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In order to study the mechanism of dissolved oxygen content on the surface corrosion behavior of Fe-based heat transfer, the first principle is used to study the adsorption of O2 monomolecular, H2O monolayer and dissolved oxygen system on Fe-based heat transfer surface. The GGA/PBE approximation is used to calculate the adsorption energy, state density and population change during the adsorption process. Calculations prove that when the dissolved oxygen is adsorbed on the Fe-based surface, the water molecule tends to adsorb at the top sites, and the oxygen molecule tends to adsorb at Griffiths. When the H2O molecule adsorbs and interacts on the Fe (001) surface, the charge distribution of the interfacial double electric layer changes to cause the Fe atoms to lose electrons, resulting in the change of the surface potential. When the O2 molecule adsorbs on the Fe (001) crystal surfaces, the electrons on the Fe (001) surface are lost and the surface potential increases. O2 molecule and the surface of the Fe atoms are prone to electron transfer, in which O atom's 2p orbit for the adsorption of O2 molecule on Fe (001) crystal surface play a major role. With the increase of the proportion of O2 molecule in the dissolved oxygen water, the absolute value of the adsorption energy increases, and the interaction of the Fe-based heat transfer surface is stronger. This study explores the influence law of different dissolved oxygen on the Fe base heat exchange surface corrosion, and the base metal corrosion mechanism for experimental study provides a theoretical reference.

With the rise of sustainable development and energy-saving mode in the manufacturing industry, a joint optimization strategy of machine predictive maintenance and tool replacement is proposed aiming to meet the needs of energy control and maintenance decision for computer numerical control (CNC) machine and tools. The non-value-added energy consumption is taken as the research emphasis, while the phased tool wear evolution is introduced into the energy modeling of the CNC machine. First, predictive maintenance (PM) scheduling of the CNC machine based on healthy evolution aims to achieve the minimization of the non-value-added power. Secondly, based on the sequential outputs of the CNC machine PM intervals, a joint replacement model of the tool is also established considering comprehensive energy saving and economy. The optimal cycle interval of tool preventive replacement and the CNC machine PM is obtained in the joint optimization layer. The case study analysis shows that compared with the traditional maintenance strategies, this joint optimization strategy can significantly reduce the total non-value-added energy consumption.

Graphene is an ideal material for energy storage application as its excellent mechanical and physical properties. 3D printed graphene materials will be widely applied in energy storage field for its precisely controllable structure and it is easy to realize large-scale preparation. In this paper, the progress of 3D printed graphene materials synthesis technology and its application in energy storage field were reviewed. The viscosity and printability of graphene ink are key factors for realizing graphene 3D printing. Scalable preparation of graphene ink with facile process, controllable concentration and additive free will be the research focus of graphene 3D printing technologies in the future. The integrated printing of graphene energy storage devices such as graphene supercapacitor, lithium-sulfur battery and lithium ion battery is the development direction in this area.