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At least 1,279 records · Page 71
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

One-Step Synthesis of Zeolite Membranes Containing Catalytic Metal Nanoclusters

Metal-loaded zeolitic membranes are promising candidates as catalytic membrane reactors. We report a one-step synthesis method to synthesize zeolite membranes containing metal nanoclusters, that has advantages in comparison to multistep methods such as impregnation and ion exchange. Pure-silica MFI zeolite-Pt hybrid membranes were prepared by hydrothermal synthesis with addition of 3-mercaptopropyl-trimethoxysilane (MPS) and a platinum precursor. Composition analysis and mapping by energy-dispersive X-ray spectroscopy (EDX) reveal that Pt ions/clusters are uniformly distributed along the membrane cross-section. High-magnification scanning transmission electron microscopy (STEM) analysis shows that Pt metal clusters in the hybrid zeolite membrane have a diameter distribution in the range of 0.5–2.0 nm. In contrast, a pure-silica MFI membrane synthesized from an MPS-free solution shows negligible incorporation of Pt metal clusters. To characterize the properties of the hybrid (zeolite/metal) membrane, it was used as a catalytic membrane reactor (CMR) for high-temperature propane dehydrogenation (PDH) at 600 °C and 1 atm. The results indicate that Pt metal clusters formed within the MFI zeolite membrane can serve as effective catalysts for high-temperature PDH reaction along with H 2 removal via membrane permeation, thereby increasing both conversion and selectivity in relation to a conventional membrane reactor containing an equivalent amount of packed Pt catalyst in contact with an MFI membrane. In conclusion, the hybrid zeolite-Pt CMR also showed stable conversion and selectivity upon extended high-temperature operation (12 h), indicating that encapsulation in the zeolite allowed thermal stabilization of the Pt nanoclusters and reduced catalyst deactivation.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Correlated Anion Disorder in Heteroanionic Cubic TiOF 2

Resolving anion configurations in heteroanionic materials is crucial for understanding and controlling their properties. For anion-disordered oxyfluorides, conventional Bragg diffraction cannot fully resolve the anionic structure, necessitating alternative structure determination methods. We have investigated the anionic structure of anion-disordered cubic (ReO 3 -type) TiOF 2 using X-ray pair distribution function (PDF), 19 F MAS NMR analysis, density functional theory (DFT), cluster expansion modeling, and genetic-algorithm structure prediction. Our computational data predict short-range anion ordering in TiOF 2 , characterized by predominant cis-[O 2 F 4 ] titanium coordination, resulting in correlated anion disorder at longer ranges. To validate our predictions, we generated partially disordered supercells using genetic-algorithm structure prediction and computed simulated X-ray PDF data and 19 F MAS NMR spectra, which we compared directly to experimental data. To construct our simulated 19 F NMR spectra, we derived new transformation functions for mapping calculated magnetic shieldings to predicted magnetic chemical shifts in titanium (oxy)fluorides, obtained by fitting DFT-calculated magnetic shieldings to previously published experimental chemical shift data for TiF 4 . We find good agreement between our simulated and experimental data, which supports our computationally predicted structural model and demonstrates the effectiveness of complementary experimental and computational techniques in resolving anionic structure in anion-disordered oxyfluorides. From additional DFT calculations, we predict that increasing anion disorder makes lithium intercalation more favorable by, on average, up to 2 eV, highlighting the significant effect of variations in short-range order on the intercalation properties of anion-disordered materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Integrated analysis reveals that STAT3 is central to the crosstalk between HER/ErbB receptor signaling pathways in human mammary epithelial cells

Human epidermal growth factor receptors (HER, also known as ErbB) drive cellular proliferation, pro-survival and stress responses by activating several downstream kinases, in particular ERK, p38, JNK (SAPK), the PI3K/AKT, as well as various transcriptional regulators such as STAT3. When co-expressed, first three members of HER family (HER1-3) can form homo- and hetero-dimers. Based on the considerable evidence which suggest that every receptor dimer activates intracellular signaling pathways differentially, we hypothesized that the HER dimerization pattern is a better predictor of downstream signaling than the total receptor activation levels. We validated our hypothesis using a combination of model-based analysis to quantify the HER dimerization patterns and multi-factorial experiments where HER dimerization patterns and signaling crosstalk were rationally perturbed. We have measured the activation of HER1-3 receptors and of the sentinel signaling proteins ERK, AKT, p38, JNK, STAT3 as a function of time in a panel of human mammary epithelial (HME) cells expressing different levels of HER1-3 stimulated with various ligand combinations. Our analysis using multiple ways of clustering the activation data has confirmed that the HER receptor dimer is a better predictor of the signaling through p38, ERK and AKT pathways than the total HER receptor expression and activation levels. Targeted inhibition studies to identify the causal effects allowed us to obtain a consensus regulatory interaction model, which revealed that STAT3 occupies a central role in the crosstalk between the studied pathways.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Heteropoly acid functionalized fluoroelastomer with outstanding chemical durability and performance for vehicular fuel cells

To further facilitate commercialization of automotive fuel cells, durability concerns need to be addressed. Currently the addition of a mechanical support in the membrane is able to adequately solve issues of mechanical degradation, but chemical degradation via oxygenated radical attack remains an unsolved challenge. Typical mitigation strategies use cerium or manganese species to serve as radical scavengers, but these ions are able to migrate in the membrane and even leach out of the system. The approach used in this paper is to covalently link and immobilize a heteropoly acid (HPA), more specifically 11-silicotungstic acid (HSiW11), a lacunary HPA of the Keggin structure to a fluoroelastomer, serving as both a radical decomposition catalyst and the proton conducting acid. This dual functionality allows for both high content of radical scavenging species and high ion-exchange capacity. An efficient three step, high yield (77%), commercially viable synthesis for this polymer is reported. The synthesis route for making this new heteropoly acid functionalized polymer is confirmed using infrared spectroscopy (IR), nuclear magnetic resonance (NMR) spectroscopy, and thermogravimetric analysis (TGA). The material exhibits clustering of the HSiW11 moieties, resulting in a poorly connected proton conducting phase when dry, but excellent conductivity is achieved at elevated humidities (0.298 S cm -1 at 80 °C and 95% RH). The proton conductivity shows an enhancement above 60 °C due to a softening of the polymer, as shown by DSC. Under an aggressive chemical accelerated stress test (AST), 90 °C, 30% RH, zero current, and pure O 2 , the PolyHPA losses only 0.05 V of open circuit voltage (OCV) after 500 h, greatly out performing any other material reported in the literature. For comparison, the Nafion® N211 fuel cell drops below 0.8 V after only 76 h under the same conditions. Finally, in fuel cell testing the PolyHPAs have outstanding chemical stability and also possess very low in situ high frequency resistance (HFR) leading to high performance (1.14 W cm -2 at 2 A cm -2 ), compared to 1.11 W cm -2 for the Nafion® N211 fuel cell at the same current. At 75 wt% HSiW11 loading, the fuel cell HFR showed a 22% decrease over N211.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2016

Relationship between cap structure and energy gap in capped carbon nanotubes

Revealing a universal relation between geometrical structures and electronic properties of capped carbon nanotubes (CNTs) is one of the current objectives in nanocarbon community. Here, we investigate the local curvature of capped CNTs and define the cap region by a crossover behavior of the curvature energy versus the number of carbon atoms integrated from the tip to the tube region. Clear correlations among the energy gap of the cap localized states, the curvature energy, the number of carbon atoms in the cap region, and the number of specific carbon clusters are observed. The present analysis opens the way to understand the cap states.

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

Accelerating and stabilizing the convergence of vibrational self-consistent field calculations via the direct inversion of the iterative subspace (vDIIS) algorithm

The vibrational self-consistent field (VSCF) method yields anharmonic states and spectra for molecular vibrations, and it serves as the starting point for more sophisticated correlated-vibration methods. Convergence of the iterative, non-linear optimization in VSCF calculations can be erratic or altogether unsuccessful, particularly for chemical systems involving low-frequency motions. In this work, a vibrational formulation of the Direct Inversion of the Iterative Subspace method of Pulay is presented and investigated. This formulation accounts for distinct attributes of the vibrational and electronic cases, including the expansion of each single-mode vibrational wavefunction in its own basis set. The resulting Direct Inversion of the Iterative Subspace method is shown to substantially accelerate VSCF convergence in all convergent cases as well as rectify many cases where Roothaan-based methods fail. Performance across systems ranging from small, rigid molecules to weakly bound molecular clusters is investigated in this analysis.

Chemistry↗
DOE OSTI2024

Accuracy, transferability, and computational efficiency of interatomic potentials for simulations of carbon under extreme conditions

Large-scale atomistic molecular dynamics (MD) simulations provide an exceptional opportunity to advance the fundamental understanding of carbon under extreme conditions of high pressures and temperatures. However, the fidelity of these simulations depends heavily on the accuracy of classical interatomic potentials governing the dynamics of many-atom systems. Here, this study critically assesses several popular empirical potentials for carbon, as well as machine learning interatomic potentials (MLIPs), in their ability to simulate a range of physical properties at high pressures and temperatures, including the diamond equation of state, its melting line, shock Hugoniot, uniaxial compressions, and the structure of liquid carbon. Empirical potentials fail to accurately predict the behavior of carbon under high pressure–temperature conditions. In contrast, MLIPs demonstrate quantum accuracy, with Spectral Neighbor Analysis Potential (SNAP) and atomic cluster expansion (ACE) being the most accurate in reproducing the density functional theory results. ACE displays remarkable transferability despite not being specifically trained for extreme conditions. Furthermore, ACE and SNAP exhibit superior computational performance on graphics processing unit-based systems in billion atom MD simulations, with SNAP emerging as the fastest. In addition to offering practical guidance in selecting an interatomic potential with a fine balance of accuracy, transferability, and computational efficiency, this work also highlights transformative opportunities for groundbreaking scientific discoveries facilitated by quantum-accurate MD simulations with MLIPs on emerging exascale supercomputers.

36 MATERIALS SCIENCE↗
DOE OSTI2014

RELAXATION PROCESSES IN SOLAR WIND TURBULENCE

Based on global conservation principles, magnetohydrodynamic (MHD) relaxation theory predicts the existence of several equilibria, such as the Taylor state or global dynamic alignment. These states are generally viewed as very long-time and large-scale equilibria, which emerge only after the termination of the turbulent cascade. As suggested by hydrodynamics and by recent MHD numerical simulations, relaxation processes can occur during the turbulent cascade that will manifest themselves as local patches of equilibrium-like configurations. Using multi-spacecraft analysis techniques in conjunction with Cluster data, we compute the current density and flow vorticity and for the first time demonstrate that these localized relaxation events are observed in the solar wind. Such events have important consequences for the statistics of plasma turbulence.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Artificial intelligence-empowered cellular morphometric risk score improves prognostic stratification of cutaneous squamous cell carcinoma

Abstract Background Risk stratification of cutaneous squamous cell carcinoma (cSCC) is essential for managing patients. Objectives To determine if artificial intelligence and machine learning might help to stratify patients with cSCC by risk using more than solely clinical and histopathological factors. Methods We retrieved a retrospective cohort of 104 patients whose cSCCs had been excised with clear margins. Clinical and histopathological risk factors were evaluated. Haematoxylin and eosin-stained slides were scanned and analysed by an algorithm based on the stacked predictive sparse decomposition technique. Cellular morphometric biomarkers (CMBs) were identified via machine learning and used to derive a cellular morphometric risk score (CMRS) that classified cSCCs into clusters of differential prognoses. Concordance analysis, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and accuracy were calculated and compared with results obtained with the Brigham and Women’s Hospital (BWH) staging system. The performance of the combination of the BWH staging system and the CMBs was also analysed. Results There were no differences among the CMRS groups in terms of clinical and histopathological risk factors and T-stage assignment, but there were significant differences in prognosis. Combining the CMRS with BWH staging systems increased distinctiveness and improved prognostic performance. C-indices were 0.91 local recurrence and 0.91 for nodal metastasis when combining the two approaches. The NPV was 94.41% and 96.00%, the PPV was 36.36% and 41.67%, and accuracy reached 86.75% and 89.16%, respectively, with the combined approach. Conclusions CMRS is helpful for cSCC risk stratification beyond classic clinical and histopathological risk features. Combining the information from the CMRS and the BWH staging system offers outstanding prognostic performance for patients with high-risk cSCC.

Pérez-Baena, Manuel J.↗
DOE OSTI2023

Non-local contribution from small scales in galaxy–galaxy lensing: comparison of mitigation schemes

ABSTRACT Recent cosmological analyses with large-scale structure and weak lensing measurements, usually referred to as 3 × 2pt, had to discard a lot of signal to noise from small scales due to our inability to accurately model non-linearities and baryonic effects. Galaxy–galaxy lensing, or the position–shear correlation between lens and source galaxies, is one of the three two-point correlation functions that are included in such analyses, usually estimated with the mean tangential shear. However, tangential shear measurements at a given angular scale θ or physical scale R carry information from all scales below that, forcing the scale cuts applied in real data to be significantly larger than the scale at which theoretical uncertainties become problematic. Recently, there have been a few independent efforts that aim to mitigate the non-locality of the galaxy–galaxy lensing signal. Here, we perform a comparison of the different methods, including the Y-transformation, the point-mass marginalization methodology, and the annular differential surface density statistic. We do the comparison at the cosmological constraints level in a combined galaxy clustering and galaxy–galaxy lensing analysis. We find that all the estimators yield equivalent cosmological results assuming a simulated Rubin Observatory Legacy Survey of Space and Time (LSST) Year 1 like set-up and also when applied to DES Y3 data. With the LSST Y1 set-up, we find that the mitigation schemes yield ∼1.3 times more constraining S8 results than applying larger scale cuts without using any mitigation scheme.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Gas density fluctuations in the Perseus Cluster: clumping factor and velocity power spectrum

X-ray surface brightness fluctuations in the core of the Perseus Cluster are analysed, using deep observations with the Chandra observatory. The amplitude of gas density fluctuations on different scales is measured in a set of radial annuli. It varies from 7 to 12 per cent on scales of ~10–30 kpc within radii of 30–220 kpc from the cluster centre. Using a statistical linear relation between the observed amplitude of density fluctuations and predicted velocity, the characteristic velocity of gas motions on each scale is calculated. The typical amplitudes of the velocity outside the central 30 kpc region are 90–140 km s -1 on ~20–30 kpc scales and 70–100 km s -1 on smaller scales ~7–10 kpc. The velocity power spectrum (PS) is consistent with cascade of turbulence and its slope is in a broad agreement with the slope for canonical Kolmogorov turbulence. The gas clumping factor estimated from the PS of the density fluctuations is lower than 7–8 per cent for radii ~30–220 kpc from the centre, leading to a density bias of less than 3–4 per cent in the cluster core. Uncertainties of the analysis are examined and discussed. Future measurements of the gas velocities with the Astro-H, Athena and Smart-X observatories will directly measure the gas density–velocity perturbation relation and further reduce systematic uncertainties in this analysis.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

In‐depth comparative analysis of Illumina ® MiSeq run metrics: Development of a wet‐lab quality assessment tool

Abstract Whole genome sequencing of bacterial isolates has become a daily task in many laboratories, generating incredible amounts of data. However, data acquisition is not an end in itself; the goal is to acquire high‐quality data useful for understanding genetic relationships. Having a method that could rapidly determine which of the many available run metrics are the most important indicators of overall run quality and having a way to monitor these during a given sequencing run would be extremely helpful to this effect. Therefore, we compared various run metrics across 486 MiSeq runs, from five different machines. By performing a statistical analysis using principal components analysis and a K ‐means clustering algorithm of the metrics, we were able to validate metric comparisons among instruments, allowing for the development of a predictive algorithm, which permits one to observe whether a given MiSeq run has performed adequately. This algorithm is available in an Excel spreadsheet: that is, MiSeq Instrument & Run (In‐Run) Forecast. Our tool can help verify that the quantity/quality of the generated sequencing data consistently meets or exceeds recommended manufacturer expectations. Patterns of deviation from those expectations can be used to assess potential run problems and plan preventative maintenance, which can save valuable time and funding resources.

Kastanis, George John↗
DOE OSTI2014

Development of an Alfalfa SNP Array and Its Use to Evaluate Patterns of Population Structure and Linkage Disequilibrium

A large set of genome-wide markers and a high-throughput genotyping platform can facilitate the genetic dissection of complex traits and accelerate molecular breeding applications. Previously, we identified about 0.9 million SNP markers by sequencing transcriptomes of 27 diverse alfalfa genotypes. From this SNP set, we developed an Illumina Infinium array containing 9,277 SNPs. Using this array, we genotyped 280 diverse alfalfa genotypes and several genotypes from related species. About 81% (7,476) of the SNPs met the criteria for quality control and showed polymorphisms. The alfalfa SNP array also showed a high level of transferability for several closely related Medicago species. Principal component analysis and model-based clustering showed clear population structure corresponding to subspecies and ploidy levels. Within cultivated tetraploid alfalfa, genotypes from dormant and nondormant cultivars were largely assigned to different clusters; genotypes from semidormant cultivars were split between the groups. The extent of linkage disequilibrium (LD) across all genotypes rapidly decayed to 26 Kbp at r 2 = 0.2, but the rate varied across ploidy levels and subspecies. A high level of consistency in LD was found between and within the two subpopulations of cultivated dormant and nondormant alfalfa suggesting that genome-wide association studies (GWAS) and genomic selection (GS) could be conducted using alfalfa genotypes from throughout the fall dormancy spectrum. However, the relatively low LD levels would require a large number of markers to fully saturate the genome.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Facial Named Entity Recognition by Attention-Based Graph Convolutional Neural Network

In the realm of facial recognition and analysis, the ability to accurately cluster large datasets of facial images stands as a cornerstone for various applications, ranging from security surveillance to user biometric identification. This project evolves a novel approach to facial data clustering by embedding facial images into a high-dimensional vector space using an advanced embedding model trained on separate data and assumes a graph-like structure on the high-dimensional vectors. We find our method works significantly better than common shallow methods.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Bacterial Biomarkers of Marcellus Shale Activity in Pennsylvania

Unconventional oil and gas (UOG) extraction, also known as hydraulic fracturing, is becoming more prevalent with the increasing use and demand for natural gas; however, the full extent of its environmental impacts is still unknown. Here we measured physicochemical properties and bacterial community composition of sediment samples taken from twenty-eight streams within the Marcellus shale formation in northeastern Pennsylvania differentially impacted by hydraulic fracturing activities. Fourteen of the streams were classified as UOG+, and thirteen were classified as UOG- based on the presence of UOG extraction in their respective watersheds. One stream was located in a watershed that previously had UOG extraction activities but was recently abandoned. We utilized high-throughput sequencing of the 16S rRNA gene to infer differences in sediment aquatic bacterial community structure between UOG+ and UOG- streams, as well as correlate bacterial community structure to physicochemical water parameters. Although overall alpha and beta diversity differences were not observed, there were a plethora of significantly enriched operational taxonomic units (OTUs) within UOG+ and UOG- samples. Our biomarker analysis revealed many of the bacterial taxa enriched in UOG+ streams can live in saline conditions, such as Rubrobacteraceae. In addition, several bacterial taxa capable of hydrocarbon degradation were also enriched in UOG+ samples, including Oceanospirillaceae. Methanotrophic taxa, such as Methylococcales, were significantly enriched as well. Several taxa that were identified as enriched in these samples were enriched in samples taken from different streams in 2014; moreover, partial least squares discriminant analysis (PLS-DA) revealed clustering between streams from the different studies based on the presence of hydraulic fracturing along the second axis. This study revealed significant differences between bacterial assemblages within stream sediments of UOG+ and UOG- streams and identified several potential biomarkers for evaluating and monitoring the response of autochthonous bacterial communities to potential hydraulic fracturing impacts.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Description of Pegethrix niliensis sp. nov., a Novel Cyanobacterium from the Nile River Basin, Egypt: A Polyphasic Analysis and Comparative Study of Related Genera in the Oculatellales Order

In this paper, we examine the filamentous cyanobacterial strain NILCB16 and describe it as a new species within the genus Pegethrix. The original population was sampled from a mat growing in an irrigation canal in the Nile River, Egypt. Initially classified under Plectonema or Planktolyngbya, the strain is a potential producer of the toxins microcystin and β-N-Methylamino-L-Alanine (BMAA). Additionally, we reviewed the taxonomic relationships between the Oculatellales genera. To describe the new species, we conducted a polyphasic study, encompassing 16S rRNA gene phylogenetic analyses performed using both Maximum Likelihood and Bayesian methods, sequence identity (p-distance) analysis, 16S-23S ITS secondary structures, and morphological and habitat comparisons. The phylogenetic analysis revealed that strain NILCB16 clustered within the Pegethrix clade with strong phylogenetic support, but in a distinct position from other species in the genus. The strain shared a maximum 16S rRNA gene identity of 97.3% with P. qiandaoensis and 96.1% with the type species, P. bostrychoides. Morphologically, NILCB16 can be differentiated from other species in the genus by its lack of false branching. Our phylogenetic analyses also show that Pegethrix, Cartusia, Elainella, and Maricoleus are clustered with strong phylogenetic support. They exhibit high 16S rRNA gene identity and are morphologically indistinguishable, suggesting they could potentially be merged into a single genus in the future.

Hentschke, Guilherme Scotta (ORCID:000000034396024↗
DOE OSTI2017

High-resolution Spectroscopic Abundances of Red Giant Branch Stars in NGC 6681

We obtain high-resolution spectra of nine red giant branch stars in NGC 6681 and perform the first detailed abundance analysis of stars in this cluster. We confirm cluster membership for these stars based on consistent radial velocities of 214.5 ± 3.7 km s{sup −1} and find a mean [Fe/H] = −1.63 ± 0.07 dex and [ α /Fe] = 0.42 ± 0.11 dex. Additionally, we confirm the existence of a Na–O anti-correlation in NGC 6681 and identify two populations of stars with unique abundance trends. With the use of HST photometry from Sarajedini et al. and Piotto et al. we are able to identify these two populations as discrete sequences in the cluster CMD. Although we cannot confirm the nature of the polluter stars responsible for the abundance differences in these populations, these results do help put constraints on possible polluter candidates.

79 ASTRONOMY AND ASTROPHYSICS↗