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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 1,135 records · Page 63
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Identification of a CARM1 Inhibitor with Potent In Vitro and In Vivo Activity in Preclinical Models of Multiple Myeloma

CARM1 is an arginine methyltransferase with diverse histone and non-histone substrates implicated in the regulation of cellular processes including transcriptional co-activation and RNA processing. CARM1 overexpression has been reported in multiple cancer types and has been shown to modulate oncogenic pathways in in vitro studies. Detailed understanding of the mechanism of action of CARM1 in oncogenesis has been limited by a lack of selective tool compounds, particularly for in vivo studies. We describe the identification and characterization of, to our knowledge, the first potent and selective inhibitor of CARM1 that exhibits anti-proliferative effects both in vitro and in vivo and, to our knowledge, the first demonstration of a role for CARM1 in multiple myeloma (MM). EZM2302 (GSK3359088) is an inhibitor of CARM1 enzymatic activity in biochemical assays (IC 50 = 6 nM) with broad selectivity against other histone methyltransferases. Treatment of MM cell lines with EZM2302 leads to inhibition of PABP1 and SMB methylation and cell stasis with IC 50 values in the nanomolar range. Oral dosing of EZM2302 demonstrates dose-dependent in vivo CARM1 inhibition and anti-tumor activity in an MM xenograft model. As a result, EZM2302 is a validated chemical probe suitable for further understanding the biological role CARM1 plays in cancer and other diseases.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Identification of dominant gas transport frequencies during barometric pumping of fractured rock

Abstract We demonstrate that although barometric pressures are complicated signals comprised of numerous frequencies, it is a subset of these frequencies that drive the overwhelming majority of gas transport in fractured rock. Using an inverse numerical analysis, we demonstrate that a single barometric component with seasonally modulated amplitude approximates gas transport due to a measured barometric signal. If past barometric tendencies are expected to continue at a location, the identification of this frequency can facilitate accurate long term predictions of barometrically induced gas transport negating the need to consider stochastic realizations of future barometric variations. Additionally, we perform an analytical analysis that indicates that there is a set of barometric frequencies, consistent with the inverse numerical analysis, with high production efficiency. Based on the corroborating inverse numerical and analytical analyses, we conclude that there is a set of dominant gas transport frequencies in barometric records.

58 GEOSCIENCES↗
DOE OSTI2019

Identification of an AgS2 Complex on Ag(110)

Adsorbed sulfur has been investigated on the Ag(110) surface at two different coverages, 0.02 and 0.25 monolayers. At the lower coverage, only sulfur adatoms are present. At the higher coverage, there are additional bright features which we identify as linear, independent AgS 2 complexes. Here, this identification is based upon density functional theory (DFT) and its comparison with experimental observations including bias dependence and separation between complexes. DFT also predicts the absence of AgS 2 complexes at low coverage, and the development of AgS 2 complexes around a coverage of 0.25 monolayers of sulfur, as is experimentally observed. To our knowledge, this is the first example of an isolated linear sulfur-metal-sulfur complex.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Structural modification of fentanyls for their retrospective identification by gas chromatographic analysis using chloroformate chemistry

Abstract The one-step breakdown and derivatization of a panel of nine fentanyls to yield uniquely tagged products that can be detected by Electron Ionization Gas Chromatography-Mass Spectrometry (EI-GC-MS) is presented. The method involves the treatment of the synthetic opioids with 2,2,2-trichloroethoxycarbonyl chloride (TrocCl) at 60 °C for 3 h in dichloromethane and furnishes two products from one fentanyl molecule that can be used to retrospectively identify the original opioid. Parameters that were studied and fully optimized for the method included temperature, solvent, nature of scavenging base and reaction time. One of the two resulting products from the reaction bears the trichloroethoxycarbonyl (Troc) tag attached to the norfentanyl portion of the original opioid and greatly aids in the opioid detection and identification process. The methodology has been applied to the chemical modification of a panel of nine fentanyls and in all cases the molecular ion peak for the Troc-norfentanyl product bearing the distinctive trichloroethyl isotopic signature can be clearly observed. The method’s LLOD was determined to be 10 ng/mL while its LLOQ was found to be 20 ng/mL. This methodology represents the first application of chloroformates in the chemical modification of this class of synthetic opioids that are notoriously inert to common derivatization strategies available for GC–MS analysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Identification of the active complex for CO oxidation over single-atom Ir-on-MgAl2O4 catalysts

Supported single atoms provide the best utilization of noble metals and provide an opportunity to design new heterogeneous catalysts. However, identification of the active single atoms structure is required for understanding the reaction mechanism and guiding catalyst design. We used in-situ infrared spectroscopy, in-operando x-ray adsorption spectroscopy and quantum chemical calculations to show that Ir(CO)/MgAl2O4 is the active single atom complex for low temperature CO oxidation and Ir(CO)(O) is the most stable intermediate. In contrast to poisoning of nanoparticles by CO, the formation of Ir(CO) on single atoms results in a different reaction mechanism and high activity for low temperature CO oxidation. This is due to the ability of single atoms to coordinate with multiple ligands, where CO, in Ir(CO)(O), acts as a facilitator by lowering the reaction barrier between gas phase CO and adsorbed O (Eley-Rideal mechanism).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Unambiguous identification and discovery of bacterial siderophores by direct injection 21 Tesla Fourier transform ion cyclotron resonance mass spectrometry

Under iron-limiting conditions, bacteria produce low molecular mass Fe(III) binding molecules known as siderophores to sequester the Fe(III), along with other elements, increasing their bioavailibility. Siderophores are thought to influence iron cycling and biogeochemistry in both marine and terrestrial ecosystems and hence the need for rapid, confident characterization of these compounds has increased. In this study, the type of siderophores produced by two marine bacterial species, Synechococcus sp. PCC 7002 and Vibrio cyclitrophicus 1F53, were characterized using a newly developed 21T Fourier Transform Ion Cyclotron Resonance Mass Spectrometer (FTICR MS) with direct injection electrospray ionization. This technique allowed for the rapid detection of synechobactins from Synechococcus sp. PCC 7002 as well as amphibactins from Vibrio cyclitrophicus 1F53 based on high mass accuracy and resolution allowing for observation of specific Fe isotopic peaks and fine isotopic structure enables highly confident identification of these sideropohores. When combined with molecular network analysis two new amphibactins were discovered and verified by tandem MS. These results show that high-field FTICR MS is a powerful technique that will greatly improve the ability to rapidly identify and discover metal binding species in the environment.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2019

Identification of the Criegee intermediate reaction network in ethylene ozonolysis: Impact on energy conversion strategies and atmospheric chemistry

The reaction network of the simplest Criegee Intermediate (CI) CH2OO has been studied experimentally during the ozonolysis of ethylene. The results provide valuable information about plasma- and ozone-assisted combustion processes and atmospheric aerosol formation. A network of CI reactions was identified, which can be described best by the sequential addition of CI with ethylene, water, formic acid, and other molecules containing hydroxy, aldehyde, and hydroperoxy functional groups. Species resulting from as many as four sequential CI addition reactions were observed, and these species are highly oxygenated oligomers that are known components of secondary organic aerosols in the atmosphere. Insights into these reaction pathways were obtained from a near-atmsopheric pressure jet-stirred reactor coupled to a high-resolution molecular-beam mass spectrometer. The mass spectrometer employs single-photon ionization with synchrotron-generated, tunable vacuum-ultraviolet radiation to minimize fragmentation via near-threshold ionization and to observe mass-selected photoionization efficiency (PIE) curves. Species identification is supported by comparisons of the mass-selected, experimentally observed photo-ionization thresholds with theoretical calculations for the ionization energies. A variety of multi-functional peroxide species are identified, including hydroxymethyl hydroperoxide (HOCH2OOH), hydroperoxymethyl formate (HOOCH2OCHO), methoxymethyl hydroperoxide (CH3OCH2OOH), ethoxymethyl hydroperoxide (C2H5OCH2OOH), 2-hydroxyethyl hydroperoxide (HOC2H4OOH), dihydroperoxy methane (HOOCH2OOH), and 1-hydroperoxypropan-2-one [CH3C(=O)CH2OOH]. A semi-quantitative analysis of the signal intensities as function of successive CI additions and temperature provides mechanistic insights and valuable information for future modeling work of the associated energy conversion processes and atmospheric chemistry. Furthermore this work provides further evidence that the CI is a key intermediate in the formation of oligomeric species via the formation of hydroperoxides.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Identification of the acetaldehyde oxide Criegee intermediate reaction network in the ozone-assisted low-temperature oxidation of trans -2-butene

Uni- and bi-molecular reactions involving Criegee intermediates (CIs) have been the focus of many studies due to the role these molecules play in atmospheric chemistry. The reactivity of CIs is known to strongly depend on their structure. The reaction network of the second simplest CI, acetaldehyde oxide (CH 3 CHOO), is investigated in this work in an atmospheric pressure jet-stirred reactor (JSR) during the ozonolysis of trans-2-butene to explore the kinetic pathways relevant to atmospheric chemistry and low-temperature combustion. The mole fraction profiles of reactants, intermediates, and final products are determined by means of molecular-beam mass spectrometry in conjunction with single-photon ionization employing tunable synchrotron-generated vacuum ultraviolet radiation. A network of CI reactions is identified in the temperature region below 600 K, characterized by CI addition to trans-2-butene, water, formaldehyde, formic acid, and methanol. No sequential additions of the CH 3 CHOO CI are observed, in contrast with the reactivity of the simplest CI (H 2 COO) and the earlier observation of an extensive reaction network with up to four H 2 COO sequential additions (Phys. Chem. Chem. Phys., 2019, 21, 7341–7357). Experimental photoionization efficiency scans recorded at 300 K and 425 K and ab initio threshold energy calculations lead to the identification and quantification of previously elusive intermediates, such as ketohydroperoxide and hydroperoxide species. Specifically, the C 4 H 8 + O 3 adduct is identified as a ketohydroperoxide (KHP, 3-hydroperoxybutan-2-one, CH 3 C([double bond, length as m-dash]O)CH(CH 3 )OOH), while hydroxyacetaldehyde (glycolaldehyde, HCOCH 2 OH) formation is attributed to unimolecular isomerization of the CIs. Other hydroperoxide species such as methyl hydroperoxide (CH 3 OOH), ethyl hydroperoxide (C 2 H 5 OOH), butyl hydroperoxide (OOH), hydroperoxyl acetaldehyde (HOOCH 2 CHO), hydroxyethyl hydroperoxide (CH 3 CH(OH)OOH), but-1-enyl-3-hydroperoxide, and 4-hydroxy-3-methylpentan-2-one (HOCH(CH 3 )CH(CH 3 )C([double bond, length as m-dash]O)CH 3 ) are also identified. Detection of additional oxygenated species such as methanol, ethanol, ketene, and aldehydes suggests multiple active oxidation routes. Finally, these results provide additional evidence that CIs are key intermediates of the ozone-unsaturated hydrocarbon reactions providing critical inputs for improved kinetics models.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Enhanced descriptor identification and mechanism understanding for catalytic activity using a data-driven framework: revealing the importance of interactions between elementary steps

We report accurate identification of descriptors for catalytic activities has long been essential to the in-depth understanding of catalysis and recently to set the basis for catalyst screening. However, commonly used methods suffer from low accuracy in predictability. This study reports an enhanced approach to accurately identify the descriptors from a kinetic dataset using a machine learning (ML) surrogate model. CO hydrogenation to methanol over Cu-based catalysts was taken as a case study. Our model captures not only the contribution from individual elementary steps but also the interaction between relevant steps within a reaction network, which was found to be essential for high accuracy. As a result, six effective descriptors are identified, which are accurate enough to ensure the trained gradient boosted regression (GBR) model for good prediction of the methanol turnover frequency (TOF) over metal (M)-doped Cu(111) model surfaces (M = Au, Cu, Pd, Pt, Ni). More importantly, going beyond the purely mathematical ML model, the catalytic role of each identified descriptor can be revealed by using model-agnostic interpretation tools, which enhances the insight into the promoting effect of alloying. The trained GBR model outperforms the conventional derivative-based methods in terms of both the predictability and the mechanism understanding. It opens alternative possibilities toward accurate descriptor-based rational catalyst optimization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Deep‐learning‐based power distribution network switch action identification leveraging dynamic features of distributed energy resources

This study proposes a data‐driven approach for identifying switch actions in power distribution networks. Simulated micro‐phasor measurement unit data is utilised to train a convolutional neural network (CNN) model. The trained CNN model can identify multi‐phase multi‐switch actions. Instead of working as a blackbox, the proposed approach extracts the features from the hidden layers of the trained CNN for engineering interpretation and error check. In addition, a random‐forest‐based feature ranking algorithm is proposed to identify the most important features. The proposed approach is validated on the IEEE 123‐node feeder modelled in GridLAB‐D. The CNN model is built and trained using TensorFlow. The proposed approach achieves 96.57% identification accuracy.

42 ENGINEERING↗
DOE OSTI2022

Ensemble voting-based fault classification and location identification for a distribution system with microgrids using smart meter measurements

This study presents an ensemble learning approach for fault classification and location identification in a smart distribution network containing photovoltaics (PV)-based microgrid. Lack of available data points and the unbalanced nature of the distribution system make fault handling a challenging task for utilities. The proposed method uses event-driven voltage data from smart meters to classify and locate faults. The ensemble voting classifier is composed of three base learners; random forest, k-nearest neighbours, and artificial neural network. The fault location (FL) task has been formulated as a classification problem where the fault type is classified in the first step and based on the fault type, the faulty bus is identified. The method is tested on IEEE-123 bus system modified with added PV-based microgrid along with dynamic loading conditions and varying fault resistances from 0 to 20 Ω for both unbalanced and balanced fault types. A further sensitivity analysis has been done to test the robustness of the proposed method under various noise levels and data loss errors in the smart meter measurements. The ensemble method shows improved performance and robustness compared to some previously proposed FL methods. Finally, the proposed method has been experimentally validated on a real-time simulation-based testbed using a state-of-the-art digital real-time simulator, industry standard DNP3 communication protocol and a cpu-based control centre running the FL algorithm.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2015

Planck intermediate results. XXVI. Optical identification and redshifts of Planck clusters with the RTT150 telescope

In this paper, we present the results of approximately three years of observations of Planck Sunyaev-Zeldovich (SZ) sources with the Russian-Turkish 1.5 m telescope (RTT150), as a part of the optical follow-up programme undertaken by the Planck collaboration. During this time period approximately 20% of all dark and grey clear time available at the telescope was devoted to observations of Planck objects. Some observations of distant clusters were also done at the 6 m Bolshoi Telescope Alt-azimutalnyi (BTA) of the Special Astrophysical Observatory of the Russian Academy of Sciences. In total, deep, direct images of more than one hundred fields were obtained in multiple filters. We identified 47 previously unknown galaxy clusters, 41 of which are included in the Planck catalogue of SZ sources. The redshifts of 65 Planck clusters were measured spectroscopically and 14 more were measured photometrically. We discuss the details of cluster optical identifications and redshift measurements. Finally, we also present new spectroscopic redshifts for 39 Planck clusters that were not included in the Planck SZ source catalogue and are published here for the first time.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

The eROSITA Final Equatorial-Depth Survey (eFEDS): Identification and characterization of the counterparts to point-like sources

In November 2019, eROSITA on board of the Spektrum-Roentgen-Gamma (SRG) observatory started to map the entire sky in X-rays. After the four-year survey program, it will reach a flux limit that is about 25 times deeper than ROSAT. During the SRG performance verification phase, eROSITA observed a contiguous 140 deg 2 area of the sky down to the final depth of the eROSITA all-sky survey (eROSITA Final Equatorial-Depth Survey; eFEDS), with the goal of obtaining a census of the X-ray emitting populations (stars, compact objects, galaxies, clusters of galaxies, and active galactic nuclei) that will be discovered over the entire sky. This paper presents the identification of the counterparts to the point sources detected in eFEDS in the main and hard samples and their multi-wavelength properties, including redshift. To identify the counterparts, we combined the results from two independent methods (NWAY and ASTROMATCH), trained on the multi-wavelength properties of a sample of 23k XMM-Newton sources detected in the DESI Legacy Imaging Survey DR8. Then spectroscopic redshifts and photometry from ancillary surveys were collated to compute photometric redshifts. Of the eFEDS sources, 24 774 of 27 369 have reliable counterparts (90.5%) in the main sample and 231 of 246 sources (93.9%) have counterparts in the hard sample, including 2514 (3) sources for which a second counterpart is equally likely. By means of reliable spectra, Gaia parallaxes, and/or multi-wavelength properties, we have classified the reliable counterparts in both samples into Galactic (2695) and extragalactic sources (22 079). For about 340 of the extragalactic sources, we cannot rule out the possibility that they are unresolved clusters or belong to clusters. Inspection of the distributions of the X-ray sources in various optical/IR colour-magnitude spaces reveal a rich variety of diverse classes of objects. The photometric redshifts are most reliable within the KiDS/VIKING area, where deep near-infrared data are also available. This paper accompanies the eROSITA early data release of all the observations performed during the performance and verification phase. Together with the catalogues of primary and secondary counterparts to the main and hard samples of the eFEDS survey, this paper releases their multi-wavelength properties and redshifts.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Merger identification through photometric bands, colours, and their errors

Aims. We present the application of a fully connected neural network (NN) for galaxy merger identification using exclusively photometric information. Our purpose is not only to test the method’s efficiency, but also to understand what merger properties the NN can learn and what their physical interpretation is. Methods. We created a class-balanced training dataset of 5860 galaxies split into mergers and non-mergers. The galaxy observations came from SDSS DR6 and were visually identified in Galaxy Zoo. The 2930 mergers were selected from known SDSS mergers and the respective non-mergers were the closest match in both redshift and r magnitude. The NN architecture was built by testing a different number of layers with different sizes and variations of the dropout rate. We compared input spaces constructed using: the five SDSS filters: u, g, r, i, and z; combinations of bands, colours, and their errors; six magnitude types; and variations of input normalization. Results. We find that the fibre magnitude errors contribute the most to the training accuracy. Studying the parameters from which they are calculated, we show that the input space built from the sky error background in the five SDSS bands alone leads to 92.64 ± 0.15% training accuracy. We also find that the input normalization, that is to say, how the data are presented to the NN, has a significant effect on the training performance. Conclusions. We conclude that, from all the SDSS photometric information, the sky error background is the most sensitive to merging processes. This finding is supported by an analysis of its five-band feature space by means of data visualization. Moreover, studying the plane of the g and r sky error bands shows that a decision boundary line is enough to achieve an accuracy of 91.59%.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

The SRG/eROSITA All-Sky Survey: Optical identification and properties of galaxy clusters and groups in the western galactic hemisphere

The first SRG/eROSITA All-Sky Survey (eRASS1) provides the largest intracluster medium-selected galaxy cluster and group catalog covering the western Galactic hemisphere. Compared to samples selected purely on X-ray extent, the sample purity can be enhanced by identifying cluster candidates using optical and near-infrared data from the DESI Legacy Imaging Surveys. Using the red-sequence-based cluster findereROMaPPer, we measured individual photometric properties (redshiftz λ , richnessλ, optical center, and BCG position) for 12000 eRASS1 clusters over a sky area of 13 116 deg 2 , augmented by 247 cases identified by matching the candidates with known clusters from the literature. The median redshift of the identified eRASS1 sample isz= 0.31, with 10% of the clusters atz> 0.72. The photometric redshifts have an accuracy ofδz/(1 +z) ≲ 0.005 for 0.05 specand velocity dispersionσ) were measured a posteriori for a subsample of 3210 and 1499 eRASS1 clusters, respectively, using an extensive compilation of spectroscopic redshifts of galaxies from the literature. We infer that the primary eRASS1 sample has a purity of 86% and optical completeness >95% forz> 0.05. For these and further quality assessments of the eRASS1 identified catalog, we applied our identification method to a collection of galaxy cluster catalogs in the literature, as well as blindly on the full Legacy Surveys covering 24069 deg 2 . Using a combination of these cluster samples, we investigated the velocity dispersion-richness relation, finding that it scales with richness as log(λ norm ) = 2.401 × log(σ) − 5.074 with an intrinsic scatter ofδ in = 0.10 ± 0.01 dex. The primary product of our work is the identified eRASS1 cluster catalog with high purity and a well-defined X-ray selection process, opening the path for precise cosmological analyses presented in companion papers.

Astronomy & Astrophysics↗