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    Lasers in Manufacturing and Materials Processing

    Lasers in Manufacturing and Materials Processing

    JournalISSN 2196-7229eISSN 2196-7237

    年发文量

    研究主题

    论文(379)

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    1Microstructure and Mechanical Properties in Laser Welded 5A06/316L Dissimilar Joints with In-Situ CoCrNi Multi-Principal Element Alloy Interlayer
    Haozhe Gao, Yancong Chen, Jianhua Shu, Wenliao Qin, Shenqin Zhou, Mantian Li,Nengru Tao,Yu Long,Jun Zhou

    This study uses an in-situ synthesized CoCrNi multi-principal element alloy (MPEA) interlayer to suppress brittle intermetallic compounds (IMCs) in laser-welded 5A06/316L dissimilar joints. The microstructure and mechanical properties of the joints were systematically examined under various welding parameters. Experimental results demonstrate that a sound joint with optimal tensile strength of 121 MPa was achieved at a laser power of 2500 W and a welding speed of 45 mm/s. SEM analysis confirmed that the in-situ formed FeCoCrNiAl medium-entropy alloy transition layer promoted more uniform elemental intermixing of Fe and Al. It effectively inhibited the excessive growth of detrimental Fe-Al IMCs. Numerical simulations further elucidated the correlation between weld pool dynamics, interlayer behavior, and IMC formation. This work provides a viable approach for enhancing Al/steel dissimilar joints via an MPEA interlayer.

    2026
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    2Precision Picosecond Laser Machining of Boron Nitride Ceramics
    C. Nojavan, H. Yazdani Sarvestani, E. Azad,Y. Martinez-Rubi, Z. Yamani, B. Ashrafi

    Boron nitride (BN) ceramics are increasingly employed in high-performance engineering systems requiring thermal stability, chemical inertness, and electrical insulation, including heat-management components, insulating structures, and protective ceramic components exposed to demanding environments. However, the complex layered and porous microstructure of hot-pressed BN makes its laser-machining behavior fundamentally different from that of conventional dense ceramics, and its response to ultrashort-pulse laser processing remains insufficiently understood. This study investigates the interaction between a Yb picosecond fiber laser operating at 1030 nm with 3 ps pulses and hot-pressed BN ceramic tiles and establishes relationships among energy delivery, groove evolution, material removal, and surface integrity. Laser power, focal position, linear speed, the number of passes, wobble amplitude, wobble frequency, and wobble trajectory were varied, and the resulting cut depth, kerf geometry, material removal rate, surface morphology, and surface elemental composition were evaluated using 3D laser-scanning microscopy, scanning electron microscopy, and energy-dispersive X-ray spectroscopy (SEM-EDX). Material removal in BN was governed not only by energy deposition and pulse overlap but also by the interaction between laser irradiation and its layered porous microstructure. Increasing laser power and cumulative irradiation primarily enhanced penetration depth, while kerf widening remained comparatively limited, indicating a penetration-dominated removal response characteristic of BN ceramics. SEM-EDX showed that non-preferred high-energy conditions resulted in redeposition and oxygen enrichment near the laser-affected zone, suggesting laser-induced oxidation. In contrast, preferred conditions produced more localized and well-defined kerf geometries with reduced near-surface chemical modification. The maximum material removal rate reached 22 mm3/min; however, higher removal rates increased surface degradation, revealing a productivity-quality trade-off. Benchmarking against alumina showed that BN exhibited a distinct machining response and greater sensitivity to processing parameters. These findings establish a process-structure-quality framework for precision laser machining of BN ceramics.

    2026
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    3Chemical-Free Removal of Ag₂S Tarnish Layers Using Pulsed Laser Irradiation: Optical, Chemical, and Electrical Evaluation
    Silas Schütz,Sebastian Suarez, Ben Josten, Miguel Pineiro Sales,Jean-François Pierson,Frank Mücklich

    Silver-coated electrical connectors are prone to the formation of silver sulfide (Ag₂S) tarnish layers, which impair both optical appearance and electrical performance. Conventional chemical cleaning can remove these layers effectively, although it may leave undesirable residues and introduces additional processing steps. This study investigates laser-based cleaning as a selective, chemical-free alternative by comparing nanosecond (long-pulse and Q-Switch) and picosecond laser irradiation. Optical microscopy, confocal laser scanning microscopy, scanning electron microscopy/ energy-dispersive X-ray spectroscopy, X-ray diffraction, and Raman spectroscopy were used to quantify the cleaning efficiency and assess potential surface damage. Long-pulse nanosecond irradiation produced largely homogeneous and mostly cleaned surfaces after several cycles, whereas Q-Switch operation enabled faster processing yet induced localized melting due to high peak powers. Picosecond laser treatment at 532 nm resulted in the most homogeneous appearance, minimal roughness and no detectable melting, with cleaning performance comparable to nanosecond irradiation from a chemical perspective. Electrical contact resistance measurements confirmed that the picosecond-cleaned samples, as well as the samples cleaned with the nanosecond laser operated in Q-switch mode, performed nearly as well as the chemically cleaned reference samples. The results highlight that laser cleaning offers a promising, selective and residue-free approach for integration into manufacturing processes involving silver-coated connectors.

    2026
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    4Deformation Characteristics and Suppression Method of Thin Plates During Nanosecond Laser Percussion Drilling
    Zijian Zhao, Xuechu Zhao,Jian Zhan, Yuzhou Gao

    Nanosecond laser percussion drilling can fabricate micro-holes with high aspect ratios on structural materials. However, dense hole arrays easily induce thermally generated residual plastic stresses, which can further cause macroscopic deformation of thin plates and limit the practical application of machined components. Most existing studies focus on micro-hole quality such as circularity, taper and recast layers, while the evolution and suppression of macroscopic thin-plate deformation have not been systematically investigated. Using 0.3 mm thick 304 stainless steel thin plates as the research object, this paper combines finite element simulation and experimental tests to systematically explore the effects of drilling path, partitioning mode and hole spacing on the deformation behavior of thin plates during laser array drilling. A thermo-mechanically coupled finite element model considering phase change, material removal and element birth and death technology is established to analyze the evolution of temperature and stress fields. Interval drilling weakens the thermo-mechanical coupling between adjacent holes, rendering their local stress fields approximately independent; this suppresses adverse stress superposition and reduces peak stress. Experimental results demonstrate that partitioning strategies and drilling paths have little influence on micro-hole geometry, and the micro-hole diameter is mainly governed by the incident single-pulse energy density. Combining partitioning strategies with an appropriate drilling path can effectively suppress deformation. Among the strategies examined, the center-to-edge drilling path combined with grid partitioning achieves the optimal deformation suppression effect with the minimum residual deformation. The edge-to-center trajectory tends to aggravate plate deformation. Owing to possible micro-scale thermoplastic displacement in the thin plate during the early processing stage, traditional staggered interval drilling may cause positional deviation of subsequent holes and uneven stress distribution, resulting in poorer deformation control than grid partitioning. This research provides experimental and process references for deformation control and process optimization in laser array drilling of thin plates.

    2026
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    5Application of Machine Learning for Defect Mitigation and Roughness Estimation in EHLA AM Process
    Jeferson Trevizan Pacheco, Lucas Weihmann, Murilo de Souza Ribeiro, Oksana Kovalenko,Tiago Vieira da Cunha

    This study presents a data-driven methodology for optimizing Extreme High-Speed Laser Cladding (EHLA) processing parameters with the aim of identifying defect-free conditions and controlling surface roughness. The proposed approach combines experimental analysis, machine learning and experimental validation. In the first stage, classification algorithms were evaluated to identify processing conditions associated with defect-free coatings. The Multilayer Perceptron (MLP) provided the best overall classification performance and was used to support the screening of feasible processing conditions. Correlation analysis identified process speed, overlap and mass flow rate as the parameters most associated with defect occurrence, while stand-off, overlap, process speed and laser power showed the strongest relationships with surface roughness. In the second stage, regression models were developed using a reduced parameter space comprising laser power, process speed and overlap. The MLP provided the best predictive performance for surface roughness among the evaluated models. Experimental validation confirmed the formation of defect-free coatings under the selected processing conditions, although prediction errors increased for some less-represented or extreme conditions. Multilayer deposition further demonstrated stable roughness and defect-free coating formation under the selected conditions.

    2026
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    高被引作者

    作者引用发文
    Kushvinder S. Bindra2196
    P. Ganesh2049
    Kaul Rakesh2049
    Ram K. Gupta1968
    Radovan Kovacevic1856
    Sundar R1744
    Kandasamy Ranganathan1744
    Alessandro Fortunato17010
    Alessandro Ascari1428
    Bhaskar Pant1351

    高产作者

    作者引用发文
    Alessandro Fortunato17010
    P. Ganesh2049
    Kaul Rakesh2049
    Thomas Graf618
    Alessandro Ascari1428
    Ram K. Gupta1968
    Alexander Olowinsky537
    Zongbao Shen57
    Radovan Kovacevic1856
    Kushvinder S. Bindra2196

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