This study investigates the particles within the metal vapor plume during laser beam welding in a vacuum of aluminum, focusing on their size and concentration using a simplified multi-wavelength method for particle size determination. This optical measurement technique relies on the varying extinction of light rays at different wavelengths as they pass through a collection of particles. Previous investigations have focused on laser beam welding in atmospheric conditions, revealing particle sizes for mild steel, stainless steel, and copper. However, the impact of reduced ambient pressure on particle formation remains underexplored in vacuum environments. The results indicate that higher oxygen levels in the chamber correlate with larger particles while simultaneously reducing particle concentration. In vacuum, analysis shows that as distance from the process increases, particle concentration first rises before declining again. The order of magnitude of both particle radius and concentration suggests that absorption plays a dominant role within extinction phenomena. The theoretical calculations reveal that increased oxygen content inside the vacuum chamber leads to reduced attenuation of incident laser radiation due to a lower particle concentration. Meanwhile, a lower oxygen content leads to smaller particles with higher particle concentration, which ultimately leads to greater attenuation of the incident laser beam.

The aluminum (Al) alloy AW-7075 is recognized for its high yield strength, making it suitable to replace high strength steels, thereby contributing with lightweight strategies worldwide. However, due to its metallurgical properties it is considered not suitable for joining via fusion methods, exhibiting a wide melting range, proneness to cracking and low solubility of the alloying elements in the solidified Al matrix. To address this problem, a new resistance spot welding (RSW) procedure to properly join AW-7075 was developed in previous work. This procedure involved continuous upslope current profiles, larger electrode force, and copper-silver electrode caps, which were implemented to validate the application of RSW to join AW-7075. In this work, a parametric study was carried out to assess the impacts of these welding parameters on the weld quality. Optical microscopy was used to assess the weld quality, electron back-scattered diffraction (EBSD) for microstructural texture characterization, and scanning-electron microscopy (SEM) along with electrondiffraction spectroscopy (EDS) to identify the resulting phases in the grains and at the grain boundaries. Defect-free weld joints were repeatedly produced, process boundaries were validated, and improvement of the microstructure was verified, whereby finer and equiaxial grains (EG) were detected directly in the vicinities of the heat-affected zone (HAZ). Results show that slower upslope grades favor the formation of EG by changing the solidification mechanism from columnar (directional) to equiaxial (non-directional).

Abstract Ultrasonic metal welding (USMW) is a solid-state welding process that is primarily used for joining electrical and electronic components. Common areas of application include series production of battery systems, power electronics and wire harnesses. The large number of disturbances in real-world applications, as well as a lack of basic knowledge about their effect on the welding result, cause difficulties to develop methods for quality prediction. In critical combinations, disturbances lead to faulty welds that can remain undetected by established monitoring strategies. Organic residues on the materials caused by production and handling have proven to be potentially critical, depending on the welding configuration. This study investigates the influence of various film-like, organic contaminants on USMW of copper sheets. For this purpose, a selection of contaminants is applied to the sheets to be joined and the welding process is monitored using a variety of sensors. In addition to evaluating their influence on tensile shear strength, suitable process signals are presented that can be used to reliably identify contamination and predict quality. For a more comprehensive analysis of the effects of contamination, differences in the thermal decomposition processes of the organic layers and their residues in the connection zone are considered. Particularly with a structure-borne sound signal at the anvil, reliable detection of film contamination is possible regardless of the welding parameters, even without complex algorithms. Maximum R² of 0.76 and a mean absolute error (MAE) of 150 N or ~ 6% in quality prediction can already be achieved using exemplary Extra Trees Regression with only 140 welds.

Ultrasonic metal welding is a widely used process for joining metals to create electrical connections using high-frequency mechanical vibrations. Despite its industrial relevance, achieving consistent joint quality remains challenging and requires a deeper understanding of the relationship between process parameters and joint quality. The challenge here is identifying the process signals that significantly correlate with the joint quality. Due to the nature of the process, manual evaluation of such signals is ineffective, leading to an increased focus on implementing statistical or machine learning-based models for predicting joint quality. This study proposes a method to improve the accuracy and interpretability of predicting joint quality using machine learning models. Welding experiments involving various machine internal and external sensors are conducted. The sensors’ measurement data are recorded synchronously as time series. Since most machine learning models require scalar input, informative features must be extracted from the time series data. Various statistical and signal-based features can be extracted from the entire time series. To distinguish between the influences of the different process phases and their overall behavior, the signals are divided into segments. Although equal-length segmentation is simple, it overlooks signal characteristics such as steep transitions or prolonged steady states. Change point detection enables segmentation based on signal behavior, allowing for more relevant feature extraction. Moreover, the detected segments can be associated with known process phases, linking data-driven insights with domain knowledge. As a result, both the predictive performance and interpretability of the ML models improve, allowing for clearer associations between process phases and quality outcomes.

During deep-penetration laser welding, the associated vapor plume attenuates the laser beam through scattering and absorption, resulting in a reduction of laser power contributing to the welding process. In the present study, the attenuation of the laser beam was measured in detail for stainless steel, aluminum, and copper under various atmospheric conditions. To achieve this, a novel beam configuration is employed, in which a coaxially aligned probe laser beam propagates along the same path as the processing laser beam through the interaction zone and the bottom opening of the keyhole during full-penetration welding. After separation from the residual processing beam, the laser power of the transmitted probe beam was measured using an integrating sphere and a photodiode. The results show that the attenuation was highest for stainless steel, followed by copper, and then aluminum. For all three materials, the attenuation occurred primarily within the keyhole and in its immediate vicinity. Furthermore, in the overall attenuation resulting from absorption and scattering, absorption was identified as the dominant effect. Mie–theory calculations for single–particle interactions matched the measured attenuation, confirming the experimental findings. Finally, lowering the ambient pressure noticeably reduced the total attenuation.

Surface defects are basically early indicators of welding quality that provide insights into potential issues in the welded joints. In arc welding, particularly for the fusion of thin metal sheets, weld defects such as cracks and burn-throughs occur quite often because the material and its thickness are prone to stresses caused by heat distortion and rapid cooling. Manual detection of welding defects through the different inspection methods is resource consuming. Automatic detection is, on the other hand, challenging due to the dynamic nature of the welding process and the subtle feature-based differences between acceptable and defective welds. To address this, a thermography camera is employed in this research to capture thermal variations during the welding process. The study uses thermographic imaging during the process of TIG welding and observes four different families of deep-learning detectors (YOLOv5, YOLOv8, YOLO11, and RT-DETR) across all size variants for each family. A singular thermal dataset was generated that represented the signs of burn-throughs, cracks, and burn spots, which were all consistently annotated without bias. Each model was trained and evaluated using precision, recall, mean average precision (mAP), and inference latency. YOLOv8 demonstrated comparable performance levels in the evaluation. YOLOv5 also performed robustly, but at a slower pace, RT-DETR had better feature extraction but also had the highest inference latency, and Yolo11 mistook and missed many small low-contrast defects. The results validate that thermography combined with modern deep-learning detectors is viable for automated detection and monitoring of weld quality.

In deep-penetration laser welding, the associated vapor plume leads to an attenuation of the laser beam and deformation of the phase front. These effects dynamically modify the intensity distribution on the workpiece, resulting in significant fluctuations of the weld penetration depth. In this study, high-speed X-ray imaging was used to quantify the effect of the fluctuations of the vapor plume on the capillary depth during welding. Identical welding parameters for stainless steel (1.4301) were applied in two cases: one without a cross-jet and one with a cross-jet positioned 20 mm above the capillary to remove the plume. The results show that with a cross-jet, the capillary geometry experienced only negligible fluctuations, and its depth remained largely constant. In contrast, without a cross-jet and with increasing plume formation, the welding depth decreased significantly, occasionally leading to complete capillary collapse. These findings highlight the direct impact of the plume on the laser beam and its connection to the penetration stability and resulting welding depth.

Upscaling hydrogen production through water electrolysis with proton exchange membranes (PEM) has established high interest in several industrial fields to achieve the ambitious goals given by legislative bodies regarding production volumes and cost reductions. One approach is the substitution of sintered bodies with joined multi-layered expanded metal mesh (EMM) composites that are used as porous transport layers in PEM electrolysis. For joining the multi-layered structures, capacitor discharge welding is a favored welding technology, which offers the possibility for automation, while being a highly economic and robust process. But since EMM exhibits anisotropic properties as well as a wide variety of mesh geometries, the design of such multi-layered composites leads to various possibilities for modifying the properties of the composites in terms of flow characteristics and cell efficiency. Simultaneously, these variations also influence the joining process itself. In this paper, different EMM geometries are joined in 90°- and 180°-layer-to-layer orientation in a resistance projection welding process with capacitor discharge welding. While compression tests reveal improved damping characteristics for 90°-orientation, the CFD simulation hints at more pronounced turbulences in fluid flow which are assumed to favor gas bubble accumulation and a cell efficiency decrease. Contrary, for 180°-orientation less flow turbulences and a smaller pressure drop across the cell are revealed.

The pursuit of lightweighting in critical industries necessitates advanced joining solutions for high-strength aluminum alloys like AW-7075. However, the inherent metallurgical characteristics of AW-7075 render it highly susceptible to hot cracking and detrimental microstructural defects during conventional fusion welding processes such as Resistance Spot Welding (RSW). Our previous work (Part 1 and Part 2 of this series) demonstrated that a novel RSW procedure, characterized by continuous upslope current profiles, significantly improves weld quality and promotes a beneficial shift from columnar to refined equiaxed grain structures within the fusion zone (FZ).The current work employs comprehensive Finite Element Method (FEM) simulations to provide a quantitative, mechanistic understanding of the underlying thermal phenomena governing this microstructural evolution. A robust multiphysics FEM model was employed and validated against experimental temperature profiles and weld nugget diameters. The model enabled the extraction and analysis of solidification parameters, including temperature gradient (G), solidification rate (R), cooling rate (GxR), and the morphological parameter (G/R), as functions of time and spatial position within the weld nugget.The simulations reveal that lower upslope grades effectively reduce the temperature difference between the FZ and the heat-affected zone (HAZ) and lead to significantly lower G/R ratios, promoting formation of fine, equiaxed grains. Additionally, higher cooling rates were associated with upslope welding current, resulting in finer grains in comparison with conventional RSW. These systematically explained the experimentally observed changes in Columnar-to-Equiaxed Transition (CET) and enhanced weld quality. This study provides fundamental, simulation-based insights into the manipulation of solidification conditions in RSW, paving the way for optimized process control and broader application of AW-7075 in high-performance structural designs.

During deep-penetration laser welding, a hot vapor plume is emitted from the keyhole which, on cooling, condenses into a particle cloud that surrounds the weld zone. This vapor plume and associated particle cloud interact with the incident laser beam through scattering, absorption, and phase front distortion, dynamically altering the beam caustic and potentially affecting weld quality. In this study, the mechanisms governing the beam-plume interaction are investigated by observation of the thermal emission and scattered laser light from the interaction zone during the welding of stainless steel, aluminum, and copper. For this analysis, a spectrometer and a high-speed camera equipped with optical filters were used. The results revealed significant material-specific differences in thermal emission and scattered laser light from the plume, indicating variations in absorption and scattering behavior and thus beam attenuation. Re-heating of plume material until evaporation took place for all three materials. Stainless steel exhibited the strongest thermal emission, while aluminum and copper showed significantly weaker emission. In contrast, the aluminum plume displayed the highest level of laser light scattering. This is attributed to the presence of liquid and solid particles rather than purely vaporized material, even close to the laser beam focus. Distinct interaction zones within the laser beam caustic were identified, each corresponding to specific aggregate states and characteristic laser-plume interactions. For stainless steel and copper, a zone forms close to the keyhole which is primarily composed of vaporized material. Beyond this there is a multi-phase zone containing both vapor and liquid or solid matter. Further from the keyhole, a particle zone with no detectable vapor appears as re-heating becomes insufficient for evaporation. In aluminum, no distinct vapor zone was detected. Instead, strong scattering near the keyhole indicates the presence of particles even at high laser intensities. Thus, only a multi-phase and a particle zone appear to form for aluminum under the welding parameters used.

Achieving the objectives set out in the Paris Agreement represents a significant challenge for science, industry and society as a whole. As a flexible energy carrier, hydrogen has the potential to make a significant contribution to reducing greenhouse gas emissions. To this end, there is a need to reduce the manufacturing costs of electrolyzer plants whilst simultaneously increasing their performance and lifespan, with the aim of expanding electrolyzer capacity in Europe to 40 GW by 2030. For Proton exchange membrane (PEM)-electrolyzers, the cost of the system peripherals accounts for approximately 50% of the total cost, which could be significantly reduced by using multilayer pipes with a thermoplastic glassfiber-reinforced polymer (GFRP) composite outer layer to withstand the inner pressure. For connecting the pipes to each other and to the other components at the plant, adhesive bonding has an important role. This study investigates various methods for surface pre-treatment of single-layer GFRP (polypropylene), with a particular focus on flame coating and plasma treatments. The characterization of the pre-treatments was carried out by different contact angle measurements, Fourier transform infrared-spectroscopy and scanning electron microscopy, whereby different surface structures were observed depending on the pre-treatment parameters. Subsequent to this, the samples were subjected to a lap-shear test, in accordance with DIN EN 1465. The results of this investigation revealed that specific surface structures could be created by different methods and parameters which led to strengths up to delamination failure of the substrate. Furthermore, the study investigated on the difference of low molecular weight oxidized material (LMWOM) surfaces and their washed counterparts with regard to their wettability and ageing behavior in water at 90 degrees C.

This study investigates the optimization of a femtosecond-pulsed laser pre-treatment process to enhance adhesion on nickel foils. Nickel, known for its excellent corrosion resistance and ductility, presents challenges in adhesive bonding due to its passive oxide layer, which results in poor adhesion. While nanosecond-pulsed laser pre-treatment processes are unsuitable for foil material due to thermal warping, femtosecond-pulsed laser pre-treatment offers minimal thermal impact and superior adhesion enhancement. This research focuses on analyzing how variations in pulse energy, frequency, and geometrical pulse pattern influence surface morphology and adhesion performance. Experimental results demonstrate that high pulse energy and pulse density yield optimal peel resistance values exceeding 1 N/mm. Furthermore, the study identifies an effective compromise between process efficiency and bonding performance by evaluating area rates against peel resistance metrics. These findings provide valuable insights for the industrial application of femtosecond-pulsed laser pre-treatment processes of nickel-based systems and metallic foils.

Due to the beneficial tribological properties of bronze alloy CuSn12Ni2-c and similar materials, it is commonly used for brazing tempered steels such as 42CrMo4. Laser brazing is a modern process that offers several advantages for such material combinations, including effective thermal control and dense structures with high bonding strength. Challenges to process this materials system arise in the form of liquid metal embrittlement (LME), a well-known phenomenon where certain metals lose ductility to the point of fracture when in contact with certain liquid metals. It has been shown that this process is highly dependent on the transient temperature. Due to the complexity of measuring such high and dynamically changing temperatures, the exact analysis of temperature distributions, cooling rates, and heating in industrially relevant sample geometries is challenging. This work investigates the thermal influences of the brazing process on liquid metal embrittlement LME using a custom 2D-ratio thermography camera, combined with standard thermography. This investigation focuses on the relationship between transient temperature and the resulting LME phenomena such as length and number of cracks. Additionally, it serves as trials and qualification of the 2D-ratio thermography for the investigation of transient temperature during laser-powder deposition brazing.

Ultrasonic metal welding (USMW) is a widely used solid-state welding process for electrical components. Despite careful dimensioning, defective welds occur due to the large number of influencing variables, which sometimes remain undetected by existing monitoring strategies. One known major influencing factor is the surface condition of the components to be welded, which is controlled in industrial applications using mostly chemical or mechanical cleaning methods. Existing surface-based mechanisms in USMW are insufficiently described in the literature or contradict each other, so that corresponding cleaning methods are usually developed on an application-specific basis. To further complicate efforts to define an optimal process, the surfaces of the materials used are usually only standardized in general terms, but not for USMW. This work, therefore, investigates the suitability of the surfaces of commonly used copper and aluminium materials for USMW and then defines an optimal state. Based on this, a nanosecond-pulsed laser process is developed that best meets these requirements. In addition, the potential of optimizing the welding process of copper joints to the laser-treated surface condition to achieve a robust overall process chain and transfer the results to the specific requirements of aluminum-copper joints is demonstrated. The welded joints are characterized in detail mechanically, electrically and metallographically in order to quantify the surface influence on the welding result.

Efforts to reduce weight and material cost in chemical and electro-chemical application drive the substitution of solid nickel sheets by foil material. However, using nickel foil requires new surface pre-treatment processes that produce an adhesive bond stable in aqueous media. This work investigates the effects of two surface types produced by femtosecond laser: laser induced periodic surface structures (LIPSS) and redeposited nanoparticle structures (RNPS), as well as atmospheric pressure plasma jet pre-treatment (APPJ), by itself and subsequent to the laser structuring, on adhesion and aging resistance to aqueous media. The surfaces are analyzed regarding wettability; adhesion is evaluated in peel tests initially and after aging in aqueous media. To better understand the effect of the surface structures, the samples are studied by SEM and STEM. Furthermore, the surface composition is probed by XPS, TOF-SIMS and STEM. While RNPS provides the best initial adhesion, LIPSS samples showed the best aging performance in the tested media. The wettability and stability of the surface depend on the surface structure and surface chemistry. The combination of laser and APPJ pre-treatment did lower the initial peel strength significantly and did not change aging behavior.

Resistance spot welding (RSW) is an economic, robust, and reliable welding process for joining thin steel sheets and structural components. Despite RSW of aluminum is already applied in automotive industry, resistance spot welds between dissimilar aluminum alloys are a major challenge, because small changes in alloy composition can already lead to significant differences in chemical and physical properties. In previous research, resistance spot welds between aluminum alloys of the 6000 series and die-cast aluminum are described as atypical with only poor nugget penetration depth (≤ 20

In deep-penetration laser welding a gaseous plume of metal vapor is ejected from the keyhole. Cooling of this vapor then leads to condensation and the formation of a particle cloud above and around the welding zone. The vapor plume and particle cloud interact with the incident laser beam by scattering, absorption, and deformation of the phase front. This complex and dynamic interaction can have detrimental effects on the welding result and is not yet fully understood. This is particularly relevant for welding applications where the vapor plume is not removed with shielding gas or a cross-jet. The present paper reports on investigations into the beam-plume interactions by analyzing the thermal emission and scattered laser light from the interaction zone while welding stainless steel. A high-speed camera with optical filters and a spectrometer were used for this analysis. In addition, Schlieren and shadow images were recorded to visualize the beam-plume interaction. Different zones of beam-plume interaction were distinguished. Near the laser beam focus, a negligible amount of condensed or solid material scattering the laser beam was found within the laser beam caustic. Instead, the thermal emission of the hot metal vapor was found to be the main source of emission in this area. At greater distances from the focus, the scattered laser light was the dominant emission source, while the thermal emission became negligible. These two zones were found to be connected by a multi-phase zone, which could be observed by its thermal emission and the scattering of the laser light, which contained both hot metal vapor and particles. The investigations presented here provide valuable insights into the interactions between the vapor plume and the particle cloud. In the future, this knowledge can be used to avoid or compensate for related adverse effects that occur during laser deep penetration welding, and as a basis for simulations of the beam-plume interaction.

The pre-treatment of polymers to enhance adhesion through the application of a plasma process is a method that has been industrially validated. However, it should be noted that plasma pre-treatment alone is not sufficient to ensure complete cohesive failure of demanding materials without the incorporation of primers. The application of primers is a critical process involving chemicals that are hazardous to health and the environment. Given the polymeric nature of adhesives, it is pertinent to investigate whether plasma pretreatment of the adhesive can enhance the adhesion between the substrate and the adhesive. Pressure-sensitive adhesives (PSAs) are particularly well-suited for this purpose, as they provide discrete surfaces for the application of physical pretreatments. In this study, the pretreatment of PSA using plasma pretreatment and flame treatment for adhesive bonding was investigated. The pre-treated surfaces of the PSA were then subjected to analysis using Fourier-transform infrared spectroscopy (FTIR) and scanning electron microscopy (SEM).

During laser beam welding of metals, process emissions are generated above the workpiece surface, through which the incident laser beam passes. One part of the process emissions are particles which arise from the hot metal vapor phase and agglomerate to form larger chains until they have cooled down completely. Depending on the chemical composition and size of this material emissions, the light waves are reflected, absorbed or scattered to varying degrees. The Mie theory comprehensively describes the scattering and absorption behavior of particles and essentially covers the welding plume produced during laser beam welding with a few assumptions. To specify these assumtions in more detail, this study analyzes the nanoparticles deposited on a glass carrier in the beam path of the laser. The deposition shows prismatic and octahedral structures in the scanning electron microscope, besides the predominantly spherical particles. In a vacuum and therefore with a reduced oxygen content, the ammount of emissions of the keyhole decreases and particles collected in the plume are identified as solid solution bcc-type particles containing Cr, Cu, Fe, Mn, and Ni. In atmosphere at 1000 mbar however, complex solid solutions phases with diffraction patterns compatible to spinel-type NiCr2O4 and NiFe2O4 are formed.

The geometry and quality of a weld seam are critical factors in laser beam welding, influencing mechanical performance and structural integrity. Dynamically modulated laser beams provide a precise means of tailoring energy input in high-power laser welding processes. This study investigates the influence of beam shape and modulated frequency on weld seam geometry, penetration depth, and capillary behaviour using a coherent beam combining (CBC) laser system from Civan Lasers. Three beam intensity distributions—single point, line–point–line (LPL), and boomerang—were applied across a modulation frequency range of 1, 10, and 100 kHz during the welding of duplex and austenitic stainless steels. High-speed imaging captured real-time capillary dynamics, and the data were analysed to assess capillary stability, measure capillary diameter, and determine the capillary front angle as a function of frequency and beam shape. Transverse cross-sections of the welds were prepared to evaluate seam geometry and microstructure. The results show that beam shape significantly affects energy distribution and weld profile, while modulation frequency critically influences capillary behaviour and penetration characteristics. These findings highlight the critical role of dynamic beam shaping and frequency modulation in optimizing laser welding processes for material-specific performance, offering a versatile platform for advancing precision manufacturing using CBC technology.