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Results for “combinatorial”
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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Improved Combinatorial Assembly and Barcode Sequencing for Gene-Sized DNA Constructs
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Combinatorial impedance spectroscopy with Bayesian analysis for triple ionic-electronic conducting perovskites
We construct an empirical map of oxide electrode materials performance relevant to intermediate-temperature electrochemical devices.
Combinatorial Biosynthesis of Sulfated Benzenediol Lactones with a Phenolic Sulfotransferase from Fusarium graminearum PH-1
Total biosynthesis or whole-cell biocatalytic production of sulfated small molecules relies on the discovery and implementation of appropriate sulfotransferase enzymes. Although fungi are prominent biocatalysts and have been used to sulfate drug-like phenolics, no gene encoding a sulfotransferase enzyme has been functionally characterized from these organisms. Here, we identify a phenolic sulfotransferase, FgSULT1, by genome mining from the plant-pathogenic fungus Fusarium graminearum PH-1. We expressed FgSULT1 in a Saccharomyces cerevisiae chassis to modify a broad range of benzenediol lactones and their nonmacrocyclic congeners, together with an anthraquinone, with the resulting unnatural natural product (uNP) sulfates displaying increased solubility. FgSULT1 shares low similarity with known animal and plant sulfotransferases. Instead, it forms a sulfotransferase family with putative bacterial and fungal enzymes for phase II detoxification of xenobiotics and allelochemicals. Among fungi, putative FgSULT1 homologues are encoded in the genomes of Fusarium spp. and a few other genera in nonsyntenic regions, some of which may be related to catabolic sulfur recycling. Computational structure modeling combined with site-directed mutagenesis revealed that FgSULT1 retains the key catalytic residues and the typical fold of characterized animal and plant sulfotransferases. Our work opens the way for the discovery of hitherto unknown fungal sulfotransferases and provides a synthetic biological and enzymatic platform that can be adapted to produce bioactive sulfates, together with sulfate ester standards and probes for masked mycotoxins, precarcinogenic toxins, and xenobiotics.
Decoding Early Candidacy of High Entropy Alloys for Nuclear Application using the Advanced Test Reactor through Predictive Methods and Combinatorial Testing
High Entropy Alloys (HEAs) are identified candidates for nuclear applications owing to their superb mechanical and thermal properties. In line with evaluating their candidacy, a challenge remains in their validity as structural replacements for extreme environments. Each compositional graded specimen consists up to four different compositions spanning the fueled zone for non-prototypical neutron irradiation testing in the Advanced Test Reactor (ATR) at Idaho National Laboratory (INL). We have fabricated a set of four compositionally graded specimens using spark plasma sintering that include at least five of the following elements: Cr, C, Al, Zr, Mo, Nb, Ta, V, Ti, W, and Fe. In time for this meeting the role of temperature expected to play a role in-pile cladding chemical interactions (FCCI), mechanical interactions (FCMI), irradiation damage, creep, and resistance will be reported. The irradiated portion has a scheduled irradiation date in April 2020 and with post irradiation examination (PIE) to follow.
Combinatorial Algorithms in Scientific Computing
We provide the final report for this grant, detailing the publications, software produced, students trained who have joined the DOE workforce, and the impact our work has had on computational mathematics and related disciplines.
The Combinatorial Approach to Testing and Characterization of Irradiated Fuels and Reactor Structural Materials
Testing and characterization of irradiated fuels and reactor structural materials
Are better combinations of DERs more profitable?: Combinatorial optimization for aggregation of DERs in wholesale electricity markets
Recently, regulatory changes in various countries have enabled the participation of small-scale distributed energy resources (DERs) aggregated in virtual power plants (VPPs) in wholesale electricity markets. The inherent uncertainty and variability of resources comprising VPPs can lead to imbalances between forecasted and metered outputs, potentially resulting in the deficient settlement of generation under imbalance settlement rules. To address this challenge, it is essential to manage variability in the planning phase and uncertainty in the operation phase. Most current research focuses on managing forecasting errors in the operational phase, with insufficient attention given to the planning phase. Here, to bridge this gap, this paper proposes an optimal combination strategy for DERs to maximize the market participation revenue of VPPs by proactively managing variability in the planning phase. To estimate the expected revenue, we conducted analyses for homogeneous and heterogeneous DERs using Monte Carlo simulations and genetic algorithms. Remarkably, the proposed method demonstrated approximately 8 % higher revenue compared to the neighboring group case when considering diversity in DER set configuration with equal proportions of photovoltaics and wind.
Mechanistic insights into the digestion of complex dietary fibre by the rumen microbiota using combinatorial high-resolution glycomics and transcriptomic analyses
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Enhanced Bulk Transport in Copper Vanadate Photoanodes Identified by Combinatorial Alloying
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