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We demonstrate significant improvement of CuO nanowire arrays as anode materials for lithium ion batteries by coating with thin NiO nanosheets conformally. The NiO nanosheets were designed two kinds of morphologies, which are porous and non-porous. By the NiO nanosheets coating, the major active CuO nanowires were protected from direct contact with the electrolyte to improve the surface chemical stability. Simultaneously, through the observation and comparison of TEM results of crystalline non-porous NiO nanosheets, before and after lithiation process, we clearly prove the effect of expected protection of CuO, and clarify the differences of phase transition, crystallinity change, ionic conduction and the mechanisms of the capacity decay further. Subsequently, the electrochemical performances exhibit lithiation and delithiation differences of the porous and non-porous NiO nanosheets, and confirm that the presence of the non-porous NiO coating can still effectively assist the diffusion of Li+ ions into the CuO nanowires, maintaining the advantage of high surface area, and improves the cycle performance of CuO nanowires, leading to enhanced battery capacity. Optimally, the best structure is validated to be non-porous NiO nanosheets, in contrary to the anticipated porous NiO nanosheets. In addition, considering the low cost and facile fabrication process can be realized further for practical applications.

Recently, the intelligent systems of technology have become one of the major items in the development of machine tools. One crucial technology is the machinery status monitoring function, which is required for abnormal warnings and the improvement of cutting efficiency. During processing, the mobility act of the spindle unit determines the most frequent and important part such as automatic tool changer. The vibration detection system includes the development of hardware and software, such as vibration meter, signal acquisition card, data processing platform, and machine control program. Meanwhile, based on the difference between the mechanical configuration and the desired characteristics, it is difficult for a vibration detection system to directly choose the commercially available kits. For this reason, it was also selected as an item for self-development research, along with the exploration of a significant parametric study that is sufficient to represent the machine characteristics and states. However, we also launched the development of functional parts of the system simultaneously. Finally, we entered the conditions and the parameters generated from both the states and the characteristics into the developed system to verify its feasibility.