation between clusters obtained in PYTHIA calculations using the algorithm exhibits the proper behavior of hard-scattering-like processes, suggesting its usefulness in isolating mini-jet-like clusters from non-hard-scattering soft processes when applied to actual nuclear-collision data, thereby allowing a closer examination of both the mini-jet and the soft mechanisms.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Elucidating the geometric and electronic structure of a fully sulfided analog of an Anderson polyoxomolybdate cluster

The catalytic activity of transition metal sulfide (TMS) clusters in small molecule activation, redox transformations, and charge transfer has inspired the design of novel TMS-based materials for energy-related catalysis and chemical applications. Polyoxometalates (POMs), known for their structural diversity, can in principle be transformed into TMS clusters; however, fully sulfided analogs are rarely isolated, likely due to the strong tendency of uncapped TMS clusters to agglomerate. Here, we report the geometric and electronic structure of a capping ligand-free fully sulfided analog of heptamolybdate Anderson POM [Mo VI 7 O 24 ] 6− , synthesized through the sulfidation of a nanoconfined POM secured within a porous Zr-metal organic framework (NU-1000). A combined computational and experimental analysis indicates that the sulfided counterpart of the Anderson POM is geometrically and electronically more sophisticated than the parent POM. Comparison of experimental pair distribution function (PDF) data with computational simulations confirms that, unlike the oxygen-only [Mo VI 7 O 24 ] 6− cluster, the [Mo IV 7 (μ 3 -S) 6 (μ 2 -SH) 6 (S 2 ) 6 ] 2− polythiometalate (PTM) exhibits diverse sulfur anions (S 2− , HS − , S 2 2− ). DFT calculations indicate that H 2 S acts as a reducing agent, and together with terminal disulfide (S 2 2− ) ligands in the PTM structure, facilitates the complete reduction of all seven Mo VI centers in the parent POM to Mo IV . These findings are supported by X-ray photoelectron spectroscopy (XPS), which confirms exclusive Mo IV , and elemental analysis, which shows quantitative sulfur incorporation. Difference envelope density (DED) mapping further reveals that the PTM clusters are spatially confined within the MOF pores, preventing agglomeration and preserving molecular integrity.

Rabbani, S. M. Gulam [The Ohio State University, C↗
DOE OSTI2021

Whole Genome Sequencing Links Mycobacterium bovis From Cattle, Cheese and Humans in Baja California, Mexico

Mycobacterium bovis causes tuberculosis (TB) in cattle, which in turn can transmit the pathogen to humans. Tuberculosis in dairy cattle is of particular concern where the consumption of raw milk and dairy products is customary. Baja California (BCA), Mexico, presents high prevalence of TB in both cattle and humans, making it important to investigate the molecular epidemiology of the disease in the region. A long-term study was undertaken to fully characterize the diversity of M. bovis genotypes circulating in dairy cattle, cheese and humans in BCA by whole-genome sequencing (WGS). During a 2-year period, 412 granulomatous tissue samples were collected from local abattoirs and 314 cheese samples were purchased from local stores and vendors in BCA and sent to the laboratory for mycobacterial culture, histology, direct PCR and WGS. For tissue samples M. bovis was recovered from 86.8%, direct PCR detected 90% and histology confirmed 85.9% as mycobacteriosis-compatible. For cheese, M. bovis was recovered from 2.5% and direct PCR detected 6% of the samples. There was good agreement between diagnostic tests. Subsequently, a total of 345 whole-genome SNP sequences were obtained. Phylogenetic analysis grouped these isolates into 10 major clades. SNP analysis revealed putative transmission clusters where the pairwise SNP distance between isolates from different dairies was ≤3 SNP. Also, human and/or cheese isolates were within 8.45 (range 0–17) and 5.8 SNP (range 0–15), respectively, from cattle isolates. Finally, a comparison between the genotypes obtained in this study and those reported previously suggests that the genetic diversity of M. bovis in BCA is well-characterized, and can be used to determine if BCA is the likely source of M. bovis in humans and cattle in routine epidemiologic investigations and future studies. In conclusion, WGS provided evidence of ongoing local transmission of M. bovis among the dairies in this high-TB burden region of BCA, as well as show close relationships between isolates recovered from humans, cheese, and cattle. This confirms the need for a coordinated One Health approach in addressing the elimination of TB in animals and humans. Overall, the study contributes to the knowledge of the molecular epidemiology of M. bovis in BCA, providing insight into the pathogen's dynamics in a high prevalence setting.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Controlling Reaction Pathways of Ethylene Hydroformylation Using Isolated Bimetallic Rhodium–Cobalt Sites

Designing efficient ligand-free heterogeneous catalysts for ethylene hydroformylation to produce C 3 oxygenates is of importance for both fundamental research and practical applications, but it is often hindered by insufficient catalytic activity and selectivity. Here, this work designs isolated rhodium–cobalt (Rh–Co) sites confined within a ZSM-5 zeolite to enhance ethylene hydroformylation rates and selectivity while maintaining catalyst stability. By adjusting the Co/Al ratio in Co-ZSM-5, different sizes of Co are formed; subsequent Rh introduction produces isolated Rh 1 Co x clusters with different Rh–Co coordination numbers (CNs). In-situ characterizations and density functional theory calculations reveal that a Rh–Co CN of 3, corresponding to an isolated Rh 1 Co 3 site, provides optimal bindings to reaction intermediates and thus achieves the highest hydroformylation rates among supported Rh-based catalysts. This study demonstrates the role of coordination-tuning via a secondary metal in effectively controlling the reaction pathway over single Rh atom catalysts.

03 NATURAL GAS↗
DOE OSTI2020

Unraveling the individual influences of supports and ionic liquid coatings on the catalytic properties of supported iridium complexes and iridium clusters

In this work, supported iridium complexes were synthesized by the reaction of Ir(CO) 2 (acac) (acac = acetylacetonato) with SiO 2 , γ-Al 2 O 3 , and MgO. Extended X-ray absorption fine structure (EXAFS) and infrared (IR) spectra demonstrate that the iridium was present as atomically dispersed species anchored to each support. The samples were treated in flowing H 2 at 673 K to form supported iridium clusters. EXAFS spectra and high-angle annular dark-field scanning transmission electron microscopy images demonstrate that the average diameter of the iridium clusters on each support was approximately 1.2 nm. Furthermore, the catalysts before and after cluster formation were coated with each of a family of 1,3-dialkylimidazolium ionic liquids (ILs) having varying electron-donor tendencies probed by their υ(C2H) frequencies determined by IR spectroscopy. The coated and uncoated samples were tested as catalysts for partial hydrogenation of 1,3-butadiene in a flow reactor at 333 K, with turnover frequencies determined from differential conversions. The individual influences of the IL coatings and supports on the catalyst performance were found to depend strongly on whether the iridium was site-isolated complexes or present in clusters. The IL coatings as ligands exerted dominant effects on the clusters as catalysts, whereas the supports exerted dominant effects on the isolated iridium atoms. The results indicate how to tune the effects of metal nuclearity, IL coatings, and supports on the electronic environments and catalytic properties of the metals.

1,3-Butadiene hydrogenation↗
NASA NTRS2011

Collaborative Clustering for Sensor Networks

Traditionally, nodes in a sensor network simply collect data and then pass it on to a centralized node that archives, distributes, and possibly analyzes the data. However, analysis at the individual nodes could enable faster detection of anomalies or other interesting events, as well as faster responses such as sending out alerts or increasing the data collection rate. There is an additional opportunity for increased performance if individual nodes can communicate directly with their neighbors. Previously, a method was developed by which machine learning classification algorithms could collaborate to achieve high performance autonomously (without requiring human intervention). This method worked for supervised learning algorithms, in which labeled data is used to train models. The learners collaborated by exchanging labels describing the data. The new advance enables clustering algorithms, which do not use labeled data, to also collaborate. This is achieved by defining a new language for collaboration that uses pair-wise constraints to encode useful information for other learners. These constraints specify that two items must, or cannot, be placed into the same cluster. Previous work has shown that clustering with these constraints (in isolation) already improves performance. In the problem formulation, each learner resides at a different node in the sensor network and makes observations (collects data) independently of the other learners. Each learner clusters its data and then selects a pair of items about which it is uncertain and uses them to query its neighbors. The resulting feedback (a must and cannot constraint from each neighbor) is combined by the learner into a consensus constraint, and it then reclusters its data while incorporating the new constraint. A strategy was also proposed for cleaning the resulting constraint sets, which may contain conflicting constraints; this improves performance significantly. This approach has been applied to collaborative clustering of seismic and infrasonic data collected by the Mount Erebus Volcano Observatory in Antarctica. Previous approaches to distributed clustering cannot readily be applied in a sensor network setting, because they assume that each node has the same view of the data set. A view is the set of features used to represent each object. When a single data set is partitioned across several computational nodes, distributed clustering works; all objects have the same view. But when the data is collected from different locations, using different sensors, a more flexible approach is needed. This approach instead operates in situations where the data collected at each node has a different view (e.g., seismic vs. infrasonic sensors), but they observe the same events. This enables them to exchange information about the likely cluster membership relations between objects, even if they do not use the same features to represent the objects.

Wagstaff. Loro :/↗
NASA NTRS2002

Mutation and premating isolation

While premating isolation might be traceable to different genetic mechanisms in different species, evidence supports the idea that as few as one or two genes may often be sufficient to initiate isolation. Thus, new mutation can theoretically play a key role in the process. But it has long been thought that a new isolation mutation would fail, because there would be no other individuals for the isolation-mutation-carrier to mate with. We now realize that premeiotic mutations are very common and will yield a cluster of progeny carrying the same new mutant allele. In this paper, we discuss the evidence for genetically simple premating isolation barriers and the role that clusters of an isolation mutation may play in initiating allopatric, and even sympatric, species divisions.

Review↗
DOE OSTI2020

Detecting anomalous packets in network transfers: investigations using PCA, autoencoder and isolation forest in TCP

Large-scale scientific workflows rely heavily on high-performance file transfers. These transfers require strict quality parameters such as guaranteed bandwidth, no packet loss or data duplication. To have successful file transfers, methods such as predetermined thresholds and statistical analysis need to be done to determine abnormal patterns. Network administrators routinely monitor and analyze network data for diagnosing and alleviating these, making decisions based on their experience. However, as networks grow and become complex, monitoring large data files and quickly processing them, makes it improbable to identify errors and rectify these. Abnormal file transfers have been classified by simply setting alert thresholds, via tools such as PerfSonar and TCP statistics (Tstat). This paper investigates the feasibility of unsupervised feature extraction methods for identifying network anomaly patterns with three unsupervised classification methods—principal component analysis, autoencoder and isolation forest. Here, we collect file transfer statistics from two experiment sets—synthetic iPerf generated traffic and 1000 Genome workflow runs, with synthetically introduced anomalies. Our results show that while PCA and a simple autoencoder finds it difficult to detect clusters, the tree-variant isolation forest is able to identify anomalous packets by breaking down TCP traces into tree classes early.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2009

Evolutionary Computation for the Identification of Emergent Behavior in Autonomous Systems

Over the past several years the Center for Evolutionary Computation and Automated Design at the Jet Propulsion Laboratory has developed a technique based on Evolutionary Computational Methods (ECM) that allows for the automated optimization of complex computationally modeled systems. An important application of this technique is for the identification of emergent behaviors in autonomous systems. Mobility platforms such as rovers or airborne vehicles are now being designed with autonomous mission controllers that can find trajectories over a solution space that is larger than can reasonably be tested. It is critical to identify control behaviors that are not predicted and can have surprising results (both good and bad). These emergent behaviors need to be identified, characterized and either incorporated into or isolated from the acceptable range of control characteristics. We use cluster analysis of automatically retrieved solutions to identify isolated populations of solutions with divergent behaviors.

Terrile, Richard J.↗
DOE OSTI2020

Comparative genetics of Enterococcus faecalis intestinal tissue isolates before and after surgery in a rat model of colon anastomosis

We have recently demonstrated that collagenolytic Enterococcus faecalis plays a key and causative role in the pathogenesis of anastomotic leak, an uncommon but potentially lethal complication characterized by disruption of the intestinal wound following segmental removal of the colon (resection) and its reconnection (anastomosis). Here we hypothesized that comparative genetic analysis of E. faecalis isolates present at the anastomotic wound site before and after surgery would shed insight into the mechanisms by which collagenolytic strains are selected for and predominate at sites of anastomotic disruption. Whole genome optical mapping of four pairs of isolates from rat colonic tissue obtained following surgical resection (herein named "pre-op" isolates) and then 6 days later from the anastomotic site (herein named "post-op" isolates) demonstrated that the isolates with higher collagenolytic activity formed a distinct cluster. In order to perform analysis at a deeper level, a single pair of E. faecalis isolates (16A pre-op and 16A post-op) was selected for whole genome sequencing and assembled using a hybrid assembly algorithm. Comparative genomics demonstrated absence of multiple gene clusters, notably a pathogenicity island in the post-op isolate. No differences were found in the fsr-gelE-sprE genes (EF1817-1822) responsible for regulation and production of collagenolytic activity. Analysis of unique genes among the 16A pre-op and post-op isolates revealed the predominance of transporter systems-related genes in the pre-op isolate and phage-related and hydrolytic enzyme-encoding genes in the post-op isolate. Despite genetic differences observed between pre-op and post-op isolates, the precise genetic determinants responsible for their differential expression of collagenolytic activity remains unknown.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

The impact of environment on size: Galaxies are 50% smaller in the Fornax Cluster compared to the field

Size is a fundamental parameter for measuring the growth of galaxies and the role of the environment on their evolution. However, the conventional size definitions used for this purpose are often biased and miss the diffuse, outermost signatures of galaxy growth, including star formation and gas accretion. We address this issue by examining low surface brightness truncations or galaxy ‘edges’ as a physically motivated tracer of size based on star formation thresholds. Our total sample consists of ∼900 galaxies with stellar masses ranging from 10 5 M ⊙ < M ⋆ < 10 11 M ⊙ . This sample of nearby cluster, group satellite, and nearly isolated field galaxies was compiled using multi-band imaging from the Fornax Deep Survey, deep IAC Stripe 82, and Dark Energy Camera Legacy Surveys. We find that the edge radii scale as R edge ∝ M ⋆ 0.42 , with a very small intrinsic scatter (∼0.07 dex). The scatter is driven by the morphology and environment of galaxies. In both the cluster and field, early-type dwarfs are systematically smaller by approximately 20% compared to late-type dwarfs. However, galaxies in the Fornax cluster are the most impacted. At a fixed stellar mass, edges in the cluster can be found at about 50% smaller radii, and the average stellar surface density at the edges is a factor of two higher, ∼1 M ⊙ /pc 2 . Our findings support the rapid removal of loosely bound neutral hydrogen (H I ) in hot, crowded environments, which truncates galaxies outside-in earlier, preventing the formation of more extended sizes and lower density edges. Our results highlight the importance of deep imaging surveys to the study of low surface brightness imprints of the large-scale structure and environment on galaxy evolution.

Astronomy & Astrophysics↗
NASA NTRS2000

Laboratory Astrophysics: The Universe in the Palm of Your Hand

Polycyclic aromatic compounds (PACs), a class of organic molecules whose structures are characterized by the presence of two or more fused aromatic rings, have been the subject of astrophysical interest for nearly two decades. Large by interstellar standards (from as few as 20 to perhaps as many as several hundred atoms), it has been suggested that these species are among the most abundant interstellar molecules impacting a wide range of astrophysical phenomena including: (1) the ubiquitous family of infrared emission bands observed in an ever-increasing assortment of astronomical objects; (2) the subtle but rich array of discrete visible/near-infrared interstellar molecular absorption features known as the diffuse interstellar bands (DIBs); (3) the broad near-infrared quasi-continuum observed in a number of nebulae known as excess red emission (ERE); (4) the interstellar ultraviolet extinction curve and broad '2200 Angstrom bump'; and (5) the heating/cooling mechanisms of interstellar clouds. Nevertheless, until recently a lack of good-quality laboratory spectroscopic data on PACs under astrophysically relevant conditions (i.e. isolated, ionized molecules, ionized molecular clusters, etc.) has hindered critical evaluation and extension of this model. Fortunately, the last decade has seen an explosion of experimental and theoretical techniques aimed specifically at addressing these issues. Indeed, many of these techniques will be explored in the series of talks which constitute this forum. This talk will provide an overview of the studies of the spectroscopic properties of isolated, neutral, and ionized PACs that have been conducted in the Astrochemistry Laboratory at NASA Ames, together with a consideration of their implications for astrophysics. Particular attention will be paid to models of the interstellar infrared emission spectra generated using the available database of laboratory PAC infrared spectra and the natural ability of this database to accommodate the variations observed in the astronomical spectra. Such models provide insight into the structure, abundance, and ionization state of the interstellar PAC population and, in turn, provide direct insight into the processes of carbon nucleation, growth and evolution as matter is processed through the interstellar medium. These models will be followed by a more in depth look at some specific aspects of the interstellar infrared emission spectrum, considering both what we can learn about them and what we can learn from them. Finally, some of the limitations of the current model and the available spectroscopic dataset will be 'dered along with future experimental directions designed to address these shortcomings. Further information about this and the related areas of research currently ongoing in the Astrochemistry Laboratory can be found at our world wide web site. http://www-space.arc.nasa.gov/(tilda)astrochem

Hudgins, Douglas M.↗
NASA NTRS2004

Vibrational Spectroscopy at Cryogenic Temperatures: From the Laboratory to the Ends of the Universe

Polycyclic aromatic compounds (PAC) have been the subject of astrophysical interest for nearly two decades. Indeed, there is now evidence that these compounds are among the most abundant interstellar molecules, comprising perhaps 10 - 30% of all the carbon in our galaxy. Ranging in size from as few as 20 to as many as hundreds or thousands of carbon atoms, these molecules are enormous by interstellar standards and impact a wide range of astrophysical phenomena including: the near- and mid-infrared emission spectrum of a wide range of astronomical objects; the ultraviolet/visible/near-infrared absorption of the diffuse medium that permeates our galaxy; and the heating and cooling mechanisms of interstellar clouds. Nevertheless, until recently a lack of laboratory spectroscopic data on PAC under astrophysically relevant conditions (i.e. isolated, ionized molecules; ionized molecular clusters, etc.) has hindered critical evaluation and extension of this model. Fortunately, the last decade has seen an explosion of experimental and theoretical techniques aimed specifically at addressing these issues. Here, we begin with a brief review of the evidence for the existence and abundance of interstellar PAC. From there, we move on to an overview of the general spectroscopic characteristics of the range of isolated, neutral and ionized PAC that we have studied over the last decade. Finally, we will conclude with a consideration of the astrophysical implications and applications of interstellar PAC. Our discussion will revolve primarily around the observed interstellar infrared emission spectra and the ability of the laboratory spectra of varying combinations of PAC to accommodate both the global appearance and the region-to-region variability of this emission. Careful models based on sound laboratory spectroscopic data such as these now have the potential to provide insight into the structure, abundance, and ionization state of the interstellar PAC population. That, in turn, will provide direct insight into the processes of carbon nucleation, growth and evolution as matter is processed through the interstellar medium.

Hudgins, Douglas M.↗
DOE OSTI2026

Bridging Control and Deployment: A Cross-Layer Analysis of Scalable Building Cluster Control

Building cluster control has emerged as a promising approach for enabling flexible and coordinated operation of distributed building systems, yet its transition from pilot demonstrations to routine grid-interactive operation remains limited. This paper argues that this gap cannot be explained by control algorithms alone. Instead, it arises from interacting barriers in communication infrastructure, data and semantic interoperability, uncertainty management, stakeholder participation, market design, and policy support. Accordingly, the paper reviews both technical and non-technical barriers to building cluster control. Technical challenges include heterogeneous devices and protocols, communication latency and reliability, distributed decision-making, and uncertainty propagation across aggregated loads. Non-technical barriers include user participation, stakeholder coordination, incentive allocation, and data governance. Existing solution approaches are synthesized, including semantic interoperability frameworks, edge and hierarchical communication architectures, distributed and transactive control strategies, uncertainty-aware optimization, policy mechanisms, and market reforms. Based on this analysis, two research directions are identified: testing infrastructures that can evaluate control performance under realistic multi-building conditions, and abstraction methods that allow building clusters to interact with other energy sectors through standardized flexibility representations. Overall, the paper provides a structured review of how building cluster control can move from isolated demonstrations toward reproducible, market-compatible, and grid-relevant implementation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Mesoscale convective clustering enhances tropical precipitation

In the tropics, extreme precipitation events are often caused by mesoscale systems of organized, spatially clustered deep cumulonimbi, posing a substantial risk to life and property. While the clustering of convective clouds has been thought to strengthen precipitation rate, no quantitative estimates of this hypothesized enhancement exist. In this study, after isolating the effects of mesoscale convective clustering on precipitation, we find that strongly clustered oceanic convection precipitates more intensely than weakly clustered convection. We further show that this enhancement is primarily attributable to an increase in convective precipitation rate when the environment is less than 70% saturated, with increases in the size of the rainy stratiform region being of equal or greater importance when the environment is closer to saturation. Our results suggest that a correct representation of mesoscale organized convective systems in numerical weather and climate models is needed for accurate predictions of extreme precipitation events.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Synthesis of Co‐Doped MoS 2 Monolayers with Enhanced Valley Splitting

Abstract Internal magnetic moments induced by magnetic dopants in MoS 2 monolayers are shown to serve as a new means to engineer valley Zeeman splitting (VZS). Specifically, successful synthesis of monolayer MoS 2 doped with the magnetic element Co is reported, and the magnitude of the valley splitting is engineered by manipulating the dopant concentration. Valley splittings of 3.9, 5.2, and 6.15 meV at 7 T in Co‐doped MoS 2 with Co concentrations of 0.8%, 1.7%, and 2.5%, respectively, are achieved as revealed by polarization‐resolved photoluminescence (PL) spectroscopy. Atomic‐resolution electron microscopy studies clearly identify the magnetic sites of Co substitution in the MoS 2 lattice, forming two distinct types of configurations, namely isolated single dopants and tridopant clusters. Density functional theory (DFT) and model calculations reveal that the observed enhanced VZS arises from an internal magnetic field induced by the tridopant clusters, which couples to the spin, atomic orbital, and valley magnetic moment of carriers from the conduction and valence bands. The present study demonstrates a new method to control the valley pseudospin via magnetic dopants in layered semiconducting materials, paving the way toward magneto‐optical and spintronic devices.

Zhou, Jiadong↗
DOE OSTI2026

Enhancing NO Reduction by CO Over NiO/CeO 2 Catalyst by Optimizing the Metal Oxide–Support Interaction

Noble metal catalysts are widely used in three-way catalysts (TWCs) due to their high efficiency, but their scarcity and high cost drive the need for effective, low-cost alternatives. Here, in this work, a series of NiO/CeO 2 catalysts were engineered by modulating the OH content and crystallite size of the CeO 2 support. This approach yielded Ni species ranging from isolated single atoms to small clusters and larger aggregates, with varied NiO/CeO 2 interaction strengths. Evaluation of their performance in NO reduction by CO, CO oxidation, and the water–gas shift reaction revealed that the NiO/CeO 2 -300 catalyst, featuring small CeO 2 crystallites and highly dispersed NiO clusters, delivered superior activity for NO reduction and CO oxidation. It was demonstrated that small NiO clusters, due to their efficient CO adsorption and activation, were more active than Ni single atoms. Furthermore, the presence of water was found to influence the catalyst stability, with NiO clusters less stable than single atoms likely due to the hydroxylation effect leading to the formation of Ni(OH) 2 . Oxygen storage capacity measurements revealed that performance was governed by a combination of CeO 2 crystallite size and the abundance of NiO/CeO 2 interfaces. These findings demonstrated that the catalytic performance of Ni/CeO 2 systems could be maximized by optimizing the Ni nanostructure and its interaction with CeO 2 support, positioning them as a promising, multifunctional nonprecious alternative for three-way catalysis application.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Possible role of grain-boundary and dislocation structure for the magnetic-flux trapping behavior of niobium: A first-principles study

In this work, first-principles methods were used to understand magnetic flux trapping at vacancies, dislocations, and grain boundaries in high-purity superconducting niobium. Full-potential linear augmented plane-wave methods were applied in progressively greater complexity, starting at simple vacancies and extending to screw dislocations and tilt grain boundaries to analyze the effects of magnetic field on the superconducting state surrounding these defects. Density-functional theory calculations identified changes in electronic structure at the dislocation core and different types of symmetric tilt grain boundaries relative to bulk niobium. Electron redistribution enhanced nonparamagnetic effects and thus perturb superconductivity, resulting in local conditions suitable for premature flux penetration and subsequently flux pinning. Since the coherence length of superconducting niobium at 0 K is significantly larger than the lattice parameter, the effects of line and planar defects in niobium are predicted to be stronger for defect clusters than single defects in isolation, which is consistent with recent experimental observations. Controlling accumulation or depletion of charge at the defects, e.g., by segregation of an impurity atom, can mitigate these tendencies thus increasing the quality of superconducting niobium.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗