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Investigating the electric power generated by wave energy converters (WECs) has attracted increasing attention along with the developments of wave energy converting technologies in recent years. Electric power estimation currently depends on wave-to-wire model-based numerical analysis and experimental studies of scale-down prototypes. However, traditional numerical simulations are time-consuming and expensive for power orediction of a full-scale WECs operated in real sea. More importantly, they cannot accurately predict WECs' power performance in real time, thereby cannot be used for prediction-based real-time control. To address those problems, four machine learning techniques are employed as an alternative to traditional, complex physical modelling processes to evaluate and predict the generated electric power, based on historical experimental data of a two-body hinge-barge WEC. Comparative results of a Backpropagation (BP) Neural Network algorithm, a Long Short-Term Memory (LSTM) algorithm, a Support Vector Machine (SVM) algorithm and a Radial Basis Neural Network (RBFF) algorithm indicate that machine-learning-based approaches can accurately predict the electric performance of this complex multi-degree-of-freedom WEC, where the coefficient of determination (R 2) of the BP Neural Network on the test dataset is up to 0.9987. • Four machine learning techniques are employed to evaluate and predict the electric power. • The machine learning techniques can be used to predict WECs' power performance under new sea state. • The coefficient of determination (R2) of the BP Neural Network is up to 0.9987. [ABSTRACT FROM AUTHOR]

Wave energy is a practical option for the sustainable powering of the drifting buoy beyond solar energy. However, efficient harvesting of wave energy from a complex and dynamic ocean environment for a drifting buoy is significantly challenging, since the buoy's global location and orientation are always in spatiotemporal variation. Herein, we propose a novel multi-DOF wave energy harvesting mechanism that integrates three sets of frequency-tunable harvesting systems into an enclosed drifting buoy, which can greatly enhance the energy harvesting ability of a long-term working drifting buoy that encounters direction-varying and frequency-varying waves. A time-averaged electric power up to 9.18 mW was achieved by a prototype that has a diameter of 45 cm, which is 32.76 % higher than the single-DOF case in sea trials. Additionally, laboratory dry test results show that the prototype provided a power up to 288.76 mW in one direction. This work provides an effective strategy for sustainably generating electricity in the offshore environment for drifting buoys. • A built-in multi-DOF wave energy harvester for a drifting buoy was presented. • Two different-sized prototypes were designed, assembled and tested in the open sea. • A time-averaged electric power of up to 9.18 mW was achieved in real sea tests. • The prototype generated a power of up to 288.76 mW in one direction in laboratory dry test. [ABSTRACT FROM AUTHOR]

• A multifunctional coating was constructed on ZE21B alloy for biodegradable vascular stents. • MgF 2 layer and hydrophilic polymers in the functional coating could effectively protect ZE21B alloy from overfast degradation. • Anticoagulant ACH 11 peptides and ECs-selective REDV peptides in the functional coating could dramatically enhance the hemocompatibility and pro-endothelialization capacity of ZE21B alloy. • The functional coating systematically improved the corrosion resistance and biocompatibility of ZE21B alloy in vitro and in vivo. Biodegradable magnesium alloy stents (MAS) have great potential in the treatment of cardiovascular diseases. However, too fast degradation and the poor biocompatibility are still two key problems for the clinical utility of MAS. In the present work, a functional coating composed of hydrophilic polymers and bioactive peptides was constructed on magnesium alloy to improve its corrosion resistance and biocompatibility in vitro and in vivo. Mg-Zn-Y-Nd (ZE21B) alloy modified with the functional coating exhibited moderate surface hydrophilicity and enhanced corrosion resistance. The favourable hemocompatibility of ZE21B alloy with the functional coating was confirmed by the in vitro blood experiments. Moreover, the modified ZE21B alloy could selectively promote the adhesion, proliferation, and migration of endothelial cells (ECs), but suppress these behaviors of smooth muscle cells (SMCs). Furthermore, the modified ZE21B alloy wires could alleviate intimal hyperplasia, enhance corrosion resistance and re-endothelialization in vivo transplantation experiment. These results collectively demonstrated that the functional coating improved the corrosion resistance and biocompatibility of ZE21B alloy. This functional coating provides new insight into the design and development of novel biodegradable stents for biomedical engineering. [ABSTRACT FROM AUTHOR]

• Cryogenic throttle valves for superfluid helium system were developed and numerically simulated. • Influences of cone angle, unilateral minimum clearance, structure type and working medium type on flow field distribution and flow characteristics of valve are studied. • Increasing the cone angle and unilateral minimum clearance enhances valve flow capacity, with the cone angle having a more pronounced impact. • Altering the spool type significantly alters the flow characteristics, whereas changing the working fluid type only affects the velocity and pressure within the valve. As one of the important methods to obtain superfluid helium, throttling has been widely used due to its simple equipment. The cryogenic throttle valve, serving as a vital component in the throttling process, directly impacts the performance of the superfluid helium system. In this study, velocity and pressure field inside valve is numerically simulated by using computational fluid dynamics (CFD), and the flow characteristics of the valve are analyzed by theoretical calculations and experiments. Moreover, influences of cone angle, unilateral minimum clearance, structure type and working medium type on flow field distribution and flow characteristics of valve are studied by altering structural parameters of spool and working medium. The results demonstrate that increasing cone angle and unilateral minimum clearance can enhance flow capacity of valves, but influence of cone angle is more obvious. Changing the spool type will significantly alter the flow characteristics of the valve, while changing the working fluid type will only affect the velocity and pressure inside the valve. [ABSTRACT FROM AUTHOR]

Hard nitride coatings have the prospect of acting as protective layers for cutting tools because of their excellent mechanical properties and wear resistance. To enhance the mechanical, tribological, and high-temperature oxidation properties, the structural design of the coating is important. In this study, TiSiN, CrAlN/TiSiN bilayer and CrAlN/TiSiN multilayer coatings were deposited on the surface of high-speed steel by multi-arc ion plating technology. The microstructure, phase composition, mechanical properties and high-temperature tribological properties of prepared coatings were analyzed. Results indicated that the TiSiN and CrAlN/TiSiN bilayer coatings contain TiN phases and the CrAlN/TiSiN multilayer coating contains three main phases of TiN, AlN and CrN. The CrAlN/TiSiN multilayer coating possesses a denser microstructure than the other two coatings. The multilayer structure improves the cohesive and bonding strength of the coating by reducing the shear stress. The CrAlN/TiSiN multilayer coating exhibits a stable coefficient of friction and excellent wear resistance during high-temperature friction. The formation of TiO2 and Al2O3 oxide layers on the surface of the coating in a high-temperature environment contributes to the desired tribological properties of the coatings. [ABSTRACT FROM AUTHOR]

With the growing worldwide attention to marine environment protection, marine resource exploration, and so on, unmanned surface vehicles (USVs) have become one of the critical mobile marine observation equipment. However, USVs generally rely on limited onboard batteries to provide electricity, and thus, they have low endurance and poor load capacity. The lack of a long-term power supply is currently a great challenge for the further application and development of USVs. Harvesting energy from the working environment of USVs is a promising solution to address that problem. To demonstrate the possibility of this scheme, a physical prototype of a novel USV with a built-in vibration energy harvester has been fabricated and tested in an open sea for the first time. Moreover, a full-coupled mathematical model is developed to further optimize the power performance of the USV based on the Taguchi method. Experimental results show that this prototype can generate a maximum instantaneous electric power of 277.71 mW , 112.95 mW and 101.27 mW when the USV is in a status of towage, propulsive and free-floating, respectively. Simulation results present that the optimized USV can achieve a mean electric power of 246.14 mW , which is improved by 49. 88 % compared with the unoptimized results of the developed prototype. • A novel USV with a built-in vibration energy harvester is developed. • A physical prototype is designed, fabricated and tested in an open sea. • A maximum instantaneous electric power of 277.71 mW is achieved in open sea tests. • The vibration energy harvester is numerically optimized based on the Taguchi method. [ABSTRACT FROM AUTHOR]

Unmanned surface vehicles (USVs) are playing a significant role in the marine science and engineering field, e.g., they have been widely used in measuring ocean waves and currents. However, their operation time and range are limited by the energy carried by internal batteries, and this challenge needs to be urgently addressed. In this study, a novel USV concept that can harvest vibration energy excited by ocean waves in the heaving and pitching direction is presented, which provides a sustainable and continuous power supply. A fully coupled wave-to-wire model that considers the viscous damping force is developed to investigate the dynamics and electric power performance of this novel device under site-specific realistic wave climates, with the external electric load optimally tuned for each sea state. Besides, the influence of the forward speed, geometric size, mass ratio and end-stop spring is studied. Numerical results show that the proposed USV in a freely floating situation can efficiently capture and convert harvested energy into electricity with a wave-to-wire efficiency of up to 20. 21 %. Additionally, it can generate an annual mean electric power of 29.73 W, under the wave climates of the national wave energy test site in China. • A novel wave-powered unmanned surface vehicle is designed. • A fully coupled wave-to-wire model is developed. • A high wave-to-wire efficiency up to 20.21% is obtained. • An annual mean electric power of 29.73 W is achieved by the USV. [ABSTRACT FROM AUTHOR]

Unmanned surface vehicles (USVs) have been widely used in various fields credited for their high flexibility and excellent manoeuvrability. However, the limited onboard electricity of USVs restricts their applications in long-term working tasks. A promising option to address that problem is employing a wave-powered USV, where a wave energy converter is integrated into the USV. For a wave-powered USV, it is challenging to achieve a precise estimation of its power generation under complex marine environments. Although there are physics-based models of WECs used for the estimation and prediction of power generation of USVs, they cannot achieve satisfactory accuracy in practice because of the linearization and simplification of those mathematical modelling. To fill up this gap, this paper proposes a data-driven modelling method utilizing feature engineering and ensemble learning to estimate the mean power generation of a wave-powered USV, relying on time-serial measurements obtained from real physical wave-flume experiments under regular waves. Results show that the estimation achieves promising performance, where the minimum RMSEs are 3.359 mW and 6.148 mW for a harvester-to-wire model and a wave-to-wire model, respectively. Additionally, the proposed method shows great potential for real-sea applications, such as online power prediction and control. • A data-driven method for power estimation of a wave-powered USV is proposed. • The robustness of the proposed method is verified with the presence of noise. • The proposed method possesses practical significance, such as data-driven control. [ABSTRACT FROM AUTHOR]

With the diversification of marine monitoring buoy functions, limited onboard batteries have been unable to meet the energy demand of multifarious carrying sensors. Finding a self-sustained power supply for marine monitoring buoys is an urgent problem, while wave energy is an ideal and promising option to address that problem. In this study, two wave-excited vibration energy harvesters (WVEHs) are proposed, which can be installed inside large buoys to provide a sustainable power supply. A full-coupled wave-to-wire model is developed to investigate the influence of blocks' mass, geometric size of buoys, mooring system and WVEH's quantity on the electric power performance of harvesters in realistic sea states. Parametric studies based on the Taguchi method imply that the sea state and the WVEH's quantity have a significant effect on the device's electric power performance. Numerical results indicate that the optimized two harvesters can produce a mean electric power of 777.50 W and 747.43 W , respectively, under a sea state with a peak wave period of 7 s and a significant wave height of 1.6 m. A high wave-to-wire efficiency of 2. 60 % is obtained for a specific system parameter combination. Furthermore, more electric power generation can be achieved by installing multiple harvesting units. • Two wave-excited vibration energy harvesters are proposed for large marine buoys. • A full-coupled wave-to-wire model is developed. • Harvesters are optimized based on the Taguchi method in realistic sea states. • A mean electric power of 777.50 W is achieved under a peak wave period of 7 s. [ABSTRACT FROM AUTHOR]

Selective catalytic reduction (SCR) has been extensively employed in industries for the removal of NO x while it is still a challenge to develop novel low-temperature catalysts. The redox and acid sites on the catalyst are often preconditions that cooperate in the SCR reaction. In this study, a series of MnO x supported on MgAl 2 O 4 spinel catalysts (denoted as Mn/MAS) were successfully prepared by incipient wetness impregnation method for low-temperature SCR of NO x with ammonia. The effects of the calcination temperature of MAS support and Mn loading on catalyst structure and performance were examined. The Mn0.12/MAS-700 catalyst showed the best low-temperature denitrification performance, with more than 80% conversion of NO at 150–300 °C and higher than 60% N 2 selectivity. Moreover, the denitrification efficiency remained at nearly 90% in the presence of H 2 O. The physicochemical properties of the catalysts were determined using various characterization methods, and the corresponding results found that the higher concentration of Mn4+ and surface chemisorption oxygen enhanced the low-temperature activity of the catalysts. The addition of Mn species increased the surface acidity of weak acid centers which promoted the catalyst activity. In situ diffuse reflectance infrared Fourier transform spectroscopy (in situ DRIFTS) revealed that the Eley-Rideal mechanism was introduced mainly at 100 °C on the Mn0.12/MAS-700 catalyst. This work provides new inspiration into the effect of Mn species, and the synergistic role of active components Mn and MAS support in the SCR reaction. [Display omitted] • The MnO x supported on Mg-Al spinel exhibited superior low-temperature activity and N 2 selectivity. • The optimal catalyst Mn0.12/MAS-700 showed excellent H 2 O resistance. • The balance of redox capacity and acid sites was considered as crucial factor. • The Eley-Rideal mechanism dominated in the SCR reaction. [ABSTRACT FROM AUTHOR]

The multi-body hinge-barge wave energy converter has the advantages of high capture width ratio and wide bandwidth of wave-excited response, which is the current hotspot of studies on wave energy converters. However, to correctly and throughfully analyse its overall efficiency, hydrodynamics, mechanical dynamics and electrical dynamics, a fully coupled wave-to-wire approach by numerical analysis and physical validation is required, which is not concerned by current studies. The work conducted in this study improves the overall wave-to-wire efficiency by optimising the mooring system, the structure and geometry of the primary capture system, and the external electric load. Results show that an optimised prototype achieves a wave-to-wire efficiency up to 25 % in flume experiments, where a significant improvement of 53 % is contributed by employing a damping plate to the right barge. Numerical results indicate that a wave-to-wire efficiency of up to 53 % is obtained by further optimisation of the damping plate. • A wave-to-wire model is developed for a hinge-barge wave energy converter, verified by flume experiments. • Adding a damping plate to the right barge can significantly improve power generation. • High wave-to-wire efficiency of 25.02% is experimentally achieved by a prototype. • High wave-to-wire efficiency of 53% is numerically achieved by optimisation. [ABSTRACT FROM AUTHOR]

In recent years, the application of convolutional neural networks (CNNs) and graph convolutional networks (GCNs) in hyperspectral image classification (HSIC) has achieved remarkable results. However, the limited label samples are still a major challenge when using CNN and GCN to classify hyperspectral images. In order to alleviate this problem, a double branch fusion network of CNN and enhanced graph attention network (CEGAT) based on key sample selection strategy is proposed. First, a linear discrimination of spectral inter-class slices (LD_SICS) module is designed to eliminate spectral redundancy of HSIs. Then, a spatial spectral correlation attention (SSCA) module is proposed, which can extract and assign attention weight to the spatial and spectral correlation features. On the graph attention (GAT) branch, the HSI is segmented into some super pixels as input to reduce the amount of network parameters. In addition, an enhanced graph attention (EGAT) module is constructed to enhance the relationship between nodes. Finally, a key sample selection (KSS) strategy is proposed to enable the network to achieve better classification performance with few labeled samples. Compared with other state-of-the-art methods, CEGAT has better classification performance under limited label samples. [ABSTRACT FROM AUTHOR]

In this study, a series of praseodymium oxides (Pr 6 O 11) was developed by CTAB-assisted coprecipitation method. The praseodymium oxides were deeply characterized by XRD, N 2 adsorption, SEM, HR-TEM, H 2 -TPR, soot-TPR, NO-TPO and in situ DRIFTS, and tested for soot combustion in absence/presence of NO atmospheres under tight/loose contact conditions. As a non-noble metal and single element oxide, the Pr 6 O 11 catalysts exhibited excellent catalytic performances for both soot oxidation (T 10 = 341 ℃, T 50 = 395 ℃) in O 2 and NO x adsorption (NAC, 906 μ mol/g) at low temperature. It was believed that the relatively large surface area, strong NO oxidation ability and high intrinsic activity contributed to the superior performances. A promoting effect on soot oxidation was found when NO introduced, which was ascribed to the NO x -assisted mechanism. The in situ DRIFTS was used to explore the possible mechanism in the soot oxidation reaction process. The carboxyl was detected over Pr 6 O 11 and was speculated as carbon-oxygen intermediate in soot oxidation. • Praseodymium oxides (Pr 6 O 11) nanorods were synthesized by a CTAB-assisted coprecipitation method. • The as-prepared Pr 6 O 11 nanocatalysts exhibited excellent soot removal ability and NOx adsorption capacity. • Large surface area, high reactivity of oxygen species and strong NO oxidation ability contributed to the good performances. • The "nitrite route" pathway was speculated in NOx adsorption. • The intermediate species (carboxyl) were detected in soot oxidation process. [ABSTRACT FROM AUTHOR]

Improving capacity utilization (CU) is a critical way for China to promote economic transformation and achieve sustainable development. As a market-based environmental regulation proposed to achieve a low-carbon economy and green transformation, whether emission trading system (ETS) can improve CU deserves an in-depth study. We conduct an empirical study by constructing a multi-period difference-in-differences model with 1,037 Chinese A-share listed firms from 2004 to 2020 as the research sample. The result shows that the ETS can significantly improve CU, which still holds after a series of robustness tests. The mechanism analysis shows that the ETS improves CU through three mechanisms: stimulating green innovation, restricting over-investment, and alleviating financing constraints. Based on the heterogeneity analysis, the improvement of CU by ETS is greater among listed firms in heavy-polluting industries, with good ESG performance, excess leverage, and central state ownership. Our study supports the global implementation of the ETS and provides ideas for resolving overcapacity in the context of global decarbonization. [ABSTRACT FROM AUTHOR]