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• Cu coating is melted, desquamated, and solidified into near-spherical particles. • Cu coating can protect MWCNTs from structural damage at a laser power of 600 W. • MWCNTs are cut into segments and transformed into near-spherical amorphous particles. • Spheroidization of amorphous carbon is driven by the reduction in surface energy. The Cu coating on carbon nanotubes (CNTs) with low infrared laser absorptivity was applied to provide a protective layer against the structural damage caused by laser irradiation in this paper. The effect of Cu coating on the structural evolution of multi-walled carbon nanotubes (MWCNTs) under a ring-shaped high-energy laser beam was studied. As the laser power increases, the morphology of 35 wt.% Cu-coated MWCNTs (35Cu-CNTs) samples transforms from discrete fine powder particles to caking structure with a roughened surface. A 45 wt.% Cu coating effectively provides structural protection for MWCNTs against laser-induced damage at a laser power of 600 W. During laser irradiation, the Cu coating melts, detaches from the surface of MWCNTs, and subsequently solidifies into a mixture of nearly spherical particles. Without the protection of Cu coating, the MWCNTs bundles are fragmented into nanoscale segments in varying sizes. These segments undergo a transformation into amorphous carbon particles as a result of the rapid heating and cooling process induced by the high-energy laser irradiation. The thermal impact of the high-energy laser beam plays a crucial role in determining the structural transformation of MWCNTs. The coalescence and spheroidization of amorphous carbon particles can be induced by the reduction of surface energy. [ABSTRACT FROM AUTHOR]

Laser directed energy deposition (LDED) was utilized to incorporate carbon nanotubes (CNTs) into WE43 magnesium alloy, aiming to enhance its wear resistance by leveraging the exceptional mechanical and self-lubricating properties of CNTs. The LDED-prepared CNTs reinforced WE43 composite (CNTs/WE43) coatings were fabricated for evaluating the wear resistance improvement. The microstructure and wear properties of the LDED-prepared CNTs reinforced WE43 composite coating were investigated in comparison to the WE43 coating. The addition of Ni coated CNTs (Ni-CNTs) led to drastic morphologic changes including the emergence of stratified structures and distinct furrow formations. The composite coating exhibited altered segregation patterns, characterized by the presence of filamentous, punctiform, porphyritic, and ring-shaped accumulations of CNTs, Mg 24 Y 5 , and Zr cores in both the central and furrow zones. The addition of Ni-CNTs induced a decrease of up to 45.8 % in wear weight loss for the WE43 coating. The friction coefficient versus the applied loads of the WE43 and CNTs/WE43 coatings showed an opposite trend. The incorporation of CNTs significantly improved the wear resistance of the WE43 coating by enhancing its ability to resist plastic deformation, forming a protective carbon film, and providing self-lubricating effects. • Successful fabrication of CNTs/WE43 composites via laser directed energy deposition • Unique altered segregation patterns in the composite coatings • Self-lubricating and strengthening effects of CNTs for improving the wear resistance • Friction coefficient of the WE43 and composite coatings showed an opposite trend. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to evaluate the corrosion resistance of fusion zones in different heat treated condition from laser welded Mg-Gd-Y alloys and analyze their intrinsic corrosion mechanism. Design/methodology/approach: The corrosion behavior of fusion zone from laser-welded Mg-Gd-Y alloy joints in the as-welded, ageing and solution + ageing conditions was investigated in the 3.5 wt.% NaCl solution by immersion tests. Findings: The corroded surface of as-welded fusion zone consists of dark and bright regions, and the bright regions were composed of high-density needle-like products, whereas some different extended direction of the cracks with lots of long ultrafine needle-shaped corrosion products appeared in the dark regions. The corrosion resistance of the fusion zone is slightly decreased after the ageing treatment. Originality/value: The solution + ageing treated fusion zone exhibits the highest corrosion resistance than that of the as-welded and ageing treated state because of the full dissolution of the cathodic coarse eutectic compound, grains growth and relatively compact protective films. The inhomogeneous distribution of the β′ can somewhat improve the corrosion rate of solution + ageing treated fusion zone when compared with base metal. [ABSTRACT FROM AUTHOR]

The precipitates evolution in the heat affected zone of laser-welded Mg-Gd-Y-Zr alloy in T6 condition was investigated based on the TEM observation. Some oval and long-rod shape precipitates along [ 2 1 ¯ 1 ¯ 0 ] α were observed, which were not involved in precipitation sequence. Compared with isothermal aged precipitates, the overaged β′ phase presented same morphology and size, while size of needle-shape β became much smaller. The width of complete dissolution zone of the β′ is smaller than that of partial dissolution and transformation zone. • Some oval and long-rod shape precipitates along [ 2 1 ¯ 1 ¯ 0 ] α were observed in the HAZ. • Some overaged β' phase can be precipitated in the HAZ. • The size of needle-shape β in the HAZ became much smaller, compared with isothermal aged precipitates. [ABSTRACT FROM AUTHOR]

The microstructure evolution in the fusion zone of laser-welded Mg-Gd-Y-Zr alloy during solution and aging treatment is investigated. The morphology of the Mg 24 (Gd,Y) 5 in the divorced eutectic at the grain boundary transforms from a continuous network to disconnected and fragmentized islands and then to spheroidal particles before complete dissolution during the solution treatment at 430 °C. During the subsequent aging treatment at 225 °C, the precipitation sequence in the fusion zone follows the order of supersaturated solid solution (SSSS) → βʺ(D0 19 ) → βʹ(cbco) → β 1 (fcc) → β(fcc). High-density precipitates are present at the original grain boundaries of the fusion zone from the welded structure but there are less precipitates in the interior of the original grains. The grain growth during the solution treatment at 430 °C comprises the slowly increasing stage, rapidly increasing stage, and stable stage. The network-distributed Mg 24 (Gd,Y) 5 impedes migration of the grain boundaries, restricts grain growth in the first slowly increasing stage, and segregation of zirconium near the grain boundaries also affects migration of the grain boundaries. [ABSTRACT FROM AUTHOR]

• The temperature distribution on weldment sidewall exhibits a certain degree of separability under different offset degrees of cladding layer. • A cladding layer offset recognition method based on infrared sensing and deep learning for WAAM is proposed. • The proposed method effectively solves the problem of arc light interference in the cladding layer offset recognition method based on visual perception. In the wire arc additive manufacturing (WAAM) procedure, the stability of the cladding layer's formation directly impacts the final dimensional precision of the WAAM weldment. To achieve high-precision forming of the WAAM weldment, online monitoring of the cladding layer offset is essential. This article explores the monitoring technology for the cladding layer offset in the WAAM process and introduces a cladding layer offset monitoring technique using infrared temperature measurement and deep learning. First, a temperature field measurement system for the WAAM weldment is set up using an infrared thermal imager. Next, a region of interest (ROI) is selected on the weldment sidewall. The optimised histogram of oriented gradient (HOG) algorithm is then employed to extract the temperature distribution characteristics of the ROI. The separability of the temperature field on the weldment sidewall is analysed under various offset degrees of the cladding layer. Finally, using the temperature image of the ROI as input, a cladding layer offset recognition model is developed using a convolutional neural network (CNN). This study also evaluates the effect of the selected ROI position on the recognition precision of the model for the cladding layer offset. Experimental results indicate that the recognition accuracy of the model for cladding layer offset, as presented in this article, exceeds 99%. Moreover, the model demonstrates strong robustness, further enriching the intelligent monitoring methods for the WAAM process. [ABSTRACT FROM AUTHOR]

• The coatings are fabricated with TiC and Ni60 mixture powders as raw materials by laser cladding. • The effect of TiC content on microstructure and properties of TiC/Ni60 coatings is revealed. In this study, the composite coatings on Ti6Al4V alloy are fabricated with TiC and Ni60 mixture powders by laser cladding. The effect of TiC content on microstructure and properties of the coatings is investigated. Many TiC particles in large size are randomly distributed in the coatings. The coatings mainly contain TiC. TiC, TiC x , Ti 2 Ni, TiNi, TiB, Cr x B and Ti phase identified by XRD. The feature of the precipitates in the coatings is various due to different TiC. The forms of the precipitates are changed in the coatings with increasing the TiC content. The wear resistance of the coatings decreases with increasing the TiC content. Numerous plowing grooves with the debris particles and white scaly patterns are found in the sliding direction. With increasing the TiC content, the bending strength of the samples decreases. The brittle fracture feature are shown on the fracture surface of the coatings. [ABSTRACT FROM AUTHOR]

• Multimodal signal features under various deviation degrees of robot trajectory demonstrate good separability. • A prediction model for robot trajectory deviation based on multimodal fusion perception is established. • The prediction model for robot trajectory deviation has strong generalization ability. During wire arc additive manufacturing (WAAM) process, the movement trajectory of robot directly determines cladding layer position, therefore, monitoring of robot trajectory is particularly important. This paper proposes an approach for monitoring robot trajectory deviation based on multimodal fusion perception. First, a visual sensing system is constructed using monochrome camera and infrared camera, which collected visual image of molten pool and measured the temperature of workpiece sidewall. Second, the weld pool contour is extracted based on deep learning, and the histogram of oriented gradient (HOG) algorithm on the basis of trilinear interpolation is adopted to extract temperature distribution characteristics of workpiece sidewall. Finally, a prediction model for robot trajectory deviation is developed using artificial neural network. The experimental results indicate that the proposed approach for monitoring robot trajectory deviation has high detection precision and strong generalization capability, it provides an effective means to ensure weldment quality in WAAM. [ABSTRACT FROM AUTHOR]