Metal Oxides nanocrystals such as TiO2, Co3O4, Cr2O3, Fe2O3, Mn2O3, NiO, CuO and ZnO were used as modifiers on the metallic aluminum (Al) powders for the production of hydrogen in deionized water or tap water at room temperature. In particular, the influences of TiO2 nanocrystals with various crystal sizes on the production of hydrogen from the reaction in tap water under ambient condition were investigated in details. It was found that hydrogen was barely generated from metal Al powders in tap water at 25-45 °C but significantly produced in deionized water above 35 °C without any modifiers. TiO2, Co3O4, and Cr2O3 nanocrystals were very effective to promote hydrogen generation from the reaction of Al and deionized water at 25 °C. In addition, while other oxide nanocrystals were ineffective to promote hydrogen generation in tap water, TiO2 nanocrystals (P90, ∼14 nm in diameter) were found to be highly effective in facilitating the production of hydrogen from the reaction of Al with tap water, comparable to the well-known γ-Al2O3. The production of hydrogen over time was found to be dependent on the passive layer of metal Al, where Al(OH)3 plays an important role during reaction. Pitting is proposed as the major mechanism behind the production of hydrogen in the nanocrystals TiO2 (P90)-modified Al/tap water system, which is thought to be originated from point defects, and differ considerably from the uniform corrosion model. 相似文献
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Autonomous driving with high velocity is a research hotspot which challenges the scientists and engineers all over the world. This paper proposes a scheme of indoor autonomous car based on ROS which combines the method of Deep Learning using Convolutional Neural Network (CNN) with statistical approach using liDAR images and achieves a robust obstacle avoidance rate in cruise mode. In addition, the design and implementation of autonomous car are also presented in detail which involves the design of Software Framework, Hector Simultaneously Localization and Mapping (Hector SLAM) by Teleoperation, Autonomous Exploration, Path Plan, Pose Estimation, Command Processing, and Data Recording (Co- collection). what’s more, the schemes of outdoor autonomous car, communication, and security are also discussed. Finally, all functional modules are integrated in nVidia Jetson TX1.
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