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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Comprehensive Quantitative Analysis of Ovarian and Breast Cancer Tumor Peptidomes

Aberrant degradation of proteins is associated with many pathological states, including cancers. Mass spectrometric analysis of tumor peptidomes, the intracellular and intercellular products of protein degradation, has the potential to provide biological insights on proteolytic processing in cancer. However, attempts to use the information on these smaller protein degradation products from tumors for biomarker discovery and cancer biology studies have been fairly limited to date, largely due to the lack of effective approaches for robust peptidomics identification and quantification, and the prevalence of confounding factors and biases associated with sample handling and processing. Herein, we have developed an effective and robust analytical platform for comprehensive analyses of tissue peptidomes, which is suitable for high throughput quantitative studies. The reproducibility and coverage of the platform, as well as the suitability of clinical ovarian tumor and patient-derived breast tumor xenograft samples with post-excision delay of up to 60 min before freezing for peptidomics analysis, have been demonstrated. Moreover, our data also show that the peptidomics profiles can effectively separate breast cancer subtypes, reflecting tumor-associated protease activities. Peptidomics complements results obtainable from conventional bottom-up proteomics, and provides insights not readily obtainable from such approaches.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2019

Comprehensive Evaluation and Application of GIS Insulation Condition Part 1: Selection and Optimization of Insulation Condition Comprehensive Evaluation Index Based on Multi-Source Information Fusion

How to select and optimize the evaluation indicators from many characteristic information to characterize the internal insulation condition of GIS equipment, and establish a scientific technical and economic evaluation model of insulation condition is a huge challenge needs to be addressed urgently. Motived by this purpose, this study simulates the deterioration process of four typical insulation defects in GIS to obtain the information of UHF, ultrasound, and SF 6 decomposition components excited by different degradation stages of each insulating defect simultaneously. Moreover, the operating environment conditions, running time, overhaul times, and the residual value of equipment are taken into account. Using the improved minimum-redundancy-maximum-relevance (mRMR) criterion and genetic algorithm, a comprehensive evaluation index system including the 23 evaluation indicators in three categories is established, which covers the PD hazard, SF 6 insulation performance, equipment running time and environment, and residual value. The research lays a foundation for the later construction and application of multi-source information fusion evaluation model of GIS equipment insulation condition considering economic value.

42 ENGINEERING↗
DOE OSTI2015

A Comprehensive Study of Formic Acid Oxidation on Palladium Nanocrystals with Different Types of Facets and Twin Defects

Palladium has been recognized as the best anodic, monometallic electrocatalyst for the formic acid oxidation (FAO) reaction in a direct formic acid fuel cell. Here we report a systematic study of FAO on a variety of Pd nanocrystals, including cubes, right bipyramids, octahedra, tetrahedra, decahedra, and icosahedra. These nanocrystals were synthesized with approximately the same size, but different types of facets and twin defects on their surfaces. Our measurements indicate that the Pd nanocrystals enclosed by {1 0 0} facets have higher specific activities than those enclosed by {1 1 1} facets, in agreement with prior observations for Pd single-crystal substrates. If comparing nanocrystals predominantly enclosed by a specific type of facet, {1 0 0} or {1 1 1}, those with twin defects displayed greatly enhanced FAO activities compared to their single-crystal counterparts. To rationalize these experimental results, we performed periodic, self-consistent DFT calculations on model single-crystal substrates of Pd, representing the active sites present in the nanocrystals used in the experiments. The calculation results suggest that the enhancement of FAO activity on defect regions, represented by Pd(2 1 1) sites, compared to the activity of both Pd(1 0 0) and Pd(1 1 1) surfaces, could be attributed to an increased flux through the HCOO-mediated pathway rather than the COOH-mediated pathway on Pd(2 1 1). Since COOH has been identified as a precursor to CO, a site-poisoning species, a lower coverage of CO at the defect regions will lead to a higher activity for the corresponding nanocrystal catalysts, containing those defect regions.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2015

The creation of a comprehensive metocean data set for offshore wind turbine simulations: Comprehensive metocean data set

A database of meteorological and ocean conditions is presented for use in offshore wind energy research and design. The original data are from 23 ocean sites around the USA and were obtained from the National Data Buoy Center run by the National Oceanic and Atmospheric Administration. The data are presented in a processed form that includes the variables of interest for offshore wind energy design: wind speed, significant wave height, wave peak-spectral period, wind direction and wave direction. For each site, a binning process is conducted to create conditional probability functions for each of these variables. The sites are then grouped according to geographic location and combined to create three representative sites, including a West Coast site, an East Coast site and a Gulf of Mexico site. Both the processed data and the probability distribution parameters for the individual and representative sites are being hosted on a publicly available domain by the National Renewable Energy Laboratory, with the intent of providing a standard basis of comparison for meteorological and ocean conditions for offshore wind energy research worldwide.

17 WIND ENERGY↗
DOE OSTI2015

Comprehensive Structural and Biochemical Analysis of the Terminal Myxalamid Reductase Domain for the Engineered Production of Primary Alcohols

Here, the terminal reductase (R) domain from the non-ribosomal peptide synthetase (NRPS) module MxaA in Stigmatella aurantiaca Sga15 catalyzes a non-processive four-electron reduction to produce the myxalamide family of secondary metabolites. Despite widespread use in nature, a lack of structural and mechanistic information concerning reductive release from polyketide synthase (PKS) and NRPS assembly lines principally limits our ability to redesign R domains with altered or improved activity. We report crystal structures for MxaA R, both in the absence and, for the first time, in the presence of the NADPH cofactor. Molecular dynamics simulations were employed to provide a deeper understanding of this domain and further identify residues critical for structural integrity, substrate binding, and catalysis. Aggregate computational and structural findings provided a basis for mechanistic investigations and, in the process, delivered a rationally altered variant with improved activity toward highly reduced substrates.

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

Method development for comprehensive extraction and analysis of marine toxins: Liquid-liquid extraction and tandem liquid chromatography separations coupled to electrospray tandem mass spectrometry

Toxins from biological sources are recognized as potential chemical weapon threats, with saxitoxin and ricin listed by the chemical weapons convention (CWC) as schedule one agents (CWC reference). These two toxins represent a metabolite (saxitoxin) and protein (ricin) from algal and plant sources, respectively. An array of toxins have been listed as "select agents" by the Health and Human Services (HHS) select agent program, including ricin, abrin, saxitoxin, tetrodotoxin, specific paralytic alpha conotoxin peptides, T-2 toxin, diacetoxyscirpenols, botulinum toxins, and staphylococcal enterotoxins [1]. The quantities of these toxins dictate whether they are considered select agents with federal oversight of their storage and use. While this list captures some of the naturally occurring toxins that may pose a threat to the public, there are a number of other naturally occurring toxins that may also be a concern.

biodetection↗
DOE OSTI2018

Comprehensive Magnetic Study of Nanostructured Mesoporous Manganese Oxide Materials and Implications for Catalytic Behavior

Magnetic behavior of nanostructured mesoporous manganese oxide materials, designated UCT-1 and UCT-18, were studied using a combination of superconducting quantum interference device (SQUID) magnetometry and 55 Mn zero-field spin–echo nuclear magnetic resonance (NMR). Curie–Weiss fits to the magnetic susceptibility for the UCT-1 and UCT-18 samples calcined at 550 °C yielded paramagnetic moment values consistent with spin-only Mn 3+ ions in the α-Mn 2 O 3 phase ( S = 2, 4.90 μ B ). However, the magnetization and NMR results reported here clearly identify a small amount of the Mn 3 O 4 second phase (ferrimagnetic with T C ≈ 43 K) that does not appear in X-ray diffraction (XRD). We report the study resulted in the observation of fascinating magnetic behavior: (1) exchange bias, which occurs in cases where a ferromagnetic (or ferrimagnetic) phase forms a boundary with an antiferromagnetic phase and (2) a magnetic contribution attributed to uncompensated spins on the surfaces of the α-Mn 2 O 3 nanoparticles. The presence of Mn 3 O 4 and the interplay of Mn 3+ and Mn 2+ impact the catalytic properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

DeePKS: A Comprehensive Data-Driven Approach toward Chemically Accurate Density Functional Theory

We propose a general machine learning-based framework for building an accurate and widely applicable energy functional within the framework of generalized Kohn–Sham density functional theory. To this end, we develop a way of training self-consistent models that are capable of taking large datasets from different systems and different kinds of labels. Here, we demonstrate that the functional that results from this training procedure gives chemically accurate predictions on energy, force, dipole, and electron density for a large class of molecules. It can be continuously improved when more and more data are available.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗