High-Frequency Metal-Oxide Varistor Modeling Response to Early-time Electromagnetic Pulses.
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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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The design of soft matter in which internal fuels or an external energy input can generate locomotion and shape transformations observed in living organisms is a key challenge. Such materials could assist in productive functions that may range from robotics to smart management of chemical reactions and communication with cells. In this context, hydrated matter that can function in aqueous media would be of great interest. Here, we report the design of hydrogels containing a scaffold of high–aspect ratio ferromagnetic nanowires with nematic order dispersed in a polymer network that change shape in response to light and experience torques in rotating magnetic fields. The synergistic response enables fast walking motion of macroscopic objects in water on either flat or inclined surfaces and also guides delivery of cargo through rolling motion and light-driven shape changes. The theoretical description of the response to the external energy input allowed us to program specific trajectories of hydrogel objects that were verified experimentally.
Ab initio electronic-structure has remained dichotomous between achievable accuracy and length-scale. Quantum many-body (QMB) methods realize quantum accuracy but fail to scale. Density functional theory (DFT) scales favorably but remains far from quantum accuracy. We present a framework that breaks this dichotomy by use of three interconnected modules: (i) invDFT: a methodological advance in inverse DFT linking QMB methods to DFT; (ii) MLXC: a machine-learned density functional trained with invDFT data, commensurate with quantum accuracy; (iii) DFT-FE-MLXC: an adaptive higher-order spectral finite-element (FE) based DFT implementation that integrates MLXC with efficient solver strategies and HPC innovations in FE-specific dense linear algebra, mixed-precision algorithms, and asynchronous compute-communication. Furthermore, we demonstrate a paradigm shift in DFT that not only provides an accuracy commensurate with QMB methods in ground-state energies, but also attains an unprecedented performance of 659.7 PFLOPS (43.1% peak FP64 performance) on 619,124 electrons using 8,000 GPU nodes of Frontier supercomputer.
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This is the final report for this project. The long-term objective of our project is to develop a general molecular-level picture of the surface chemistry associated with ALD processes. Our central hypothesis is that the chemistry of ALD precursors can differ significantly from that seen in solution. Awareness of such differences should provide general guidelines on what to watch for when synthesizing new ALD precursors and designing and optimizing new ALD processes, especially in terms of minimizing the incorporation of impurities in the growing films and of carrying out depositions under mild pressure and temperature conditions. The main objective of our research project has been to advance the fundamental knowledge of the surface chemistry of ALD precursors needed for the design and optimization of film deposition processes. A modern surface-science approach has been implemented to both elucidate the mechanism of the reactions of the precursors on the surface and characterize the composition and morphology of the growing films.
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Experimental values of heat of adsorption for sodium, rubidium, and cesium on tungsten substrate
Heats of adsorption of sodium, rubidium, and cesium ions on tungsten substrate
Nondestructive measurement of residual stress production during high strength aluminum alloy structure fabrication
Vapor pressures and vaporization rates of components in /Ta, Hf/C systems at high temperatures, using Schottky-Wagner model