15,942 research outputs found
Remarkably strong chemisorption of nitric oxide on insulating oxide films promoted by hybrid structure
The remarkably strong chemical adsorption behaviors of nitric oxide on
magnesia (001) film deposited on metal substrate have been investigated by
employing periodic density functional calculations with Van der Waals
corrections. The molybdenum supported magnesia (001) show significantly
enhanced adsorption properties and the nitric oxide is chemisorbed strongly and
preferably trapped in flat adsorption configuration on metal supported oxide
film, due to the substantially large adsorption energies and transformation
barriers. The analysis of Bader charges, projected density of states,
differential charge densities, electron localization function, highest occupied
orbital and particular orbital with largest Mg-NO-Mg bonding coefficients, are
applied to reveal the electronic adsorption properties and characteristics of
bonding between nitric oxide and surface as well as the bonding within the
hybrid structure. The strong chemical binding of nitric oxide on magnesia
deposited on molybdenum slab offers new opportunities for toxic gas detection
and treatment. We anticipate that hybrid structure promoted remarkable chemical
adsorption of nitric oxide on magnesia in this study will provide versatile
strategy for enhancing chemical reactivity and properties of insulating oxide
New Negentropy Optimization Schemes for Blind Signal Extraction of Complex Valued Sources
Blind signal extraction, a hot issue in the field of communication signal processing, aims to retrieve the sources through the optimization of contrast functions. Many contrasts based on higher-order statistics such as kurtosis, usually behave sensitive to outliers. Thus, to achieve robust results, nonlinear functions are utilized as contrasts to approximate the negentropy criterion, which is also a classical metric for non-Gaussianity. However, existing methods generally have a high computational cost, hence leading us to address the problem of efficient optimization of contrast function. More precisely, we design a novel “reference-based” contrast function based on negentropy approximations, and then propose a new family of algorithms (Alg.1 and Alg.2) to maximize it. Simulations confirm the convergence of our method to a separating solution, which is also analyzed in theory. We also validate the theoretic complexity analysis that Alg.2 has a much lower computational cost than Alg.1 and existing optimization methods based on negentropy criterion. Finally, experiments for the separation of single sideband signals illustrate that our method has good prospects in real-world applications
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