recently introduced self-powered anticorrosion system is the integration of triboelectric nanogenerator (TENG) and cathodic protection, which can realize energy harvesting and self-utilization. [9][10][11][12][13][14] Since it was first reported in 2012, [15] developments of TENG spurt. [16][17][18][19] Based on the coupling effects of triboelectrification and electrostatic induction, TENG has the excellent ability to collect various types of energy and convert it to electric energy, including bioenergy, wave energy, raindrop energy, wind energy, and mechanical energy. Besides, TENG has the advantages of high voltage, low cost, and especially high reliability, robustness, and adaptability. [20,21] TENG has already been applied for small electronic equipment, clinical medicine, supercapacitors, sensors, etc. [22,23] Especially in the ocean, wave energy is huge, abundant, regardless of day and night. [24,25] Comparing with traditional wave energy harvesting technology-electromagnetic power generation, TENG possesses many advantages in converting wave energy into electrical energy, such as higher output power and energy conversion efficiency in low-frequency motion and fairly lower integration construction cost. [26,27] Constructing TENG device and applying it into cathodic protection is one important application of harvesting wave energy. [9] Cui and Wang designed contact-separation mode through modified materials and Zhao fabricated single-electrode mode TENG via polytetrafluoroethylene (PTFE) and electrodes array. [28] Many innovative materials are used to fabricate TENG and applied into cathodic protection, such as, PTFE/polyvinyl alcohol, [13] lead-free KNbO 3 /polyvinyl chloride, [29] hydrophobic A vertical contact-separation mode triboelectric nanogenerator (TENG) to collect mechanical energy and protect stainless steel from corrosion is constructed by spraying to combine MXene powder and polydimethylsiloxane (PDMS). The output of TENG increases significantly by spraying a very small amount (1.2 mg) of MXene, which has excellent conductivity and electronegativity. The MXene/PDMS TENG (MP/PP-TENG) shows the output performance with a short current circuit of 22 µA and output voltage of 900 V, and the output peak power increases by 2.6 times. Meanwhile, MP-TENG is a reliable alternative to power supply for cathodic protection. The electrochemical measurement results show that the open circuit potential drop of the stainless steel coupled with the MP-TENG is about 300 mV. Continuous motion of TENG can realize processive protection of metals, proving its potential practical application to all-weather marine corrosion protection.

Coating matching design is one of the important parts of ship coating process design. The selection of coating matching is influenced by various factors such as marine corrosive environment, anti-corrosion period and working conditions. There are also differences in the coating performance requirements for different ship types and different coating parts. At present, the design of coating matching in shipyards depends on the experience of technologist, which is not conducive to the scientific management of ship painting process and the macro control of ship construction cost. Therefore, this paper proposes a hybrid algorithm of fuzzy comprehensive evaluation and collaborative filtering based on user label improvement (IFCE-CF). Based on the analytic hierarchy process (AHP), the evaluation index system of coating matching is constructed, and the weight calculation process of fuzzy comprehensive evaluation is optimized by introducing the user label weight. The collaborative filtering algorithm based on matrix decomposition is used to realize the accurate recommendation of coating matching. Historical coating process data of a shipyard between 2010 and 2020 are selected to verify the recommendation ability of the method in the paper. The results show that using the coating matching intelligent recommendation algorithm proposed in this paper, the root mean square error is < 1.02 and the mean absolute error is < 0.75, the prediction accuracy is significantly better than other research methods, which proves the effectiveness of the method.

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In this work, we have fabricated lithium-ion capacitor using SnO2/PCN as anode and waste coffee grounds derived PCN as cathode, which delivers good combination of high energy and power characteristics.

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SnS2-sensitized TiO2 nanotubes were fabricated via anodic oxidation and a successive ionic layer adsorption and reaction process. The prepared SnS2/TiO2 composites were used as photoanodes, and the corresponding photocathodic protection effect on 304 stainless steel was studied. The effect of the number of adsorbed SnS2 molecules on the photocatalytic protection conferred by the SnS2/TiO2 composites was also analyzed. The morphology and composition of the samples were analyzed by scanning electron microscopy, X-ray diffraction and X-ray photoelectron spectroscopy. The optical absorption properties of the samples were analyzed by ultraviolet-visible diffuse reflectance spectroscopy. The electrochemical properties of the SnS2/TiO2 composites were characterized in terms of their open circuit potential, the photocurrent density, the electrochemical impedance spectrum and the current-voltage curve and used to analyze the photocatalytic protection effect. The results show that the SnS2/TiO2 composite exhibits higher visible light absorption and offers more photocathodic protection than pure TiO2 nanotubes. Using SnS2/TiO2(6C) as a photoanode reduces the potential of 304 stainless steel to −730 mV.

The painting process is an essential part of the shipbuilding process. Its quality is directly related to the service life and maintenance cost of the ship. Currently, the design of the painting process relies on the experience of technologists. It is not conducive to scientific management of the painting process and effective control of painting cost. Therefore, an intelligent design algorithm for the ship painting process is proposed in this paper. Density-Based Spatial Clustering of Applications with Noise (DBSCAN) is used to form categories of painting objects by cluster analysis. The grey wolf optimization (GWO) is introduced to realize the adaptive determination of clustering parameters and avoid the deviation of clustering results. Then, a painting object classification model is constructed based on the random forest (RF). Finally, the recommendation of the painting process is realized based on the multi-objective evaluation function. Effectiveness is verified by taking the outer plate above the waterline of a shipyard H1127/7 as the object. The results show that the performance of DBSCAN is significantly improved. Furthermore, the accurate classification of painting objects by RF is achieved. The experiment proves that the dry film thickness qualification rate obtained by the painting process designed by IDBSCAN-RF is 92.3%, which meets the requirements of the performance standard of protective coatings (PSPC).

The structure and electron transfer paths of semiconductor heterojunctions are important for solar energy harvesting and conversion. In this work, a hollow Ni2P/TiO2 S-scheme heterojunction was designed for harvest solar...