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Results for “Nanowire”
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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Platinum–Nickel Nanowires with Improved Hydrogen Evolution Performance in Anion Exchange Membrane-Based Electrolysis
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Self-Sustainable Lattice Strains of Morphology-Tuned Nanowires in Electrocatalysis
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Red Light-Powered Nanowire Photochemical Diodes for Unassisted Hydrogen Evolution and Glycerol Valorization
Artificial photosynthesis via unassisted photochemical diodes is a promising approach for generating solar fuels. However, photoelectrochemical systems often degrade under solar diurnal cycling, and reliance on solar insolation exacerbates land use. Narrow-band LED illumination offers continuous and constant operation, enabling the vertical integration of stable photochemical diodes. In this study, 740 nm red light was investigated as the illumination source for silicon-based photochemical diodes integrating the hydrogen evolution reaction with the glycerol oxidation reaction (GOR), where replacing the oxygen evolution reaction with GOR increases attainable bias-free photocurrents. Increasing photovoltages, saturation current densities, and power conversion efficiencies were observed with increasing incident red light intensity. Under a red light intensity of 60 mW cm –2 , these systems are stable above 7.5 mA cm –2 for 6 days with periodic electrolyte refreshing. In conclusion, these results offer a promising prospect for red light-powered photochemical diodes that integrate other significant reduction reactions, such as CO 2 reduction.
Optical Nonlinearity in Silicon Nanowires Enabled by Bound States in the Continuum
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Strategy for Addressing the Low Quantum Efficiency of Nanowire Photodetectors
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A new class of acene-based polymers: nanowires made from linear-ladder hydroxy-substituted acene quinones
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Self-Induced Ultrafast Electron-Hole-Plasma Temperature Oscillations in Nanowire Lasers
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Junction-free microwave two-mode radiation from a kinetic inductance nanowire
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New constraints on dark matter from superconducting nanowires
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Supervised and unsupervised machine learning of structural phases of polymers adsorbed to nanowires
Here, we identify configurational phases and structural transitions in a polymer nanotube composite by means of machine learning. We employ various unsupervised dimensionality reduction methods, conventional neural networks, as well as the confusion method, an unsupervised neural-network-based approach. We find neural networks are able to reliably recognize all configurational phases that have been found previously in experiment and simulation. Furthermore, we locate the boundaries between configurational phases in a way that removes human intuition or bias. This could be done before only by relying on preconceived, ad hoc order parameters.
New Constraints on Dark Photon Dark Matter with Superconducting Nanowire Detectors in an Optical Haloscope
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Lead Telluride Nanowires for Surface Passivation in Cadmium Telluride Photovoltaics
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