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Results for “BaSe”
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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The role of interface boundary conditions and sampling strategies for Schwarz-based coupling of projection-based reduced order models
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Comparative characteristics of coal-based and graphite-based reduced graphene oxide materials
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Role of polarization evolution in the hysteresis effect of Pb-based antiferroelecrtics
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Enabling high-strength cement-based materials for thermal energy storage via fly-ash cenosphere encapsulated phase change materials
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A novel machine learning based lumping approach for the reduction of large kinetic mechanisms for plasma-assisted combustion applications
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Electronic Structures and Magnetism of Zr-, Th-, and U-based Metal-Organic Frameworks (MOFs) by Density Functional Theory
Metal-organic frameworks (MOFs) have recently gained wide interest as candidate materials for nuclear waste immobilization. While the fundamental thermodynamic properties, such as the substitution energies determine the favorability of radionuclide sequestration by utilization of a MOF matrix, the studies of MOF electronic structure reveal the role of d-, and/or f-electrons on changes in physical properties of actinide-containing materials. We use density functional theory (DFT) calculations to investigate the electronic structures of Zr-, Th-, and U-MOFs, including their electronic band structures and, where appropriate, their magnetic properties. We employ various DFT methods including DFT+U, collinear spin-polarization, spin-orbit coupling, and different flavors of exchange-correlation functionals to assess the robustness to the specific exchange-correlation functional. Unlike the Zr-, and Th-MOFs, the U-MOF is found to be sensitive to electron localization and spin; hence we explore the magnetic structure of the U-MOF in further detail.
Graph-based deep learning frameworks for molecules and solid-state materials
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Output-based adaptive aerodynamic simulations using convolutional neural networks
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Effect of Sonicated Deionized Water on The Early Age Behavior of Portland Cement-Based Concrete and Paste
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Voxel-based strain tensors from near-field High Energy Diffraction Microscopy
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DP-GEN: A concurrent learning platform for the generation of reliable deep learning based potential energy models
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Potassium iodide cluster based superhalogens and superalkalis: Theoretical calculations and experimental confirmation
We studied a series of potassium-iodide clusters with formulas of (KI)nI- and (KI)nK+ (n = 1-3) by quantum chemical calculations. The calculated vertical detachment energies (VDEs) of (KI)nI- clusters are all higher than those of halogen anions, and thus can be classified as superhalogen anions; while the calculated vertical electron affinities (VEAs) of (KI)nK+ clusters are all lower than those of alkali metal cations, and thus they can be recognized as superalkali cations. Our calculated VEA for (KI)K+, i.e., K2I+, agrees well with the previously measured value by thermal ionization mass spectrometry. We confirmed the theoretical predictions by measuring the negative ion photoelectron (NIPE) spectra of (KI)nI- anions, from which the measured VDEs are found to be in good agreement with the theoretically calculated values. In addition, we also explored the possibility of supersalts formed by these superhalogen anions and superalkali cations, for example, K3I3 can be regarded as a supersalt formed by K2I+ and KI2– subunits.
Amino acid residue at the 165th position tunes EYFP chromophore maturation. A structure-based design
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